use strict;
my $str = '<div data-video-id="a6afa8d5-cb1f-e4b1-02e2-e74c8943fea6" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/a6afa8d5-cb1f-e4b1-02e2-e74c8943fea6" data-video-poster="https://universe-files.dacast.com/87aad1e1-8fe7-96b0-3071-2ef62f5e797f" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/87aad1e1-8fe7-96b0-3071-2ef62f5e797f" alt="1_1 - DICOM, HL7, IHE: from zero to hero"></div></div><div class="item item-description ec-flex-row"><div><h4>1_1 - DICOM, HL7, IHE: from zero to hero</h4><p><span class="icon icon-clock">48:37</span><span class="icon icon-moderator">F. Zanca, Heverlee/BE</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="b63f8367-8f6e-cdcc-0f06-2d8fdb92b8dc" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/b63f8367-8f6e-cdcc-0f06-2d8fdb92b8dc" data-video-poster="https://universe-files.dacast.com/af38b13e-32bb-7cc5-2b58-d786a0833c64.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/af38b13e-32bb-7cc5-2b58-d786a0833c64.jpeg" alt="1_2 - Knowing the rules: from GDPR to MDR"></div></div><div class="item item-description ec-flex-row"><div><h4>1_2 - Knowing the rules: from GDPR to MDR</h4><p><span class="icon icon-clock">41:40</span><span class="icon icon-moderator">F. Zanca, Heverlee/BE</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="aa57c8f1-9025-d84c-6576-2037c17d7d67" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/aa57c8f1-9025-d84c-6576-2037c17d7d67" data-video-poster="https://universe-files.dacast.com/cf6b3fe7-ee79-7ba7-ad55-2df76c20c110" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/cf6b3fe7-ee79-7ba7-ad55-2df76c20c110" alt="1_3 - Information systems used by Radiology"></div></div><div class="item item-description ec-flex-row"><div><h4>1_3 - Information systems used by Radiology</h4><p><span class="icon icon-clock">46:16</span><span class="icon icon-moderator">D. Pinto dos Santos, Cologne / DE</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="bda709a3-4f7d-ea30-d65e-0bbfdf7b85d0" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/bda709a3-4f7d-ea30-d65e-0bbfdf7b85d0" data-video-poster="https://universe-files.dacast.com/ed27246d-546f-15b1-8393-39c0366f0f9f" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/ed27246d-546f-15b1-8393-39c0366f0f9f" alt="2_1 - Communicating image results: from structured reporting to ontologies"></div></div><div class="item item-description ec-flex-row"><div><h4>2_1 - Communicating image results: from structured reporting to ontologies</h4><p><span class="icon icon-clock">41:29</span><span class="icon icon-moderator">D. Pinto dos Santos, Cologne / DE</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="528dd01e-bf84-cdb0-ab34-c1fbd8edb208" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/528dd01e-bf84-cdb0-ab34-c1fbd8edb208" data-video-poster="https://universe-files.dacast.com/0acf064e-97be-cc5d-c44e-91194010a813" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 5 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/0acf064e-97be-cc5d-c44e-91194010a813" alt="2_2 - Working with image data: from postprocessing to segmentations"></div></div><div class="item item-description ec-flex-row"><div><h4>2_2 - Working with image data: from postprocessing to segmentations</h4><p><span class="icon icon-clock">49:07</span><span class="icon icon-moderator">E. Kotter, Freiburg / DE</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="14f01a8a-6125-d62b-ca04-bdd7bf3ea2fd" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/14f01a8a-6125-d62b-ca04-bdd7bf3ea2fd" data-video-poster="https://universe-files.dacast.com/e8c3dfa7-9bfd-87e2-2627-757cf6e60ce0" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 6 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/e8c3dfa7-9bfd-87e2-2627-757cf6e60ce0" alt="2_3 - CAD, Radiomics, AI and beyond"></div></div><div class="item item-description ec-flex-row"><div><h4>2_3 - CAD, Radiomics, AI and beyond</h4><p><span class="icon icon-clock">49:14</span><span class="icon icon-moderator">E. Kotter, Freiburg / DE</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="9857f3b8-2bb9-5cf8-b84d-48fc60c87507" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/9857f3b8-2bb9-5cf8-b84d-48fc60c87507" data-video-poster="https://universe-files.dacast.com/47e7dcf6-7ebb-ae17-ce90-cbebf1f7185c" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/47e7dcf6-7ebb-ae17-ce90-cbebf1f7185c" alt="RPS 2504-1 - Introduction"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2504-1 - Introduction</h4><p><span class="icon icon-clock">00:46</span><span class="icon icon-moderator">Ivan Vollmer.mp4</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="d5d78eb7-4215-19d5-4ff3-da9ab4420438" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/d5d78eb7-4215-19d5-4ff3-da9ab4420438" data-video-poster="https://universe-files.dacast.com/c7e46fb7-5c69-5d60-7e69-a1d1e1552016" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/c7e46fb7-5c69-5d60-7e69-a1d1e1552016" alt="RPS 2504-2 - Ultrasound-guided percutaneous needle biopsy of pleural and peripheral lung lesion- comparison with computed tomography guided biopsy"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2504-2 - Ultrasound-guided percutaneous needle biopsy of pleural and peripheral lung lesion- comparison with computed tomography guided biopsy</h4><p><span class="icon icon-clock">10:25</span><span class="icon icon-moderator">Binoy Choudhury.mp4</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="ceada2c3-61e8-bc3c-3a9f-a9424459a0bf" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/ceada2c3-61e8-bc3c-3a9f-a9424459a0bf" data-video-poster="https://universe-files.dacast.com/d417b456-de9a-c34f-fd20-e018e9d56c2c" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/d417b456-de9a-c34f-fd20-e018e9d56c2c" alt="RPS 2504-3 - Artificial intelligence-driven pleural plaque segmentation and volume correlation to lung function"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2504-3 - Artificial intelligence-driven pleural plaque segmentation and volume correlation to lung function</h4><p><span class="icon icon-clock">09:30</span><span class="icon icon-moderator">Kevin Groot Lipman.mp4</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="9f575e63-df15-955f-c04c-c6051abc0d46" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/9f575e63-df15-955f-c04c-c6051abc0d46" data-video-poster="https://universe-files.dacast.com/81a5d755-dd21-0055-dbb8-89de3084d6ed" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/81a5d755-dd21-0055-dbb8-89de3084d6ed" alt="RPS 2504-4 - Development and validation of CT-based radiomics nomogram for prognostic prediction in patients with malignant pleural mesothelioma"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2504-4 - Development and validation of CT-based radiomics nomogram for prognostic prediction in patients with malignant pleural mesothelioma</h4><p><span class="icon icon-clock">05:35</span><span class="icon icon-moderator">Xie Xiaojie.mp4</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="bdfc99dc-330f-1b7e-5ce1-c36c8050b76a" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/bdfc99dc-330f-1b7e-5ce1-c36c8050b76a" data-video-poster="https://universe-files.dacast.com/c720dc89-5edc-d52f-c0e9-ff9fa8dc9b5c" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 5 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/c720dc89-5edc-d52f-c0e9-ff9fa8dc9b5c" alt="RPS 2504-5 - Training and validation of DL algorithms for the detection of pneumothorax based on data from a competition in diagnostic imaging"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2504-5 - Training and validation of DL algorithms for the detection of pneumothorax based on data from a competition in diagnostic imaging</h4><p><span class="icon icon-clock">07:25</span><span class="icon icon-moderator">Maurice Henkel.mp4</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="dc25164c-a728-096c-cb40-d4f4ac5b4a10" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/dc25164c-a728-096c-cb40-d4f4ac5b4a10" data-video-poster="https://universe-files.dacast.com/98ba56bf-09b6-72be-486c-588600aa8dd7" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 6 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/98ba56bf-09b6-72be-486c-588600aa8dd7" alt="RPS 2504-7 - Imaging IRAE-pericardial effusion on chest CT- clinical and radiologic manifestations and implications for management"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2504-7 - Imaging IRAE-pericardial effusion on chest CT- clinical and radiologic manifestations and implications for management</h4><p><span class="icon icon-clock">08:22</span><span class="icon icon-moderator">Kathleen Capaccione.mp4</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="f9379957-1452-f638-0f99-f881dc8d8643" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/f9379957-1452-f638-0f99-f881dc8d8643" data-video-poster="https://universe-files.dacast.com/fefd1fca-5df1-20d0-3111-52889754416a" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/fefd1fca-5df1-20d0-3111-52889754416a" alt="Introduction to Radiation Protection in Interventional Radiology"></div></div><div class="item item-description ec-flex-row"><div><h4>Introduction to Radiation Protection in Interventional Radiology</h4><p><span class="icon icon-clock">80:21</span><span class="icon icon-moderator">Ask EuroSafe Imaging</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="c022b30c-0d53-6c40-ba05-cbe05664e90a" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/c022b30c-0d53-6c40-ba05-cbe05664e90a" data-video-poster="https://universe-files.dacast.com/8e688816-9c29-a48d-cfa2-983d712ed2c5" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/8e688816-9c29-a48d-cfa2-983d712ed2c5" alt="RPS 2607-1 - Introduction"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2607-1 - Introduction</h4><p><span class="icon icon-clock">01:11</span><span class="icon icon-moderator">Alexander Baur, Lorenzo E. Derchi</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="9355f2e6-694a-5f81-3060-0b8010679eb1" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/9355f2e6-694a-5f81-3060-0b8010679eb1" data-video-poster="https://universe-files.dacast.com/5d305a7f-a636-4ac3-6c5d-d4a15f45eda4" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/5d305a7f-a636-4ac3-6c5d-d4a15f45eda4" alt="RPS 2607-2 - MR perfusion imaging of the prostate without contrast media using arterial spin labelling"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2607-2 - MR perfusion imaging of the prostate without contrast media using arterial spin labelling</h4><p><span class="icon icon-clock">06:13</span><span class="icon icon-moderator">Matthias Boschheidgen</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>M. Boschheidgen</u>, L. Schimmöller, T. Ullrich, C. Arsov, G. Antoch, H. Wittsack; Düsseldorf/DE<br><b>Purpose or Learning Objective: </b>To determine the capability of gadolinium-free arterial spin labelling (ASL) sequence as contrast-free, non-invasive alternative perfusion imaging method to differentiate prostate cancer (PCA) from benign prostate tissue compared to conventional DCE MRI.<br><b>Methods or Background: </b>Thirty men with histologically confirmed PCA were included in this prospectively enrolled single-centre cohort study. All patients received multiparametric MRI (T2, DWI, DCE) at 3T with additional ASL of the PCA lesion. The primary endpoint was the differentiability of PCA versus normal prostate tissue in ASL in comparison to DCE. Secondary objectives were differences in signal intensities (SI), contrast ratios (CR), and differences in the attenuation pattern of peripheral (PZ) and transition zone (TZ) PCA.<br><b>Results or Findings: </b>In both ASL and DCE, the average SI of PCA areas differed significantly from SI in reference areas in the TZ and PZ (p<0,01, respectively). ASL had significantly higher CR discerning PCA and benign tissue in PZ and TZ (PZ=5.2; TZ=6.5) compared to DCE (PZ=1.6; TZ=1.4) (p<0.01, respectively). In subjective evaluation, ASL could visualise PCA in 28 patients, compared to 29 in DCE.<br><b>Conclusion: </b>ASL had significantly higher contrast-ratios discerning PCA and benign tissue in PZ and TZ compared to DCE and visual discrimination of PCA does not differ significantly between the two sequences. As perfusion gadolinium-based contrast media is seen more critical in the last few years, ASL seems to be a promising alternative to DCE in PCA detection.<br><b>Limitations: </b>Single-centre design. Small sample size. Single slice sequence. Long acquisition time.<br><b>Ethics committee approval: </b>The study was approved by the local ethics committee.<br><b>Funding for this study: </b>No funding was received for this study.<br></p></div></div><div data-video-id="d7d0bb4d-2133-b583-da5e-b8e76e572c56" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/d7d0bb4d-2133-b583-da5e-b8e76e572c56" data-video-poster="https://universe-files.dacast.com/7ebdc021-5f93-99db-c7b2-4d0cbee0ea1d" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/7ebdc021-5f93-99db-c7b2-4d0cbee0ea1d" alt="RPS 2607-3 - Diagnostic performance of MRI-derived capsular enhancement sign for the detection of prostate cancer extracapsular extension"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2607-3 - Diagnostic performance of MRI-derived capsular enhancement sign for the detection of prostate cancer extracapsular extension</h4><p><span class="icon icon-clock">05:38</span><span class="icon icon-moderator">Nikita Sushentsev</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>N. Sushentsev</u><sup>1</sup>, I. Caglič<sup>1</sup>, A. Colarieti<sup>2</sup>, A. Warren<sup>1</sup>, B. Lamb<sup>1</sup>, N. Shah<sup>1</sup>, T. Barrett<sup>1</sup>; <sup>1</sup>Cambridge/UK, <sup>2</sup>Milan/IT<br><b>Purpose or Learning Objective: </b>To retrospectively determine the prevalence and diagnostic performance of the capsular enhancement sign (CES) on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the detection of prostate cancer (PCa) extracapsular extension (ECE).<br><b>Methods or Background: </b>This retrospective study included patients who underwent DCE-MRI prior to radical prostatectomy. CES was defined as an area of asymmetrical early hyperenhancement on DCE-MRI that was adjacent to a peripheral zone tumour, matched or exceeded the tumour circumferential diameter, and persisted beyond the washout of contrast within the adjacent tumour. Two expert uro-radiologists evaluated the presence of CES on DCE-MRI, independently and then in consensus, with the interobserver agreement calculated using a bias-adjusted and prevalence-adjusted kappa (PABAK). CES diagnostic performance for prediction of ECE was assessed using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).<br><b>Results or Findings: </b>The study included 146 patients, of whom 91/146 (62%) harboured ECE on final surgical pathology. Following the initial review of the images, Reader 1 called 12/146 (8%) CES-positive cases, while Reader 2 reported 14/146 (10%) CES-positive cases, and a total of 15/146 (10%) lesions were subsequently identified as CES-positive following a consensus read. PABAK for CES between the two readers was high at 0.90. All consensus determined CES-positive lesions represented pathological ≥T3a disease, with the overall prevalence of CES among tumours with confirmed ECE being 15/91 (17%). Hence, whilst showing 100% specificity and PPV for ECE detection, CES had sensitivity, NPV, and accuracy of 16.5%, 41.29%, and 47.38%, respectively.<br><b>Conclusion: </b>The presence of CES on DCE-MRI is highly predictive for the presence of ECE and may improve local staging in the small but significant percentage of patients in whom it is demonstrated.<br><b>Limitations: </b>Not applicable.<br><b>Ethics committee approval: </b>This study was funded by the NREC East of England.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div><div data-video-id="3937b4d6-9446-3443-45b1-564fffe10385" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/3937b4d6-9446-3443-45b1-564fffe10385" data-video-poster="https://universe-files.dacast.com/11482f13-b01e-2740-361d-5766e933c9a2" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/11482f13-b01e-2740-361d-5766e933c9a2" alt="RPS 2607-4 - Utility of computed diffusion-weighted imaging b2000 for detection of prostate cancer"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2607-4 - Utility of computed diffusion-weighted imaging b2000 for detection of prostate cancer</h4><p><span class="icon icon-clock">07:18</span><span class="icon icon-moderator">Yeonjung Kim</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>Y. KIM</u>, S. H. Kim, H. PARK, T. Baek; Busan/KR<br><b>Purpose or Learning Objective: </b>To compare the diagnostic performance in tumour detection and inter-observer agreement between acquired diffusion-weighted imaging (aDWI) b2000 and computed DWI (cDWI) b2000 for patients with prostate cancer (PCa).<br><b>Methods or Background: </b>A total of 88 patients (mean age: 68.6 years, range: 47-82 years) who had been diagnosed with PCa by radical prostatectomy and undergone pre-operative 3.0-Tesla magnetic resonance imaging (3T-MRI) including DWI (b values, 0, 100, 1000, 2000 s/mm2) were included in this study. cDWI b2000 was made from aDWI b0, 100 and 1000 under a mono-exponential decay model. Two independent reviewers performed a 4-week-interval review of aDWI b2000 images and then cDWI b2000 in random order for each session. T2-weighted images were presented for both sessions. A region of interest was drawn for an index tumour on each dataset, and a PIRADS score based on PIRADS v2.1 was recorded. Topographic maps served as the reference standard. The McNemar test was performed to compare the sensitivities for tumour detection, and kappa statistics were used to evaluate the inter-observer agreement on the PIRADS score on each dataset.<br><b>Results or Findings: </b>The study population consisted of Gleason score (GS) 6 (n=16), GS 7 (n=53), GS 8 (n=9) and GS 9 (n=10) patients. For both reviewers, the sensitivities of cDWI b2000 and aDWI b2000 for detection of PCa showed no significant difference (for reviewer 1, both 94% (83/88); for reviewer 2, both 90% (79/88), P = 1.000, respectively). The kappa values of cDWI b2000 and aDWI b2000 for the PIRADS scores were 0.422 (95% CI, 0.240-0.603) and 0.495 (95% CI, 0.308-0.683), respectively.<br><b>Conclusion: </b>cDWI b2000 showed comparable diagnostic performance and sustained moderate inter-observer agreement with aDWI b2000 for detection of PCa.<br><b>Limitations: </b>No limitations were identified.<br><b>Ethics committee approval: </b>This study was approved by the Pertinent institutional review board.<br><b>Funding for this study: </b>No funding was received for this study.<br></p></div></div><div data-video-id="1de941e4-f48a-a638-6bb6-122787fb1da0" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/1de941e4-f48a-a638-6bb6-122787fb1da0" data-video-poster="https://universe-files.dacast.com/78bb39e1-018f-9b41-2c54-16d75995398f" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 5 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/78bb39e1-018f-9b41-2c54-16d75995398f" alt="RPS 2607-5 - Prediction of PET-positive lymph nodes with multiparametric MRI and clinical information in primary staging of prostate cancer"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2607-5 - Prediction of PET-positive lymph nodes with multiparametric MRI and clinical information in primary staging of prostate cancer</h4><p><span class="icon icon-clock">05:51</span><span class="icon icon-moderator">Andreas M. Hötker</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>A. M. Hötker</u><sup>1</sup>, U. J. Mühlematter<sup>1</sup>, S. Skawran<sup>1</sup>, S. Ghafoor<sup>1</sup>, I. A. Burger<sup>2</sup>, M. Huellner<sup>1</sup>, O. F. Donati<sup>1</sup>; <sup>1</sup>Zurich/CH, <sup>2</sup>Baden/CH<br><b>Purpose or Learning Objective: </b>To predict the presence of PET-positive pelvic lymph nodes in prostate cancer using quantitative parameters of multiparametric MRI (mpMRI) and clinical information.<br><b>Methods or Background: </b>This study included 35 patients with high suspicion for prostate cancer undergoing multiparametric prostate MRI and PSMA-PET/CT prior to MRI-guided biopsy. All MRI examinations were assessed by a radiologist, and the Apparent Diffusion Coefficient (ADC, mean and volume), capsular contact length, volume and maximal diameter on T2-weighted sequences and parameters of dynamic contrast-enhanced MRI (iAUC, kep, Ktrans, ve) were calculated for the index lesion. Clinical data was extracted from the hospital information system to calculate the Briganti 2018 nomogram scores. PET examinations were evaluated by two board-certified nuclear medicine physicians and served as the standard of reference.<br><b>Results or Findings: </b>Quantitative imaging parameters of mpMRI mostly demonstrated mediocre to good performance in prediction of PET-positive nodes (AUCs, ADCmean: 0.74, ADCvol: 0.55, iAUC: 0.42, kep: 0.71, Ktrans: 0.64, ve: 0.37, T2capsular: 0.59, T2diameter: 0.58, T2vol: 0.55), while the Briganti 2018 nomogram (including maximum diameter of the index lesion) reached an AUC of 0.78 (95%-CI: 0.61-0.95). Quantitative MR parameter did not provide added value to the Briganti 2018 model alone.<br><b>Conclusion: </b>The Briganti 2018 model, which includes clinical/pathological data and the maximal tumour length of the index lesion on prostate MRI, performed well in predicting PET-positive lymph nodes and may serve as a tool to stratify patients for primary staging using PSMA-PET.<br><b>Limitations: </b>The relatively low number of patients. Retrospective study design.<br><b>Ethics committee approval: </b>Approved by local IRB.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div><div data-video-id="45a04ed6-6ccc-e74a-d54c-40e8af406bd0" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/45a04ed6-6ccc-e74a-d54c-40e8af406bd0" data-video-poster="https://universe-files.dacast.com/638036db-d679-ecb1-9df3-b6317001afa5" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 6 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/638036db-d679-ecb1-9df3-b6317001afa5" alt="RPS 2607-6 - Independent evaluation of the PI-QUAL score for prostate MRI: does it provide value?"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2607-6 - Independent evaluation of the PI-QUAL score for prostate MRI: does it provide value?</h4><p><span class="icon icon-clock">05:53</span><span class="icon icon-moderator">Nina Pötsch</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>N. Pötsch</u><sup>1</sup>, E. Rainer<sup>1</sup>, P. Clauser<sup>1</sup>, G. Vatteroni<sup>2</sup>, T. H. Helbich<sup>1</sup>, P. A. Baltzer<sup>1</sup>; <sup>1</sup>Vienna/AT, <sup>2</sup>Milan/IT<br><b>Purpose or Learning Objective: </b>To test the inter-reader agreement of the Prostate Imaging Quality (PI-QUAL) score for multiparametric prostate MRI and its impact on diagnostic performance.<br><b>Methods or Background: </b>Prebioptic multiparametric (T2-weighted, DWI and DCE) prostate MRIs (mpMRI) of 50 patients undergoing transrectal ultrasound-guided MRI-fusion and systematic prostate biopsy were included. Two radiologists independently assigned a PI-QUAL score to each patient. PI-RADS categories were assigned in a lesion-based approach, dividing the prostate into six regions (left and right: base/midglandular/apex). Additionally, the diagnostic quality of each sequence was evaluated independently. Inter-reader agreement was calculated by using Cohen’s kappa and diagnostic performance was compared by the area under the ROC curve (AUC).<br><b>Results or Findings: </b>In a total of 274 diagnostic areas, the malignancy rate was 62.2% (22.7% clinically significant prostate cancer ISUP ≥ 2). Inter-reader agreement for the diagnostic quality was only slight for T2w (kappa 0.19) and fair for DWI and DCE (kappa 0.23 and 0.29). For PI-QUAL as such, the inter-reader agreement was moderate (kappa 0.51). For PI-RADS category assignments, the inter-reader agreement was almost perfect (kappa 0.86). Overall diagnostic performance was significantly better in studies with a PI-QUAL score > 3 compared to a score ≤ 3 (P=0.03; AUC 0.805 and 0.839).<br><b>Conclusion: </b>In conclusion, the diagnostic performance of mpMRI for the detection of prostate cancer does depend on MRI image quality. Though there is room for improvement regarding inter-reader reproducibility, PI-QUAL is a tool that provides value by predicting the accuracy of diagnostic mpMRI results.<br><b>Limitations: </b>As all patients underwent MRI-US fusion biopsy due to suspicious mpMRI findings, the rate of malignancy is higher compared to routine clinical practice which may bias the outcomes in non-selected patients.<br><b>Ethics committee approval: </b>IRB waived the need for informed consent.<br><b>Funding for this study: </b>No funding was received for this study.<br></p></div></div><div data-video-id="0ea8d912-ed51-863c-e876-8c29e06e61bf" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/0ea8d912-ed51-863c-e876-8c29e06e61bf" data-video-poster="https://universe-files.dacast.com/a3d66660-27b1-2e30-31c8-cac928b67f29" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 7 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/a3d66660-27b1-2e30-31c8-cac928b67f29" alt="RPS 2607-7 - Quantitative evaluation of diffusion-weighted imaging may help to avoid biopsies for low PI-RADSv2.1 categories in transition zone lesions"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2607-7 - Quantitative evaluation of diffusion-weighted imaging may help to avoid biopsies for low PI-RADSv2.1 categories in transition zone lesions</h4><p><span class="icon icon-clock">05:45</span><span class="icon icon-moderator">Hannes Engel</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>H. Engel</u>, B. Oerther, M. Reisert, A. Sigle, E. Kellner, F. Bamberg, M. Benndorf; Freiburg im Breisgau/DE<br><b>Purpose or Learning Objective: </b>To analyse whether low PI-RADS categories of transition zone (TZ) lesions can be downgraded based on mean apparent diffusion coefficients (mADC) without risking false-negative results.<br><b>Methods or Background: </b>This retrospective cohort study consists of consecutive patients with TZ lesions in multiparametric prostate MRI and subsequent MRI-ultrasound-fusion-biopsy between 05/2017-04/2020. Patients with known prostate cancer (PCa) are excluded. All lesions are scored by two blinded radiologists according to PI-RADSv2.1 guidelines. To determine mADC, lesions are manually segmented. Regression and ROC analyses are performed to determine the diagnostic performance of PI-RADSv2.1 categories and mADC.<br><b>Results or Findings: </b>Among 85 patients with 98 TZ lesions, 33 (33.7%) are PCa and 65 (66.3%) are benign. 24 (72.7%) of the 33 PCa lesions are clinically significant (csPCa, ISUP-grade>1). mADC for PCa are significantly lower than for benign lesions (894 vs 1.091µm2/s, p<0.001). AUC values from ROC analysis with csPCa as outcome variable are 0.916 for PI-RADSv2.1 and 0.806 for mADC. Compared to PI-RADSv2.1 alone, a combination with an mADC cut-off of 950µm2/s for TZ lesions ≤ PI-RADS 3 improves the negative predictive value (0.95 vs 1.00). Among 58 TZ lesions ≤ PI-RADS 3, only 8 (13.8%) have mADC below 950µm2/s, 3 (37.5%) PCa and 1 (12.5%) csPCa.<br><b>Conclusion: </b>The key question after a prostate MRI is whether a biopsy is indicated: cancer detection rates for PI-RADS 1+2 are very low while being too high for PI-RADS 3 to abandon biopsies completely. Thus, further parameters which allow avoiding unnecessary biopsies are desirable. Our data indicate that by applying an mADC cut-off for TZ lesions ≤ PI-RADS 3 most biopsies could be avoided without overlooking prostate cancer.<br><b>Limitations: </b>mADC can differ between vendors/algorithms. External validation of our findings is warranted before clinical use.<br><b>Ethics committee approval: </b>The ethics committee approval was obtained.<br><b>Funding for this study: </b>No funding was received for this study.<br></p></div></div><div data-video-id="e2286319-9813-90a0-66ea-daf030d6769f" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/e2286319-9813-90a0-66ea-daf030d6769f" data-video-poster="https://universe-files.dacast.com/e967da2f-57f5-a85e-3fea-c5ac429292ed" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 8 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/e967da2f-57f5-a85e-3fea-c5ac429292ed" alt="RPS 2607-8 - Improving workflow in prostate MRI: AI-based decision-making on biparametric or multiparametric MRI"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2607-8 - Improving workflow in prostate MRI: AI-based decision-making on biparametric or multiparametric MRI</h4><p><span class="icon icon-clock">18:23</span><span class="icon icon-moderator">Andreas M. Hötker</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>A. M. Hötker</u>, A. Tiessen, D. M. Raffaele, E. Konukoglu, O. F. Donati; Zurich/CH<br><b>Purpose or Learning Objective: </b>To develop and validate an artificial intelligence algorithm to decide on the necessity of dynamic contrast-enhanced sequences (DCE) in prostate MRI.<br><b>Methods or Background: </b>A convolutional neural network (CNN) was developed on 300 prostate MRI examinations. The consensus of two expert readers on the necessity of DCE acted as the reference standard. The CNN was validated in a separate cohort of 100 prostate MRI examinations from the same vendor and 31 examinations from a different vendor. Sensitivity/specificity were calculated using ROC curve analysis and results were compared to decisions made by a radiology technician.<br><b>Results or Findings: </b>The CNN reached a sensitivity of 94.4% and specificity of 68.8% (AUC: 0.88) for the necessity of DCE, correctly assigning 44%/34% of patients to a biparametric/multiparametric protocol. In 2% of all patients, the CNN incorrectly decided on omitting DCE. With a technician reaching a sensitivity of 63.9% and specificity of 89.1%, the use of the CNN would allow for an increase in sensitivity of 30.5%. The CNN achieved an AUC of 0.73 in a set of examinations from a different vendor.<br><b>Conclusion: </b>The CNN would have correctly assigned 78% of patients to a biparametric or multiparametric protocol, with only 2% of all patients requiring re-examination to add DCE sequences. Integrating this CNN in clinical routine could render the requirement for on-table monitoring obsolete by performing contrast-enhanced MRI only when needed.<br><b>Limitations: </b>The decision rendered by the neural network was dichotomous. The performance of the AI could be improved by defining a range of probability values in which it\'s unsure and prompt the technician to call a radiologist for this particular examination.<br><b>Ethics committee approval: </b>This study was approved by the institutional review board and the requirement for study-specific informed consent was waived.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div>
<div data-video-id="e75b09dc-7912-a301-14c3-dfc2b380d57c" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/e75b09dc-7912-a301-14c3-dfc2b380d57c" data-video-poster="https://universe-files.dacast.com/5b3b251a-1989-7689-915d-50b3e2025969.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/5b3b251a-1989-7689-915d-50b3e2025969.jpeg" alt="Head CT"></div></div><div class="item item-description ec-flex-row"><div><h4>Head CT</h4><p><span class="icon icon-clock">82:53</span><span class="icon icon-moderator">Ask EuroSafe Imaging</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="69dcf637-0840-ea6e-8688-e4d2b177d9a1" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/69dcf637-0840-ea6e-8688-e4d2b177d9a1" data-video-poster="https://universe-files.dacast.com/8ac7c747-34a2-bd9e-7875-8af161e230ae" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/8ac7c747-34a2-bd9e-7875-8af161e230ae" alt="RT 26-1 - Chairpersons\' introduction"></div></div><div class="item item-description ec-flex-row"><div><h4>RT 26-1 - Chairpersons\' introduction</h4><p><span class="icon icon-clock">04:50</span><span class="icon icon-moderator">Regina G.H. Beets-Tan, Michael H. Fuchsjäger</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p>1. To know how editors handle your manuscript and how the review process of manuscripts is carried out.<br> 2. To know how to carefully and systematically assess the outcome of scientific research (evidence) to judge ist trustworthiness, value and relevance.<br></p></div></div><div data-video-id="2b2cc9bd-fd9a-4c58-8b92-9f09e68ad52f" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/2b2cc9bd-fd9a-4c58-8b92-9f09e68ad52f" data-video-poster="https://universe-files.dacast.com/87aaa4ef-b508-8da6-1cca-7a07bdf0a8f4" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/87aaa4ef-b508-8da6-1cca-7a07bdf0a8f4" alt="RT 26-2 - My manuscript was rejected, why?"></div></div><div class="item item-description ec-flex-row"><div><h4>RT 26-2 - My manuscript was rejected, why?</h4><p><span class="icon icon-clock">13:34</span><span class="icon icon-moderator">Yves Menu</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="fd9df836-ff1c-f093-7a08-71e4a8559d16" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/fd9df836-ff1c-f093-7a08-71e4a8559d16" data-video-poster="https://universe-files.dacast.com/4d090235-2da7-8c36-3dc0-7cd401865727" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/4d090235-2da7-8c36-3dc0-7cd401865727" alt="RT 26-3 - How do I critically appraise a scientific publication"></div></div><div class="item item-description ec-flex-row"><div><h4>RT 26-3 - How do I critically appraise a scientific publication</h4><p><span class="icon icon-clock">11:09</span><span class="icon icon-moderator">Francesco Sardanelli</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="cda541b7-c7c9-6d65-9e73-ea2d88357811" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/cda541b7-c7c9-6d65-9e73-ea2d88357811" data-video-poster="https://universe-files.dacast.com/dc85d5a5-783c-830a-25fa-84a7878276c4" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/dc85d5a5-783c-830a-25fa-84a7878276c4" alt="RT 26-4 - Discussion"></div></div><div class="item item-description ec-flex-row"><div><h4>RT 26-4 - Discussion</h4><p><span class="icon icon-clock">32:52</span><span class="icon icon-moderator"></span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="a3c72bac-ad4b-b694-785d-58eb2c27c76b" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/a3c72bac-ad4b-b694-785d-58eb2c27c76b" data-video-poster="https://universe-files.dacast.com/ed47e3c3-05fe-5b0d-f771-6cdcbb69c7a9" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/ed47e3c3-05fe-5b0d-f771-6cdcbb69c7a9" alt="RPS 2616-1 - Introduction"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2616-1 - Introduction</h4><p><span class="icon icon-clock">00:47</span><span class="icon icon-moderator">Giuseppe Brancatelli</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="e1375d4f-481c-b3d3-cbe4-56efa9bffa95" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/e1375d4f-481c-b3d3-cbe4-56efa9bffa95" data-video-poster="https://universe-files.dacast.com/deafc962-d86f-66b5-02ba-8ddd050338e0" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/deafc962-d86f-66b5-02ba-8ddd050338e0" alt="RPS 2616-3 - Feasibility of quantitative dynamic contrast-enhanced MRI for prediction of microvascular invasion in small solitary hepatocellular carcinoma based on a dual-input two-compartment model"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2616-3 - Feasibility of quantitative dynamic contrast-enhanced MRI for prediction of microvascular invasion in small solitary hepatocellular carcinoma based on a dual-input two-compartment model</h4><p><span class="icon icon-clock">11:00</span><span class="icon icon-moderator">Yongjian Zhu</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b>C. Wei, <u>Y. ZHU</u>, X. Ma, X. Zhao; Beijing/CN<br><b>Purpose or Learning Objective: </b>Microvascular invasion (MVI) serves as an important prognostic factor for hepatocellular carcinoma (HCC) after an operation. However, predicting MVI in patients with HCC is a clinical challenge as MVI is a histopathological diagnosis. The aim of this study is to investigate the feasibility of quantitative dynamic contrast-enhanced MRI (DCE-MRI) for predicting MVI in small solitary HCC (ssHCC).<br><b>Methods or Background: </b>A total of 63 patients with pathologically confirmed ssHCC (≤ 3cm) underwent quantitative DCE-MRI studies and received hepatic resection. A dual-input two-compartment exchange model (2CXM) was used to calculate the values of quantitative permeability and perfusion parameters. The differences in parameters between different MVI status groups were analysed. Multivariate logistic regression was used to build the combined prediction model for MVI prediction with the statistically significant parameters. The predictive performance was evaluated using ROC analysis.<br><b>Results or Findings: </b>Among the 63 patients with ssHCC, 22 (34.9%) exhibited MVI positive. The MVI positive group had higher volume transfer constant (Ktrans), reverse reflux rate constant (kep), portal vein blood flow (BFpv), and lower extracellular extravascular volume fraction (ve), hepatic arterial perfusion index (HPI) values than negative group (1.532 min-1 vs. 0.853 min-1, 0.547 min-1 vs. 0.362 min-1, 84.63 mL/min/100g vs. 34.95 mL/min/100g, 0.316 vs. 0.582, 65.32 vs. 84.59, respectively) (P<0.05). Quantitative parameters Ktrans, kep and BFpv values independently associated with MVI with OR values of 4.36, 2.53 and 3.74 (P<0.05) through multivariate logistic regression. ROC analysis showed that the AUC, sensitivity, specificity in predicting MVI by combined Ktrans, kep and BFv values were 0.903, 87.6%, 95.4%, respectively.<br><b>Conclusion: </b>Quantitative DCE-MRI derived parameters showed potential value in the prediction MVI in ssHCC.<br><b>Limitations: </b>The sample size was relatively small.<br><b>Ethics committee approval: </b>Approved by the Independent Ethics Committee of the Cancer Hospital, CAMS (no. 20/412-2608).<br><b>Funding for this study: </b>No funding was received for this study.<br></p></div></div><div data-video-id="950f0d30-57a9-3d23-f816-523c098e4219" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/950f0d30-57a9-3d23-f816-523c098e4219" data-video-poster="https://universe-files.dacast.com/0fe8ee98-b3a8-e079-6085-a6baee662dc3" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/0fe8ee98-b3a8-e079-6085-a6baee662dc3" alt="RPS 2616-7 - Hepatocellular carcinoma- radiomics analysis of contrast-enhanced computed tomography images in prediction tumour grade"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2616-7 - Hepatocellular carcinoma- radiomics analysis of contrast-enhanced computed tomography images in prediction tumour grade</h4><p><span class="icon icon-clock">07:29</span><span class="icon icon-moderator">Mariia Shantarevich</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>M. Shantarevich</u>, E. V. Kondratyev, G. G. Karmazanovsky; Moscow/RU<br><b>Purpose or Learning Objective: </b>Poor tumour differentiation of hepatocellular carcinoma (HCC) correlates with lower overall and disease-free survival. Therefore, accurate non-invasive preoperative prediction of the tumour histologic grade is crucial for patient prognosis. The purpose of this study was to investigate the value of radiomics analysis of contrast-enhanced computed tomography images (CECT) in estimating the histologic tumour grade before surgery in patients with HCC.<br><b>Methods or Background: </b>The 36 patients with HCC and preoperative liver CECT who had undergone surgical resection were retrospectively enrolled in the study (25 patients with the tumour Grade 1+Grade2, and 11 patients - with Grade 3). The LIFEx application software (version v7.1.0, www.lifexsoft.org) was used to obtain texture features. 3D ROI that covered the whole tumour was delineated in the images for each patient. Radiomic features were extracted from four phases (native, arterial, portal, and delay). A total of 497 radiomic features were extracted from each CECT phase.<br><b>Results or Findings: </b>Tree radiomic features: CONVENTIONAL_HUKurtosis, DISCRETIZED_HUExcessKurtosis and GLZLM_SZE derived from native and arterial phases showed significant positive associations with the histologic grade (p<0,05) and were selected after multiple linear regression analysis. The sensitivity and specificity of radiomics-based model in detecting poor-differentiated HCC from well- and moderate- differentiated HCC were 87,5% and 94,7%, respectively (AUC 0,901±0,078 CI: 0,749-1,0).<br><b>Conclusion: </b>The use of the CECT radiomics-based model reflects a better evaluating performance in the prediction of HCC grade, which may contribute to personalised treatment.<br><b>Limitations: </b>The limitation of our research is the small number of included patients.<br><b>Ethics committee approval: </b>Not applicable.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div><div data-video-id="98d28086-f83c-9a3a-07bf-4df72d07bd61" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/98d28086-f83c-9a3a-07bf-4df72d07bd61" data-video-poster="https://universe-files.dacast.com/fc61e0ac-ae44-deae-b88a-08e3ed34760d" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/fc61e0ac-ae44-deae-b88a-08e3ed34760d" alt="RPS 2616-8 - Assessment of radiogenomic venous invasion to predict the outcome after loco-regional therapies in patients with hepatocellular carcinoma"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2616-8 - Assessment of radiogenomic venous invasion to predict the outcome after loco-regional therapies in patients with hepatocellular carcinoma</h4><p><span class="icon icon-clock">11:06</span><span class="icon icon-moderator">Robin Schmidt</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>R. Schmidt</u>, C. Hamm, H. XU, V. H. Broukal, L. A. Gottwald, B. Gebauer, L. J. Savic; Berlin/DE<br><b>Purpose or Learning Objective: </b>Radiogenomic venous invasion (RVI) is a set of imaging biomarkers indicative of the presence of microvascular invasion. This study aims to investigate the predictive value of RVI regarding response and survival of patients with HCC receiving LRT.<br><b>Methods or Background: </b>This retrospective study included 95 patients with unresectable HCC, who received ablation using CT-guided high dose-rate brachytherapy alone (n=48) or in combination with transarterial chemoembolisation (TACE, n=47) between 01/2016-12/2017. Patients were stratified according to positive or negative RVI assessed on baseline contrast-enhanced MRI using two decision-tree-models: RVI (art) and RVI (ven) based on the presence of internal vessels in the arterial or portal-venous phase, respectively, and the absence of both a hypointense halo and a sharp tumour-liver-transition in native T1-weighted images. Primary endpoints were overall (OS), progression-free survival (PFS), and time to progression (TTP). Statistics included Fisher’s exact test and Kaplan-Meier analysis.<br><b>Results or Findings: </b>Regarding brachytherapy alone, stratification according to RVI (art) achieved significant separation of OS (p=<0.001) and PFS (p=0.029) but not TTP (p=0.142), revealing poorer outcomes for RVI positive patients. RVI (ven) was predictive of TTP (p=0.032) and PFS (p=0.004) but not OS (p=0.078). On the contrary, both RVI types achieved no significant stratification for any endpoint following TACE/brachytherapy. In patients receiving brachytherapy alone, median OS, PFS, and TTP were shorter for RVI (ven) positive compared to negative patients (12.4 vs 40.4, 5.9 vs 13.2, 6.4 vs 11.8 months). In contrast, no difference could be observed for patients receiving TACE/brachytherapy.<br><b>Conclusion: </b>While decisions for LRT are currently based on visual assessments of tumour enhancement on baseline MRI, the findings underscore the potential of RVI to identify HCC patients who would benefit from TACE before brachytherapy.<br><b>Limitations: </b>This study was done retrospectively at a single site.<br><b>Ethics committee approval: </b>Ethics committee approval was obtained.<br><b>Funding for this study: </b>No funding was received for this study.<br></p></div></div>
<div data-video-id="4f7ba7ec-54e3-cfa9-99d3-2a56c4695c2e" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/4f7ba7ec-54e3-cfa9-99d3-2a56c4695c2e" data-video-poster="https://universe-files.dacast.com/56b437e1-b8bd-d863-84ea-941e16e6becb" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/56b437e1-b8bd-d863-84ea-941e16e6becb" alt="1_1 - US Imaging of thyroid gland: the essential"></div></div><div class="item item-description ec-flex-row"><div><h4>1_1 - US Imaging of thyroid gland: the essential</h4><p><span class="icon icon-clock">40:12</span><span class="icon icon-moderator">Ana-Sofia Germano, Amadora / PT</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="2e9dc851-daab-239f-7c2b-845ac348027e" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/2e9dc851-daab-239f-7c2b-845ac348027e" data-video-poster="https://universe-files.dacast.com/6869606c-9d97-8231-08cb-9231ca0ebeab.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/6869606c-9d97-8231-08cb-9231ca0ebeab.jpeg" alt="1_2 - Imaging of TMJ: techniques and reporting"></div></div><div class="item item-description ec-flex-row"><div><h4>1_2 - Imaging of TMJ: techniques and reporting</h4><p><span class="icon icon-clock">28:15</span><span class="icon icon-moderator">Soraya Robinson, Vienna / AT</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="2e4e79c6-2b02-c948-1d59-b127d3b075b4" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/2e4e79c6-2b02-c948-1d59-b127d3b075b4" data-video-poster="https://universe-files.dacast.com/1aaaa066-ab89-58ad-9451-244302aa75dd.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/1aaaa066-ab89-58ad-9451-244302aa75dd.jpeg" alt="1_3 - CBCT in Head and Neck Imaging: when & how"></div></div><div class="item item-description ec-flex-row"><div><h4>1_3 - CBCT in Head and Neck Imaging: when & how</h4><p><span class="icon icon-clock">46:10</span><span class="icon icon-moderator">Roberto Maroldi, Concesio / IT</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="9f0a4676-e1e5-1b13-96ff-7ed145e6bc5f" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/9f0a4676-e1e5-1b13-96ff-7ed145e6bc5f" data-video-poster="https://universe-files.dacast.com/2b01dccd-c821-3c50-9b0d-3315fe4e2f56.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/2b01dccd-c821-3c50-9b0d-3315fe4e2f56.jpeg" alt="2_1 - Imaging of parathyroid gland"></div></div><div class="item item-description ec-flex-row"><div><h4>2_1 - Imaging of parathyroid gland</h4><p><span class="icon icon-clock">36:57</span><span class="icon icon-moderator">Ana-Sofia Germano, Amadora / PT</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="f268ff5b-fff5-5415-f56a-8002f0923ca7" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/f268ff5b-fff5-5415-f56a-8002f0923ca7" data-video-poster="https://universe-files.dacast.com/86c4fcb7-92a3-0931-e58b-4d6e90188a9e.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 5 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/86c4fcb7-92a3-0931-e58b-4d6e90188a9e.jpeg" alt="2_2 - Disorders of the teeth: a reasoned reporting"></div></div><div class="item item-description ec-flex-row"><div><h4>2_2 - Disorders of the teeth: a reasoned reporting</h4><p><span class="icon icon-clock">35:42</span><span class="icon icon-moderator">Soraya Robinson, Vienna / AT</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="5008c3f5-724c-20cb-2be2-f49dc92001cc" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/5008c3f5-724c-20cb-2be2-f49dc92001cc" data-video-poster="https://universe-files.dacast.com/0f5b8fc9-0352-9dc3-1500-64521b003ff4.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 6 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/0f5b8fc9-0352-9dc3-1500-64521b003ff4.jpeg" alt="2_3 - Maxillo-facial trauma: key points for imaging"></div></div><div class="item item-description ec-flex-row"><div><h4>2_3 - Maxillo-facial trauma: key points for imaging</h4><p><span class="icon icon-clock">38:36</span><span class="icon icon-moderator">Roberto Maroldi, Concesio / IT</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="db1128b1-bbcd-da80-5c5e-7188b35d1719" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/db1128b1-bbcd-da80-5c5e-7188b35d1719" data-video-poster="https://universe-files.dacast.com/95c42f4f-e51b-bd19-1f77-1e593b81f445.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/95c42f4f-e51b-bd19-1f77-1e593b81f445.jpeg" alt="Radiation Protection of Patients in FGI"></div></div><div class="item item-description ec-flex-row"><div><h4>Radiation Protection of Patients in FGI</h4><p><span class="icon icon-clock">90:51</span><span class="icon icon-moderator">Ask EuroSafe Imaging</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="9057aa4e-1cf2-64bf-6b53-bd11155a7d2d" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/9057aa4e-1cf2-64bf-6b53-bd11155a7d2d" data-video-poster="https://universe-files.dacast.com/3bb7dfda-5686-0519-a49d-2c1f964be9ce.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/3bb7dfda-5686-0519-a49d-2c1f964be9ce.jpeg" alt="Abdominopelvic FGI"></div></div><div class="item item-description ec-flex-row"><div><h4>Abdominopelvic FGI</h4><p><span class="icon icon-clock">86:57</span><span class="icon icon-moderator">Ask EuroSafe Imaging</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="497088fa-49ca-aeff-bca1-227159b02e78" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/497088fa-49ca-aeff-bca1-227159b02e78" data-video-poster="https://universe-files.dacast.com/73ef6617-83a5-07a5-8bd3-b7ccf1a4824c" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/73ef6617-83a5-07a5-8bd3-b7ccf1a4824c" alt="RPS 2509-1 - Introduction"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2509-1 - Introduction</h4><p><span class="icon icon-clock">00:34</span><span class="icon icon-moderator">Ines Gil</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="7d55741f-4ec6-e674-8bfc-00e86c731ebb" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/7d55741f-4ec6-e674-8bfc-00e86c731ebb" data-video-poster="https://universe-files.dacast.com/bb16848c-7409-9fb4-7ee8-2ff36b2eaba6" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/bb16848c-7409-9fb4-7ee8-2ff36b2eaba6" alt="RPS 2509-4 - Clinical consequence of vessel perforations during endovascular treatment for acute ischaemic stroke"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2509-4 - Clinical consequence of vessel perforations during endovascular treatment for acute ischaemic stroke</h4><p><span class="icon icon-clock">12:45</span><span class="icon icon-moderator">Matthijs van der Sluijs</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>M. van der Sluijs</u><sup>1</sup>, R. Su<sup>1</sup>, J. Hofmeijer<sup>2</sup>, T. van Walsum<sup>1</sup>, G. Lycklama<sup>3</sup>, A. van Es<sup>4</sup>, S. Cornelissen<sup>1</sup>, A. Van Der Lugt<sup>1</sup>; <sup>1</sup>Rotterdam/NL, <sup>2</sup>Arnhem/NL, <sup>3</sup>The Hague/NL, <sup>4</sup>Leiden/NL<br><b>Purpose or Learning Objective: </b>Endovascular treatment of acute ischaemic stroke can be complicated by vessel perforation. In this work we study the incidence of this specific complication in clinical practice and its effects on functional outcome, including the relation with the location of a vessel perforation.<br><b>Methods or Background: </b>All patients in the MR CLEAN Registry who underwent EVT were analysed for the presence of vessel perforation. DSA imaging of cases mentioned by interventionalist or corelab were studied. Additionally, DSAs of SAH cases were reassessed for potential vessel perforations. In cases where an interventionalist mentioned a perforation, but corelab did not find any, perforation was assumed. Functional outcome was measured using the modified Rankin Scale (mRS) at 90 days. The association between vessel perforation and outcome was analysed with ordinal logistic regression models adjusted for confounding parameters, such as NIHSS at baseline, reperfusion and collaterals. Results were described as unadjusted common (cOR) and adjusted common odds ratio (acOR).<br><b>Results or Findings: </b>Vessel perforation occurred in 74 (2,7%) of 2794 patients who underwent EVT. The proportion of vessel perforations in females was higher compared to non-perforation cases. (63.5% vs 47.5% p=0.009). Anatomical location of perforations was located respectively in ICA-M1 (35%), M2-M3 (45%), posterior (6.3%) and missing in 14.9% of cases. Functional outcome (mRS) was worse in patients with vessel perforations (cOR 0.31, 95%CI 0.20-0.49, acOR 0.50, 95%CI 0.29-0.85) compared to patients without a vessel perforation. No association was observed with anatomical location proximal vs distal (cOR 2.36, 95%CI 0.83-6,73, acOR 1.10, 95%CI 0.29-4.17).<br><b>Conclusion: </b>Incidence of vessel perforation during EVT is low, but has severe clinical consequences, regardless of the anatomical location of the vessel perforation.<br><b>Limitations: </b>Potential bias by reviewing SAH patients, therefore, a higher chance of poor outcome.<br><b>Ethics committee approval: </b>Not applicable.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div><div data-video-id="27f45688-0be1-3cc4-55bf-dd3d00153ca4" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/27f45688-0be1-3cc4-55bf-dd3d00153ca4" data-video-poster="https://universe-files.dacast.com/9ed1766c-0dda-d7c4-be56-5a7146292fc5" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/9ed1766c-0dda-d7c4-be56-5a7146292fc5" alt="RPS 2509-5 - Analysis of the clinical results of the endovascular treatment of indirect carotid-cavernous fistulae"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2509-5 - Analysis of the clinical results of the endovascular treatment of indirect carotid-cavernous fistulae</h4><p><span class="icon icon-clock">06:33</span><span class="icon icon-moderator">José Rodríguez Castro</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>J. Rodríguez Castro</u>, L. Martínez Camblor, M. Martínez-Cachero García, S. Budiño Torres, E. Murias Quintana, J. M. Jiménez Pérez, J. Chaviano Grajera, F. García Arias, P. Vega Valdés; Oviedo/ES<br><b>Purpose or Learning Objective: </b>The purpose of this study was to (1) demonstrate that endovascular treatment of indirect carotid-cavernous fistulae is effective and stable in the long term, (2) describe the techniques and materials most used in our centre, (3) evidence that this treatment reduces patient’s symptomatology, and (4) display the safety of this treatment.<br><b>Methods or Background: </b>A retrospective observational study was carried out. A database was made with 39 interventions in 32 patients with indirect carotid-cavernous fistulae treated in our centre from 2006 to 2020. A collection of epidemiological, clinical, intervention-related, and postoperative variables was made for subsequent statistical analysis.<br><b>Results or Findings: </b>In 28 (72%) of the interventions, complete closure of the fistula was achieved, with 26 patients (81.3%) being achieved in the initial intervention. The fistula was closed with stable treatment in 92% of the cases at 6 months. The access route was also analysed, the most frequent being the venous route through the inferior petrosal sinus (71.9%). Coils were the preferably used material (84.6%). Regarding the improvement of symptoms at 6 months after the intervention, 29 patients (74.3%) had a complete remission of symptoms. Complications were associated barely to 7.7% of the interventions.<br><b>Conclusion: </b>Endovascular treatment of indirect carotid-cavernous fistulae is effective and stable in the long term. The most used and effective access route in our centre is the venous one through the inferior petrosal sinus. The most widely used and effective material for closing indirect carotid-cavernous fistulae are coils. Most of the patients had symptomatic improvement immediately after the intervention and nearly all had no symptoms 6 months after the procedure. Endovascular treatment is a technique that has few perioperative complications and does not usually require reoperation.<br><b>Limitations: </b>This study has a small sample size.<br><b>Ethics committee approval: </b>The ethics committee approval was obtained.<br><b>Funding for this study: </b>No funding was needed.<br></p></div></div><div data-video-id="965dde86-2367-fb12-1438-8185633a9a91" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/965dde86-2367-fb12-1438-8185633a9a91" data-video-poster="https://universe-files.dacast.com/207d25c6-f508-e72f-868d-8d7f40a7f9b8" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/207d25c6-f508-e72f-868d-8d7f40a7f9b8" alt="RPS 2509-6 - Patients\' perception and satisfaction of Vim MRgFUS thalamotomy: comparative evaluation of the influence of interactive video-assisted vs standard informed consent"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2509-6 - Patients\' perception and satisfaction of Vim MRgFUS thalamotomy: comparative evaluation of the influence of interactive video-assisted vs standard informed consent</h4><p><span class="icon icon-clock">06:38</span><span class="icon icon-moderator">Leonardo Pertici</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>L. Pertici</u>, F. Sgalambro, V. Pagliei, F. Bruno, A. Gagliardi, C. Fagotti, A. Barile, A. Splendiani, C. Masciocchi; L\'Aquila/IT<br><b>Purpose or Learning Objective: </b>MRgFUS thalamotomy for the treatment of tremor in ET and PD is usually perceived as a simple procedure by patients, who fail to consider it as an ablative procedure with some risks, that, therefore, requires strong compliance from patients. We evaluated the influence of interactive video-assisted vs standard informed consent on patients’ treatment perception, understanding and satisfaction.<br><b>Methods or Background: </b>We prospectively evaluated 58 patients eligible for MRgFUS thalamotomy. Before treatment, patients were randomly assigned to two groups: group A (28 patients, 15 males, mean age 65 y/o, ET/PD 18/10) received the standard written informed consent and group B (30 patients, 16 males, mean age 64 y/o, ET/PD 19/11) the video-assisted consent. Two questionnaires were then given to all study participants: the first one at the end of the consent process (5 items, score 0-4, total score 20), assessing patients’ understanding of the procedure, the second one at the end of the treatment (2 items, score 0-4, total score 8), assessing patients’ perception and satisfaction based on the expectations they had after the consent information received.<br><b>Results or Findings: </b>In ET patients, mean total understanding and satisfaction scores were 25.2 and 27.6 in groups B and A respectively (p=.234). In PD patients, scores were 23 and 28 in groups B and A. In younger patients (28-75 y/o) scores were 21 (A) and 28 (B), while in the older patients’ group (>75yo) 25 and 22.<br><b>Conclusion: </b>Video-assisted integrated informed consent increases understanding of the procedure and its risks, as well as satisfaction regarding the treatment, especially in younger patients. In older patients and individuals with mild cognitive impairment, the computer interaction may represent a limitation compared to direct communication.<br><b>Limitations: </b>Not applicable.<br><b>Ethics committee approval: </b>Not applicable.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div><div data-video-id="db823f73-4bc7-bde8-92e0-d57664f08884" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/db823f73-4bc7-bde8-92e0-d57664f08884" data-video-poster="https://universe-files.dacast.com/b1988ac6-dcac-8236-1117-6f6f96fac1c0" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 5 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/b1988ac6-dcac-8236-1117-6f6f96fac1c0" alt="RPS 2509-7 - A novel thrombectomy device: an in vitro evaluation of a prototype catheter"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2509-7 - A novel thrombectomy device: an in vitro evaluation of a prototype catheter</h4><p><span class="icon icon-clock">11:49</span><span class="icon icon-moderator">Yasemin Tanyildizi</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>Y. Tanyildizi</u>, S. Krost-Reuhl, A. Heimann, O. Kempski, R. Kloeckner, F. Hahn, M. A. Brockmann; Mainz/DE<br><b>Purpose or Learning Objective: </b>This prototype catheter is a newly-developed distal access catheter featuring a self-expanding, flexible, funnel-shaped tip. The purpose of its design is to reduce the risk of thrombus fragmentation during mechanical thrombectomy and improve first pass recanalisation (TICI 3). In this experimental setup, we preclinically evaluated the effectiveness and navigability of the new catheter.<br><b>Methods or Background: </b>A vessel model was filled with a blood-like-viscous medium, and the image was projected with the corresponding vessel area by camera transmission to corresponding to the conditions in an angiography. Thrombi from porcine blood were placed into the arteria carotis interna of the vascular model and subsequently mechanically thrombectomised with a stent retriever. In the first part, the prototype was compared to a standard distal-access-catheter without using an external catheter. (N=20 for each catheter). In the second part, the prototype was inserted through a guiding catheter (n=11) to determine the navigability performance.<br><b>Results or Findings: </b>In the first experimental series, mechanical thrombectomy was successful 19 out of 20 times (95% success rate) for the prototype catheter versus 15 out of 20 times (75% success rate) for the standard distal-access catheter. In the second experimental series, the prototype catheter achieved first-pass recanalisation 10 out of 11 times (91% success rate) and 1 out of 11 times at second pass (9%).<br><b>Conclusion: </b>This series of experiments demonstrated higher first-pass recanalisation rates for the newly-developed funnel-shaped prototype featuring a self-expanding tip in comparison to a cylindrical standard distal-access-catheter.<br><b>Limitations: </b>This study is limited by (1) no in vivo testing and (2) the limited number of thrombectomies.<br><b>Ethics committee approval: </b>The ethics committee approved this study (AZ G 14-1-093 and AZ 23177 07 A16 -1-001 AFW).<br><b>Funding for this study: </b>This study was funded by the WIPANO (Wissens- und Technologietransfer durch Patente und Normen) and Bundesministerium für Wirtschaft und Energie.<br></p></div></div>
<div data-video-id="a9285a3d-647b-4b04-59eb-dea13adf0c14" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/a9285a3d-647b-4b04-59eb-dea13adf0c14" data-video-poster="https://universe-files.dacast.com/3015468f-6b8f-990b-fdb9-83304e20967e" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/3015468f-6b8f-990b-fdb9-83304e20967e" alt="RPS 2511-1 - Introduction"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2511-1 - Introduction</h4><p><span class="icon icon-clock">02:51</span><span class="icon icon-moderator">Teresa Nunes</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="7a11e184-fbdf-17fc-28b7-59a0eaf306fe" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/7a11e184-fbdf-17fc-28b7-59a0eaf306fe" data-video-poster="https://universe-files.dacast.com/fa607603-cb0b-5ed7-9052-b796e2db36b3" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/fa607603-cb0b-5ed7-9052-b796e2db36b3" alt="RPS 2511-2 - AI-enhanced multi-shot multi-contrast EPI protocol- a preliminary clinical experience"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2511-2 - AI-enhanced multi-shot multi-contrast EPI protocol- a preliminary clinical experience</h4><p><span class="icon icon-clock">06:26</span><span class="icon icon-moderator">Silvia Pistocchi</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>S. Pistocchi</u><sup>1</sup>, T. Hilbert<sup>1</sup>, D. Rodriguez<sup>1</sup>, B. Clifford<sup>2</sup>, T. Feiweier<sup>3</sup>, Z. Hosseini<sup>4</sup>, V. Dunet<sup>1</sup>, S. Cauley<sup>2</sup>, T. Kober<sup>1</sup>; <sup>1</sup>Lausanne/CH, <sup>2</sup>Boston, MA/US, <sup>3</sup>Erlangen/DE, <sup>4</sup>Atlanta, GA/US<br><b>Purpose or Learning Objective: </b>The duration of MRI acquisitions is a major limitation of this imaging modality, but especially for time-sensitive applications such as stroke or when imaging non-compliant or very young patients. Here we aim to evaluate the image quality of a new fast AI-enhanced protocol utilising a prototype multi-shot, multi-contrast EPI sequence and compare it to the standard imaging protocol at our institution.<br><b>Methods or Background: </b>Between the 1st and 31st of June 2021, the AI-enhanced multi-shot multi-contrast EPI prototype sequence was added to our standard protocol in 30 brain MRI examinations with mixed clinical indications. The prototype sequence provided five contrasts (2D sagittal T1, axial FLAIR, T2GE, DWI) in a total of two minutes of scan time. Images were prospectively reviewed and independently compared to the standard 7:30 min: sec protocol by two experienced neuroradiologists. Six items (overall image quality, grey-white matter interface, basal ganglia delineation, sulci, motion, and susceptibility artefacts) were assessed on each generated contrast using a 4-point Likert scale. Inter-observer concordance was assessed using the Gwet AC1 coefficient.<br><b>Results or Findings: </b>The AI-enhanced multi-shot multi-contrast EPI protocol allowed a 73% reduction of acquisition time and showed good to excellent overall image quality (mean score ≥3). Inter-observer concordance was good to excellent (Gwet AC1: 0.52 to 1.0). Motion and susceptibility artefacts were mostly rated as absent or minor with no adverse effect on diagnostic use, but with more heterogeneous inter-observer concordance (Gwet AC1: 0.27 to 0.83).<br><b>Conclusion: </b>The AI-enhanced multi-shot multi-contrast EPI protocol demonstrated good image quality with a 73% reduction in acquisition time. Further studies evaluating diagnostic performance in time-sensitive clinical applications should be planned.<br><b>Limitations: </b>This study is monocentric and has a small sample size.<br><b>Ethics committee approval: </b>Not applicable.<br><b>Funding for this study: </b>No funding has been used for this study.<br></p></div></div><div data-video-id="d76cbdf8-8f94-a9bf-27de-7b36ddd2c78a" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/d76cbdf8-8f94-a9bf-27de-7b36ddd2c78a" data-video-poster="https://universe-files.dacast.com/ca379006-c4bf-8985-7afd-5528fb7b8487" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/ca379006-c4bf-8985-7afd-5528fb7b8487" alt="RPS 2511-3 - Comparison of image quality improvements among deep learning reconstruction, hybrid-type and model-based iterative reconstruction on brain contrast-enhanced CT angiography for ultra-high-resolution CT"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2511-3 - Comparison of image quality improvements among deep learning reconstruction, hybrid-type and model-based iterative reconstruction on brain contrast-enhanced CT angiography for ultra-high-resolution CT</h4><p><span class="icon icon-clock">06:27</span><span class="icon icon-moderator">Kazuhiro Murayama</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>K. Murayama</u><sup>1</sup>, Y. Ohno<sup>1</sup>, H. Ikeda<sup>1</sup>, H. KImata<sup>2</sup>, N. Akino<sup>2</sup>, K. Fujii<sup>2</sup>, Y. Kataoka<sup>1</sup>, A. Katagata<sup>1</sup>, H. Toyama<sup>1</sup>; <sup>1</sup>Toyoake/JP, <sup>2</sup>Otawara/JP<br><b>Purpose or Learning Objective: </b>To directly compare the capability for image quality improvements on brain contrast-enhanced CT angiography (CE-CTA) for ultra-high-resolution CT (UHR-CT) in intracranial aneurysms patients among deep learning reconstruction (DLR) and hybrid-type iterative reconstruction (IR) and model-based IR.<br><b>Methods or Background: </b>21 intracranial aneurysm patients underwent brain CE-CTA and reconstructed by DLR, hybrid-type IR and model-based IR using a UHR-CT system with super-high resolution mode (SHR: 0.25mm×160 rows/1792 channels). CT values at MCA were assessed by ROI measurements. Image J software was used to generate the profile curves. To assess the capability for improvement of spatial resolution with UHR-CT and DLR, full width at half maximum (FWHM), the width of the edge rise distance (ERD) and the edge rise slope (ERS) were measured at each vessel. For qualitative assessment, overall image quality, artefact, aneurysm, and vascular depiction levels were assessed by 5-point scales by two board-certified radiologists. CT values, ERS and all qualitative indexes were compared by Tukey’s HSD test. Inter-observer agreements of each method were evaluated by kappa statistics with χ2 test.<br><b>Results or Findings: </b>CT values and ERS of model-based IR and DLR were significantly higher than those of hybrid-type IR at MCA (p<0.05). Inter-observer agreement of each index by all methods was determined as moderate, substantial or excellent (0.51≤κ≤0.92, p<0.001). In addition, overall image quality and artefact of DLR were significantly improved as compared with others (p<0.05). Aneurysm and vascular depiction levels had no significant difference among all methods (p>0.05).<br><b>Conclusion: </b>DLR has a potential for image quality improvements than hybrid-type and model-based IR on brain CE-CTA for UHR-CT.<br><b>Limitations: </b>Not applicable.<br><b>Ethics committee approval: </b>This retrospective study was approved by the Institutional Review Board of Fujita Health University.<br><b>Funding for this study: </b>This study was financially supported by Canon Medical Systems Corporation.<br></p></div></div><div data-video-id="f33a24bd-96cc-431d-3336-82799cd8ea12" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/f33a24bd-96cc-431d-3336-82799cd8ea12" data-video-poster="https://universe-files.dacast.com/03aa2dce-4a13-b4ac-113a-f08db2a3f108" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/03aa2dce-4a13-b4ac-113a-f08db2a3f108" alt="RPS 2511-5 - Development and validation of a deep learning-based automatic brain volumetry for parkinsonian syndromes using 3D T1-weighted images"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2511-5 - Development and validation of a deep learning-based automatic brain volumetry for parkinsonian syndromes using 3D T1-weighted images</h4><p><span class="icon icon-clock">08:40</span><span class="icon icon-moderator">Seongken Kim</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>S. Kim</u>, C. Suh, H. Oh, E. P. Hong, S. Park, J. K. SUNG, W. H. SHIM, S. J. Kim; Seoul/KR<br><b>Purpose or Learning Objective: </b>To develop and validate a deep learning-based automatic brain volumetry (DLABV) for the differentiation of parkinsonian syndromes using 3D T1-weighted brain MR images.<br><b>Methods or Background: </b>A DLABV was trained using a dataset of 3D T1-weighted brain MR images. 2D U-Net model was used for model architecture. The training dataset which contains 300 cognitively normal subjects (CN, 129 men) was labelled with FreeSurfer 6.0 brainstem substructure module. The test dataset consists of 207 CN, 52 progressive supranuclear palsy (PSP) patients, 65 multiple system atrophy (MSA) patients, and 189 Parkinson disease (PD) patients. The volume of the midbrain, pons, medulla, SCP, the midbrain-pons area ratio (MP) and the midbrain-pons volume ratio (MP_vol) were measured for differentiation of parkinsonian syndromes. Normalised volume using intracranial volume (ICV) was also used. To distinguish between each group, the receiver operating characteristic curve and area under the curve (AUC) was calculated and classification accuracy was measured by support vector machine (SVM).<br><b>Results or Findings: </b>Compared with simple volumetry, volumetry using ICV normalisation showed more accurate performance in the differentiation of parkinsonian syndromes. The AUC in PSP vs PD using normalised midbrain volume was 0.89. In addition, the AUC in MSA vs PD using normalised pons volume was 0.97. MP_vol in MSA patients were significantly larger than in PSP patients and AUC was 0.98. Using normalised volume and MP showed highest classification accuracy.<br><b>Conclusion: </b>The DLABV using ICV normalisation allowed an accurate differentiation of parkinsonian syndromes using 3D T1-weighted brain MR images.<br><b>Limitations: </b>It is unclear whether the early parkinsonian syndromes can be differentiated using brain volumetry since our study did not target early parkinsonian syndrome patients.<br><b>Ethics committee approval: </b>Our institutional review board approved this study.<br><b>Funding for this study: </b>This study has received funding by the National Research Foundation of Korea.<br></p></div></div><div data-video-id="fdfe2f12-92c4-c351-3d32-6c274597e9c4" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/fdfe2f12-92c4-c351-3d32-6c274597e9c4" data-video-poster="https://universe-files.dacast.com/6b00e2ba-22c3-115f-3561-3c3c7f76db62" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 5 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/6b00e2ba-22c3-115f-3561-3c3c7f76db62" alt="RPS 2511-7 - Patient-specific vs normative brain connectivity: a symptom-specific artificial intelligence-based comparison"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2511-7 - Patient-specific vs normative brain connectivity: a symptom-specific artificial intelligence-based comparison</h4><p><span class="icon icon-clock">07:48</span><span class="icon icon-moderator">Quirin Strotzer</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b>Q. D. Strotzer, J. Schlaier, A. Beer; Regensburg/DE<br><b>Purpose or Learning Objective: </b>Structural connectivity based on diffusion-weighted magnetic resonance imaging (DWI) is gaining importance in research and clinical use in fields like deep brain stimulation. Individual DWI is often unavailable. Therefore, normative connectomes based on averaged whole-brain tractography are a practical alternative. Comparisons of these concepts are sparse. Here, we compared patient-specific and normative approaches by their ability to predict the effects of deep brain stimulation using a symptom-specific, machine learning-based approach.<br><b>Methods or Background: </b>Twenty-one patients who received bilateral subthalamic deep brain stimulation for Parkinson’s disease were included. For every electrode contact (168 in total), we computed tractography patterns based on individual DWI and two normative connectomes (32 healthy individuals, 90 Parkinson’s patients). Connectivity strength to 36 brain structures was calculated for every electrode contact, resulting in a dataset of 168 observations (electrode contacts) with 36 attributes (connectivity strength) for each connectome. Stimulation-associated symptom mitigation and side effects were assessed for every contact. We tested the prediction of stimulation outcomes based on connectivity strength using several supervised learning algorithms.<br><b>Results or Findings: </b>Support vector machines yielded overall the best results. Averaged across all clinical classes (symptoms, side effects), the individual connectome achieved the highest area under the receiver operating characteristic curve (AUC-ROC; .81) compared to the normative healthy (.76) and disease-matched connectomes (.74). By clinical class, there were significant differences for paresthesia and autonomous side effects in favour of the individual connectome. Results differed considerably between clinical classes, from a mean AUC-ROC of 0.68 for paraesthesia to 0.91 for hyperkinesia.<br><b>Conclusion: </b>Clinical effects may be mediated by different networks, as revealed by tractography methods based on DWI. Individual connectomes may be superior in predicting stimulation effectiveness.<br><b>Limitations: </b>This study is done with single-centre data and has a limited sample size.<br><b>Ethics committee approval: </b>Approval by the local ethics committee.<br><b>Funding for this study: </b>No funding was received for this study.<br></p></div></div><div data-video-id="520ae6a6-482c-5bd9-d383-aee0fc6708f8" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/520ae6a6-482c-5bd9-d383-aee0fc6708f8" data-video-poster="https://universe-files.dacast.com/5c481ba3-18b5-4c57-9b91-8e61496b2650" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 6 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/5c481ba3-18b5-4c57-9b91-8e61496b2650" alt="RPS 2511-8 - Real-world evaluation of artificial intelligence software for cerebral large vessel occlusion detection in CT angiography"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2511-8 - Real-world evaluation of artificial intelligence software for cerebral large vessel occlusion detection in CT angiography</h4><p><span class="icon icon-clock">09:53</span><span class="icon icon-moderator">Kicky van Leeuwen</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>K. G. van Leeuwen</u><sup>1</sup>, R. Becks<sup>1</sup>, S. Schalekamp<sup>1</sup>, B. Van Ginneken<sup>1</sup>, M. J. Rutten<sup>2</sup>, M. De Rooij<sup>1</sup>, F. J. A. Meijer<sup>1</sup>; <sup>1</sup>Nijmegen/NL, <sup>2</sup>\'S-Hertogenbosch/NL<br><b>Purpose or Learning Objective: </b>The commercially available AI tool (StrokeViewer v2, Nicolab) supports the diagnostic process of stroke by detecting large vessel occlusions (LVO) on CTA. We prospectively evaluated this tool in our department to monitor safety and impact.<br><b>Methods or Background: </b>We implemented the software with the goal to improve the diagnosis of LVO and elevate the diagnostic confidence of the radiologist (resident). We used quantitative measures (data from clinical systems, vendor log files) and qualitative measures (user survey) to analyse diagnostic performance, number of users, login attempts, radiologists’ diagnostic confidence, and user experience.<br><b>Results or Findings: </b>In total, 226 CTAs with a clinical indication of stroke between January-June 2021 were prospectively evaluated. Thirteen cases of posterior circulation and distal vessel occlusions were excluded as they were outside the intended use of the AI tool. The AI tool missed 12 of the 36 occlusions in the middle cerebral or intracranial internal carotid artery (M1=1, M2=10, ICA=1) resulting in an accuracy of 86.4%. Irrespective of location, the sensitivity was 77.8% and specificity 90.4%. The number of monthly unique users varied between 8 and 24 radiologists/residents. Log in attempts dropped after the initial month (which included training) to a monthly average of 44 attempts. The diagnostic confidence did not increase during the use of the tool. The likelihood that users would recommend StrokeViewer to colleagues was rated 4.5/10.<br><b>Conclusion: </b>Over six months, the use of StrokeViewer dropped and users did not sense improvement of diagnostic confidence. Measures have been taken to stimulate adoption for the latter six months of the trial period.<br><b>Limitations: </b>Because of the prospective character, no comparison could be made between radiologists supported by AI vs radiologists without AI.<br><b>Ethics committee approval: </b>Not applicable.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div>
<div data-video-id="55ee4ca0-857a-8fd9-fd33-5a1eac0f054f" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/55ee4ca0-857a-8fd9-fd33-5a1eac0f054f" data-video-poster="https://universe-files.dacast.com/3b5d401e-ea1d-d629-188c-ebf693b972f4" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/3b5d401e-ea1d-d629-188c-ebf693b972f4" alt="CC-1 - Closing Ceremony"></div></div><div class="item item-description ec-flex-row"><div><h4>CC-1 - Closing Ceremony</h4><p><span class="icon icon-clock">03:23</span><span class="icon icon-moderator">Regina G.H. Beets-Tan</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="c2626f4e-4733-1278-0056-6c97252adc56" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/c2626f4e-4733-1278-0056-6c97252adc56" data-video-poster="https://universe-files.dacast.com/a6a540d5-ce57-1686-f16a-a3665cf7c920" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/a6a540d5-ce57-1686-f16a-a3665cf7c920" alt="RPS 2611-1 - Introduction"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2611-1 - Introduction</h4><p><span class="icon icon-clock">00:51</span><span class="icon icon-moderator">Agata Majos</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="a8f4f335-0dcf-4ff3-5466-ea611d4a7471" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/a8f4f335-0dcf-4ff3-5466-ea611d4a7471" data-video-poster="https://universe-files.dacast.com/3757efb6-669f-98c6-edc7-941c8ab76684" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/3757efb6-669f-98c6-edc7-941c8ab76684" alt="RPS 2611-3 - Preliminary study on subclinical brain alterations in patients with asymptomatic carotid vulnerable plaques using DTI"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2611-3 - Preliminary study on subclinical brain alterations in patients with asymptomatic carotid vulnerable plaques using DTI</h4><p><span class="icon icon-clock">07:31</span><span class="icon icon-moderator">Shuai Yang.mp4</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>S. Yang</u>; Changsha/CN<br><b>Purpose or Learning Objective: </b>To assess the alterations in the topological properties of the white matter brain network in carotid vulnerable plaque group and carotid hard plaque group based on magnetic resonance diffusion tensor imaging(DTI).<br><b>Methods or Background: </b>One hundred and nineteen volunteers were included and performed DTI examination, among who, 58 volunteers had carotid vulnerable plaques, 23 volunteers had carotid hard plaques. The differences in the topological properties among the three groups were explored at both the global and local levels using one-way ANOVA and Bonferroni t-test (p<0.05). Then network-based statistic (NBS) method was employed to assess the alterations of the interregional connections among three groups (NBS corrected, p<0.001 at voxel level, p<0.05 at cluster level, permutated for 5000 times).<br><b>Results or Findings: </b>Compared with the control group and vulnerable plaque group, the hard plaque group demonstrated significantly increased betweenness centrality in the left supramarginal gyrus region. Compared with the control group and hard plaque group, the vulnerable plaque group demonstrated significantly decreased nodal clustering coefficiency in the left putamen region. The vulnerable-plaque group presented a significantly decreased subnetwork component and two significantly increased subnetwork components in the NBS analysis results.<br><b>Conclusion: </b>The topological organisation of white matter networks in carotid hard plaque group is different from vulnerable plaque group, which tends to increase the local efficiency of network communication to compensate. Furthermore, the carotid vulnerable plaque group showed more disorder of topological properties.<br><b>Limitations: </b>First, we were limited by the cross-sectional design and small sample size of this study. Second, we only analysed the anatomical connectivity of white matter. The combination of structural and functional network analysis might provide a more comprehensive perspective for the disorder of topological properties in patients with carotid vulnerable plaques.<br><b>Ethics committee approval: </b>Approved by the institutional review boards of Xiangya Hospital.<br><b>Funding for this study: </b>No funding was received for this study.<br></p></div></div><div data-video-id="f43e725b-f01a-09dc-a417-78b3c145c8b9" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/f43e725b-f01a-09dc-a417-78b3c145c8b9" data-video-poster="https://universe-files.dacast.com/4b5806bd-7570-ecb1-7f25-76ddaf1c92a9" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/4b5806bd-7570-ecb1-7f25-76ddaf1c92a9" alt="RPS 2611-5 - The impact of acceleration factors of compressed sensing on the image quality of 3D-TOF-MRA for cervical vessels"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2611-5 - The impact of acceleration factors of compressed sensing on the image quality of 3D-TOF-MRA for cervical vessels</h4><p><span class="icon icon-clock">04:50</span><span class="icon icon-moderator">Qingwei Song</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>Q. Song</u>; Dalian/CN<br><b>Purpose or Learning Objective: </b>Explore the impact of acceleration factors of CS on the image quality of 3D-TOF-MRA for cervical vessels.<br><b>Methods or Background: </b>22 healthy volunteers were recruited and underwent the 3D-TOF MRA scan of neck vessels on a 3.0 T MR scanner. Four groups with different acceleration schemes were set up in our study, group A with a routine clinical setup of SENSE acceleration factor 3, and groups B, C, and D with CS factors of 4, 6, and 8. Regions of interest were placed manually at both sides of the carotid artery and nearby sternocleidomastoid muscle by experienced radiologists for the measurement of SNR and CNR. The two observers used a four-point scoring method to evaluate the quality of the four groups of images. The Kappa statistics were calculated for determining the interobserver agreement. The assessment of intermethod agreement was based on the evaluation of the senior physicians. Kruskal-Wallis test was employed to assess the difference of SNR, CNR and image scores between the 4 groups. Mann-Whitney U test was used to make a pairwise comparison.<br><b>Results or Findings: </b>There were no statistically significant differences in SNR, CNR between the four groups. However, if CS acceleration factor of 8 was used, the subjective scores decreased obviously (p < 0.05, Table. 3). And no significant differences in image quality were detected between conventional SENSE acceleration with a factor of 3 and CS acceleration with factors of 4 and 6.<br><b>Conclusion: </b>CS acceleration factor of 6 is recommended for clinical 3D-TOF carotid MRA to achieve an optimal balance between imaging time and image quality.<br><b>Limitations: </b>This study was limited by the few amount of volunteers.<br><b>Ethics committee approval: </b>This study has been approved by the local IRB.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div><div data-video-id="92cba8a1-1ad6-1e83-1c21-fff479d04557" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/92cba8a1-1ad6-1e83-1c21-fff479d04557" data-video-poster="https://universe-files.dacast.com/69e032b9-fbe0-dc2e-70f0-e97831f33f62" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/69e032b9-fbe0-dc2e-70f0-e97831f33f62" alt="RPS 2611-6 - Effect of MRI acquisition parameters on accuracy and precision of phase-contrast measurements in a small lumen vessel phantom"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2611-6 - Effect of MRI acquisition parameters on accuracy and precision of phase-contrast measurements in a small lumen vessel phantom</h4><p><span class="icon icon-clock">07:22</span><span class="icon icon-moderator">Maria Correia de Verdier</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>M. Correia de Verdier</u>, J. Wikström; Uppsala/SE<br><b>Purpose or Learning Objective: </b>To assess the effects of spatial resolution, number of excitations (NEX) and velocity encoding (VENC) on accuracy and precision of phase-contrast (PC) MRI measurements in a vessel phantom with a small lumen diameter.<br><b>Methods or Background: </b>A 3 T scanner and a 32-channel head coil were used for all the PC-MRI measurements. An in vitro flow model consisting of a plastic tube (2.3 mm inner diameter) passing through an agar gel was constructed to provide a continuous flow. The flow rate was controlled using a reservoir with a scale and timer and used as the standard reference. A PC-MRI sequence was performed with varying voxel size (0.6 x 0.8 x 5 mm, 1 x 1 x 5 mm, 1.2 x 1.2 x 5 mm), NEX (1, 2, 3) and VENC (200, 300, 400 cm/s). Measurements were repeated 9 times for each setting. Mean flow and peak velocity were calculated for each combination of settings and the least detectable difference (LDD) was computed.<br><b>Results or Findings: </b>All PC-MRI mean flow measurements were higher than our standard reference (mean values ranging from 7.3 to 9.5 ml/s compared with 6.5 ml/s). Decreasing voxel size improved the accuracy of mean flow measurements, with measured values changing from 9.5 to 7.3 ml/s. LDD for mean flow decreased with increasing voxel size and NEX (p<0.05). LDD for peak velocity decreased with increasing voxel size (p<0.05). No change in LDD was observed with different VENC settings.<br><b>Conclusion: </b>Accuracy in PC-MRI flow measurements in a small vessel phantom is low, with higher measured values than control. Improved accuracy is obtained with increased spatial resolution. Improved precision is obtained with decreased spatial resolution and increased NEX.<br><b>Limitations: </b>Not applicable.<br><b>Ethics committee approval: </b>Not applicable.<br><b>Funding for this study: </b>Not applicable.<br></p></div></div><div data-video-id="b5c77485-52cf-924d-579d-6ffc0c128197" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/b5c77485-52cf-924d-579d-6ffc0c128197" data-video-poster="https://universe-files.dacast.com/6d1e01a9-2fa2-b889-0bca-eee4592b2a97" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 5 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/6d1e01a9-2fa2-b889-0bca-eee4592b2a97" alt="RPS 2611-7 - Collateral status at single-delay arterial spin labelling MRI can non-invasively predict cerebral hyperperfusion after carotid endarterectomy"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2611-7 - Collateral status at single-delay arterial spin labelling MRI can non-invasively predict cerebral hyperperfusion after carotid endarterectomy</h4><p><span class="icon icon-clock">05:25</span><span class="icon icon-moderator">Xiaoyuan Fan</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>X. Fan</u>, T. Lin, Z. Lai, H. You, J. Qu, F. Feng; Beijing/CN<br><b>Purpose or Learning Objective: </b>To explore and compare the predictive ability of collateral score systems assessed with single-delay ASL and conventional CT/MRI protocols for cerebral hyperperfusion after carotid endarterectomy (CEA).<br><b>Methods or Background: </b>Eighty-five patients who underwent CEA between May 2015 and July 2021 were included (mean age 65.3±7.1 years, 76.5% male). Cerebral hyperperfusion was defined as an increase in cerebral blood flow >100% compared with preoperative values. Preoperative ASL images were scored based on the presence of arterial transit artefacts (ATAs) in 10 regions of interest corresponding to ASPECTS methodology as follows: 0, no or minimal ASL signal; 1, low/moderate ASL signal with ATA; 2, high ASL signal with ATA; and 3, normal perfusion without ATA. The degree of stenosis, primary and secondary collaterals were evaluated on conventional CTA, MRA and T2 FLAIR images.<br><b>Results or Findings: </b>Cerebral hyperperfusion was presented in 16 (18.8%) patients. Preoperative ASL score was an independent predictor of cerebral hyperperfusion (OR=0.47, 95% CI [0.32-0.71], p<0.001). ROC curve analysis revealed that the predictive ability for cerebral hyperperfusion was statistically higher for ASL score (AUC=0.98, 95% CI [0.923-0.998]) than for degree of stenosis (AUC=0.786, 95% CI [0.684-0.868], p=0.002), type of circle of Willis (AUC=0.771, 95% CI [0.667-0.855], p=0.002) or leptomeningeal collaterals (AUC=0.798, 95% CI [0.697-0.877],p=0.004). The ASL score performed as well as the combination of degree of stenosis, type of circle of Willis and leptomeningeal collaterals (AUC=0.947, 95% CI [0.876, 0.984],p=0.258).<br><b>Conclusion: </b>Single-delay ASL can non-invasively predict cerebral hyperperfusion after CEA in patients with carotid stenosis.<br><b>Limitations: </b>The sample size was relatively small.<br><b>Ethics committee approval: </b>This study was approved by the Medical Ethics Committee of the Peking Union Medical College Hospital.<br><b>Funding for this study: </b>This work was supported by the Beijing Natural Science Foundation grant (L182067) and National Nature Science Foundation of China grant (82071899).<br></p></div></div><div data-video-id="2aad00f3-30ec-5894-4f1f-3aa22058c068" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/2aad00f3-30ec-5894-4f1f-3aa22058c068" data-video-poster="https://universe-files.dacast.com/438784bd-1153-fcf1-b3f5-3366837bbb27" data-ads="[{"id":"42aa5ff8-f863-e39b-c091-e8156556fd64","url":"https:\\/\\/iframe.dacast.com\\/vod\\/acae82153ef4d7a7344ae4eaa86af534\\/42aa5ff8-f863-e39b-c091-e8156556fd64"}]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 6 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/438784bd-1153-fcf1-b3f5-3366837bbb27" alt="RPS 2611-8 - Microbleeds in cerebral fat embolism"></div></div><div class="item item-description ec-flex-row"><div><h4>RPS 2611-8 - Microbleeds in cerebral fat embolism</h4><p><span class="icon icon-clock">09:11</span><span class="icon icon-moderator">Omar Giyab</span></p></div><div class="item item-button"><button class="read-more">Read More</button></div></div></div><div class="ec-lecture-description"><p><b>Author Block: </b><u>O. Giyab</u>, B. L. Balogh, P. P. Bogner, G. Orsi, A. Tóth; Pécs/HU<br><b>Purpose or Learning Objective: </b>Our aim was to prove our hypothesis according to which cerebral fat embolism commonly presents with a characteristic microbleed pattern on MRI.<br><b>Methods or Background: </b>We searched the literature and the database of our home institution for cases of cerebral fat embolism (CFE). The hypothesized CFE characteristic microbleed pattern (diffuse presence of round microbleeds of monotonous size in the subcortical white matter involving but not limited to the U-fibers, internal capsule and the corpus callosum, mostly sparing the corona radiata and the non-subcortical centrum semiovale on T2* GRE or SWI images), the starfield pattern as described by Parizel et al (scattered bright spots on a dark background in DWI with diffusion restriction), and confluent diffusion restriction in the corpus callosum were statistically compared. Temporal characteristics of the imaging features were also analysed.<br><b>Results or Findings: </b>141 patients with cerebral fat embolism were included. The characteristic ""walnut kernel microbleed pattern"" was found in 89.74%. Diffusion abnormality in general was seen in 97.64%. A definitive starfield pattern was ascertained in 68.5%. Confluent restricted diffusion was seen in the corpus callosum in 77.27%. The walnut kernel microbleed pattern had a more consistent presence among time periods compared to the starfield pattern.<br><b>Conclusion: </b>Microbleeds in CFE are very common and mainly occur in a characteristic pattern in SWI or T2*, which along with the starfield pattern and corpus callosum diffusion restriction in DWI/ADC appear to be the most important imaging markers of CFE and may aid the differential diagnosis in clinically equivocal cases.<br><b>Limitations: </b>More articles investigated diffusion abnormalities than microbleeds.<br><b>Ethics committee approval: </b>The Institutional Review Board approved the institutional medical database search that was performed related to this study.<br><b>Funding for this study: </b>Funding was received from the Bolyai Scholarship Hungarian Academy of Science.<br></p></div></div>
<div data-video-id="a0350d9b-71fb-e55d-b6da-330f3374c6f6" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/a0350d9b-71fb-e55d-b6da-330f3374c6f6" data-video-poster="https://universe-files.dacast.com/21536d98-0ea0-2394-88a4-ce9f1dd9b1c5" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/21536d98-0ea0-2394-88a4-ce9f1dd9b1c5" alt="1_1 - Structured reporting with BIRADS"></div></div><div class="item item-description ec-flex-row"><div><h4>1_1 - Structured reporting with BIRADS</h4><p><span class="icon icon-clock">43:14</span><span class="icon icon-moderator">Isabelle Thomassin-Naggara, / </span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="cb161796-464a-8115-8253-c6fd609c39db" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/cb161796-464a-8115-8253-c6fd609c39db" data-video-poster="https://universe-files.dacast.com/5bd81940-4dfc-d98d-347a-8db9d7418267" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 2 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/5bd81940-4dfc-d98d-347a-8db9d7418267" alt="1_2 - Risk-based breast screening"></div></div><div class="item item-description ec-flex-row"><div><h4>1_2 - Risk-based breast screening</h4><p><span class="icon icon-clock">49:59</span><span class="icon icon-moderator">Sarah Vinnicombe, / </span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="9733a899-0883-a3ba-ba58-4497ddc8abdb" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/9733a899-0883-a3ba-ba58-4497ddc8abdb" data-video-poster="https://universe-files.dacast.com/1d71c781-6b07-1ed3-ba2e-9b22474cbcd4" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 3 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/1d71c781-6b07-1ed3-ba2e-9b22474cbcd4" alt="1_3 - The digital revolution in mammography"></div></div><div class="item item-description ec-flex-row"><div><h4>1_3 - The digital revolution in mammography</h4><p><span class="icon icon-clock">35:52</span><span class="icon icon-moderator">Thomas Helbich, / </span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="1ac8962a-0f70-c958-7b21-06869fa483f7" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/1ac8962a-0f70-c958-7b21-06869fa483f7" data-video-poster="https://universe-files.dacast.com/fe2ce295-4776-d76a-6c6b-907ef357e54c" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 4 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/fe2ce295-4776-d76a-6c6b-907ef357e54c" alt="2_1 - Ultrasound of the breast: from diagnosis to therapy monitoring"></div></div><div class="item item-description ec-flex-row"><div><h4>2_1 - Ultrasound of the breast: from diagnosis to therapy monitoring</h4><p><span class="icon icon-clock">43:45</span><span class="icon icon-moderator">Isabelle Thomassin-Naggara, / </span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="0289fe7a-613f-fc5c-3ee8-6e8debac0b7c" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/0289fe7a-613f-fc5c-3ee8-6e8debac0b7c" data-video-poster="https://universe-files.dacast.com/6517e6e0-fcf7-835e-2515-6ab330582447" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 5 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/6517e6e0-fcf7-835e-2515-6ab330582447" alt="2_2 - MRI of the breast: when and how?"></div></div><div class="item item-description ec-flex-row"><div><h4>2_2 - MRI of the breast: when and how?</h4><p><span class="icon icon-clock">40:59</span><span class="icon icon-moderator">Thomas Helbich, / </span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="d37eabb1-8615-1007-bae3-d6cd3ba9a495" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/d37eabb1-8615-1007-bae3-d6cd3ba9a495" data-video-poster="https://universe-files.dacast.com/a78fe73f-6b93-74e9-bd70-3a965558b4fc" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 6 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/a78fe73f-6b93-74e9-bd70-3a965558b4fc" alt="2_3 - Breast interventions: a primer"></div></div><div class="item item-description ec-flex-row"><div><h4>2_3 - Breast interventions: a primer</h4><p><span class="icon icon-clock">42:57</span><span class="icon icon-moderator">Sarah Vinnicombe, / </span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="cec8909d-988d-4b50-809c-a5d468c5e7f4" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/cec8909d-988d-4b50-809c-a5d468c5e7f4" data-video-poster="https://universe-files.dacast.com/8946f345-9e59-cb85-d7bb-08df10201264.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/8946f345-9e59-cb85-d7bb-08df10201264.jpeg" alt="Lower Limb FGI"></div></div><div class="item item-description ec-flex-row"><div><h4>Lower Limb FGI</h4><p><span class="icon icon-clock">80:47</span><span class="icon icon-moderator">Ask EuroSafe Imaging</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
<div data-video-id="4ff0c16d-7d6f-7a7f-cc5b-66b45f5f5f8e" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/4ff0c16d-7d6f-7a7f-cc5b-66b45f5f5f8e" data-video-poster="https://universe-files.dacast.com/faf1c1af-1607-fc03-9b2e-08d1cc9a9c3b.jpeg" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 1 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/faf1c1af-1607-fc03-9b2e-08d1cc9a9c3b.jpeg" alt="Radiation Protection of Patients in FGI"></div></div><div class="item item-description ec-flex-row"><div><h4>Radiation Protection of Patients in FGI</h4><p><span class="icon icon-clock">85:19</span><span class="icon icon-moderator">Ask EuroSafe Imaging</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>
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Anatomical variants and congenital malformations diagnosed in adulthood"></div></div><div class="item item-description ec-flex-row"><div><h4>2_2 - Anatomical variants and congenital malformations diagnosed in adulthood</h4><p><span class="icon icon-clock">45:04</span><span class="icon icon-moderator">Guillaume Chassagnon / FR</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div><div data-video-id="4f134d1c-c0f5-158e-8186-81f0824698b9" data-video-url="https://iframe.dacast.com/vod/acae82153ef4d7a7344ae4eaa86af534/4f134d1c-c0f5-158e-8186-81f0824698b9" data-video-poster="https://universe-files.dacast.com/030d2da3-1bb7-dc13-ba05-2e24948dbf79" data-ads="[]" data-ads-min-time="10" class="ec-lecture-item-row ec-library-tile-js ec-congress-hover"><div class="ec-lecture-info"><div class="item item-number"> 6 </div><div class="item item-img"><div class="item-img-container"><img src="https://universe-files.dacast.com/030d2da3-1bb7-dc13-ba05-2e24948dbf79" alt="2_3 - Nodular patterns"></div></div><div class="item item-description ec-flex-row"><div><h4>2_3 - Nodular patterns</h4><p><span class="icon icon-clock">46:48</span><span class="icon icon-moderator">Helmut Prosch / AT</span></p></div></div></div><div class="ec-lecture-description"><p></p></div></div>';
my $regex = qr/(?<=alt=\")(.*?)(?=\"><)/mp;
if ( $str =~ /$regex/g ) {
print "Whole match is ${^MATCH} and its start/end positions can be obtained via \$-[0] and \$+[0]\n";
# print "Capture Group 1 is $1 and its start/end positions can be obtained via \$-[1] and \$+[1]\n";
# print "Capture Group 2 is $2 ... and so on\n";
}
# ${^POSTMATCH} and ${^PREMATCH} are also available with the use of '/p'
# Named capture groups can be called via $+{name}
Please keep in mind that these code samples are automatically generated and are not guaranteed to work. If you find any syntax errors, feel free to submit a bug report. For a full regex reference for Perl, please visit: http://perldoc.perl.org/perlre.html