{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1360567181514723968.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1007/s13239-018-00374-2"}},{"identifier":{"@type":"URI","@value":"http://link.springer.com/article/10.1007/s13239-018-00374-2/fulltext.html"}},{"identifier":{"@type":"URI","@value":"http://link.springer.com/content/pdf/10.1007/s13239-018-00374-2.pdf"}},{"identifier":{"@type":"DOI","@value":"10.60692/wpc7p-bh153"}},{"identifier":{"@type":"DOI","@value":"10.60692/bmv3z-56z45"}},{"identifier":{"@type":"PMID","@value":"30203115"}},{"identifier":{"@type":"HANDLE","@value":"11336/112699"}}],"resourceType":"学術雑誌論文(journal article)","dc:title":[{"@value":"Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge"}],"description":[{"notation":[{"@value":"La dynamique des fluides computationnelle (CFD) basée sur l'image est largement utilisée pour prédire la contrainte de cisaillement de la paroi de l'anévrisme intracrânien (WSS), en particulier dans le but d'améliorer l'évaluation du risque de rupture. Néanmoins, des préoccupations ont été exprimées au sujet de la variabilité des WSS prévus et des associations incohérentes avec la rupture. Les défis précédents et les études de groupes individuels se sont concentrés sur des aspects individuels du pipeline CFD basé sur l'image. L'objectif de ce défi était de quantifier la variabilité totale de l'ensemble du pipeline. Les volumes d'images d'angiographie rotationnelle 3D de cinq anévrismes de l'artère cérébrale moyenne ont été fournis aux participants, qui étaient libres de choisir leurs méthodes de segmentation, leurs conditions limites, leur résolveur CFD et leurs paramètres. Les participants ont été invités à remplir un questionnaire sur leurs stratégies de solution et leur expérience en matière de CFD anévrismique, et à fournir des distributions de surface de l'ampleur du WSS, à partir desquelles nous avons objectivement dérivé une variété de paramètres hémodynamiques. Au total, 28 ensembles de données ont été soumis, provenant de 26 équipes ayant différents niveaux d'expérience auto-évaluée. La grande variabilité des segmentations, des étendues du modèle CFD et des taux d'entrée a entraîné des plages interquartiles de WSS moyen de sac allant jusqu'à 56 %, qui ont été réduites à < 30 % après normalisation par le WSS de l'artère mère. Le WSS sac-maximum et la zone de cisaillement faible étaient plus variables, tandis que l'ordre de classement des cas par cisaillement faible ou élevé ne montrait qu'un consensus modeste entre les équipes. L'expérience n'était pas un prédicteur significatif de la variabilité. Une grande variabilité existe dans la prédiction de l'anévrisme intracrânien WSS. Bien que les techniques de segmentation et de résolution de CFD puissent être difficiles à normaliser entre les groupes, nos résultats suggèrent qu'une partie de la variabilité de la CFD basée sur l'image pourrait être réduite en établissant des lignes directrices pour les étendues du modèle, les taux d'entrée et les propriétés sanguines, et en encourageant la déclaration de paramètres hémodynamiques normalisés."}]},{"notation":[{"@value":"La dinámica de fluidos computacional (CFD) basada en imágenes se utiliza ampliamente para predecir la tensión de corte de la pared del aneurisma intracraneal (WSS), particularmente con el objetivo de mejorar la evaluación del riesgo de ruptura. Sin embargo, se ha expresado preocupación por la variabilidad del WSS predicho y las asociaciones inconsistentes con la ruptura. Los desafíos anteriores, y los estudios de grupos individuales, se han centrado en aspectos individuales de la cartera de CFD basada en imágenes. El objetivo de este Desafío fue cuantificar la variabilidad total de toda la tubería.3D se proporcionaron volúmenes de imágenes de angiografía rotacional de cinco aneurismas de la arteria cerebral media a los participantes, que eran libres de elegir sus métodos de segmentación, condiciones de límite y solucionador y configuración de CFD. Se pidió a los participantes que completaran un cuestionario sobre sus estrategias de solución y experiencia con CFD de aneurisma, y proporcionaran distribuciones de superficie de la magnitud de WSS, a partir de las cuales derivamos objetivamente una variedad de parámetros hemodinámicos. Se presentaron un total de 28 conjuntos de datos, de 26 equipos con diferentes niveles de experiencia autoevaluada. La amplia variabilidad de las segmentaciones, las extensiones del modelo CFD y las tasas de flujo de entrada dieron como resultado rangos intercuartílicos de WSS promedio de SAC de hasta el 56%, que se redujeron a < 30% después de la normalización por WSS de la arteria madre. El WSS saco-máximo y el área de bajo cizallamiento fueron más variables, mientras que el orden de rango de los casos por cizallamiento bajo o alto mostró solo un consenso modesto entre los equipos. La experiencia no fue un predictor significativo de la variabilidad. Existe una amplia variabilidad en la predicción del WSS del aneurisma intracraneal. Si bien las técnicas de segmentación y resolución de CFD pueden ser difíciles de estandarizar entre grupos, nuestros hallazgos sugieren que parte de la variabilidad en la CFD basada en imágenes podría reducirse estableciendo pautas para la extensión del modelo, las tasas de entrada y las propiedades de la sangre, y fomentando el informe de parámetros hemodinámicos normalizados."}]},{"notation":[{"@value":"Image-based computational fluid dynamics (CFD) is widely used to predict intracranial aneurysm wall shear stress (WSS), particularly with the goal of improving rupture risk assessment. Nevertheless, concern has been expressed over the variability of predicted WSS and inconsistent associations with rupture. Previous challenges, and studies from individual groups, have focused on individual aspects of the image-based CFD pipeline. The aim of this Challenge was to quantify the total variability of the whole pipeline.3D rotational angiography image volumes of five middle cerebral artery aneurysms were provided to participants, who were free to choose their segmentation methods, boundary conditions, and CFD solver and settings. Participants were asked to fill out a questionnaire about their solution strategies and experience with aneurysm CFD, and provide surface distributions of WSS magnitude, from which we objectively derived a variety of hemodynamic parameters.A total of 28 datasets were submitted, from 26 teams with varying levels of self-assessed experience. Wide variability of segmentations, CFD model extents, and inflow rates resulted in interquartile ranges of sac average WSS up to 56%, which reduced to < 30% after normalizing by parent artery WSS. Sac-maximum WSS and low shear area were more variable, while rank-ordering of cases by low or high shear showed only modest consensus among teams. Experience was not a significant predictor of variability.Wide variability exists in the prediction of intracranial aneurysm WSS. While segmentation and CFD solver techniques may be difficult to standardize across groups, our findings suggest that some of the variability in image-based CFD could be reduced by establishing guidelines for model extents, inflow rates, and blood properties, and by encouraging the reporting of normalized hemodynamic parameters."}]},{"notation":[{"@value":"تُستخدم ديناميكيات السوائل الحسابية القائمة على الصور (CFD) على نطاق واسع للتنبؤ بإجهاد قص جدار تمدد الأوعية الدموية داخل الجمجمة (WSS)، لا سيما بهدف تحسين تقييم مخاطر التمزق. ومع ذلك، فقد تم الإعراب عن القلق بشأن تباين خدمات المياه والصرف الصحي المتوقعة والارتباطات غير المتسقة مع التمزق. ركزت التحديات السابقة والدراسات من المجموعات الفردية على الجوانب الفردية لخط أنابيب عقود الفروقات القائمة على الصور. كان الهدف من هذا التحدي هو تحديد التباين الكلي لخط الأنابيب بأكمله. تم توفير أحجام صور التصوير الوعائي الدوراني ثلاثي الأبعاد لخمسة تمددات في الشريان الدماغي الأوسط للمشاركين، الذين كانوا أحرارًا في اختيار طرق التجزئة، وظروف الحدود، وآلة حل عقود الفروقات والإعدادات. طُلب من المشاركين ملء استبيان حول استراتيجيات حلهم وتجربتهم مع تمدد الأوعية الدموية CFD، وتقديم توزيعات سطحية لحجم WSS، والتي استخلصنا منها بشكل موضوعي مجموعة متنوعة من المعلمات الديناميكية الدموية. تم تقديم ما مجموعه 28 مجموعة بيانات، من 26 فريقًا بمستويات مختلفة من تجربة التقييم الذاتي. أدى التباين الواسع في التقسيمات، ونطاقات نموذج العقود مقابل الفروقات، ومعدلات التدفق إلى نطاقات ربيعية لمتوسط مساحة تخزين الكيس تصل إلى 56 ٪، والتي انخفضت إلى أقل من 30 ٪ بعد تطبيعها بواسطة مساحة تخزين الشريان الأم. كان الحد الأقصى لحجم الكيس ومساحة القص المنخفضة أكثر تباينًا، في حين أن ترتيب رتب الحالات حسب القص المنخفض أو العالي أظهر إجماعًا متواضعًا فقط بين الفرق. لم تكن التجربة مؤشرًا مهمًا على التباين. يوجد تباين واسع في التنبؤ بتمدد الأوعية الدموية داخل الجمجمة. في حين أنه قد يكون من الصعب توحيد تقنيات التجزئة وحل العقود مقابل الفروقات عبر المجموعات، إلا أن النتائج التي توصلنا إليها تشير إلى أنه يمكن تقليل بعض التباين في العقود مقابل الفروقات القائمة على الصور من خلال وضع مبادئ توجيهية لنطاقات النموذج ومعدلات التدفق وخصائص الدم، ومن خلال تشجيع الإبلاغ عن المعلمات الديناميكية الدموية الطبيعية."}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1380567181514723968","@type":"Researcher","foaf:name":[{"@value":"Kristian Valen-Sendstad"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724101","@type":"Researcher","foaf:name":[{"@value":"Aslak W. 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Graeme Houston"}]},{"@id":"https://cir.nii.ac.jp/crid/1420282801184491648","@type":"Researcher","personIdentifier":[{"@type":"KAKEN_RESEARCHERS","@value":"20814908"},{"@type":"NRID","@value":"1000020814908"},{"@type":"NRID","@value":"9000261023147"},{"@type":"NRID","@value":"9000367430428"},{"@type":"NRID","@value":"9000391503835"},{"@type":"NRID","@value":"9000266429667"},{"@type":"NRID","@value":"9000292187719"},{"@type":"RESEARCHMAP","@value":"https://researchmap.jp/Tsuji-masa"}],"foaf:name":[{"@value":"Masanori Tsuji"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724102","@type":"Researcher","foaf:name":[{"@value":"Fujimaro Ishida"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724230","@type":"Researcher","foaf:name":[{"@value":"Prahlad G. Menon"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724359","@type":"Researcher","foaf:name":[{"@value":"Leonard D. 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Brown"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514723846","@type":"Researcher","foaf:name":[{"@value":"Kristian Debus"}]},{"@id":"https://cir.nii.ac.jp/crid/1420564276182136064","@type":"Researcher","personIdentifier":[{"@type":"KAKEN_RESEARCHERS","@value":"10643330"},{"@type":"NRID","@value":"1000010643330"},{"@type":"NRID","@value":"9000283421126"},{"@type":"NRID","@value":"9000258292172"},{"@type":"NRID","@value":"9000006087260"},{"@type":"NRID","@value":"9000263041883"},{"@type":"NRID","@value":"9000018182435"},{"@type":"NRID","@value":"9000398150753"},{"@type":"NRID","@value":"9000414350174"},{"@type":"NRID","@value":"9000408637589"},{"@type":"NRID","@value":"9000412135776"},{"@type":"NRID","@value":"9000412135709"},{"@type":"NRID","@value":"9000273006523"},{"@type":"NRID","@value":"9000399344486"},{"@type":"NRID","@value":"9000366512515"},{"@type":"NRID","@value":"9000308729630"},{"@type":"NRID","@value":"9000412160043"},{"@type":"NRID","@value":"9000412254782"},{"@type":"NRID","@value":"9000273022681"},{"@type":"NRID","@value":"9000415414412"},{"@type":"NRID","@value":"9000409324777"},{"@type":"RESEARCHMAP","@value":"https://researchmap.jp/7000014649"}],"foaf:name":[{"@value":"Kuniyasu Niizuma"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514723976","@type":"Researcher","foaf:name":[{"@value":"Sherif Rashad"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514723977","@type":"Researcher","foaf:name":[{"@value":"Shin-ichiro Sugiyama"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514723975","@type":"Researcher","foaf:name":[{"@value":"M. Owais Khan"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724112","@type":"Researcher","foaf:name":[{"@value":"Adam R. Updegrove"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724367","@type":"Researcher","foaf:name":[{"@value":"Shawn C. Shadden"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724374","@type":"Researcher","foaf:name":[{"@value":"Bart M. W. Cornelissen"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514723984","@type":"Researcher","foaf:name":[{"@value":"Charles B. L. M. Majoie"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724103","@type":"Researcher","foaf:name":[{"@value":"Philipp Berg"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514723847","@type":"Researcher","foaf:name":[{"@value":"Sylvia Saalfield"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724104","@type":"Researcher","foaf:name":[{"@value":"Kenichi Kono"}]},{"@id":"https://cir.nii.ac.jp/crid/1380567181514724108","@type":"Researcher","foaf:name":[{"@value":"David A. 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