Numerical Assessment of the Risk of Abnormal Endothelialization for Diverter Devices: Clinical Data Driven Numerical Study Научная публикация
Журнал |
Journal of Personalized Medicine
ISSN: 2075-4426 |
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Вых. Данные | Год: 2022, Том: 12, Номер: 4, Номер статьи : 652, Страниц : 25 DOI: 10.3390/jpm12040652 | ||||
Ключевые слова | artery stenosis; cerebral aneurysm; computational fluid dynamics; endothe-lialization; flow diverting device; occlusion; wall shear | ||||
Авторы |
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Организации |
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Реферат:
Numerical modeling is an effective tool for preoperative planning. The present work is devoted to a retrospective analysis of neurosurgical treatments for the occlusion of cerebral aneurysms using flow-diverters and hemodynamic factors affecting stent endothelization. Several different geometric approaches have been considered for virtual flow-diverters deployment. A comparative analysis of hemodynamic parameters as a result of computational modeling has been carried out basing on the four clinical cases: one successful treatment, one with no occlusion and two with in stent stenosis. For the first time, a quantitative assessment of both: the limiting magnitude of shear stresses that are necessary for the occurrence of in stent stenosis (MaxWSS > 1.23) and for conditions in which endothelialization is insufficiently active and occlusion of the cervical part of the aneurysm does not occur (MaxWSS < 1.68)—has been statistacally proven (p < 0.01).
Библиографическая ссылка:
Tikhvinskii D.
, Kuianova J.
, Kislitsin D.
, Orlov K.
, Gorbatykh A.
, Parshin D.
Numerical Assessment of the Risk of Abnormal Endothelialization for Diverter Devices: Clinical Data Driven Numerical Study
Journal of Personalized Medicine. 2022. V.12. N4. 652 :1-25. DOI: 10.3390/jpm12040652 WOS Scopus РИНЦ OpenAlex
Numerical Assessment of the Risk of Abnormal Endothelialization for Diverter Devices: Clinical Data Driven Numerical Study
Journal of Personalized Medicine. 2022. V.12. N4. 652 :1-25. DOI: 10.3390/jpm12040652 WOS Scopus РИНЦ OpenAlex
Идентификаторы БД:
Web of science: | WOS:000786242000001 |
Scopus: | 2-s2.0-85129141480 |
РИНЦ: | 48581136 |
OpenAlex: | W4224253620 |