Object. Rupture of a cerebral aneurysm occurs mainly in a thin-walled area (TWA). Prediction of TWAs would help to assess the risk of rupture and select appropriate treatment strategy. There are several limitations of current prediction techniques for TWAs. To predict TWAs more accurately, HP should be normalized to minimize the influence of analysis conditions, and the effectiveness of normalized, combined hemodynamic parameters (CHPs) should be investigated with help of the quantitative color analysis of intraoperative images. Methods. A total of 21 unruptured cerebral aneurysms in 19 patients were analyzed. A normalized CHP was newly suggested as a weighted average of normalized wall shear stress (WSS) and normalized oscillatory shear index (OSI). Delta E from International Commission on Illumination was used to more objectively quantify color differences in intraoperative images. Results. CFD analysis results indicated that WSS and OSI were more predictive of TWAs than pressure (P<.001 p=".187," respectively these two parameters were selected to define the normalized chp. chp became more statistically significant as weighting factor of wss increased and that osi decreased. locations with high values corresponded well those delta e predicted twas based on showed a relatively good agreement intraoperative images in cases conclusion. produced most result. normalization scheme for suggested this work was validated using quantitative color analyses rather than subjective judgments it might be clinically useful predicting unruptured cerebral aneurysms. would also integrated into further fluid-structure interaction analysis reliable estimation risk aneurysm rupture.>
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Πέμπτη 20 Σεπτεμβρίου 2018
Prediction of Thin-Walled Areas of Unruptured Cerebral Aneurysms through Comparison of Normalized Hemodynamic Parameters and Intraoperative Images
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Αλέξανδρος Γ. Σφακιανάκης Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,0030693260717...
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heory of COVID-19 pathogenesis Publication date: November 2020Source: Medical Hypotheses, Volume 144Author(s): Yuichiro J. Suzuki ScienceD...
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