In‐silico calibration of intracranial aneurysm thrombosis models based on clinical data

Qiongyao Liu, Ali Sarrami Foroushani, Yongxing Wang, Michael Macraild, Christopher Kelly, Nishant Ravikumar, Zeike A. Taylor, Tufail Patankar, Toni Lassila, Alejandro F. Frangi

Research output: Other contributionpeer-review

Abstract

How common is spontaneous thrombosis (ST) formation in intracranial aneurysms (IAs); and how ST differs in normo- and hypertensive conditions? We address the former question by a thorough analysis of published datasets to identify the incidence of ST across different patients and demographics. Based on the statistical ST incidence in large and giant (LG) aneurysms (>10 mm), we perform an in-silico observational study in 89 virtual patients to calibrate two trigger thresholds, residence time (RT) and shear rate (SR). We then address the second question by using a calibrated thrombosis model to study the effects of hypertension on thrombus formation. According to our statistical analysis, the clinical ST (partial or complete) incidence for LG IAs is 40.67% (85/290) ±5.59%, with 90% confidence. The accuracy of our calibrated model in predicting ST is 75.8% by comparison with 62 documented clinical cases. Our model predicts a lower ST incidence in hypertensive patients due to the smaller maximum RT in the aneurysm sac caused by hypertension. This study not only collates ST literature and improves our clotting model by providing more accurate threshold parameters, but also reveals that ST may be less common in hypertensive patients.
Original languageUndefined
DOIs
Publication statusPublished - 9 May 2022

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