Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study
How prevalent is spontaneous thrombosis in a population containing all sizes of intracranial aneurysms? How can we calibrate computational models of thrombosis based on published data? How does spontaneous thrombosis differ in normo- and hypertensive subjects? We address the first question through a...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2023-09-01
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| Series: | APL Bioengineering |
| Online Access: | http://dx.doi.org/10.1063/5.0144848 |
| _version_ | 1827796642154151936 |
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| author | Qiongyao Liu Ali Sarrami-Foroushani Yongxing Wang Michael MacRaild Christopher Kelly Fengming Lin Yan Xia Shuang Song Nishant Ravikumar Tufail Patankar Zeike A. Taylor Toni Lassila Alejandro F. Frangi |
| author_facet | Qiongyao Liu Ali Sarrami-Foroushani Yongxing Wang Michael MacRaild Christopher Kelly Fengming Lin Yan Xia Shuang Song Nishant Ravikumar Tufail Patankar Zeike A. Taylor Toni Lassila Alejandro F. Frangi |
| author_sort | Qiongyao Liu |
| collection | DOAJ |
| description | How prevalent is spontaneous thrombosis in a population containing all sizes of intracranial aneurysms? How can we calibrate computational models of thrombosis based on published data? How does spontaneous thrombosis differ in normo- and hypertensive subjects? We address the first question through a thorough analysis of published datasets that provide spontaneous thrombosis rates across different aneurysm characteristics. This analysis provides data for a subgroup of the general population of aneurysms, namely, those of large and giant size (>10 mm). Based on these observed spontaneous thrombosis rates, our computational modeling platform enables the first in silico observational study of spontaneous thrombosis prevalence across a broader set of aneurysm phenotypes. We generate 109 virtual patients and use a novel approach to calibrate two trigger thresholds: residence time and shear rate, thus addressing the second question. We then address the third question by utilizing this calibrated model to provide new insight into the effects of hypertension on spontaneous thrombosis. We demonstrate how a mechanistic thrombosis model calibrated on an intracranial aneurysm cohort can help estimate spontaneous thrombosis prevalence in a broader aneurysm population. This study is enabled through a fully automatic multi-scale modeling pipeline. We use the clinical spontaneous thrombosis data as an indirect population-level validation of a complex computational modeling framework. Furthermore, our framework allows exploration of the influence of hypertension in spontaneous thrombosis. This lays the foundation for in silico clinical trials of cerebrovascular devices in high-risk populations, e.g., assessing the performance of flow diverters in aneurysms for hypertensive patients. |
| first_indexed | 2024-03-11T19:09:56Z |
| format | Article |
| id | doaj.art-2a390c65b52445b0b510b53bdc1b5297 |
| institution | Directory Open Access Journal |
| issn | 2473-2877 |
| language | English |
| last_indexed | 2024-03-11T19:09:56Z |
| publishDate | 2023-09-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | APL Bioengineering |
| spelling | doaj.art-2a390c65b52445b0b510b53bdc1b52972023-10-09T20:09:13ZengAIP Publishing LLCAPL Bioengineering2473-28772023-09-0173036102036102-1010.1063/5.0144848Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational studyQiongyao Liu0Ali Sarrami-Foroushani1Yongxing Wang2Michael MacRaild3Christopher Kelly4Fengming Lin5Yan Xia6Shuang Song7Nishant Ravikumar8Tufail Patankar9Zeike A. Taylor10Toni Lassila11Alejandro F. Frangi12 Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Leeds General Infirmary, Leeds, United Kingdom School of Mechanical Engineering, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United KingdomHow prevalent is spontaneous thrombosis in a population containing all sizes of intracranial aneurysms? How can we calibrate computational models of thrombosis based on published data? How does spontaneous thrombosis differ in normo- and hypertensive subjects? We address the first question through a thorough analysis of published datasets that provide spontaneous thrombosis rates across different aneurysm characteristics. This analysis provides data for a subgroup of the general population of aneurysms, namely, those of large and giant size (>10 mm). Based on these observed spontaneous thrombosis rates, our computational modeling platform enables the first in silico observational study of spontaneous thrombosis prevalence across a broader set of aneurysm phenotypes. We generate 109 virtual patients and use a novel approach to calibrate two trigger thresholds: residence time and shear rate, thus addressing the second question. We then address the third question by utilizing this calibrated model to provide new insight into the effects of hypertension on spontaneous thrombosis. We demonstrate how a mechanistic thrombosis model calibrated on an intracranial aneurysm cohort can help estimate spontaneous thrombosis prevalence in a broader aneurysm population. This study is enabled through a fully automatic multi-scale modeling pipeline. We use the clinical spontaneous thrombosis data as an indirect population-level validation of a complex computational modeling framework. Furthermore, our framework allows exploration of the influence of hypertension in spontaneous thrombosis. This lays the foundation for in silico clinical trials of cerebrovascular devices in high-risk populations, e.g., assessing the performance of flow diverters in aneurysms for hypertensive patients.http://dx.doi.org/10.1063/5.0144848 |
| spellingShingle | Qiongyao Liu Ali Sarrami-Foroushani Yongxing Wang Michael MacRaild Christopher Kelly Fengming Lin Yan Xia Shuang Song Nishant Ravikumar Tufail Patankar Zeike A. Taylor Toni Lassila Alejandro F. Frangi Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study APL Bioengineering |
| title | Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study |
| title_full | Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study |
| title_fullStr | Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study |
| title_full_unstemmed | Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study |
| title_short | Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study |
| title_sort | hemodynamics of thrombus formation in intracranial aneurysms an in silico observational study |
| url | http://dx.doi.org/10.1063/5.0144848 |
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