ArticleAJNR. American journal of neuroradiology2019
A Multicenter Pilot Study on the Clinical Utility of Computational Modeling for Flow-Diverter Treatment Planning.
Article in AJNR. American journal of neuroradiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Physics constrained graph neural network for real time prediction of intracranial aneurysm hemodynamics.NPJ digital medicine · 2026Article
- Semi-automated cerebral aneurysm segmentation and geometric analysis for WEB sizing utilizing a cloud-based computational platform.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2021Article
- Virtual and augmented reality for biomedical applications.Cell reports. Medicine · 2021Review
- Association Between Aneurysmal Haemodynamics and Device Microstructural Characteristics After Flow-Diversion Treatments With Dual Stents of Different Sizes: A Numerical Study.Frontiers in physiology · 2021Article
- Cerebral Aneurysm Occlusion at 12-Month Follow-Up After Flow-Diverter Treatment: Statistical Modeling for V&V With Real-World Data.Frontiers in medical technology · 2021Article
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14 authors.
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Abstract
background and purposeSelection of the correct flow-diverter size is critical for cerebral aneurysm treatment success, but it remains challenging due to the interplay of device size, anatomy, and deployment. Current convention does not address these challenges well. The goals of this pilot study were to determine whether computational modeling improves flow-diverter sizing over current convention and to validate simulated deployments. MATERIALS AND
methodsSeven experienced neurosurgeons and interventional neuroradiologists used computational modeling to prospectively plan 19 clinical interventions. In each patient case, physicians simulated 2-4 flow-diverter sizes that were under consideration based on preprocedural imaging. In addition, physicians identified a preferred device size using the current convention. A questionnaire on the impact of computational modeling on the procedure was completed immediately after treatment. Rotational angiography image data were acquired after treatment and compared with flow-diverter simulations to validate the output of the software platform.
resultsAccording to questionnaire responses, physicians found the simulations useful for treatment planning, and they increased their confidence in device selection in 94.7% of cases. After viewing the simulations results, physicians selected a device size that was different from the original conventionally planned device size in 63.2% of cases. The average absolute difference between clinical and simulated flow-diverter lengths was 2.1 mm. In 57% of cases, average simulated flow-diverter diameters were within the measurement uncertainty of clinical flow-diverter diameters.
conclusionsPhysicians found computational modeling to be an impactful and useful tool for flow-diverter treatment planning. Validation results showed good agreement between simulated and clinical flow-diverter diameters and lengths.
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