A Multicenter Pilot Study on the Clinical Utility of Computational Modeling for Flow-Diverter Treatment Planning

Abstract

BACKGROUND AND PURPOSE: Selection 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 METHODS: Seven 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. RESULTS: According 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. CONCLUSIONS: Physicians 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.

Virtual and augmented reality for biomedical applications

“…58 AR was used for visualizing presurgical neurovascular anatomy before endovascular intervention (Figures 3B and S6A). 59 However, many of these studies have been demonstrative and exploratory; far fewer have quantified the effect of AR-based approaches on outcomes. A notable exception focused on AR navigation for spine fixation.…”

Association Between Aneurysmal Haemodynamics and Device Microstructural Characteristics After Flow-Diversion Treatments With Dual Stents of Different Sizes: A Numerical Study

“…Inappropriate choice of the first stent, however, may inadvertently result in a gap between the stent and the arterial wall, through which a jet of bypass flow may enter the aneurysm, impinging on the aneurysm wall (Chong et al, 2014). To assist in identifying the optimal stent size for a specific patient, as demonstrated in the present study as well as in other relevant works (Zhang et al, 2017a;Chong et al, 2019), virtual stenting and the subsequent CFD analysis may be a useful tool for clinicians to examine the stent structure and assess the haemodynamic outcomes prior to a real treatment.…”

Semi-automated cerebral aneurysm segmentation and geometric analysis for WEB sizing utilizing a cloud-based computational platform

“…More recently virtual simulation has been utilized to predict the deployment of flow diverters in the treatment of cerebral aneurysms. [15][16][17] As computational imaging technologies and artificial intelligence platforms evolve it is likely that more of these will be utilized in cerebral aneurysm treatment planning especially for single implants such as currently for the WEB and for similar devices in the future. 18…”