B W Chong1,2, B R Bendok3, C Krishna3, M Sattur3, B L Brown4, R G Tawk4, D A Miller4, L Rangel-Castilla5, H Babiker6, D H Frakes2, A Theiler5, H Cloft5, D Kallmes5, G Lanzino5. 1. From the Department of Neurosurgery (B.W.C., B.R.B., C.K., M.S.), Mayo Clinic, Phoenix, Arizona Chong.Brian@mayo.edu. 2. Department of Biological and Health Systems Engineering (B.W.C., D.H.F.), Arizona State University, Tempe, Arizona. 3. From the Department of Neurosurgery (B.W.C., B.R.B., C.K., M.S.), Mayo Clinic, Phoenix, Arizona. 4. Department of Neurosurgery (B.L.B., R.G.T., D.A.M.), Mayo Clinic, Jacksonville, Florida. 5. Department of Neurosurgery (L.R.-C., A.T., H.C., D.K., G.L.), Mayo Clinic, Rochester, Minnesota. 6. Endovantage, LLC (H.B.), Phoenix, Arizona.
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.
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.
Authors: Ana Paula Narata; Laura Obradó; Raquel Kalé Moyano; Juan M Macho; Jordi Blasco; Antonio López Rueda; Luis San Roman; Sebastian Remollo; Claudia Marinelli; Rosana Cepeda; Héctor Fernández; Ignacio Larrabide Journal: Front Med Technol Date: 2021-09-17
Authors: Mythreye Venkatesan; Harini Mohan; Justin R Ryan; Christian M Schürch; Garry P Nolan; David H Frakes; Ahmet F Coskun Journal: Cell Rep Med Date: 2021-07-21