From the Department of Neurosurgery (B.W.C., B.R.B., C.K., M.S.), Mayo Clinic, Phoenix, Arizona
Department of Biological and Health Systems Engineering (B.W.C., D.H.F.), Arizona State University, Tempe, Arizona.
AJNR Am J Neuroradiol. 2019 Oct;40(10):1759-1765. doi: 10.3174/ajnr.A6222. Epub 2019 Sep 26.
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.
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.
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.
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.
选择正确的血流导向装置尺寸对于脑动脉瘤治疗的成功至关重要,但由于装置尺寸、解剖结构和部署方式的相互作用,这仍然具有挑战性。目前的惯例并不能很好地解决这些挑战。本研究的目的是确定计算建模是否能改善血流导向装置的尺寸选择,优于当前的惯例,并验证模拟的部署。
7 名经验丰富的神经外科医生和介入神经放射学家使用计算模型前瞻性地规划了 19 例临床干预。在每个患者病例中,医生模拟了 2-4 种正在考虑的血流导向装置尺寸,这些尺寸是基于术前成像确定的。此外,医生还使用当前的惯例来确定首选装置尺寸。在治疗后立即完成了一份关于计算建模对手术影响的调查问卷。在治疗后获取旋转血管造影图像数据,并与血流导向装置模拟进行比较,以验证软件平台的输出。
根据问卷回答,医生认为模拟对于治疗计划很有用,在 94.7%的情况下增加了他们对装置选择的信心。在查看模拟结果后,医生在 63.2%的情况下选择了与最初常规计划装置尺寸不同的装置尺寸。临床和模拟血流导向装置长度之间的平均绝对差异为 2.1 毫米。在 57%的情况下,平均模拟血流导向装置直径在临床血流导向装置直径的测量不确定度范围内。
医生发现计算建模是血流导向装置治疗计划的一个有影响力和有用的工具。验证结果表明,模拟和临床血流导向装置直径和长度之间具有良好的一致性。