Artificial intelligence-driven measurements of brain metastases’ response to SRS compare favorably with current manual standards of assessment

K. Prezelski, D. G. Hsu, L.A. del Balzo, Erica Heller, Jennifer Ma, Luke R G Pike, A. Ballangrud, M. Aristophanous
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Abstract

Evaluation of treatment response for brain metastases (BMs) following stereotactic radiosurgery (SRS) becomes complex as the number of treated BMs increases. This study uses artificial intelligence (AI) to track BMs after SRS and validates its output compared with manual measurements. Patients with BMs who received at least one course of SRS and followed up with MRI scans were retrospectively identified. A tool for automated detection, segmentation, and tracking of intracranial metastases on longitudinal imaging, MEtastasis Tracking with Repeated Observations (METRO), was applied to the dataset. The longest three-dimensional (3D) diameter identified with METRO was compared with manual measurements of maximum axial BM diameter, and their correlation was analyzed. Change in size of the measured BM identified with METRO after SRS treatment was used to classify BMs as responding, or not responding, to treatment, and its accuracy was determined relative to manual measurements. From 71 patients, 176 BMs were identified and measured with METRO and manual methods. Based on a one-to-one correlation analysis, the correlation coefficient was R2 = 0.76 (p = 0.0001). Using modified BM response classifications of BM change in size, the longest 3D diameter data identified with METRO had a sensitivity of 0.72 and a specificity of 0.95 in identifying lesions that responded to SRS, when using manual axial diameter measurements as the ground truth. Using AI to automatically measure and track BM volumes following SRS treatment, this study showed a strong correlation between AI-driven measurements and the current clinically used method: manual axial diameter measurements.
人工智能驱动的脑转移瘤 SRS 反应测量结果优于现行人工评估标准
立体定向放射外科手术(SRS)后,脑转移瘤(BMs)治疗反应的评估随着治疗的 BMs 数量的增加而变得复杂。本研究利用人工智能(AI)跟踪 SRS 后的脑转移瘤,并与人工测量结果进行比较验证。 研究人员回顾性地识别了至少接受过一个疗程SRS治疗并接受磁共振成像扫描随访的BMs患者。数据集采用了纵向成像颅内转移灶自动检测、分割和追踪工具--METRO(MEtastasis Tracking with Repeated Observations)。用 METRO 确定的最长三维(3D)直径与人工测量的最大轴向基质直径进行了比较,并分析了两者的相关性。在 SRS 治疗后,用 METRO 确定的测量基质大小的变化被用来将基质划分为对治疗有反应或无反应,并确定其相对于人工测量的准确性。 在 71 名患者中,使用 METRO 和人工方法识别并测量了 176 个 BM。根据一对一相关分析,相关系数为 R2 = 0.76 (p = 0.0001)。使用修改后的基底膜反应分类法对基底膜的大小变化进行分类,以手动轴向直径测量为基本事实,用 METRO 确定的最长三维直径数据在确定对 SRS 有反应的病变方面的灵敏度为 0.72,特异度为 0.95。 这项研究利用人工智能自动测量和跟踪 SRS 治疗后的 BM 体积,显示出人工智能驱动的测量与目前临床使用的方法(手动轴直径测量)之间存在很强的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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