SAHVAI-3D 和 4D：使用非对比度头部 CT 扫描的新型蛛网膜下腔出血容积自动人工智能（SAHVAI）测量方法

medRxiv - Neurology Pub Date : 2024-08-30 DOI:10.1101/2024.08.29.24312799

Melina Wirtz, Saif Salman, Yujia Wei, Vishal Patel, Rohan Sharma, Vikash Gupta, Qiangqiang Gu, Benoit Dherin, Sanjana Reddy, Rabih Tawk, Bradley J Erickson, William David Freeman

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摘要

目的利用动脉瘤性蛛网膜下腔出血（SAH）患者的非对比头部 CT（NCCT）成像数据，自动计算蛛网膜下腔出血量（SAHV）（SAHVAI-SAHV 人工智能）并创建三维容积图像（SAHVAI-3D）。我们还定义了代表 SAHV 随时间变化的 SAHVAI-4D。我们的目的是比较自动 SAHVAI 容量与手动 SAHV 方法和计算时间，探索这些成像生物标志物在识别延迟性脑缺血（DCI）高危脑区方面的潜力，并探索未来神经治疗干预对 SAH 患者康复的潜在启示。

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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SAHVAI-3D and 4D: A New, Automated Subarachnoid Hemorrhage Volumetric Artificial Intelligence (SAHVAI) Measurement Approach Using Non-Contrast Head CT Scans

Objectives To automate subarachnoid hemorrhage volume (SAHV) calculation (SAHVAI-SAHV Artificial Intelligence) and create 3D volumetric images (SAHVAI-3D) using non-contrast head CT (NCCT) imaging data in aneurysmal subarachnoid hemorrhage (SAH) patients. We also defined SAHVAI-4D, representing SAHV over time. The aim was to compare automated SAHVAI volumes to manual SAHV methods and computation times, explore these imaging biomarkers’ potential in identifying at-risk brain regions for delayed cerebral ischemia (DCI), and explore potential insights in future neurotherapeutic interventions for SAH patient recovery.

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medRxiv - Neurology

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