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个性化模拟脑血管疾病中的血液动力学:从诊断准确性的研究中吸取的教训

Jonas Behland^1,2, Vince I Madai^1,3,4, Orhun U Aydin¹

¹Charité Lab for AI in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany.

Frontiers in neurology

|September 29, 2023

概括

在内动脉样硬化疾病 (ICAD) 中预测中风风险的机械模拟显示中等准确度. 这些大脑血液动力学模型的临床应用需要进一步改进.

科学领域:

神经学神经学
生物医学工程生物医学工程
医疗成像医学成像

背景情况:

内动脉样硬化疾病 (ICAD) 是重复性中风的主要原因.
目前ICAD的中风预防策略是有限的.
机械模拟大脑血液动力学为ICAD提供了精准医学方法,但需要验证.

研究的目的:

量化验证基于模拟的精准医学框架,用于评估ICAD患者的大脑血液动力学.
评估模拟模型在识别血动力学上脆弱的大脑区域的准确性,从而预测随后的中风.

主要方法:

对68名患有严重单侧内动脉或中脑动脉狭窄症的患者进行了回顾性分析.
利用0维模拟模型来预测血液动力学上脆弱的大脑区域.
经过验证的模拟预测与动态灵敏度对比MRI (DSC-MRI) 的相对平均传输时间 (relMTT) 测量.

主要成果:

模拟模型在识别脆弱的大脑区域时,获得了0.65的灵敏度和0.67的特异性.
接收器操作特征曲线 (ROC AUC) 下的面积为0.68,表明准确度低至中等.
限制包括牛顿血流的假设,刚性血管壁和基于MRI的几何表示.

结论:

目前ICAD的机械模拟需要对临床翻译进行显著改进.
未来的研究应该专注于整合更多的患者数据,并提高模型的可访问性.
进一步验证和改进对于利用血液动力学模拟来预防ICAD患者中风至关重要.

关键词:

大脑血液动力学脑血管疾病脑血管疾病内动脉样硬化的疾病.精准医学是一门精准医学.模拟模拟是指一个模拟模拟.一次性中风中风中风中风中风

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