Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.
Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
PLoS One. 2022 Sep 28;17(9):e0274220. doi: 10.1371/journal.pone.0274220. eCollection 2022.
Cerebrovascular Reactivity (CVR) provides an assessment of the brain's vascular reserve and has been postulated to be a sensitive marker in cerebrovascular diseases. MRI-based CVR measurement typically employs alterations in arterial carbon dioxide (CO2) level while continuously acquiring Blood-Oxygenation-Level-Dependent (BOLD) images. CO2-inhalation and resting-state methods are two commonly used approaches for CVR MRI. However, processing of CVR MRI data often requires special expertise and may become an obstacle in broad utilization of this promising technique. The aim of this work was to develop CVR-MRICloud, a cloud-based CVR processing pipeline, to enable automated processing of CVR MRI data. The CVR-MRICloud consists of several major steps including extraction of end-tidal CO2 (EtCO2) curve from raw CO2 recording, alignment of EtCO2 curve with BOLD time course, computation of CVR value on a whole-brain, regional, and voxel-wise basis. The pipeline also includes standard BOLD image processing steps such as motion correction, registration between functional and anatomic images, and transformation of the CVR images to canonical space. This paper describes these algorithms and demonstrates the performance of the CVR-MRICloud in lifespan healthy subjects and patients with clinical conditions such as stroke, brain tumor, and Moyamoya disease. CVR-MRICloud has potential to be used as a data processing tool for a variety of basic science and clinical applications.
脑血管反应性（CVR）提供了对大脑血管储备能力的评估，并且被认为是脑血管疾病的一个敏感标志物。基于 MRI 的 CVR 测量通常采用动脉二氧化碳（CO2）水平的变化，同时连续获取血氧水平依赖性（BOLD）图像。CO2 吸入和静息状态方法是 CVR MRI 常用的两种方法。然而，CVR MRI 数据的处理通常需要特殊的专业知识，这可能成为广泛应用这项有前途技术的障碍。本研究的目的是开发 CVR-MRICloud，这是一个基于云的 CVR 处理管道，以实现 CVR MRI 数据的自动处理。CVR-MRICloud 由几个主要步骤组成，包括从原始 CO2 记录中提取呼气末 CO2（EtCO2）曲线，将 EtCO2 曲线与 BOLD 时间过程对齐，在全脑、区域和体素水平上计算 CVR 值。该管道还包括标准的 BOLD 图像处理步骤，如运动校正、功能和解剖图像之间的配准，以及 CVR 图像向标准空间的转换。本文描述了这些算法，并展示了 CVR-MRICloud 在健康受试者和具有临床情况（如中风、脑肿瘤和烟雾病）的患者中的性能。CVR-MRICloud 有可能成为各种基础科学和临床应用的数据处理工具。
