From the Departments of Radiology (S. Dogra, A.G., J.V., S. Dehkharghani) and Neurology (K.I., S. Dehkharghani), New York University Langone Health, 660 First Ave, New York, NY 10016; Department of Radiology, Weill Cornell Medical College, New York, NY (X.W.); and Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (D.Q.).
Radiology. 2023 May;307(3):e221473. doi: 10.1148/radiol.221473. Epub 2023 Mar 14.
Background Exhaustion of cerebrovascular reactivity (CVR) portends increased stroke risk. Acetazolamide-augmented blood oxygenation level-dependent (BOLD) MRI has been used to estimate CVR, but low signal-to-noise conditions relegate its use to terminal CVR (CVR) measurements that neglect dynamic features of CVR. Purpose To demonstrate comprehensive characterization of acetazolamide-augmented BOLD MRI response in chronic steno-occlusive disease using a computational framework to precondition signal time courses for dynamic whole-brain CVR analysis. Materials and Methods This study focused on retrospective analysis of consecutive patients with unilateral chronic steno-occlusive disease who underwent acetazolamide-augmented BOLD imaging for recurrent minor stroke or transient ischemic attack at an academic medical center between May 2017 and October 2020. A custom principal component analysis-based denoising pipeline was used to correct spatially varying non-signal-bearing contributions obtained by a local principal component analysis of the MRI time series. Standard voxelwise CVR maps representing terminal responses were produced and compared with maximal CVR (CVR) as isolated from binned (per-repetition time) denoised BOLD time course. A linear mixed-effects model was used to compare CVR and CVR in healthy and diseased hemispheres. Results A total of 23 patients (median age, 51 years; IQR, 42-61, 13 men) who underwent 32 BOLD examinations were included. Processed MRI data showed twofold improvement in signal-to-noise ratio, allowing improved isolation of dynamic characteristics in signal time course for sliding window CVR analysis to the level of each BOLD repetition time (approximately 2 seconds). Mean CVR was significantly higher than mean CVR in diseased (5.2% vs 3.8%, < .01) and healthy (5.5% vs 4.0%, < .01) hemispheres. Several distinct time-signal signatures were observed, including nonresponsive; delayed/blunted; brisk; and occasionally nonmonotonic time courses with paradoxical features in normal and abnormal tissues (ie, steal and reverse-steal patterns). Conclusion A principal component analysis-based computational framework for analysis of acetazolamide-augmented BOLD imaging can be used to measure unsustained CVR through twofold improvements in signal-to-noise ratio. © RSNA, 2023
背景 脑血管反应性(CVR)的耗竭预示着中风风险的增加。乙酰唑胺增强的血氧水平依赖(BOLD)MRI 已被用于估计 CVR,但低信噪比条件限制了其用于忽视 CVR 动态特征的终末 CVR(CVR)测量。目的 利用计算框架对慢性狭窄性闭塞性疾病中的乙酰唑胺增强 BOLD MRI 反应进行全面表征,为动态全脑 CVR 分析对信号时间过程进行预处理。材料与方法 本研究侧重于对 2017 年 5 月至 2020 年 10 月在学术医疗中心因复发性小中风或短暂性脑缺血发作而接受乙酰唑胺增强 BOLD 成像的单侧慢性狭窄性闭塞性疾病连续患者进行回顾性分析。使用基于主成分分析的定制去噪流水线,通过对 MRI 时间序列的局部主成分分析来纠正空间变化的无信号承载贡献。生成代表终末反应的标准体素 CVR 图,并将其与从分桶(每个重复时间)去噪 BOLD 时间过程中分离出的最大 CVR(CVR)进行比较。使用线性混合效应模型比较健康和患病半球的 CVR 和 CVR。结果 共纳入 23 例患者(中位年龄,51 岁;IQR,42-61;13 例男性),共进行了 32 次 BOLD 检查。处理后的 MRI 数据显示信噪比提高了两倍,从而可以改善信号时间过程中动态特征的隔离,以便对每个 BOLD 重复时间(约 2 秒)进行滑动窗口 CVR 分析。患病半球的平均 CVR 明显高于平均 CVR(5.2%比 3.8%,<.01)和健康半球(5.5%比 4.0%,<.01)。观察到几种不同的时间信号特征,包括无反应;延迟/迟钝;迅速;以及在正常和异常组织中偶尔出现的非单调时间过程,具有反常特征(即盗血和反向盗血模式)。结论 基于主成分分析的计算框架可用于分析乙酰唑胺增强的 BOLD 成像,通过信噪比提高两倍来测量不持续的 CVR。