Cai Kejia, Tain Rongwen, Das Sandhitsu, Damen Frederick C, Sui Yi, Valyi-Nagy Tibor, Elliott Mark A, Zhou Xiaohong J
Department of Radiology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA; Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA.
Department of Radiology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA; Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA.
J Neurosci Methods. 2015 Dec 30;256:151-6. doi: 10.1016/j.jneumeth.2015.09.001. Epub 2015 Sep 8.
Dilated brain perivascular spaces (PVSs) are found to be associated with many conditions, including aging, dementia, and Alzheimer's disease (AD). Conventionally, PVS assessment is mainly based on subjective observations of the number, size and shape of PVSs in MR images collected at clinical field strengths (≤3T). This study tests the feasibility of imaging and quantifying brain PVS with an ultra-high 7T whole-body MRI scanner.
3D high resolution T2-weighted brain images from healthy subjects (n=3) and AD patients (n=5) were acquired on a 7T whole-body MRI scanner. To automatically segment the small hyperintensive fluid-filling PVS structures, we also developed a quantitative program based on algorithms for spatial gradient, component connectivity, edge-detection, k-means clustering, etc., producing quantitative results of white matter PVS volume densities.
The 3D maps of automatically segmented PVS show an apparent increase in PVS density in AD patients compared to age-matched healthy controls due to the PVS dilation (8.0±2.1 v/v% in AD vs. 4.9±1.3 v/v% in controls, p<0.05).
We demonstrated that 7T provides sufficient SNR and resolution for quantitatively measuring PVSs in deep white matter that is challenging with clinical MRI systems (≤3T). Compared to the conventional visual counting and rating for the PVS assessment, the quantitation method we developed is automatic and objective.
Quantitative PVS MRI at 7T may serve as a non-invasive and endogenous imaging biomarker for diseases with PVS dilation.
脑扩张性血管周围间隙(PVSs)与许多疾病相关,包括衰老、痴呆和阿尔茨海默病(AD)。传统上,PVS评估主要基于在临床场强(≤3T)下采集的MR图像中对PVS数量、大小和形状的主观观察。本研究测试了使用超高场7T全身MRI扫描仪对脑PVS进行成像和定量分析的可行性。
在一台7T全身MRI扫描仪上获取了健康受试者(n = 3)和AD患者(n = 5)的3D高分辨率T2加权脑图像。为了自动分割小的高强度液体填充PVS结构,我们还基于空间梯度、组件连通性、边缘检测、k均值聚类等算法开发了一个定量程序,得出白质PVS体积密度的定量结果。
自动分割的PVS的3D图谱显示,与年龄匹配的健康对照相比,AD患者的PVS密度明显增加,这是由于PVS扩张所致(AD患者为8.0±2.1 v/v%,对照组为4.9±1.3 v/v%,p<0.05)。
我们证明,7T为定量测量深部白质中的PVS提供了足够的信噪比和分辨率,而这对于临床MRI系统(≤3T)来说具有挑战性。与传统的PVS评估视觉计数和评分相比,我们开发的定量方法是自动且客观的。
7T定量PVS MRI可能作为一种用于PVS扩张相关疾病的非侵入性内源性成像生物标志物。