Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University LMU, Munich, Germany.
Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Department of Neurology, Nijmegen, the Netherlands.
Ann Neurol. 2016 Oct;80(4):581-92. doi: 10.1002/ana.24758. Epub 2016 Aug 29.
To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD.
We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study.
PSMD was associated with processing speed in all study samples with SVD (p-values between 2.8 × 10(-3) and 1.8 × 10(-10) ). PSMD explained most of the variance in processing speed (R(2) ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers.
PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581-592.
建立一种全自动、稳健的脑小血管病(SVD)及相关认知障碍成像标志物,该标志物易于实施,反映疾病负担,与认知障碍的主要领域——加工速度密切相关。
我们开发了一种基于弥散张量成像、白质束骨架化和直方图分析的新型磁共振成像标志物。该标志物(骨架化平均弥散度峰宽[PSMD])与传统 SVD 成像标志物一起进行评估。我们首先在遗传性 SVD(n=113)患者中评估与加工速度的相关性。接下来,我们在遗传性 SVD(n=57)、散发性 SVD(n=444)和 SVD 记忆诊所患者(n=105)的独立样本中验证我们的发现。新标志物进一步应用于健康对照组(n=241)和阿尔茨海默病患者(n=153)。我们进一步进行了纵向分析和扫描仪间可重复性研究。
PSMD 与所有 SVD 研究样本的加工速度相关(p 值在 2.8×10(-3) 至 1.8×10(-10) 之间)。PSMD 解释了加工速度的大部分方差(R(2) 范围从 8.8%到 46%),并在多元回归分析中始终优于传统成像标志物(脑白质高信号体积、腔隙体积和脑容量)。PSMD 的增加与血管疾病而不是神经退行性疾病有关。在纵向分析中,PSMD 比其他成像标志物更好地捕捉 SVD 的进展。
PSMD 是一种新的全自动、稳健的 SVD 成像标志物。PSMD 可以很容易地应用于大样本,对于研究和临床应用都非常有用。