Multi-shell Diffusion MRI Models for White Matter Characterization in Cerebral Small Vessel Disease
Multi-shell Diffusion MRI Models for White Matter Characterization in Cerebral Small Vessel Disease
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DOI：
10.1212/wnl.0000000000011213
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发表时间：
2021-02-02
期刊：
影响因子：
9.9
通讯作者：
Duering, Marco
中科院分区：
文献类型：
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作者：
Konieczny, Marek J.;Dewenter, Anna;Duering, Marco
目的探讨多壳层扩散模型改善脑小血管病变(SVD)微结构改变特征的假设，评估其与处理速度表现、纵向变化和弥散测量的重复性之间的关系。方法对50例散发性和59例遗传性常染色体显性遗传性脑动脉病(CADASIL)患者进行认知测试和标准化3T磁共振成像，包括多壳层扩散成像。我们应用了简单扩散张量成像(DTI)模型和两种先进模型：扩散峰度成像(DKI)和轴突定位、弥散和密度成像(NODI)。使用线性回归和多变量随机森林回归(包括传统的奇异值分解标记)来确定扩散度量和处理速度性能之间的关联。在49例散发性SVD患者中，采用纵向高频成像(总共459个磁共振成像)，通过线性混合模型对疾病短期进展的检测进行评估。对10例CADASIL患者在两种不同的3T MRI扫描仪上进行背靠背扫描，对其站点间重复性进行分析。结果在散发性SVD患者和SVD负荷较低的CADASIL患者中，DKI的指标与处理速度性能的相关性最强(R-2高达21%)，并且比传统的SVD成像标记物增加了最大的益处。DTI和DKI的几个指标在检测疾病进展方面表现相似。DTI和DKI指标的重复性很好(组内相关系数为0.93)。结节指标重复性较差。结论多层扩散成像和DKI提高了认知相关脑白质微结构改变的检测和定性。扩散指标的良好重复性证实了它们在研究和临床护理中作为SVD标记的使用。我们公开可用的站点间数据集为未来的研究提供了便利。证据分类本研究提供了I类证据，表明在SVD患者中，弥散磁共振指标与处理速度性能相关。
ObjectiveTo test the hypothesis that multi-shell diffusion models improve the characterization of microstructural alterations in cerebral small vessel disease (SVD), we assessed associations with processing speed performance, longitudinal change, and reproducibility of diffusion metrics.MethodsWe included 50 patients with sporadic and 59 patients with genetically defined SVD (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CADASIL]) with cognitive testing and standardized 3T MRI, including multi-shell diffusion imaging. We applied the simple diffusion tensor imaging (DTI) model and 2 advanced models: diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI). Linear regression and multivariable random forest regression (including conventional SVD markers) were used to determine associations between diffusion metrics and processing speed performance. The detection of short-term disease progression was assessed by linear mixed models in 49 patients with sporadic SVD with longitudinal high-frequency imaging (in total 459 MRIs). Intersite reproducibility was determined in 10 patients with CADASIL scanned back-to-back on 2 different 3T MRI scanners.ResultsMetrics from DKI showed the strongest associations with processing speed performance (R-2 up to 21%) and the largest added benefit on top of conventional SVD imaging markers in patients with sporadic SVD and patients with CADASIL with lower SVD burden. Several metrics from DTI and DKI performed similarly in detecting disease progression. Reproducibility was excellent (intraclass correlation coefficient >0.93) for DTI and DKI metrics. NODDI metrics were less reproducible.ConclusionMulti-shell diffusion imaging and DKI improve the detection and characterization of cognitively relevant microstructural white matter alterations in SVD. Excellent reproducibility of diffusion metrics endorses their use as SVD markers in research and clinical care. Our publicly available intersite dataset facilitates future studies.Classification of evidenceThis study provides Class I evidence that in patients with SVD, diffusion MRI metrics are associated with processing speed performance.