Lu Wenli, Yang Li, Chen Ran, Chen Xinyi, Zhu Shengnan, Ji Liya, Liao Han, Qiang Jing, Li Wenyi, Li Cheng, Zhou Dan
Department of Radiology, BenQ Medical Center, the Affiliated BenQ Hospital of Nanjing Medical University, Nanjing, China.
Quant Imaging Med Surg. 2025 Sep 1;15(9):8173-8188. doi: 10.21037/qims-2025-733. Epub 2025 Aug 15.
Cerebral small vessel disease (CSVD) is a major contributor to cognitive impairment and dementia. Growing evidence suggests that impaired perivascular clearance plays a pivotal role in CSVD pathogenesis, yet non-invasive biomarkers for early cognitive decline remain limited. This study aimed to explore the diagnostic value of the diffusion tensor imaging analysis along perivascular spaces (DTI-ALPS) index, enlarged perivascular spaces (EPVS) numbers/volume, and choroid plexus volume (CPV) across different cognitive stages of CSVD.
We retrospectively analyzed data from 102 CSVD patients [33 CSVD-cognitive normal (CSVD-CN); 39 CSVD-mild cognitive impairment (CSVD-MCI); 30 vascular dementia (VaD)] and 29 normal controls (NCs). Quantitative measurements of the DTI-ALPS index, EPVS numbers/volume, and CPV were obtained. Correlations with Montreal Cognitive Assessment (MoCA) scores and diagnostic performance were also evaluated.
Progressive DTI-ALPS index reduction (NCs: 1.50±0.19, CSVD-CN: 1.41±0.17, CSVD-MCI: 1.34±0.16, VaD: 1.33±0.17; P<0.001, r=0.36) and increases in basal ganglia (BG)-EPVS numbers {NCs: 4 [3, 6], CSVD-CN: 14 [10, 17], CSVD-MCI: 16 [12, 25], VaD: 22 [13, 31]; P<0.001, r=-0.45} and CPV {NCs: 1.35 [1.02, 1.65] cm, CSVD-CN: 1.39 [1.11, 1.72] cm, CSVD-MCI: 1.88 [1.41, 2.94] cm, VaD: 2.89 [2.09, 3.39] cm; P<0.001, r=-0.43} correlated with cognitive decline. BG-EPVS numbers excellently distinguished CSVD from NCs [area under the receiver operating characteristic (ROC) curve (AUC) =0.926; 95% confidence interval (CI): 0.882-0.971; sensitivity =84.2%; specificity =89.7%]. CPV emerged as the optimal standalone biomarker for VaD (AUC =0.758; 95% CI: 0.647-0.869; sensitivity =82.8%; specificity =69.5%). The multiparametric model (DTI-ALPS + BG-EPVS numbers + CPV) achieved high diagnostic accuracy: NCs CSVD: AUC =0.978, 95% CI: 0.958-0.998; VaD NCs/CSVD-CN/CSVD-MCI: AUC =0.825, 95% CI: 0.747-0.903; CSVD-MCI/VaD NCs/CSVD-CN: AUC =0.900, 95% CI: 0.847-0.952.
Combining the DTI-ALPS index, BG-EPVS numbers, and CPV may enhance early diagnosis and subtype differentiation in CSVD-related cognitive impairment, supporting targeted interventions.
脑小血管病（CSVD）是认知障碍和痴呆的主要原因。越来越多的证据表明，血管周围清除功能受损在CSVD发病机制中起关键作用，但用于早期认知衰退的非侵入性生物标志物仍然有限。本研究旨在探讨沿血管周围间隙的扩散张量成像分析（DTI-ALPS）指数、扩大的血管周围间隙（EPVS）数量/体积和脉络丛体积（CPV）在CSVD不同认知阶段的诊断价值。
我们回顾性分析了102例CSVD患者[33例CSVD认知正常（CSVD-CN）；39例CSVD轻度认知障碍（CSVD-MCI）；30例血管性痴呆（VaD）]和29例正常对照（NCs）的数据。获得了DTI-ALPS指数、EPVS数量/体积和CPV的定量测量值。还评估了与蒙特利尔认知评估（MoCA）评分的相关性及诊断性能。
DTI-ALPS指数逐渐降低（NCs：1.50±0.19，CSVD-CN：1.41±0.17，CSVD-MCI：1.34±0.16，VaD：1.33±0.17；P<0.001，r=0.36），基底节（BG）-EPVS数量增加{NCs：4[3,6]，CSVD-CN：14[10,17]，CSVD-MCI：16[12,25]，VaD：22[13,31]；P<0.001，r=-0.45}以及CPV增加{NCs：1.35[1.02,1.65]cm，CSVD-CN：1.39[1.11,1.72]cm，CSVD-MCI：1.88[1.41,2.94]cm，VaD：2.89[2.09,3.39]cm；P<0.001，r=-0.43}与认知衰退相关。BG-EPVS数量能很好地区分CSVD与NCs[受试者操作特征（ROC）曲线下面积（AUC）=0.926；95%置信区间（CI）：0.882-0.971；敏感性=84.2%；特异性=89.7%]。CPV成为VaD的最佳独立生物标志物（AUC=0.758；95%CI：0.647-0.869；敏感性=82.8%；特异性=69.5%）。多参数模型（DTI-ALPS+BG-EPVS数量+CPV）具有较高的诊断准确性：NCs与CSVD：AUC=0.978，95%CI：0.958-0.998；VaD与NCs/CSVD-CN/CSVD-MCI：AUC=0.825，95%CI：0.747-0.903；CSVD-MCI/VaD与NCs/CSVD-CN：AUC=0.900，95%CI：0.847-0.952。
结合DTI-ALPS指数、BG-EPVS数量和CPV可能会提高CSVD相关认知障碍的早期诊断和亚型区分能力，为靶向干预提供支持。
