Frontiers in neurology · 2026
Perivascular diffusion and white matter free water improve identification of cognitive impairment in cerebral small vessel disease.
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Yang Chunhong, Cai Sunmei, Wang Bing, Zhou Jie, Wu Dongmei, Li Muzi, Geng Wenlu, Wu Lianshuang, Peng Kaiyue, Yang Yi, Gu Wenquan
Аннотация
INRODUCTION: Cerebral small vessel disease contributes substantially to cognitive decline in older adults, but conventional structural magnetic resonance imaging markers mainly reflect accumulated lesion burden and do not directly characterize diffusion-derived alterations in brain fluid homeostasis. We investigated whether combining diffusion imaging along the perivascular space and white matter free-water imaging improves identification of Montreal Cognitive Assessment (MoCA)-defined cognitive impairment in elderly patients with cerebral small vessel disease.
METHODS: This prospective study included 100 patients with cerebral small vessel disease and 50 healthy controls. According to MoCA scores, patients were classified as cognitively normal (n = 42) or cognitively impaired (n = 58). All participants underwent 3.0-T magnetic resonance imaging, including conventional structural imaging and diffusion tensor imaging. Conventional structural magnetic resonance imaging markers were evaluated on anatomical imaging, whereas diffusion-derived metrics were used to assess perivascular diffusion and free-water burden. Group comparisons, correlation analyses, multivariate logistic regression, and receiver operating characteristic analyses were performed.
RESULTS: Analysis along the perivascular space decreased progressively from healthy controls to cognitively normal patients and cognitively impaired patients, whereas white matter free water increased in the opposite direction (all p < 0.001). Lower ALPS-Index values and higher white matter free-water values were both associated with lower MoCA scores. The clinical information model showed moderate discrimination for MoCA-defined cognitive impairment (area under the curve = 0.764, 95% confidence interval: 0.669-0.859). After incorporating age, sex, education, hypertension, and diabetes as covariates, the traditional cerebral small vessel disease marker model achieved an area under the curve of 0.819 (95% confidence interval: 0.731-0.908), whereas the glymphatic-edema signature combining ALPS-Index and white matter free water achieved better discriminative performance (area under the curve = 0.928, 95% confidence interval: 0.875-0.981). The combined imaging model incorporating conventional structural markers, ALPS-Index, and white matter free water achieved the highest discriminative performance (area under the curve = 0.950, 95% confidence interval: 0.906-0.993).
DISCUSSION: Perivascular diffusion imaging and white matter free water capture complementary aspects of altered perivascular diffusion and extracellular free-water accumulation in cerebral small vessel disease and improve identification of MoCA-defined cognitive impairment beyond conventional structural magnetic resonance imaging markers.
METHODS: This prospective study included 100 patients with cerebral small vessel disease and 50 healthy controls. According to MoCA scores, patients were classified as cognitively normal (n = 42) or cognitively impaired (n = 58). All participants underwent 3.0-T magnetic resonance imaging, including conventional structural imaging and diffusion tensor imaging. Conventional structural magnetic resonance imaging markers were evaluated on anatomical imaging, whereas diffusion-derived metrics were used to assess perivascular diffusion and free-water burden. Group comparisons, correlation analyses, multivariate logistic regression, and receiver operating characteristic analyses were performed.
RESULTS: Analysis along the perivascular space decreased progressively from healthy controls to cognitively normal patients and cognitively impaired patients, whereas white matter free water increased in the opposite direction (all p < 0.001). Lower ALPS-Index values and higher white matter free-water values were both associated with lower MoCA scores. The clinical information model showed moderate discrimination for MoCA-defined cognitive impairment (area under the curve = 0.764, 95% confidence interval: 0.669-0.859). After incorporating age, sex, education, hypertension, and diabetes as covariates, the traditional cerebral small vessel disease marker model achieved an area under the curve of 0.819 (95% confidence interval: 0.731-0.908), whereas the glymphatic-edema signature combining ALPS-Index and white matter free water achieved better discriminative performance (area under the curve = 0.928, 95% confidence interval: 0.875-0.981). The combined imaging model incorporating conventional structural markers, ALPS-Index, and white matter free water achieved the highest discriminative performance (area under the curve = 0.950, 95% confidence interval: 0.906-0.993).
DISCUSSION: Perivascular diffusion imaging and white matter free water capture complementary aspects of altered perivascular diffusion and extracellular free-water accumulation in cerebral small vessel disease and improve identification of MoCA-defined cognitive impairment beyond conventional structural magnetic resonance imaging markers.