Clinical neurology and neurosurgery · 2025
Spatial distribution of enlarged perivascular spaces as a potential biomarker for distinguishing vascular dementia from Alzheimer's disease in older adults.
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Liu Wanhu, Bu Wei, Meng Linghui, Luo Weigang, Liu Cuicui, Li Xiaohui, Li Wenjun, Ren Huiling
Аннотация
OBJECTIVE: We aimed to examine the potential value of enlarged perivascular space (EPVS) volume as a biomarker for distinguishing between Alzheimer's disease (AD) and vascular dementia (VD) in older people.
METHODS: A total of 93 patients with Alzheimer's disease and 122 patients with vascular dementia, all aged > 65 years and diagnosed via clinical and neuropsychological assessments, were enrolled in this study. A deep learning model based on VB-Net was utilized to automatically quantify the EPVS volume in four brain regions: the basal nuclei (BN), centrum semiovale (CSO), temporal lobe (T), and midbrain (MB). Univariate analysis was conducted to compare the clinical data and EPVS volume characteristics across different regions between patients with Alzheimer's disease and vascular dementia. Multivariate analysis was employed to identify independent factors for distinguishing AD from VD, and the discriminative ability was evaluated using the area under the receiver operating characteristic (ROC) curve.
RESULTS: Univariate analysis revealed that, in comparison with the AD group, the VD group had a higher proportion of patients with hypertension, hyperlipidemia, and lacune, along with a higher Fazekas score for white matter hyperintensities, an increased volume of BN-EPVS, and decreased volumes of CSO-EPVS and T-EPVS (all p < 0.05). Logistic regression analysis showed that BN-EPVS, CSO-EPVS, and T-EPVS volumes were independent factors influencing the differentiation of dementia subtypes (all p < 0.05). Furthermore, ROC curve analysis revealed that the areas under the curve for BN-EPVS, CSO-EPVS, and T-EPVS volumes in distinguishing dementia subtypes were 0.791, 0.712, and 0.700, respectively.
CONCLUSION: There exist spatial disparities in the volumetric distribution of EPVS between AD and VD. The volume of EPVS at various locations can serve as a reliable imaging biomarker for the differential diagnosis of these two dementia subtypes.
METHODS: A total of 93 patients with Alzheimer's disease and 122 patients with vascular dementia, all aged > 65 years and diagnosed via clinical and neuropsychological assessments, were enrolled in this study. A deep learning model based on VB-Net was utilized to automatically quantify the EPVS volume in four brain regions: the basal nuclei (BN), centrum semiovale (CSO), temporal lobe (T), and midbrain (MB). Univariate analysis was conducted to compare the clinical data and EPVS volume characteristics across different regions between patients with Alzheimer's disease and vascular dementia. Multivariate analysis was employed to identify independent factors for distinguishing AD from VD, and the discriminative ability was evaluated using the area under the receiver operating characteristic (ROC) curve.
RESULTS: Univariate analysis revealed that, in comparison with the AD group, the VD group had a higher proportion of patients with hypertension, hyperlipidemia, and lacune, along with a higher Fazekas score for white matter hyperintensities, an increased volume of BN-EPVS, and decreased volumes of CSO-EPVS and T-EPVS (all p < 0.05). Logistic regression analysis showed that BN-EPVS, CSO-EPVS, and T-EPVS volumes were independent factors influencing the differentiation of dementia subtypes (all p < 0.05). Furthermore, ROC curve analysis revealed that the areas under the curve for BN-EPVS, CSO-EPVS, and T-EPVS volumes in distinguishing dementia subtypes were 0.791, 0.712, and 0.700, respectively.
CONCLUSION: There exist spatial disparities in the volumetric distribution of EPVS between AD and VD. The volume of EPVS at various locations can serve as a reliable imaging biomarker for the differential diagnosis of these two dementia subtypes.