Predictors and integrative index of severity of cognitive disorders in cerebral microangiopathy

Abstract

To search for sensitive predictors of cognitive impairment (CI) and an integrative index of their severity. We assessed CI and diffusion-tensor MRI (DT-MRI) in the regions of interest (ROI) significant for CI in 74 patients (48 women, mean age 60.6±6.9 years) with cerebral small vessel disease (CSVD). The results of DT-MRI were used to construct a predictive model of CI using binary logistic regression and to calculate an integrative index of CI severity. According to the constructed model, the predictors of CI were axial diffusivity (AD) of posterior frontal periventricular normal-appearing white matter (pvNAWM), right middle cingulum bundle (CB) and mid-posterior corpus callosum (CC). ROC analysis showed strong model predictive power for CI in cSVD (AUC (95% CI): 0.845 (0.740-0.950)). The threshold value of the AD predictors model for CI in cSVD was 0.53 (sensitivity 84%, specificity 76%). AD predictors of CI showed significant correlations with white matter hyperintensities volume and MoCA scores. The presence of CI as measured by neuropsychological testing and regression equation solution was corresponded to individual AD predictors of patients exceeding the CI model's threshold. Disturbances in the AD of pvNAWM, right middle CB and mid-posterior CC associated with axonal damage are a predominant factor in the development of CI in CSVD. The predictors of CI and the integrative index of CI severity calculated on their basis can potentially be used as a tool for assessing the severity of CI and the effectiveness of treatment, as well as in clarifying the interaction between vascular and degenerative pathology and in developing measures for the prevention of CI in patients with MRI signs of cSVD.