Rating scales and indicators of diffusion tensor imaging in predicting motor deficit regression in patients with cerebral stroke

Stroke and subsequent movement disorders are a significant medical and social problem. In 2021, 500 thousand newly diagnosed strokes were registered in the Russian Federation. No more than 10 % of people return to work within the first year after a stroke, 30 % remain disabled for life. In this regard, it is the relevant to predict motor disease outcomes at different periods in patients with a cerebral stroke. The currently existing severity scales are mostly used to characterize early movement disorders, and long-term effects often remain unassessed. There are no methods for predicting the degree of movement disorders in patients with a cerebral stroke in the long term. Objectively, information on the ratio of the level of brain damage and the likelihood of subsequent motor deficit improvement in vivo can be obtained from neuroimaging images. Predicting the severity of movement disorders is potentially possible by analyzing the state of CNS conducting pathways, primarily the corticospinal tracts. This paper presents our vision on using a clinical neuroimaging method to predict the regression of motor consequences after a cerebral stroke using neurological rating scales and visual assessment of the corticospinal tracts during MRI based on the modern literature analysis. According to the literature, clinical scales used in the acute period of acute cerebrovascular accident correlate with the assessment of corticospinal tract profile. Therefore, the combination of these methods is promising while assessing motor deficit regression.