Modelling the Anatomic Distribution of Neurologic Events in Patients with COVID-19: A Systematic Review of MRI Findings.

ABSTRACT

BACKGROUND: Neurologic events have been reported in patients with coronavirus disease 2019 (COVID-19). However, a model-based evaluation of the spatial distribution of these events is lacking. PURPOSE: Our aim was to quantitatively evaluate whether a network diffusion model can explain the spread of small neurologic events. DATA SOURCES The MEDLINE, EMBASE, Scopus, and LitCovid data bases were searched from January 1, 2020, to July 19, 2020. STUDY SELECTION Thirty-five case series and case studies reported 317 small neurologic events in 123 unique patients with COVID-19. DATA ANALYSIS: Neurologic events were localized to gray or white matter regions of the Illinois Institute of Technology (gray-matter and white matter) Human Brain Atlas using radiologic images and descriptions. The total proportion of events was calculated for each region. A network diffusion model was implemented, and any brain regions showing a significant association (P < .05, family-wise error-corrected) between predicted and measured events were considered epicenters. DATA SYNTHESIS: Within gray matter, neurologic events were widely distributed, with the largest number of events (∼10%) observed in the bilateral superior temporal, precentral, and lateral occipital cortices, respectively. Network diffusion modeling showed a significant association between predicted and measured gray matter events when the spread of pathology was seeded from the bilateral cerebellum (r = 0.51, P < .001, corrected) and putamen (r = 0.4, P = .02, corrected). In white matter, most events (∼26%) were observed within the bilateral corticospinal tracts. LIMITATIONS: The risk of bias was not considered because all studies were either case series or case studies. CONCLUSIONS: Transconnectome diffusion of pathology via the structural network of the brain may contribute to the spread of neurologic events in patients with COVID-19.