RESUMEN
Pathophysiological mechanisms of neurological disorders in patients with coronavirus disease 2019 (COVID-19) are poorly understood, partly because of a lack of high-resolution neuroimaging data. We applied SynthSR, a convolutional neural network that synthesizes high-resolution isotropic research-quality data from thick-slice clinical MRI data, to a cohort of 11 patients with severe COVID-19. SynthSR successfully synthesized T1-weighted MPRAGE data at 1 mm spatial resolution for all 11 patients, each of whom had at least one brain lesion. Correlations between volumetric measures derived from synthesized and acquired MPRAGE data were strong for the cortical grey matter, subcortical grey matter, brainstem, hippocampus, and hemispheric white matter (r=0.84 to 0.96, p[≤]0.001), but absent for the cerebellar white matter and corpus callosum (r=0.04 to 0.17, p>0.61). SynthSR creates an opportunity to quantitatively study clinical MRI scans and elucidate the pathophysiology of neurological disorders in patients with COVID-19, including those with focal lesions.