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There is also immense scientific interest and potential clinical utility to evaluate the sensitivity of single\u2010shell diffusion magnetic resonance imaging (MRI) methods for detecting such effects. In this work, the performances of three single\u2010shell\u2010compatible diffusion MRI modeling methods are compared for detecting the effect of COVID\u201019, including diffusion\u2010tensor imaging, diffusion\u2010tensor decomposition of orthogonal moments and correlated diffusion imaging. Imaging was performed on self\u2010isolated patients at the study initiation and 3\u2010month follow\u2010up, along with age\u2010 and sex\u2010matched controls. We demonstrate through simulations and experimental data that correlated diffusion imaging is associated with far greater sensitivity, being the only one of the three single\u2010shell methods to demonstrate COVID\u201019\u2010related brain effects. Results suggest less restricted diffusion in the frontal lobe in COVID\u201019 patients, but also more restricted diffusion in the cerebellar white matter, in agreement with several existing studies highlighting the vulnerability of the cerebellum to COVID\u201019 infection. These results, taken together with the simulation results, suggest that a significant proportion of COVID\u201019 related white\u2010matter microstructural pathology manifests as a change in tissue diffusivity. Interestingly, different <jats:italic>b<\/jats:italic>\u2010values also confer different sensitivities to the effects. No significant difference was observed in patients at the 3\u2010month follow\u2010up, likely due to the limited size of the follow\u2010up cohort. To summarize, correlated diffusion imaging is shown to be a viable single\u2010shell diffusion analysis approach that allows us to uncover opposing patterns of diffusion changes in the frontal and cerebellar regions of COVID\u201019 patients, suggesting the two regions react differently to viral infection.<\/jats:p>","DOI":"10.1002\/hbm.26322","type":"journal-article","created":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T04:30:02Z","timestamp":1683779402000},"page":"3998-4010","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Feasibility of diffusion\u2010tensor and correlated diffusion imaging for studying white\u2010matter microstructural abnormalities: Application in <scp>COVID<\/scp>\u201019"],"prefix":"10.1002","volume":"44","author":[{"given":"Nick","family":"Teller","sequence":"first","affiliation":[{"name":"Rotman Research Institute Baycrest Health Sciences  Toronto 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