{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T06:09:50Z","timestamp":1784268590051,"version":"3.55.0"},"reference-count":98,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T00:00:00Z","timestamp":1784246400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Myalgic Encephalomyelitis\/Chronic Fatigue Syndrome (ME\/CFS) and long COVID have overlapping symptoms, such as profound fatigue, cognitive impairment, post-exertional malaise, pain and sleep disturbances that are debilitating and reduce quality of life. While Magnetic Resonance Imaging (MRI) techniques, specifically Diffusion Tensor Imaging (DTI) and Diffusion Kurtosis Imaging (DKI), have been used to investigate brain tissue microstructure in ME\/CFS or long COVID, no study has yet combined these modalities to directly compare tissue microstructural differences between people living with ME\/CFS and long COVID.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We recruited 37 ME\/CFS participants (Age: 43.56 \u00b1 12.5), 19 long COVID participants (Age: 47.92 \u00b1 13.3), and 27 healthy controls (Age: 37.9 \u00b1 10.4). Data were acquired using a 3 Tesla (3T) Prisma MRI scanner. DTI and DKI metrics were determined using MRtrix v3.0.7 and Designer V2.0 software, respectively. Voxel-based statistical analysis of cohort differences was performed using the Statistical Parametric Mapping (SPM12) toolbox in MATLAB. Correlation analysis was performed between DTI, DKI metrics and clinical measures such as duration of illness, fatigue severity, SF36 domains and WHODAS domains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Compared with healthy controls, individuals with ME\/CFS showed microstructural alterations in the cingulum, supplementary motor areas, and parts of the corpus callosum (all\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.05). Long COVID participants demonstrated microstructural alterations in regions including the fusiform and precentral gyrus and in major white matter tracks (all\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.05). Direct comparisons between ME\/CFS and long COVID revealed difference in the left corona radiata (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study identifies distinct tissue microstructural alterations in ME\/CFS and long COVID and offers a vital insight into the neuropathological basis of shared symptoms in both conditions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1824498","type":"journal-article","created":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T05:45:53Z","timestamp":1784267153000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Microstructural alterations in brain tissue of ME\/CFS and long COVID using diffusion tensor imaging and diffusion kurtosis imaging"],"prefix":"10.3389","volume":"13","author":[{"given":"Tanoj Bahadur","family":"Singh","sequence":"first","affiliation":[{"name":"National Center for Neuroimmunology and Emerging Diseases, Griffith University","place":["Gold Coast, QLD, Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sonya","family":"Marshall-Gradisnik","sequence":"additional","affiliation":[{"name":"National Center for Neuroimmunology and Emerging Diseases, Griffith University","place":["Gold Coast, QLD, Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leighton","family":"Barnden","sequence":"additional","affiliation":[{"name":"National Center for Neuroimmunology and Emerging Diseases, Griffith University","place":["Gold Coast, QLD, Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natalie","family":"Eaton-Fitch","sequence":"additional","affiliation":[{"name":"National Center for Neuroimmunology and Emerging Diseases, 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