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Neuroimaging methods such as diffusion magnetic resonance imaging (MRI), functional MRI (fMRI), and positron emission tomography (PET) provide insight into micro\u2010 and macro\u2010scale changes post\u2010traumatic brain injury (TBI), but the relationships between regional cellular and functional alterations remain unclear. In this exploratory study, we conducted a longitudinal, multimodal neuroimaging analysis quantifying TBI\u2010related pathologies in four biomarkers, namely flumazenil PET derived binding potential, diffusion MRI (dMRI)\u2010derived structural connectivity, and resting\u2010state fMRI\u2010derived functional connectivity and fractional amplitude of low\u2010frequency fluctuations in individuals with complicated mild\u2010to\u2010severe brain injury at the subacute (4\u20136\u2009months post\u2010injury) and chronic (1\u2010year post\u2010injury) stages. The TBI sample consisted of 41 fMRI, 40 dMRI, and nine PET subjects, with 16 fMRI and dMRI and seven PET longitudinal measurements. The control sample consisted of 14 dMRI and fMRI and 19 PET subjects scanned at a single time point for comparison with TBI subjects at both time points. Most of the PET and MRI subjects are overlapping in both TBI and control groups. Brain injury related regional pathologies, and their changes over time in TBI subjects, were correlated across the four biomarkers. Our results reveal complex, dynamic changes over time. We found that flumazenil\u2010PET binding potential was significantly reduced in frontal and thalamic regions in brain\u2010injured subjects, consistent with neural loss and dysfunction, with partial recovery over time. Functional hyperconnectivity was observed in brain injured subjects initially but declined while remaining elevated compared to non\u2010injured controls, whereas cortical structural hypoconnectivity persisted. Importantly, we observed that brain injury\u2010related alterations across MRI modalities became more strongly correlated with flumazenil\u2010PET at the chronic stage. Regions with chronic reductions in flumazenil\u2010PET binding also showed weaker structural node strength and lower amplitude of low\u2010frequency fluctuations, a relationship that was not found at the subacute stage. This observation could suggest a progressive convergence of structural and functional disruptions with neuronal dysfunction and loss over time. Additionally, regions with declining structural node strength also exhibited decreases in functional node strength, while these same regions showed increased amplitude of low\u2010frequency fluctuations over time. This pattern suggests that heightened intrinsic regional activity may serve as a compensatory mechanism in regions increasingly disconnected due to progressive axonal degradation. Altogether, these findings advance our understanding of how multimodal neuroimaging captures the evolving interplay between neuronal integrity, structural connectivity, and functional dynamics after brain injury. Given the exploratory nature of this study, stemming from the modest sample size, future work in larger cohorts will be essential to validate and refine these preliminary associations as well as the inclusion of multiple measures of healthy controls. Clarifying these interrelationships could inform prognostic models and enhance knowledge of degenerative, compensatory, and recovery mechanisms in traumatic brain injury.<\/jats:p>","DOI":"10.1002\/hbm.70534","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T03:54:35Z","timestamp":1777348475000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Longitudinal Multimodal Neuroimaging After Traumatic Brain Injury"],"prefix":"10.1002","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-5819-7616","authenticated-orcid":false,"given":"Ana","family":"Radanovic","sequence":"first","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keith W.","family":"Jamison","sequence":"additional","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"},{"name":"Department of Computational Biology Cornell University  Ithaca New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yeona","family":"Kang","sequence":"additional","affiliation":[{"name":"Department of Mathematics Howard University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6828-886X","authenticated-orcid":false,"given":"Ceren","family":"Tozlu","sequence":"additional","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sudhin A.","family":"Shah","sequence":"additional","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy","family":"Kuceyeski","sequence":"additional","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"},{"name":"Department of Computational Biology Cornell University  Ithaca New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,27]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.03.017"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.10.019"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.23269"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1023\/a:1025063811290"},{"issue":"7","key":"e_1_2_11_6_1","first-page":"999","article-title":"Neurobehavioral Consequences of Traumatic Brain Injury","volume":"73","author":"Ashman T. 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