The influence of contralesional brain age gradients on chronic stroke aphasia severity and treatment response

The adult brain follows normative aging trajectories, yet stroke abruptly disrupts this process. Beyond the focal lesion, undamaged regions can deviate from expected aging due to diaschisis or pre-existing vulnerabilities, reflecting tissue health that may constrain recovery. Chronic post-stroke aphasia, a persistent language disorder, shows wide individual variability in severity and treatment response, and these differences are not fully captured by lesion characteristics or demographic factors. Further, prior imaging biomarkers have been difficult to scale because they rely on specialized acquisitions or non-standardized analytical pipelines. Here, we used a standardized, lifespan-informed brain age model (volBrain) trained on large public datasets to quantify regional deviations from normative aging using only routine structural MRI (T1-weighted). In 188 individuals with chronic stroke (67 female, 121 male), regional aging deviations in the contralesional hemisphere explained aphasia severity beyond lesion volume, lesion location, and basic demographics. In a treated subgroup, baseline brain aging patterns also predicted language gains that persisted six months after therapy, indicating prognostic value. By characterizing how individual brains diverge from expected aging, this approach captures variation in tissue integrity that is relevant for both impairment and recovery. This provides a scalable framework that can be integrated across sites and studies, linking normative aging models with post-stroke prognostics and informing precision neurorehabilitation.Significance Statement Stroke can change the brain in ways that extend beyond the visible lesion. This study shows that parts of the brain that appear structurally intact can show signs of accelerated or altered aging, and that these changes relate to how severe a person's language impairment is after stroke and how much they benefit from therapy. Using a standardized 'brain age' model that works on routine MRI scans, we identified patterns of tissue integrity that explained who had better or worse outcomes, even when accounting for lesion size and location. This approach is scalable and can be used across research and clinical settings. These findings highlight the role of brain aging in recovery and can support more personalized rehabilitation planning.