{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T23:58:23Z","timestamp":1789516703864,"version":"build-2803163510"},"reference-count":50,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:00:00Z","timestamp":1740182400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009408","name":"Fondation Brain Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009408","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009017","name":"ALS Society of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009017","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Annals of Neurology"],"published-print":{"date-parts":[[2025,6]]},"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>Accurate personalized survival prediction in amyotrophic lateral sclerosis is essential for effective patient care planning. This study investigates whether grey and white matter changes measured by magnetic resonance imaging can improve individual survival predictions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We analyzed data from 178 patients with amyotrophic lateral sclerosis and 166 healthy controls in the Canadian Amyotrophic Lateral Sclerosis Neuroimaging Consortium study. A voxel\u2010wise linear mixed\u2010effects model assessed disease\u2010related and survival\u2010related atrophy detected through deformation\u2010based morphometry, controlling for age, sex, and scanner variations. Additional linear mixed\u2010effects models explored associations between regional imaging and clinical measurements, and their associations with time to the composite outcome of death, tracheostomy, or permanent assisted ventilation. We evaluated whether incorporating imaging features alongside clinical data could improve the performance of an individual survival distribution model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Deformation\u2010based morphometry uncovered distinct voxel\u2010wise atrophy patterns linked to disease progression and survival, with many of these regional atrophies significantly associated with clinical manifestations of the disease. By integrating regional imaging features with clinical data, we observed a substantial enhancement in the performance of survival models across key metrics. Our analysis identified specific brain regions, such as the corpus callosum, rostral middle frontal gyrus, and thalamus, where atrophy predicted an increased risk of mortality.<\/jats:p><\/jats:sec><jats:sec><jats:title>Interpretation<\/jats:title><jats:p>This study suggests that brain atrophy patterns measured by deformation\u2010based morphometry provide valuable insights beyond clinical assessments for prognosis. It offers a more comprehensive approach to prognosis and highlights brain regions involved in disease progression and survival, potentially leading to a better understanding of amyotrophic lateral sclerosis. 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