Regional cerebral atrophy contributes to personalized survival prediction in ALS: a multicentre, machine learning, deformation based morphometry study

ObjectiveAccurate personalized survival prediction in amyotrophic lateral sclerosis is essential for effective patient care planning. This study investigates whether gray and white matter changes measured by magnetic resonance imaging can improve individual survival predictions. MethodsWe analyzed data from 178 amyotrophic lateral sclerosis patients and 166 healthy controls in the Canadian ALS Neuroimaging Consortium study. A voxel-wise linear mixed- effects model assessed disease-related and survival-related atrophy detected through deformation-based morphometry, controlling for age, sex, and scanner variations. Additional linear mixed-effects 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. An individual survival distributions model was evaluated using clinical data alone, imaging data alone, and a combination of both features. ResultsDeformation-based morphometry uncovered distinct voxel-wise atrophy patterns linked to disease progression and survival, with many of these regional atrophy 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. InterpretationThis study suggests that brain atrophy patterns measured by deformation- based 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.