The accuracy of T1-weighted voxel-wise and region-wise metrics for brain age estimation. (February 2022) - Beheshti, Iman; Maikusa, Norihide; Matsuda, Hiroshi
Highlights: We compared accuracy of anatomical measurements and voxel-wise metrics for predicting brain age. Fifteen different T1-weighted MRI-wise metrics were assessed. Integrated voxel-wise and region-wise metrics may provide a sensitive brain age framework. Abstract: Introduction: The brain age score has recently been introduced for robust monitoring of brain morphological alterations throughout the lifespan, prediction of mortality risk, and early detection of neurological disorders. Methods: We assessed the brain age prediction accuracy of the widely used T1-weighted voxel-wise and region-wise metrics (i.e., T1-weighted magnetic resonance imaging [MRI]-wise metrics)) separately and their integration. We assessed 788 healthy individuals (age, 18–94 years) in a training set to build a brain age estimation framework based on different T1-weighted MRI-wise metrics (15 different metrics in total) and then validated each T1-weighted MRI-wise metric in an independent test set comprising 88 healthy individuals. We also assessed the accuracy of each T1-weighted MRI-wise metric in a clinical set of 70 patients with mild cognitive impairment and another of 30 patients with Alzheimer's disease. Results: Integration of gray matter voxel-wise maps and all region-wise metrics achieved the highest brain age prediction accuracy (mean absolute error, 4.63 years). These metrics on their own achieved lower accuracy (mean absolute error, 4.97 years and 5.75 years, respectively). Discussion: For tracing brain atrophy levels in neurological disorders at the clinical level, integration of voxel-wise and region-wise metrics may contribute to a more sensitive brain age framework than when these metrics are used on their own.