| Popis: |
We demonstrate high sensitivity for detecting longitudinal change as well as diagnostic sensitivity in ALS by applying recent advances in MRI data acquisition and analysis to multimodal brain and cervical spinal cord data. We acquired high quality diffusion MRI data from the brain and cervical cord, and high quality T1 data from the brain, of 20 participants with ALS and 20 healthy control participants. Ten participants with ALS and 14 healthy control participants, and 11 participants with ALS and 13 healthy control participants were re-scanned at 6-month and 12-month follow-up visits respectively. We analyzed cross-sectional differences and longitudinal changes in brain diffusion metrics and cortical thickness to identify white and gray matter areas affected by the disease. We also used fixel-based microstructure measures, i.e. fiber density and fiber cross-section, that are found more sensitive to longitudinal changes. Combining the brain metrics with our previously reported diffusion and cross-sectional area measures of the spinal cord, we demonstrate improved disease diagnostic accuracy and sensitivity through multimodal analysis of cross-sectional data, including high sensitivity for diagnosis of lower motor neuron-predominant ALS. Fiber density and cross-section provided the greatest sensitivity for change in our longitudinal dataset. We demonstrate evidence of progression in a cohort of 11 participants with slowly progressive ALS, including in participants with very slow change in ALSFRS-R (less than 0.5 points per month). More importantly, we demonstrate that longitudinal change is detectable at a six-month follow-up visit. Our findings suggest that fixel-based measures may serve as potential biomarkers of disease progression in clinical trials. We also provide a comprehensive list of affected areas both in the white matter and cortical gray matter, and report correlations between ALSFRS-R and the fiber density and cross-section. |
