$125,000 awarded to Dr. Mahsa Dadar, McGill University, in collaboration with Dr. Sanjay Kalra, University of Alberta.
Previous imaging studies have revealed changes in specific brain regions among people living with ALS. However, the extent and location of these changes can differ significantly from person to person. This has led researchers to question whether the variability in brain atrophy patterns is linked to the diversity in symptoms often observed in people with ALS, such as age of onset, disease duration, cognitive changes, and more. If such a link exists, measuring these brain changes could provide a non-invasive way for health care professionals to monitor disease progression more accurately and possibly even predict future clinical symptoms and survival outcomes.
Deformation-based morphometry (DBM) is a sensitive method for quantifying changes in various brain regions using magnetic resonance imaging (MRI). The team previously demonstrated the potential of DBM as a biomarker for ALS in a small group of individuals with the disease. With this award, they will leverage a more comprehensive data set collected through national initiatives such as the Canadian ALS Neuroimaging Consortium (CALSNIC) and the Comprehensive Analysis Platform To Understand, Remedy, and Eliminate ALS (CAPTURE ALS) to explore the relationship between DBM measurements and clinical symptoms.
Using artificial intelligence, Dr. Dadar aims to uncover complex patterns in the data that otherwise may have remained undetectable with individual methods alone. This multidimensional approach may reveal insights into the mechanisms behind disease progression, survival, and clinical symptoms. The goal of this study is to develop non-invasive MRI-based biomarkers for ALS and predictive models that could change how healthcare professionals monitor and track the disease. Ultimately, these findings will contribute to a deeper understanding of ALS and advance our ability to effectively manage the disease.