Back

The Canadian ALS Neuroimaging Consortium (CALSNIC) - a multicentre platform for standardized imaging and clinical studies in ALS

Kalra, S.; Khan, M. U.; Barlow, L.; Beaulieu, C.; Benatar, M.; Briemberg, H.; Chenji, S.; Clua, M. G.; Das, S.; Dionne, A.; Dupre, N.; Emery, D.; Eurich, D.; Frayne, R.; Genge, A.; Gibson, S.; Graham, S.; Hanstock, C.; Ishaque, A.; Joseph, J. T.; Keith, J.; Korngut, L.; Krebs, D.; McCreary, C. R.; Pattany, P.; Seres, P.; Shoesmith, C.; Szekeres, T.; Tam, F.; Welsh, R. C.; Wilman, A.; Yang, Y. H.; Yunusova, Y.; Zinman, L.; Canadian ALS Neuroimaging Consortium,

2020-08-13 neurology
10.1101/2020.07.10.20142679 medRxiv
Show abstract

BackgroundAmyotrophic lateral sclerosis (ALS) is a disabling and rapidly progressive neurodegenerative disorder. Increasing age is an important risk factor for developing ALS, thus the societal impact of this devastating disease will become more profound as the population ages. A significant hurdle to finding effective treatment has been an inability to accurately quantify cerebral degeneration associated with ALS in humans. Advanced magnetic resonance imaging (MRI) techniques hold promise in providing a set of biomarkers to assist in aiding diagnosis and in efficiently evaluating new drugs to treat ALS. MethodsThe Canadian ALS Neuroimaging Consortium (CALSNIC) was founded to develop and evaluate advanced MRI-based biomarkers that delineate biological heterogeneity, track disease progression, and predict survival in a large and heterogeneous sample of ALS patients. FindingsCALSNIC has launched two studies to date (CALSINC-1, CALSNIC-2), acquiring multimodal neuroimaging, neurological, neuropsychological data, and neuropathological data from ALS patients and healthy controls in a prospective and longitudinal fashion from multiple centres in Canada and, more recently, the United States. Clinical and MRI protocols are harmonized across research centres and different MR vendors. InterpretationCALSNIC provides a multicentre platform for studying ALS biology and developing MRI-based biomarkers. FundingCanadian Institutes of Health Research, ALS Society of Canada, Brain Canada Foundation, Shelly Mrkonjic Research Fund

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.