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Abstract #1254

 Estimation of Multiple Sclerosis Lesion Age without Gadolinium using Quantitative Susceptibility Maps

Elizabeth Margaret Sweeney1, Thanh Nygen1, Amy Kuceyeski1, Sarah Ryan 2, Shun Zhang1, Yi Wang1, and Susan Gauthier1
1Weill Cornell, New York, NY, United States, 2University of Colorado Denver, Denver, CO, United States

We propose a method to estimate multiple sclerosis (MS) lesion age (less than or greater than a year old) using non-gadolinium magnetic resonance imaging. The method utilizes the less invasive Quantitative Susceptibility Map. Radiomic features are calculated over a lesion and a random forest classification model is used. In a validation set, the model has an AUC of 0.79 (95% CI: [0.63, 0.86]) and an accuracy of 0.73 (95% CI: [0.60, 0.80]). This method can be used to aid in the diagnosis of MS, as part of the diagnostic criteria is to show lesion dissemination in time.

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