Abstract #2535

Automated evaluation of deep gray matter neuronal damage in multiple sclerosis patients

Bénédicte Maréchal^1,2,3, Alexis Roche^1,2,3, Tobias Kober^1,2,3, Wadie Ben Hassen⁴, Alain Créange⁵, Jérome Hodel⁶, and Pierre Brugières⁶

¹Advanced Clinical Imaging Technology, Siemens Healthcare HC CEMEA SUI DI PI, Lausanne, Switzerland, ²Department of Radiology, CHUV, Lausanne, Switzerland, ³LTS5, EPFL, Lausanne, Switzerland, ⁴Siemens Healthcare S.A.S., Saint-Denis, France, ⁵Department of Neurology, University Hospital Henri Mondor, Créteil, Switzerland, ⁶Department of Neuroradiology, University Hospital Henri Mondor, Créteil, France

We investigate the potential of a technique to automatize quantification of neuronal damage from T1-weighted MR scans in multiple sclerosis patients. T1 hypointense component measures in the deep nuclei are derived from 40 MPRAGE scans (21 relapsing-remitting MS and 19 age-matched controls) through combined brain tissue classification and atlas-based segmentation algorithms. Our analysis shows that these automated measures are significantly lower in the thalamus and putamen of MS patients, which is in line with previously reported loss of structure in these regions.

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