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Abstract #0789

Comparing the SPIJN algorithm for myelin water fraction mapping with conventional NNLS evaluation in healthy and multiple sclerosis brains

Ronja C. Berg1, Thomas Amthor2, Irene Vavasour3, Mariya Doneva2, and Christine Preibisch1
1Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany, 2Philips Research Europe, Hamburg, Germany, 3Department of Radiology, University of British Columbia, Vancouver, BC, Canada


Myelin water fraction (MWF) mapping provides information on myelin concentration, which can be affected by neurological diseases. Most commonly, a non-negative least squares (NNLS) algorithm is used to obtain MWF. A faster alternative is the Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm. Here, we compared both methods in several brain regions from healthy participants and normal-appearing and lesion tissue from MS patients (EDSS 0-1.5). We found that NNLS-based lesion-average MWF was rather comparable to white matter while SPIJN-based MWF was lower. Thus, SPIJN could be more sensitive to demyelination in lesions but comparisons to gold standard techniques are clearly needed.

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