Abstract #1828

Detection of small cerebral lesions using multi-component MR Fingerprinting with local joint sparsity

Martijn Nagtegaal¹, Ingo Hermann^1,2, Sebastian Weingärtner¹, Jeroen de Bresser³, and Frans Vos¹

¹Department of Imaging Physics, Delft University of Technology, Delft, Netherlands, ²Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, ³Department of Radiology, Leiden University Medical Centre, Leiden, Netherlands

We propose a novel multi-component analysis for MR fingerprinting that enables detection of small lesions, while taking partial volume effects into account. The algorithm uses a joint sparsity constraint limiting the number of components in local regions. It is evaluated in simulations and on MRF-EPI data from a patient with multiple sclerosis (MS). MS-lesions are separated from other tissues based on having increased T₂^* relaxation times. The improved sensitivity to multiple components makes it possible to detect components with long relaxation times within the lesion, possibly increasing our insight into these small pathologies.

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