Abstract #4489

SlicerDMRI: a suite of clinician-accessible tools for neurosurgical planning research using diffusion MRI and tractography

Fan Zhang¹, Thomas Noh¹, Parikshit Juvekar¹, Sarah F Frisken¹, Laura Rigolo¹, Isaiah Norton¹, Tina Kapur¹, Sonia Pujol¹, William Wells III^1,2, Alex Yarmarkovich³, Gordon Kindlmann⁴, Demian Wassermann⁵, Raul San Jose Estepar¹, Yogesh Rathi¹, Ron Kikinis^1,6, Hans J Johnson⁷, Carl-Fredrik Westin¹, Steve Pieper³, Alexandra J Golby¹, and Lauren J O'Donnell¹

¹Harvard Medical School, Boston, MA, United States, ²Massachusetts Institute of Technology, Boston, MA, United States, ³Isomics, Inc., Cambridge, MA, United States, ⁴University of Chicago, Chicago, IL, United States, ⁵Université Paris-Saclay, Palaiseau, France, ⁶University of Bremen and Fraunhofer MEVIS, Bremen, Germany, ⁷University of Iowa, Iowa City, IA, United States

We present an open-source software suite, SlicerDMRI (dmri.slicer.org), that enables neurosurgical planning research using diffusion magnetic resonance imaging (dMRI). SlicerDMRI is built upon and deeply integrated with 3D Slicer, an NIH-supported open-source platform for medical image informatics, image processing, and three-dimensional visualization. In this work, we give a demonstration of SlicerDMRI to enable end-to-end dMRI analyses in two retrospective imaging datasets from patients with high-grade glioma. Analyses demonstrated here include conventional diffusion tensor imaging (DTI) analysis, advanced multi-fiber tractography, automated identification of critical fiber tracts, and integration of multimodal imagery with dMRI.

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