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Abstract #2748

Stroke atlas of the brain: A voxel-wise density-based clustering of infarct lesion topographic distribution

Yanlu Wang1,2, Hadrien Van Loo3, Julia Juliano4, Sook-Lei Liew5,6, Alexander McKinney IV7, and Sam Payabvash8

1Clinical Sciences, Intervention and Technology, Karolinska Institute, Sollentuna, Sweden, 2Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden, 3Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Huddinge, Sweden, 4University of Southern California, Los Angeles, CA, United States, 5Viterbi School, Department of Biomedical Engineering, Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Kek School of Medicine, Los Angeles, CA, United States, 6Department of Neurology USC Stevens Neuroimaging and Informatics Institute, Division of Biokinesiology and Physical Therapy, University of Southern California, Keck School of Medicin, Los Angeles, CA, United States, 7Department of Radiology, University of Minnesota, Minneapolis, MN, United States, 8Yale Medicine, New Haven, CT, United States

In stroke patients, both infarct volume and location affect functional outcome; however, infarct topography is far less commonly incorporated in prognostic models, given the complexity of assessing infarct topographic distribution. In this study, we applied data-driven density clustering analysis, using the OPTICS algorithm, on 793 infarct lesions from 438 stroke patients to devise a “stroke-atlas of the brain” stratifying brain voxels likely to infarct together. This atlas can help with differentiation of infarct lesions in clinical practice, assess topographic distribution of infarct in prognostic models for stroke patients, or be applied for defining regional infarct thresholds in CT/MR perfusion maps.

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