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Abstract #3132

Effects of Treatment on Brain Tissue Classification with Serial MRI-Based ISODATA Cluster Analysis in an Experimental Subarachnoid Hemorrhage Model

Mark J.R.J. Bouts1, Ivo A.C.W. Tiebosch1, Ren Zwartbol1, Ona Wu2, Rick M. Dijkhuizen1

1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands; 2Athinoula A. Martinos center for biomedical imaging, Massachusetts General Hospital, Charlestown, MA, United States

Voxel-wise clustering of multiparametric MRI data enables classification of heterogeneous ischemic lesions into distinct categories. Previously, we have introduced a lesion clustering approach that incorporates temporal T2 and diffusion dynamics for tissue characterization. In the current study we extend this approach in an experimental subarachnoid hemorrhage model, to evaluate lesion characteristics in a treatment and control group based on temporal changes in T2, diffusion, and perfusion parameters. Five distinct signatures with different characteristics of cerebrovascular injury were identified and signature distribution revealed a different prevalence in Interferon-β treated animals compared to controls.