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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