biostudies-literatureWang YNICHD NIH HHS101981https://www.ebi.ac.uk/biostudies/studies/S-EPMC6728875biostudies-literatureUnknown24<h4>Objective</h4>The supply territories of main cerebral arteries are predominantly identified based on distribution of infarct lesions in patients with large arterial occlusion; whereas, there is no consensus atlas regarding the supply territories of smaller end-arteries. In this study, we applied a data-driven approach to construct a stroke atlas of the brain using hierarchical density clustering in large number of infarct lesions, assuming that voxels/regions supplied by a common end-artery tend to infarct together.<h4>Methods</h4>A total of 793 infarct lesions on MRI scans of 458 patients were segmented and coregistered to MNI-152 standard brain space. Applying a voxel-wise data-driven hierarchical density clustering algorithm, we identified those voxels that were most likely to be paNeuroImage. ClinicalStroke atlas of the brain: Voxel-wise density-based clustering of infarct lesions topographic distribution.PMC6728875K01 HD091283McKinney AMLiew SLWang YJuliano JMPayabvash SfalseStroke atlas of the brain: Voxel-wise density-based clustering of infarct lesions topographic distribution.<h4>Objective</h4>The supply territories of main cerebral arteries are predominantly identified based on distribution of infarct lesions in patients with large arterial occlusion; whereas, there is no consensus atlas regarding the supply territories of smaller end-arteries. In this study, we applied a data-driven approach to construct a stroke atlas of the brain using hierarchical density clustering in large number of infarct lesions, assuming that voxels/regions supplied by a common end-artery tend to infarct together.<h4>Methods</h4>A total of 793 infarct lesions on MRI scans of 458 patients were segmented and coregistered to MNI-152 standard brain space. Applying a voxel-wise data-driven hierarchical density clustering algorithm, we identified those voxels that were most likely to be pa2019-01-01T00:00:00Z20192025-04-04T10:33:14.114Z2019-09-24T07:08:06ZS-EPMC67288753147354410.1016/j.nicl.2019.101981