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Vascular Territory template and atlases in MNI space

<p><strong>Data</strong></p> <p>Sixteen subjects (mean age (sd): 69.6 (8.2); 37.5% female) were recruited to generate a high-resolution template. The cohort consists of twelve stroke-free, non-demented patients with the sporadic form of cerebral amyloid angiopathy (CAA), and similarly-aged healthy controls (n=4). Each participant underwent high-resolution MRI&nbsp;with a Siemens Magnetom Prisma 3T scanner (using a 32-channel head coil) as part of a separate study. The standardized protocol included a Multiecho T1-weighted (voxel size: 1x1x1 mm<sup>3</sup>; Repetition Time [TR]: 2510 ms), a 3D-FLAIR (voxel size: 0.9x0.9x0.9 mm<sup>3</sup>; TR: 5000 ms; TE: 356 ms), and a T2-weighted Turbo Spin Echo (voxel size: 0.5x0.5x2.0 mm<sup>3</sup>; TR: 7500 ms; TE: 84 ms) sequence. Scans were manually assessed to ensure no gross pathology was present, such as hemorrhage or silent brain infarcts.</p> <p><strong>Template and territorial map creation</strong></p> <p>We employed Advanced Normalization Tools (ANTs) for image processing (Avants et al., 2010, 2011) for creating a brain template based on multimodal information using T1, T2 and 3D-FLAIR sequences. After template creation, we smoothed the resulting templates (FSL; Gaussian smoothing, sigma = 1) and registered the resulting templates into MNI space, again using ANTs (Avants et al., 2011).</p> <p>Vascular territories were outlined on the right hemisphere in the T1-weighted atlas image and contain anatomically validated ACA, MCA, and PCA territories supratentorially. The right hemispheric map was then mirrored onto the left hemisphere to create a full-brain vascular territory map, which was manually assessed and corrected where necessary.</p> <p>&nbsp;</p> <p>For more details, please see the original publication that utilized the template. If you utilize this template, please also cite</p> <p>Schirmer, Markus D., et al. &quot;Spatial signature of white matter hyperintensities in stroke patients.&quot; <em>Frontiers in neurology</em> 10 (2019): 208.</p> <p><a href="https://doi.org/10.3389/fneur.2019.00208">https://doi.org/10.3389/fneur.2019.00208</a></p> <p>&nbsp;</p> <p><strong>Files</strong></p> <p><strong>FLAIR template</strong>: caa_flair_in_mni_template_smooth.nii.gz<br> <br> <strong>FLAIR template after brain extraction and intensity normalization</strong>: caa_flair_in_mni_template_smooth_brain_intres.nii.gz<br> <br> <strong>T1 template</strong>: caa_t1_in_mni_template_smooth.nii.gz 27.7 Mb<br> <br> <strong>T2 template</strong>: caa_t2_in_mni_template_smooth.nii.gz 27.7 Mb<br> <br> <strong>Vascular territory map</strong>: mni_vascular_territories.nii.gz</p>

ShareScore

52/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
20
Reuse readiness
8
Engagement
12

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