{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,20]],"date-time":"2026-09-20T11:17:18Z","timestamp":1789903038782,"version":"4.0.1"},"reference-count":32,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2017,7,13]],"date-time":"2017-07-13T00:00:00Z","timestamp":1499904000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer's Disease Reports"],"published-print":{"date-parts":[[2017,9,28]]},"abstract":"<jats:p>This work explores the feasibility of combining anatomical MRI data across two public repositories namely, the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) and the Progressive Parkinson\u2019s Markers Initiative (PPMI). We compared cortical thickness and subcortical volumes in cognitively normal older adults between datasets with distinct imaging parameters to assess if they would provide equivalent information. Three distinct datasets were identified. Major differences in data were scanner manufacturer and the use of magnetization inversion to enhance tissue contrast. Equivalent datasets, i.e., those providing similar volumetric measurements in cognitively normal controls, were identified in ADNI and PPMI. These were datasets obtained on the Siemens scanner with TI\u200a=\u200a900\u200ams. Our secondary goal was to assess the agreement between subcortical volumes that are obtained with different software packages. Three subcortical measurement applications (FSL, FreeSurfer, and a recent multi-atlas approach) were compared. Our results show significant agreement in the measurements of caudate, putamen, pallidum, and hippocampus across the packages and poor agreement between measurements of accumbens and amygdala. This is likely due to their smaller size and lack of gray matter-white matter tissue contrast for accurate segmentation. This work provides a segue to combine imaging data from ADNI and PPMI to increase statistical power as well as to interrogate common mechanisms in disparate pathologies such as Alzheimer\u2019s and Parkinson\u2019s diseases. It lays the foundation for comparison of anatomical data acquired with disparate imaging parameters and analyzed with disparate software tools. Furthermore, our work partly explains the variability in the results of studies using different software packages.<\/jats:p>","DOI":"10.3233\/adr-170008","type":"journal-article","created":{"date-parts":[[2017,12,20]],"date-time":"2017-12-20T10:41:44Z","timestamp":1513766504000},"page":"59-70","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["Comparison of Cortical and Subcortical Measurements in Normal Older Adults across Databases and Software Packages"],"prefix":"10.1177","volume":"1","author":[{"given":"Swati","family":"Rane","sequence":"first","affiliation":[{"name":"Department of Radiology, University of Washington Medical Center, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Plassard","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, School of Engineering, Vanderbilt University, Nashville, TN, 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