{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T12:58:36Z","timestamp":1781873916324,"version":"3.54.5"},"reference-count":54,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2017,2,10]],"date-time":"2017-02-10T00:00:00Z","timestamp":1486684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2017,3,4]]},"abstract":"<jats:p>Background: Depression and cognitive disorders (CDs) are two common co-morbid afflictions that commonly present with overlapping symptoms.<\/jats:p>\n                  <jats:p>Objective: To evaluate if perfusion neuroimaging with brain SPECT can distinguish persons with depression from those with CDs or both conditions.<\/jats:p>\n                  <jats:p>Methods: Inclusion criteria were DSM-IV defined depression or CDs (Alzheimer\u2019s disease, vascular dementia, dementia not otherwise specified, and amnestic disorders not otherwise specified) including persons with both (total n\u200a=\u200a4,541; 847 CDs, 3,269 depression, 425 with both). Perfusion differences between the groups were calculated using two-sampled t-tests corrected for multiple comparisons. Diagnostic separation was determined with discriminant analysis. Feature selection revealed predictive regions in delineating depression from CDs and comorbid cases.<\/jats:p>\n                  <jats:p>Results: Persons with CDs had lower cerebral perfusion compared to depression. In co-morbid persons, cerebral hypoperfusion was additive, with regions showing lower regional cerebral blood flow compared to either diagnosis alone. Both baseline and concentration SPECT regions yielded correct classification of 86% and leave one out cross-validation of 83%. AUC analysis for SPECT regions showed 86% accuracy, 80% sensitivity and 75% specificity. Discriminant analysis separated depression and CDs from comorbid cases with correct classification of 90.8% and cross validated accuracy of 88.6%. Area under the curve was 83% with sensitivity of 80% and specificity of 70%. Feature selection identified the most predictive regions in left hippocampus, right insula, cerebellar, and frontal lobe regions.<\/jats:p>\n                  <jats:p>Conclusion: Quantitative perfusion SPECT neuroimaging distinguishes depression from dementia and those with both co-morbidities. Perfusion brain SPECT can be utilized clinically to delineate between these two disorders.<\/jats:p>","DOI":"10.3233\/jad-161232","type":"journal-article","created":{"date-parts":[[2017,2,10]],"date-time":"2017-02-10T09:46:52Z","timestamp":1486720012000},"page":"253-266","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":15,"title":["Classification of Depression, Cognitive Disorders, and Co-Morbid Depression and Cognitive Disorders with Perfusion SPECT Neuroimaging"],"prefix":"10.1177","volume":"57","author":[{"given":"Daniel G.","family":"Amen","sequence":"first","affiliation":[{"name":"Amen Clinics, Costa Mesa, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pavitra","family":"Krishnamani","sequence":"additional","affiliation":[{"name":"Thomas Jefferson University School of Medicine, Philadelphia, PA, 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