4.2 Article

An optimized MRI and PET based clinical protocol for improving the differential diagnosis of geriatric depression and Alzheimer's disease

期刊

PSYCHIATRY RESEARCH-NEUROIMAGING
卷 320, 期 -, 页码 -

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.pscychresns.2022.111443

关键词

Late-life depression; Hippocampus; Amyloid; 18-F Flutemetamol; Biomarker; Classification

资金

  1. Research Foundation Flanders (FWO) [G074609]
  2. Research Grant Old Age Psychiatry UZ Leuven [R94859]
  3. FWO [G0C0319N]
  4. KU Leuven [C24/18/095, OT/08/056, OT/12/097]
  5. Sequoia Fund
  6. Foundation for Alz-heimer Research (SAO-FRMA) [09013, 11020, 13007]

向作者/读者索取更多资源

Amyloid positron emission tomography (PET) and hippocampal volume derived from magnetic resonance imaging can serve as useful clinical biomarkers for differentiating geriatric depression from Alzheimer's disease (AD). Hippocampal volume is an important diagnostic predictor for identifying individuals with depression who are at risk for AD, and additional amyloid biomarkers can further improve diagnostic accuracy when available.
Amyloid positron emission tomography (PET) and hippocampal volume derived from magnetic resonance imaging may be useful clinical biomarkers for differentiating between geriatric depression and Alzheimer's disease (AD). Here we investigated the incremental value of using hippocampal volume and 18F-flutemetmol amyloid PET measures in tandem and sequentially to improve discrimination in unclassified participants. Two approaches were compared in 41 participants with geriatric depression and 27 participants with probable AD: (1) amyloid and hippocampal volume combined in one model and (2) classification based on hippocampal volume first and then subsequent stratification using standardized uptake value ratio (SUVR)-determined amyloid positivity. Hippocampal volume and amyloid SUVR were significant diagnostic predictors of depression (sensitivity: 95%, specificity: 89%). 51% of participants were correctly classified according to clinical diagnosis based on hippocampal volume alone, increasing to 87% when adding amyloid data (sensitivity: 94%, specificity: 78%). Our results suggest that hippocampal volume may be a useful gatekeeper for identifying depressed individuals at risk for AD who would benefit from additional amyloid biomarkers when available.

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