An optimized MRI and PET based clinical protocol for improving the differential diagnosis of geriatric depression and Alzheimer's disease. (March 2022)

• Record Type: Journal Article
• Authors: Emsell, Louise; Vanhaute, Heleen; Vansteelandt, Kristof; De Winter, François-Laurent; Christiaens, Danny; Van den Stock, Jan; Vandenberghe, Rik; Van Laere, Koen; Sunaert, Stefan; Bouckaert, Filip; Vandenbulcke, Mathieu
• Is Part Of: Psychiatry research. Volume 320(2022)
• Publication Date: 2022-03
• Subjects: Late-life depression -- Hippocampus -- Amyloid -- 18-F Flutemetamol -- Biomarker -- Classification; Psychiatry -- Periodicals; Brain -- Imaging -- Periodicals; Psychiatry -- Periodicals; Diagnostic Imaging -- Periodicals; Psychiatrie -- Périodiques; Cerveau -- Imagerie pour le diagnostic -- Périodiques; 616.890754
• DOI: 10.1016/j.pscychresns.2022.111443
• Languages: English
• ISSNs: 0925-4927

Abstract

Highlights: HV discriminated depression from AD in half of cases in a psychiatry setting. MRI can be used to identify patients who would benefit from amyloid assessment. Combining amyloid PET with HV improves the differential diagnosis of AD and LLD. Abstract: 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.