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Quantified Brain Magnetic Resonance Imaging Volumes Differentiate Behavioral Variant Frontotemporal Dementia from Early-Onset Alzheimer's Disease

Authors :
Somayeh Meysami
Cyrus A. Raji
Mario F. Mendez
Source :
J Alzheimers Dis
Publication Year :
2022

Abstract

Background: The differentiation of behavioral variant frontotemporal dementia (bvFTD) from early-onset Alzheimer’s disease (EOAD) by clinical criteria can be inaccurate. The volumetric quantification of clinically available magnetic resonance (MR) brain scans may facilitate early diagnosis of these neurodegenerative dementias. Objective: To determine if volumetric quantification of brain MR imaging can identify persons with bvFTD from EOAD. Methods: 3D T1 MR brain scans of 20 persons with bvFTD and 45 with EOAD were compared using Neuroreader to measure subcortical, and lobar volumes, and Volbrain for hippocampal subfields. Analyses included: 1) discriminant analysis with leave one out cross-validation; 2) input of predicted probabilities from this process into a receiver operator characteristic (ROC) analysis; and 3) Automated linear regression to identify predictive regions. Results: Both groups were comparable in age and sex with no statistically significant differences in symptom duration. bvFTD had lower volume percentiles in frontal lobes, thalamus, and putamen. EOAD had lower parietal lobe volumes. ROC analyses showed 99.3% accuracy with Neuroreader percentiles and 80.2% with subfields. The parietal lobe was the most predictive percentile. Although there were differences in hippocampal (particularly left CA2-CA3) subfields, it did not add to the discriminant analysis. Conclusion: Percentiles from an MR based volumetric quantification can help differentiate between bvFTD from EOAD in routine clinical care. Use of hippocampal subfield volumes does not enhance the diagnostic separation of these two early-onset dementias.

Details

ISSN :
18758908
Volume :
87
Issue :
1
Database :
OpenAIRE
Journal :
Journal of Alzheimer's disease : JAD
Accession number :
edsair.doi.dedup.....14adbcfad300863db26b7f4304501100