Morphometric MRI as a diagnostic biomarker of frontotemporal dementia: A systematic review to determine clinical applicability

Abstract

Frontotemporal dementia (FTD) is difficult to diagnose, due to its heterogeneous nature and overlap in symptoms with primary psychiatric disorders. Brain MRI for atrophy is a key biomarker but lacks sensitivity in the early stage. Morphometric MRI-based measures and machine learning techniques are a promising tool to improve diagnostic accuracy. Our aim was to review the current state of the literature using morphometric MRI to classify FTD and assess its applicability for clinical practice. A search was completed using Pubmed and PsychInfo of studies which conducted a classification of subjects with FTD from non-FTD (controls or another disorder) using morphometric MRI metrics on an individual level, using single or combined approaches. 28 relevant articles were included and systematically reviewed following PRISMA guidelines. The studies were categorized based on the type of FTD subjects included and the group(s) against which they were classified. Studies varied considerably in subject selection, MRI methodology, and classification approach, and results are highly heterogeneous. Overall many studies indicate good diagnostic accuracy, with higher performance when differentiating FTD from controls (highest result was accuracy of 100%) than other dementias (highest result was AUC of 0.874). Very few machine learning algorithms have been tested in prospective replication. In conclusion, morphometric MRI with machine learning shows potential as an early diagnostic biomarker of FTD, however studies which use rigorous methodology and validate findings in an independent real-life cohort are necessary before this method can be recommended for use clinically.

Diagnostic imaging of dementia with Lewy bodies, frontotemporal lobar degeneration, and normal pressure hydrocephalus

“…MRI allows detection of bvFTD-specific brain atrophy, which includes frontal and anterior temporal volume loss, and shows a good diagnostic accuracy for differentiating FTD from normal subjects and other dementias in clinical practice [38][39][40]. MRI of bvFTD can show severe frontal and anterior temporal atrophy (Figs.…”

Deformation based morphometry study of longitudinal MRI changes in behavioral variant frontotemporal dementia

“…In an effort to address the need for improved diagnostic biomarkers for the behavioural variant frontotemporal dementia (bvFTD), several studies have demonstrated the potential value of morphometric MRI analysis for diagnostic purposes (McCarthy et al., 2018). Here, we performed a deformation-based morphometry (DBM) study of longitudinal MRI changes in bvFTD.…”

Data-driven algorithm for the diagnosis of behavioral variant frontotemporal dementia

“…The best AUC was reported by Raamana et al (AUC 0.938, 100% sensitivity and 88% specificity). However, the main limitation of that study is that the bvFTD diagnosis from the validation cohort was based on clinical criteria (39). Contrarily, the bvFTD subjects from our validation cohort are known carriers of a pathogenic mutation and have therefore, definite bvFTD diagnosis.…”