The Cortical Asymmetry Index for subtyping dementia patients.

Abstract

Objectives: Frontotemporal dementia (FTD) usually shows more asymmetric atrophy patterns than Alzheimer's disease (AD). We aim to quantify this asymmetry to differentiate FTD, AD, and FTD subtypes.

Methods: We studied T1-MRI scans, including FTD (different phenotypes), AD, and healthy controls (CTR). We defined the Cortical Asymmetry Index (CAI) using measures based on a metric derived from information theory with the cortical thickness measures. Some participants had additional follow-up MRIs, cerebrospinal fluid (CSF), or plasma measures. We analysed differences at cross-sectional and longitudinal levels. We then clustered FTD and AD participants based on the CAI values and studied the patients' fluid biomarker characteristics within each cluster.

Results: A total of 101 FTD patients (64  ±  8 years, 53 men), 230 AD patients (65  ±  10 years, 84 men), and 173 CTR (59  ±  15 years, 67 men) were studied. CAI differentiated FTD, AD, and CTR. It also distinguished the semantic variant primary progressive aphasia (svPPA) from the other FTD phenotypes. In FTD, the CAI increased over time. The cluster analysis identified two subgroups within FTD, characterised by different neurofilament-light (NfL) levels, and two subgroups within AD, with different plasma glial fibrillary acidic protein (GFAP) levels. In AD, CAI correlated with GFAP and Mini-Mental State Examination (MMSE); in FTD, the CAI was associated with NfL levels.

Conclusions: The proposed method quantifies asymmetries previously described visually. The CAI could define clinically and biologically meaningful disease subgroups in the differential diagnosis of AD and FTD and its subtypes. CAI could also be of interest in tracking disease progression in FTD.

Key points: Question There is a need to find quantitative metrics from MRI that can identify disease subgroups, and that could be useful for diagnosis and tracking. Findings We propose a Cortical Asymmetry Index that differentiates Alzheimer's disease (AD) from Frontotemporal dementia (FTD), distinguishes FTD subtypes, correlates with NFL and GFAP levels, and monitors FTD progression. Clinical relevance Our proposed index holds the potential to support clinical applications for diagnosis and disease tracking in AD and FTD, using a quantitative summary metric from MRI data. It also contributes to the understanding of these diseases.