Distinct spatiotemporal atrophy patterns in corticobasal syndrome are associated with different underlying pathologies

Abstract

Objective: To identify imaging subtypes of the cortico-basal syndrome (CBS) based solely on a data-driven assessment of MRI atrophy patterns, and investigate whether these subtypes provide information on the underlying pathology.

Methods: We applied Subtype and Stage Inference (SuStaIn), a machine learning algorithm that identifies groups of individuals with distinct biomarker progression patterns, to a large cohort of 135 CBS cases (52 had a pathological or biomarker defined diagnosis) and 252 controls. The model was fit using volumetric features extracted from baseline T1-weighted MRI scans and validated using follow-up MRI. We compared the clinical phenotypes of each subtype and investigated whether there were differences in associated pathology between the subtypes.

Results: SuStaIn identified two subtypes with distinct sequences of atrophy progression; four-repeat-tauopathy confirmed cases were most commonly assigned to the Subcortical subtype (83% of CBS-PSP and 75% of CBS-CBD), while CBS-AD was most commonly assigned to the Fronto-parieto-occipital subtype (81% of CBS-AD). Subtype assignment was stable at follow-up (98% of cases), and individuals consistently progressed to higher stages (100% stayed at the same stage or progressed), supporting the model's ability to stage progression.

Interpretation: By jointly modelling disease stage and subtype, we provide data-driven evidence for at least two distinct and longitudinally stable spatiotemporal subtypes of atrophy in CBS that are associated with different underlying pathologies. In the absence of sensitive and specific biomarkers, accurately subtyping and staging individuals with CBS at baseline has important implications for screening on entry into clinical trials, as well as for tracking disease progression.

Keywords: Cortico-basal syndrome; Subtype and Stage Inference; biomarkers; disease progression; machine learning.

Figure 1 -. Two-subtype model of atrophy progression in CBS identified by Subtype and Stage Inference (SuStaIn).

(A) Spatial distribution and severity of atrophy at each SuStaIn stage by Subtype. Each row (Subcortical top, Fronto-parieto-occipital bottom) represents a subtype progression pattern identified by SuStaIn consisting of a set of stages at which brain volumes in CBS cases reach different z-scores relative to controls. (B) Assignment of CBS pathology to each SuStaIn subtype. Size of bar (x-axis) represents percentage of cases labelled with that PSP syndrome assigned to that SuStaIn subtype (y-axis). PSP = PSP pathology at post-mortem, CBD = at post-mortem, AD = AD pathology at post-mortem or a positive AD biomarker (CSF or Amyloid PET) during life.

Figure 2 -. Three-subtype model of atrophy progression in CBS identified by Subtype and Stage Inference (SuStaIn).

(A) Spatial distribution and severity of atrophy at each SuStaIn stage by Subtype. Each row (Subcortical top, Fronto-parietal middle and Parieto-occipital bottom) represents a subtype progression pattern identified by SuStaIn consisting of a set of stages at which brain volumes in CBS cases reach different z-scores relative to controls (B) Assignment of CBS pathology to each SuStaIn subtype. Size of bar (x-axis) represents percentage of cases labelled with that PSP syndrome assigned to that SuStaIn subtype (y-axis). PSP = PSP pathology at post-mortem, CBD = at post-mortem, AD = AD pathology at post-mortem or a positive AD biomarker (CSF or Amyloid PET) during life.

Figure 3 -. Stage progression at follow-up visits by SuStaIn subtype.

Scatter plots of each subtype for (A) the two-subtype model (B) the three-subtype model showing predicted stage at baseline (x-axis) versus predicted stage at follow-up scan (y-axis) for those subtypable CBS cases with a follow-up scan (n = 103). The area of the circle is weighted by the number of scans at each point, and the colour of the circle represents the time (years) between visits.