Temporal Progression Patterns of Brain Atrophy in Corticobasal Syndrome and Progressive Supranuclear Palsy Revealed by Subtype and Stage Inference (SuStaIn)

Abstract

Differentiating corticobasal degeneration presenting with corticobasal syndrome (CBD-CBS) from progressive supranuclear palsy with Richardson's syndrome (PSP-RS), particularly in early stages, is often challenging because the neurodegenerative conditions closely overlap in terms of clinical presentation and pathology. Although volumetry using brain magnetic resonance imaging (MRI) has been studied in patients with CBS and PSP-RS, studies assessing the progression of brain atrophy are limited. Therefore, we aimed to reveal the difference in the temporal progression patterns of brain atrophy between patients with CBS and those with PSP-RS purely based on cross-sectional data using Subtype and Stage Inference (SuStaIn)—a novel, unsupervised machine learning technique that integrates clustering and disease progression modeling. We applied SuStaIn to the cross-sectional regional brain volumes of 25 patients with CBS, 39 patients with typical PSP-RS, and 50 healthy controls to estimate the two disease subtypes and trajectories of CBS and PSP-RS, which have distinct atrophy patterns. The progression model and classification accuracy of CBS and PSP-RS were compared with those of previous studies to evaluate the performance of SuStaIn. SuStaIn identified distinct temporal progression patterns of brain atrophy for CBS and PSP-RS, which were largely consistent with previous evidence, with high reproducibility (99.7%) under cross-validation. We classified these diseases with high accuracy (0.875) and sensitivity (0.680 and 1.000, respectively) based on cross-sectional structural brain MRI data; the accuracy was higher than that reported in previous studies. Moreover, SuStaIn stage correctly reflected disease severity without the label of disease stage, such as disease duration. Furthermore, SuStaIn also showed the genialized performance of differentiation and reflection for CBS and PSP-RS. Thus, SuStaIn has potential for improving our understanding of disease mechanisms, accurately stratifying patients, and providing prognoses for patients with CBS and PSP-RS.

Clinical and neuroimaging features of the progressive supranuclear palsy- corticobasal degeneration continuum

“…2). This pattern of spread was concordant to that identified in PSP-RS using similar methodology [50,51]. The ‘cortical’ subtype also showed early midbrain and insula atrophy, with spread to involve posterior frontal lobes, thalamus, ventral diencephalon and basal ganglia at a similar time, and then spread into other cortical regions (Fig.…”

“…Nevertheless, this study provides insight into patterns of disease spread in PSP that can help inform the development of appropriate MRI biomarkers. The SuStaIn model has also been used to demonstrate that patterns of disease spread differ between PSP-RS and CBS [51]. In contrast to the patterns of spread in PSP-RS which start in midbrain and superior cerebellar peduncle, earliest atrophy in CBS was identified in the frontoparietal lobe, followed by temporo-occipital lobe and basal ganglia, and later reached the cingulate and brainstem.…”

Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer’s disease

“…Finally, while results in the CBS group were likely underpowered and should be interpreted with caution, we observed a distributed pattern of WM degeneration encompassing left cingulum, the body of the corpus callosum, bilateral parietal aslant tracts, and the right superior longitudinal fasciculus. These tracts are located adjacent to previously reported epicenters of GM disease observed in CBS, including the left angular and supramarginal gyri as well as bilateral superior parietal lobules (Phillips et al, 2018a;Saito et al, 2022). Notably, WM differences between CBS and controls involved bilateral nodes of the somatomotor network (Supplementary Table 2), presenting possible WM correlates of the sensorimotor deficits observed in CBS (Armstrong et al, 2013).…”

Staging of progressive supranuclear palsy-Richardson syndrome using MRI brain charts for the human lifespan

“… 36 This method simultaneously infers patient sub-groups and the corresponding trajectories of disease progression. So far, this unsupervised machine-learning technique has mainly used to cluster the heterogeneity of atrophy progression in PSP 37 , 38 and other tauopathies. 36 …”