Alzheimer\'s disease (AD) is a progressive neurodegenerative disorder where pathophysiological changes begin decades before the onset of clinical symptoms. Analysis of brain atrophy patterns using structural MRI and multivariate data analysis are an effective tool in identifying patients with subjective cognitive decline (SCD) at higher risk of progression to AD dementia. Atrophy patterns obtained from models trained to classify advanced AD versus normal subjects, may not be optimal for subjects at an early stage, like SCD. In this study, we compared the accuracy of the SCD progression prediction using the \'severity index\' generated using a standard classification model trained on patients with AD dementia versus a new model trained on β-amyloid (Aβ) positive patients with amnestic mild cognitive impairment (aMCI).
We used structural MRI data of 504 patients from the Swedish BioFINDER-1 study cohort (cognitively normal (CN), Aβ-negative = 220; SCD, Aβ positive and negative = 139; aMCI, Aβ-positive = 106; AD dementia = 39). We applied multivariate data analysis to create two predictive models trained to discriminate CN individuals from either individuals with Aβ positive aMCI or AD dementia. Models were applied to individuals with SCD to classify their atrophy patterns as either high-risk \"disease-like\" or low-risk \"CN-like\". Clinical trajectory and model accuracy were evaluated using 8 years of longitudinal data.
In predicting progression from SCD to MCI or dementia, the standard, dementia-based model, reached 100% specificity but only 10.6% sensitivity, while the new, aMCI-based model, reached 72.3% sensitivity and 60.9% specificity. The aMCI-based model was superior in predicting progression from SCD to MCI or dementia, reaching a higher receiver operating characteristic area under curve (AUC = 0.72; P = 0.037) in comparison with the dementia-based model (AUC = 0.57).
When predicting conversion from SCD to MCI or dementia using structural MRI data, prediction models based on individuals with milder levels of atrophy (i.e. aMCI) may offer superior clinical value compared to standard dementia-based models.

UNASSIGNED: Heterogeneity in downstream atrophy in Alzheimer\'s disease (AD) is predominantly investigated in relation to pathological hallmarks (Aβ, tau) and co-pathologies (cerebrovascular burden) independently. However, the proportional contribution of each pathology in determining atrophy pattern remains unclear. We assessed heterogeneity in atrophy using two recently conceptualized dimensions: typicality (typical AD atrophy at the center and deviant atypical atrophy on either extreme including limbic predominant to hippocampal sparing patterns) and severity (overall neurodegeneration spanning minimal atrophy to diffuse typical AD atrophy) in relation to Aβ, tau, and cerebrovascular burden.
UNASSIGNED: We included 149 Aβ + individuals on the AD continuum (cognitively normal, prodromal AD, AD dementia) and 163 Aβ- cognitively normal individuals from the ADNI. We modeled heterogeneity in MRI-based atrophy with continuous-scales of typicality (ratio of hippocampus to cortical volume) and severity (total gray matter volume). Partial correlation models investigated the association of typicality/severity with (a) Aβ (global Aβ PET centiloid), tau (global tau PET SUVR), cerebrovascular (total white matter hypointensity volume) burden (b) four cognitive domains (memory, executive function, language, visuospatial composites). Using multiple regression, we assessed the association of each pathological burden and typicality/severity with cognition.
UNASSIGNED: (a) In the AD continuum, typicality (r = -0.31, p < 0.001) and severity (r = -0.37, p < 0.001) were associated with tau burden after controlling for Aβ, cerebrovascular burden and age. Findings imply greater tau pathology in limbic predominant atrophy and diffuse atrophy. (b) Typicality was associated with memory (r = 0.49, p < 0.001) and language scores (r = 0.19, p = 0.02). Severity was associated with memory (r = 0.26, p < 0.001), executive function (r = 0.24, p = 0.003) and language scores (r = 0.29, p < 0.001). Findings imply better cognitive performance in hippocampal sparing and minimal atrophy patterns. Beyond typicality/severity, tau burden but not Aβ and cerebrovascular burden explained cognition.
UNASSIGNED: In the AD continuum, atrophy-based severity was more strongly associated with tau burden than typicality after accounting for Aβ and cerebrovascular burden. Cognitive performance in memory, executive function and language domains was explained by typicality and/or severity and additionally tau pathology. Typicality and severity may differentially reflect burden arising from tau pathology but not Aβ or cerebrovascular pathologies which need to be accounted for when investigating AD heterogeneity.

Clinical differentiation between Alzheimer\'s disease (AD) and behavioural-variant frontotemporal dementia (bvFTD) is challenging due to overlapping clinical features at presentation. Whilst diagnostic criteria for both disorders incorporate evidence of frontal and temporal cortical atrophy, understanding of the progression of atrophy in these disorders is limited. This study aimed to elucidate common and disease-specific progressive changes in cortical and subcortical brain structures in AD and bvFTD.
Forty-one AD, 37 bvFTD and 33 healthy controls underwent baseline MRI and of these longitudinal follow-up was obtained for 20AD and 20 bvFTD (1 to 4years). A total of 87 AD and 70 bvFTD consecutive scans were included in the study. The trajectories of progression in cortical and subcortical structures were identified with FreeSurfer and linear mixed effect modelling.
The results uncovered cortical and subcortical disease-specific trajectories of neurodegeneration in AD and bvFTD. Specifically, direct comparisons between patient groups revealed that over time AD showed greater cortical atrophy in the inferior parietal and posterior cingulate cortex than bvFTD. Conversely, bvFTD patients showed greater atrophy in the striatum than AD over time.
These results indicate that atrophy in the posterior cingulate and the striatum diverges with disease progression in these dementia syndromes and may represent a potential diagnostic biomarker for tracking rates of progression of AD and bvFTD. These findings may help inform future drug trials by identifying appropriate outcome measures to quantify drug efficacy and their ability to modulate disease progression over time.