Structural MRI is routinely acquired in clinical practice, yet quantitative morphometry has had limited impact on clinical decision-making. Overlapping symptoms, trajectories and comorbidities remain difficult to interpret within disease-specific frameworks, leaving it unclear how individual patients relate to the broader organization of brain disease. Here, we construct a cross-disease morphological reference space from 110,591 T1w MRI scans of 78,794 participants, spanning four disease families, 19 diagnoses, and seven subtypes. To construct this space, we developed NeuroMorph, an AI framework deriving thirteen interpretable morphological descriptors and individual normative deviation profiles. The reference space reveals shared and distinct morphological signatures that distinguish conditions within a hierarchy of disease families, diagnoses, subtypes and individual profiles. It identifies overlapping and comorbid morphological profiles and captures longitudinal deviations that precede clinical diagnosis and track progression. Together, these findings establish a unified framework for mapping brain disease organization and positioning individual patients within its morphological landscape.
Multimodal MRI analysed with SuStaIn identified reproducible subtypes of multiple sclerosis with clinically meaningful differences in phenotype, age at onset, disability, and relapse-independent progression, while cognitive impairment was related to advancing SuStaIn stage within each subtype.
P. Preziosa, L. Storelli, F. Clarelli et al.· Brain : a journal of neurolo...· 0 citations
Clinical brain MRIs from pediatric health systems represent a viable resource for modeling early neurodevelopmental trajectories and studying neurodevelopmental risk in real-world populations, and a robust segmentation approach tailored to early-life clinical MRIs with variable orientation, resolution, and contrast is...
E. Levitis, Henry F. J. Tregidgo, D. Zimmerman et al.· medRxiv· 0 citations
Lesion composition may offer a more informative framework than global WMH burden for understanding cerebrovascular contributions to aging and neurodegeneration, with potential implications for risk stratification, clinical interpretation, and targeted interventions.
Raúl González-Gómez, Enzo Tagliazuchi, C. G. Campo et al.· Neurology· 0 citations
Psychiatric disorders share common-variant liability, and the Psychiatric Genomics Consortium has identified five correlated cross-disorder genetic dimensions derived from diagnoses. Whether these dimensions also organize heterogeneous clinical observations and their cortical associations remains unclear. We used F1-F5...
