A probabilistic histological atlas of the human brain for MRI segmentation
In human neuroimaging, brain atlases are essential for segmenting regions of interest (ROIs) and comparing subjects in a common coordinate frame. State-of-the-art atlases derived from histology<sup>1-3</sup> provide exquisite three-dimensional cytoarchitectural maps but lack probabilistic labels throughout the whole brain: that is, the likelihood of each location belonging to a given ROI. Here we present NextBrain, a probabilistic histological atlas of the whole human brain. We developed artificial intelligence-enabled methods to align roughly 10,000 histological sections from five whole brain hemispheres into three-dimensional volumes and to produce delineations for 333 ROIs on these sections. We also created a companion Bayesian tool for automatic segmentation of these ROIs in magnetic resonance imaging (MRI) scans. We showcase two applications of the atlas: segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimer's disease using in vivo MRI. We publicly release raw and aligned data, an online visualization tool, the atlas, the segmentation tool, and ground truth delineations for a high-resolution ex vivo hemisphere used in validation. By enabling researchers worldwide to automatically analyse brain MRIs at a higher level of granularity, NextBrain holds promise to increase the specificity of findings and accelerate our quest to understand the human brain in health and disease.
Authors
- Dorit Kliemann (ORCID: https://orcid.org/0000-0003-2069-919X)
- Alessia Atzeni (ORCID: https://orcid.org/0000-0001-8320-230X)
- James E Hughes (ORCID: https://orcid.org/0000-0002-3022-3104)
- Brian L. Edlow (ORCID: https://orcid.org/0000-0001-7235-8456)
- Shauna Crampsie (ORCID: https://orcid.org/0000-0002-4399-5218)
- Loïc Peter (ORCID: https://orcid.org/0000-0002-8293-5330)
- Emily Blackburn (ORCID: https://orcid.org/0000-0003-4009-2715)
- Benjamin Billot (ORCID: https://orcid.org/0000-0002-3018-1282)
- Lilla Zöllei (ORCID: https://orcid.org/0000-0002-6447-9626)
- Peter J. Schmidt (ORCID: https://orcid.org/0000-0002-6565-0181)
- E. A. G. Robinson
- Juan Eugenio Iglesias (ORCID: https://orcid.org/0000-0001-7569-173X)
- Janice L. Holton (ORCID: https://orcid.org/0000-0002-3882-5249)
- Zane Jaunmuktane (ORCID: https://orcid.org/0000-0001-7738-8881)
- Matteo Mancini (ORCID: https://orcid.org/0000-0001-7194-4568)
- Catherine Strand
- Adrià Casamitjana (ORCID: https://orcid.org/0000-0002-0539-3638)
- Martina Bocchetta (ORCID: https://orcid.org/0000-0003-1814-5024)
- Oula Puonti (ORCID: https://orcid.org/0000-0003-3186-244X)
- Juri Althonayan
- Jean C. Augustinack (ORCID: https://orcid.org/0000-0002-3129-6671)
- David L. Thomas (ORCID: https://orcid.org/0000-0003-1491-1641)
- Yaël Balbastre (ORCID: https://orcid.org/0000-0001-8758-9978)
- Roberto Annunziata (ORCID: https://orcid.org/0000-0002-7832-8079)
Institutions
- University of Iowa (US)
- Harvard University (US)
- Universitat de Girona (ES)
- Ragon Institute of MGH, MIT and Harvard (US)
- Copenhagen University Hospital (DK)
- Mondelēz International (United Kingdom) (GB)
- Massachusetts General Hospital (US)
- Center for Neuro-Oncology (US)
- Centro Ricerche Enrico Fermi (IT)
- UK Dementia Research Institute (GB)
- Athinoula A. Martinos Center for Biomedical Imaging (US)
- National Hospital for Neurology and Neurosurgery (GB)
- University College London (GB)
- Brunel University of London (GB)
- Massachusetts Institute of Technology (US)
- Cardiff University (GB)
Publication Details
- Journal
- Nature
- Published
- 2025-11-05
- DOI
- https://doi.org/10.1038/s41586-025-09708-2
- Citations
- 4
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 5.72