Mind the brain age: How segmentation and template selection reshape structural connectomes
Year: 2026
Type: article
Abstract: Diffusion-weighted MRI samples the directional diffusion of water in vivo, and tractography uses this information to reconstruct brain fiber pathways. Mapping streamlines to an anatomical parcellation yields structural connectomes. However, in older adults, where white matter alterations and atrophy are common, the choice of reference template and tissue segmentation could be particularly consequential for obtaining accurate, interpretable structural connectomes. Using a conventional pipeline, we evaluated how these two factors, the normalization template and the segmentation used to constrain anatomically guided tractography, affect connectome estimates in cognitively healthy elderly participants. These methodological choices produced systematic and significant differences in network topology and their relationships with clinically relevant variables across standard connectome measures, particularly in patients with white matter hyperintensities. Age-appropriate normalization and lesion-aware anatomically constrained tractography yielded networks with more plausible anatomy and more consistent relationships with cognition and imaging measures, whereas unconstrained tracking inflated density without improving interpretability. These findings demonstrate that structural connectome outcomes are contingent upon template and segmentation selection. We, therefore, advocate for explicit reporting of these methodological parameters and recommend the use of age-appropriate templates combined with white matter lesion-aware segmentation incorporating anatomically informed constraints.
Source: Imaging Neuroscience
DOI: 10.1162/imag.a.1384
Institutions: Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Inserm, Institut de Recherche en Informatique et Systèmes Aléatoires, Empenn, Université de Rennes, Laboratoire des Sciences et Techniques de l’Information de la Communication et de la Connaissance, Centre Hospitalier Universitaire de Rennes
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Funders: U.S. Department of Defense, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Biogen, University of Southern California, F. Hoffmann-La Roche, Meso Scale Diagnostics, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, Agence Nationale de la Recherche, Eisai, Centre National de la Recherche Scientifique, Servier, H. Lundbeck A/S, IXICO, National Institutes of Health, Genentech, Canadian Institutes of Health Research, National Institute on Aging
OpenAlex ID: W7120739026