Topographic reference modelling of white matter hyperintensities across the adult lifespan

@misc{alshikho2026topographic,
  title = {{Topographic reference modelling of white matter hyperintensities across the adult lifespan}},
  author = {M. J. Alshikho and J. D. Pyne and N. C. Edwards and C. Hale and D. C. Samuel and C. D. Morales and N. Morel and R. V. Lippert and D. B. Archer and M. L. Cuccaro and A. W. Toga and A. J. Saykin and S. L. Risacher and M. E. Belloy and W. Kukull and S. Biber and J. Mez and P. K. Crane and S. Mukherjee and G. Erus and R. A. Sperling and D. A. Bennett and L. L. Barnes and J. A. Schneider and S. C. Johnson and A. J. Lee and C. Davatzikos and , S. O'Bryant and R. Barber and C. Cruchaga and T. L. S. Benzinger and D. Y. Lee and D. Yi and A4 Study team and HABS-HD Study Team and Alzheimers Disease Neuroimaging Initiative (ADNI) and Alzheimers Disease Sequencing Project},
  howpublished = {bioRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.28.760476},
  url = {https://www.biorxiv.org/content/10.64898/2026.10.28.760476v1},
  note = {CC BY},
}

TY  - UNPB
TI  - Topographic reference modelling of white matter hyperintensities across the adult lifespan
AU  - M. J. Alshikho
AU  - J. D. Pyne
AU  - N. C. Edwards
AU  - C. Hale
AU  - D. C. Samuel
AU  - C. D. Morales
AU  - N. Morel
AU  - R. V. Lippert
AU  - D. B. Archer
AU  - M. L. Cuccaro
AU  - A. W. Toga
AU  - A. J. Saykin
AU  - S. L. Risacher
AU  - M. E. Belloy
AU  - W. Kukull
AU  - S. Biber
AU  - J. Mez
AU  - P. K. Crane
AU  - S. Mukherjee
AU  - G. Erus
AU  - R. A. Sperling
AU  - D. A. Bennett
AU  - L. L. Barnes
AU  - J. A. Schneider
AU  - S. C. Johnson
AU  - A. J. Lee
AU  - C. Davatzikos
AU  - , S. O'Bryant
AU  - R. Barber
AU  - C. Cruchaga
AU  - T. L. S. Benzinger
AU  - D. Y. Lee
AU  - D. Yi
AU  - A4 Study team
AU  - HABS-HD Study Team
AU  - Alzheimers Disease Neuroimaging Initiative (ADNI)
AU  - Alzheimers Disease Sequencing Project
PY  - 2026
DA  - 2026/10/28
PB  - bioRxiv
DO  - 10.64898/2026.10.28.760476
UR  - https://www.biorxiv.org/content/10.64898/2026.10.28.760476v1
AB  - White matter hyperintensities (WMH) are among the most common MRI findings in older adults. They are widely regarded as markers of brain aging and cerebral small-vessel disease, and associated with risk for cognitive decline, Alzheimers disease and related dementias (ADRD), and stroke. White matter hyperintensities (WMH) are typically interpreted by total lesion burden, but lesions with similar volumes can occupy different anatomical locations, potentially reflecting distinct pathological processes. Here we present voxelwise topographic reference modelling (vTRM), a framework for characterizing individual WMH masks against age- and sex-stratified frequency maps derived from cognitively unimpaired individuals. Using 42,469 FLAIR-derived lesion masks from twelve adult cohorts, we mapped population-level WMH spatial vulnerability, characterized age-related changes in its distribution across periventricular, lobar and arterial-territory compartments, and constructed paired percentile charts for lesion burden and spatial typicality. A quadrant-based classification defined by these two percentile dimensions revealed graded relationships with ADRD pathophysiology, neurodegeneration, and cognitive impairment, while identifying WMH patterns differentially associated with ageing-related, vascular and neurodegenerative processes among individuals with similar lesion volumes. These reference charts establish a benchmark for normative WMH ageing, enabling quantification of individual deviations from typical age-, sex- and burden-related patterns and identification of WMH phenotypes associated with vascular, neurodegenerative or mixed etiologies. The framework, together with a deployable 3D U-Net model trained on these data for automated WMH segmentation, is available through the Brain Lesion Analytics platform (https://brainlesionanalytics.org/).
ER  -