4.5 Article

ARTS: A novel In-vivo classifier of arteriolosclerosis for the older adult brain

Journal

NEUROIMAGE-CLINICAL
Volume 31, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.nicl.2021.102768

Keywords

Arteriolosclerosis; Brain; MRI; Pathology; Machine learning; Cognition

Categories

Funding

  1. NIH [P30AG010161, UH2NS100599, UH3NS100599, R01AG064233, R01AG15819, RF1AG022018, R01AG056405, R01AG17917, R01AG067482]
  2. Illinois Department of Public Health (Alzheimer's Disease Research Fund) - Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]
  3. DOD ADNI (Department of Defense) [W81XWH-12-2-0012]
  4. National Institute on Aging
  5. National Institute of Biomedical Imaging and Bioengineering
  6. Alzheimer's Association
  7. Alzheimer's Drug Discovery Foundation
  8. Araclon Biotech
  9. Biogen
  10. Bristol-Myers Squibb Company
  11. CereSpir, Inc.
  12. Cogstate
  13. Eisai
  14. Elan Pharma-ceuticals, Inc.
  15. Eli Lilly and Company
  16. EuroImmun
  17. Fujirebio
  18. Johnson & Johnson Pharmaceutical Research & Development LLC.
  19. Merck Co., Inc.
  20. Meso Scale Diagnostics
  21. NeuroRx Research
  22. Novartis Pharmaceuticals Corporation
  23. Pfizer Inc.
  24. Piramal Imaging
  25. Takeda Pharmaceutical Company
  26. Canadian Institutes of Health Research
  27. ADNI clinical sites in Canada
  28. Foundation for the National Institutes of Health
  29. Northern California Institute for Research and Education
  30. Laboratory for NeuroImaging at the University of Southern California

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The study developed an in-vivo classifier of arteriolosclerosis based on brain MRI, named ARTS, showing good predictive performance and associations with cognitive decline in non-demented older adults.
Brain arteriolosclerosis, one of the main pathologies of cerebral small vessel disease, is common in older adults and has been linked to lower cognitive and motor function and higher odds of dementia. In spite of its frequency and associated morbidity, arteriolosclerosis can only be diagnosed at autopsy. Therefore, the purpose of this work was to develop an in-vivo classifier of arteriolosclerosis based on brain MRI. First, an ex-vivo classifier of arteriolosclerosis was developed based on features related to white matter hyperintensities, diffusion anisotropy and demographics by applying machine learning to ex-vivo MRI and pathology data from 119 participants of the Rush Memory and Aging Project (MAP) and Religious Orders Study (ROS), two longitudinal cohort studies of aging that recruit non-demented older adults. The ex-vivo classifier showed good performance in predicting the presence of arteriolosclerosis, with an average area under the receiver operating characteristic curve AUC = 0.78. The ex-vivo classifier was then translated to in-vivo based on available in-vivo and ex-vivo MRI data on the same participants. The in-vivo classifier was named ARTS (short for ARTerioloSclerosis), is fully automated, and provides a score linked to the likelihood a person suffers from arteriolosclerosis. The performance of ARTS in predicting the presence of arteriolosclerosis in-vivo was tested in a separate, 91% dementia-free group of 79 MAP/ROS participants and exhibited an AUC = 0.79 in persons with antemortem intervals shorter than 2.4 years. This level of performance in mostly non-demented older adults is notable considering that arterio-losclerosis can only be diagnosed at autopsy. The scan-rescan reproducibility of the ARTS score was excellent, with an intraclass correlation of 0.99, suggesting that application of ARTS in longitudinal studies may show high sensitivity in detecting small changes. Finally, higher ARTS scores in non-demented older adults were associated with greater decline in cognition two years after baseline MRI, especially in perceptual speed which has been linked to arteriolosclerosis and small vessel disease. This finding was shown in a separate group of 369 non- demented MAP/ROS participants and was validated in 72 non-demented Black participants of the Minority Aging Research Study (MARS) and also in 244 non-demented participants of the Alzheimer's Disease Neuroimaging Initiative 2 and 3. The results of this work suggest that ARTS may have broad implications in the advancement of diagnosis, prevention and treatment of arteriolosclerosis. ARTS is publicly available at https://www.nitrc.org/ projects/arts/.

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