An Augmented Aging Process in Brain White Matter in HIV

T. Kuhn; T. Kaufmann; N.T. Doan; L.T. Westlye; J. Jones; R.A. Nunez; S.Y. Bookheimer; E.J. Singer; C.H. Hinkin; A.D. Thames

Next, the SVR-modeling of the DTI data appeared to be less accurate (MAE = 7.39 years) than that using T1-MRI to measure brain volume (MAE = 5.01 years) 9 . This could be due to differences in the neuroimaging methodology used (e.g. size, variability and number of features of training sample set). However, it is also the case that we sought to test a different biological entity (DTI-based WM microstructure), and as such a direct comparison between SVR-derived brain ages may not be appropriate, as Cole et al sought to determine a best-predicted brain age based on grey/white matter volume and we sought to determine the best-predicted age of WM microstructure.. The fact that data was acquired at multiple sites using different MR scanner could be a factor and a limitation. However, scanner was included as a variable in the model and the data was homogenized using a single, uniform processing pipeline which has become an accepted standard of practice in the field and indeed has been used in similar machine learning papers 9, 10 where the training data and the disease-specific data were collected at separate sites using different scanners and non-identical scanning parameters. Therefore, this is a limitation of note but one whose impact on the findings was minimized to the best of our abilities. Additionally, although the TBSS method applied should limit the impact of atrophy on our findings, this study did not employ any specific control regarding possible WM lesions. Given that WM lesions have been reported in the brains of HIV+ patients, it is possible that our prediction of WM age could . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/265199 doi: bioRxiv preprint 20 Kuhn, T., Ph.D. 20 be improved had we included WM lesions from any affected patient in the model.