Advanced diffusion‐weighted MRI methods demonstrate improved sensitivity to white matter aging: Percentile charts for over 15, 000 UK Biobank participants. (1st February 2022)

• Record Type: Journal Article
• Authors: Lawrence, Katherine E.; Nabulsi, Leila; Santhalingam, Vigneshwaran; Abaryan, Zvart; Villalon‐Reina, Julio E.; Nir, Talia M.; Gari, Iyad Ba; Zhu, Alyssa H.; Haddad, Elizabeth; Muir, Alexandra M.; Laltoo, Emily; John, John P.; Venkatasubramanian, Ganesan; Jahanshad, Neda; Thompson, Paul M.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-01
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.051187
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Aging and Alzheimer's disease are both associated with alterations in the brain's white matter. Understanding how the brain's white matter changes as we age may also improve our understanding of processes involved in Alzheimer's disease. Here we investigated the ability of both traditional and advanced diffusion‐weighted MRI methods to capture age effects on white matter microstructure in a large‐scale, population‐based sample of middle‐aged and older adults. Method: Diffusion‐weighted MRI (dMRI) scans were analyzed from 15, 628 UK Biobank participants (age: 45‐80 years; 47.6% male). Diffusivity metrics were derived using four dMRI reconstruction models, including traditional diffusion tensor imaging (DTI) and the following advanced dMRI models: the tensor distribution function (TDF), neurite orientation dispersion and density imaging (NODDI), and mean apparent propagator MRI (MAPMRI). Metrics were projected to a standard white matter skeleton using publicly available ENIGMA protocols based on FSL's tract‐based spatial statistics and the JHU atlas. Mean values for each dMRI metric were extracted from the whole white matter skeleton (full WM) and for the corpus callosum (CC). We investigated effects of age, sex, and their interaction on each dMRI metric for the full WM and the CC separately, to rank the sensitivity of these different metrics. Sex‐stratified centile reference curves were created for each dMRI metric to provide normative charts of white matter aging for this population. Result: Participant age and sex were both significantly associated with full WM and CC microstructure for nearly all dMRI metrics, with TDF exhibiting the greatest sensitivity to age and NODDI the greatest sensitivity to participant sex (Figure 1). A significant age by sex interaction was observed in the full WM and the CC for many dMRI measures; NODDI detected this interaction with the greatest sensitivity. (Figure 1). Normative centile reference curves are presented for all dMRI indices separately for men and women (Figures 2 and 3). Conclusion: Participant age and sex robustly impact the brain's white matter microstructure, with advanced dMRI models displaying the greatest sensitivity to such differences. These findings offer a normative reference to guide future studies and treatment of Alzheimer's disease.