This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2* relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. These findings highlight the importance of a combined evaluation of multimodal biomarkers for the study of aging and point to a number of novel applications for the method described.
Brain tissues atrophy is not always the best structural biomarker of physiological aging: A multimodal cross-sectional study / Cherubini, Andrea; Caligiuri, Maria Eugenia; Peran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco. - 2015-:(2015), pp. 5436-5440. ( 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 MiCo Center, Milano Congressi Center, ITALY 25-29 agosto 2015) [10.1109/EMBC.2015.7319621].
Brain tissues atrophy is not always the best structural biomarker of physiological aging: A multimodal cross-sectional study
Amato, Francesco
2015
Abstract
This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2* relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. These findings highlight the importance of a combined evaluation of multimodal biomarkers for the study of aging and point to a number of novel applications for the method described.| File | Dimensione | Formato | |
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