Abstract #0576

Normative trajectories of R1, R2*, and Susceptibility values of the healthy human brain cortex

Xinjie Chen^1,2,3, Po-Jui Lu^1,2,3, Mario Ocampo-Pineda ^1,2,3, Matthias Weigel^1,2,3,4, Kwok-Shing Chan^5,6, Alessandro Cagol^1,2,3,7, Marcel Zwiers⁸, Michelle G. Jansen⁸, David G. Norris ⁸, Sabine Schädelin^1,2,3, Muhamed Barakovic^1,2,3, Jens Kuhle^2,3, Ludwig Kappos^2,3, Lester Melie-Garcia^1,2,3, Cristina Granziera^1,2,3, and José P Marques⁸

¹Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland, ²Department of Neurology, University Hospital Basel, Basel, Switzerland, ³Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland, ⁴Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland, ⁵Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, ⁶Department of Radiology, Harvard Medical School, Boston, MA, United States, ⁷Department of Health Sciences, University of Genova, Genova, Italy, ⁸Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands

Synopsis

Keywords: Quantitative Imaging, Quantitative Imaging

Motivation: Quantitative MRI (qMRI) offers sensitive and specific measures to study age-related microstructural changes in the brain. However, models assessing age trajectories in qMRI brain properties are often incomparable among centers.

Goal(s): Develop normative models reflecting aging trajectories and assess the impact of bi-centric, non-fully matched protocols in brain aging studies.

Approach: Investigating age trajectories in cortical regions using polynomial regression models, focusing on quantitative R1, R2*, and susceptibility mapping (QSM).

Results: We validated data harmonization by observing the impact on normative trajectories using bicentric data, where we noted significantly different maturation and aging inflections for R1 and R2* trajectories across cortical regions.

Impact: This bi-centric, multi-parameter qMRI study investigates age-dependent variations across cortical regions, offering a valuable reference for subsequent qMRI aging research and emphasizing age effects on the cortical surface.

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