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Longitudinal changes of cortical microstructure in Parkinson's disease assessed with T1 relaxometry
(2016)
Background: Histological evidence suggests that pathology in Parkinson's disease (PD) goes beyond nigrostriatal degeneration and also affects the cerebral cortex. Quantitative MRI (qMRI) techniques allow the assessment of changes in brain tissue composition. However, the development and pattern of disease-related cortical changes have not yet been demonstrated in PD with qMRI methods. The aim of this study was to investigate longitudinal cortical microstructural changes in PD with quantitative T1 relaxometry.
Methods: 13 patients with mild to moderate PD and 20 matched healthy subjects underwent high resolution T1 mapping at two time points with an interval of 6.4 years (healthy subjects: 6.5 years). Data from two healthy subjects had to be excluded due to MRI artifacts. Surface-based analysis of cortical T1 values was performed with the FreeSurfer toolbox.
Results: In PD patients, a widespread decrease of cortical T1 was detected during follow-up which affected large parts of the temporo-parietal and occipital cortices and also frontal areas. In contrast, age-related T1 decrease in the healthy control group was much less pronounced and only found in lateral frontal, parietal and temporal areas. Average cortical T1 values did not differ between the groups at baseline (p = 0.17), but were reduced in patients at follow-up (p = 0.0004). Annualized relative changes of cortical T1 were higher in patients vs. healthy subjects (patients: − 0.72 ± 0.64%/year; healthy subjects: − 0.17 ± 0.41%/year, p = 0.007).
Conclusions: In patients with PD, the development of widespread changes in cortical microstructure was observed as reflected by a reduction of cortical T1. The pattern of T1 decrease in PD patients exceeded the normal T1 decrease as found in physiological aging and showed considerable overlap with the pattern of cortical thinning demonstrated in previous PD studies. Therefore, cortical T1 might be a promising additional imaging marker for future longitudinal PD studies. The biological mechanisms underlying cortical T1 reductions remain to be further elucidated.
Aim: There is ongoing debate about the role of cortical and subcortical brain areas in force modulation. In a whole-brain approach, we sought to investigate the anatomical basis of grip force whilst acknowledging interindividual differences in connectivity patterns. We tested if brain lesion mapping in patients with unilateral motor deficits can inform whole-brain structural connectivity analysis in healthy controls to uncover the networks underlying grip force.
Methods: Using magnetic resonance imaging (MRI) and whole-brain voxel-based morphometry in chronic stroke patients (n=55) and healthy controls (n=67), we identified the brain regions in both grey and white matter significantly associated with grip force strength. The resulting statistical parametric maps (SPMs) provided seed areas for whole-brain structural covariance analysis in a large-scale community dwelling cohort (n=977) that included beyond volume estimates, parameter maps sensitive to myelin, iron and tissue water content.
Results: The SPMs showed symmetrical bilateral clusters of correlation between upper limb motor performance, basal ganglia, posterior insula and cortico-spinal tract. The covariance analysis with the seed areas derived from the SPMs demonstrated a widespread anatomical pattern of brain volume and tissue properties, including both cortical, subcortical nodes of motor networks and sensorimotor areas projections.
Conclusion: We interpret our covariance findings as a biological signature of brain networks implicated in grip force. The data-driven definition of seed areas obtained from chronic stroke patients showed overlapping structural covariance patterns within cortico-subcortical motor networks across different tissue property estimates. This cumulative evidence lends face validity of our findings and their biological plausibility.