Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a condition that often evolves into Parkinson's disease (PD). Therefore, by monitoring iRBD it is possible to track the neurodegeneration of individuals who may progress to PD. Here we aimed at piloting the characterization of brain tissue properties in mid-brain subcortical regions of 10 healthy subjects, 8 iRBD, and 9 early-diagnosed PD. We used a battery of magnetic resonance imaging (MRI) contrasts at 3 T, including adiabatic and non-adiabatic rotating frame techniques developed by our group, along with diffusion tensor imaging (DTI) and resting-state fMRI. Adiabatic T1ρ and T2ρ, and non-adiabatic RAFF4 (Relaxation Along a Fictitious Field in the rotating frame of rank 4) were found to have lower coefficient of variations and higher sensitivity to detect group differences as compared to DTI parameters such as fractional anisotropy and mean diffusivity. Significantly longer T1ρ were observed in the amygdala of PD subjects vs. controls, along with a trend of lower functional connectivity as measured by regional homogeneity, thereby supporting the notion that amygdalar dysfunction occurs in PD. Significant abnormalities in reward networks occurred in iRBD subjects, who manifested lower network strength of the accumbens. In agreement with previous studies, significantly longer T1ρ occurred in the substantia nigra compacta of PD vs. controls, indicative of neuronal degeneration, while regional homogeneity was lower in the substantia nigra reticulata. Finally, other trend-level findings were observed, i.e., lower RAFF4 and T2ρ in the midbrain of iRBD subjects vs. controls, possibly indicating changes in non-motor features as opposed to motor function in the iRBD group. We conclude that rotating frame relaxation methods along with functional connectivity measures are valuable to characterize iRBD and PD subjects, and with proper validation in larger cohorts may provide pathological signatures of iRBD and PD.
Bibliographical noteFunding Information:
We are grateful to the study coordinators and volunteers who participated in the study and thereby made this research possible. The authors acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for providing resources that contributed to the research results reported within this paper. URL: http://www.msi.umn.edu. In addition, the authors would like to thank Karin Shmueli and Alejandra Sierra-Lopez for helpful discussions and feedback on the manuscript. Research reported in this publication was supported by the University of Minnesota Foundation, by the National Institutes of Health (Funding P41 EB015894, P30 NS076408, 1S10OD017974, UL1TR000114, and KL2TR000113), by the Academy of Finland (grant #285909) and by the Ministry of Education, Youth and Sports of the Czech Republic under the National Sustainability Programme II (project CEITEC 2020, LQ1601). This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant, agreement #691110 (MICROBRADAM). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding bodies.
© 2017 Mangia, Svatkova, Mascali, Nissi, Burton, Bednarik, Auerbach, Giove, Eberly, Howell, Nestrasil, Tuite and Michaeli.
- Functional connectivity
- Parkinson's disease
- Rotating frame MRI
PubMed: MeSH publication types
- Journal Article