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Updated: Jan 15, 2026
MALDI Imaging Mass Spectrometry of Neuropeptides in Parkinson's Disease
Published on: February 14, 2012
Diagnostic Potential of Macromolecular Proton Fraction Mapping Combined with Quantitative Susceptibility Mapping as a
Yasuhiro Fujiwara1, Nobutaka Sakae2, Hiroyuki Kumazoe3
1Department of Medical Imaging Technology, Faculty of Life Sciences, Kumamoto University, Kumamoto Kumamoto, Japan.
Purpose:
This study aimed to evaluate the diagnostic potential of macromolecular proton fraction (MPF) mapping combined with magnetic susceptibility measurements as subcortical biomarkers in Parkinson's disease (PD).
Methods:
Twenty patients with PD and 9 age-matched healthy controls underwent 3.0T magnetic resonance imaging, including MPF mapping and quantitative susceptibility mapping (QSM). MPF and magnetic susceptibility values of the 16 subcortical nuclei were measured in both the PD group and healthy control group, and these values were compared between the 2 groups. Diagnostic performance of MPF and magnetic susceptibility in the subcortical nuclei was individually evaluated using receiver operating characteristic (ROC) analysis. A logistic regression model was developed for the diagnosis of PD using a combination of MPF and magnetic susceptibility values.
Results:
Quantitative analyses revealed significantly reduced MPF values (false discovery rate-corrected P < 0.05) in 7 subcortical nuclei in the PD group, namely the hypothalamus, parabrachial pigmented nucleus, red nucleus, substantia nigra pars reticulata, substantia nigra pars compacta, ventral pallidum, and ventral tegmental area. Additionally, magnetic susceptibility was significantly elevated (false discovery rate-corrected P < 0.05) in the parabrachial pigmented nucleus and substantia nigra pars compacta. ROC curve analysis demonstrated strong diagnostic performance, with the ventral pallidum showing the highest MPF-based diagnostic accuracy (area under the curve [AUC] = 0.82) and the substantia nigra pars compacta showing the highest QSM-based accuracy (AUC = 0.88). The logistic regression model combining MPF and magnetic susceptibility showed the best performance (AUC = 0.93).
Conclusion:
MPF mapping, particularly when combined with magnetic susceptibility measurements, may serve as a quantitative diagnostic biomarker for PD, and the observed widespread alterations across multiple subcortical nuclei provide new insights into the pathology of PD beyond the classic nigrostriatal pathway.
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