CEST 2022-three-dimensional amide proton transfer (APT) imaging can identify the changes of cerebral cortex in Parkinson's disease.

Magn Reson Imaging

Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730 Beijing, China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 100730 Beijing, China. Electronic address:

Published: October 2023

AI Article Synopsis

  • The study investigates the effectiveness of 3D amide proton transfer (APT) imaging in diagnosing Parkinson's disease (PD) by examining its impact on cerebral cortex parameters.
  • 34 PD patients and 29 matched controls were analyzed using advanced imaging techniques, revealing significant differences in specific APT-related metrics, particularly in the temporal grey matter.
  • Findings showed that while clinical assessments did not correlate with APT signals, the imaging metrics demonstrated strong diagnostic performance, especially when combined, indicating 3D-APT's potential in enhancing PD diagnosis.

Article Abstract

Purpose: Amide proton transfer (APT) imaging has shown its diagnostic and predictive superiority in Parkinson's disease (PD) in our previous studies using 2D APT imaging based on deep nuclei. We hypothesized that the pathophysiological abnormality of PD will change the APT-related parameters in the cerebral cortex, and the signal changes can contribute to accurate diagnosis of PD.

Methods: 34 patients with idiopathic Parkinson's disease (IPD) and 29 age- and sex-matched normal controls (NC) were enrolled in this prospective study. 3D-APT imaging and 3D-T1WI was performed in our participants. A volume-based morphometry algorithm was used and get automated cortical segmentations. Quantitative parameter maps of APT-related metrics were calculated by using SPM and MATLAB. The unpaired Student's t-test or Mann-Whitney U test was used for comparison of these values between IPD and NC groups. The associations between APT-related metrics and clinical assessments were investigated by Spearman correlation analysis. The receiver-operating characteristic (ROC) analysis was used to assess the diagnostic performances. The binary logistic regression model was used to combine the imaging parameters.

Results: There wasn't any correlations between cortical APT-related signals and clinical assessment, including the H&Y scale, the disease duration, the UPDRS III scores and the MMSE scores. The MTRasym, CESTRnr and MTRRex had significantly higher values (p <0.001, corrected by Bonferroni methods) in the IPD group than NC groups in the region of bilateral and total temporal grey matter. The single parameters achieved the best diagnostic performance among all APT-related metrics was MTRRex on the right temporal grey matter, with an area under the ROC curve (AUC) of 0.865. The combined parameters achieved the highest diagnostic performance (AUC: 0.932).

Conclusions: 3D-APT imaging could identify the changes of the cerebral cortex in Parkinson's disease. The cortical changes of APT-related parameters could potentially serve as imaging biomarkers to aid in the non-invasive diagnosis of PD.

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Source
http://dx.doi.org/10.1016/j.mri.2023.06.006DOI Listing

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