Abstract #4545

Guanidino Chemical Exchange Saturation Transfer MRI (GuanCEST) signal intensity reductions as a surrogate biomarker for Parkinson’s Disease

Kexin Wang^1,2, Nirbhay Narayan Yadav^2,3, Zijiang Yang^2,4, Peter van Zijl^2,3, Kelly Mills^5,6, Jiadi Xu^2,3, and Jannik Prasuhn^2,7,8,9

¹Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²Kennedy Krieger Institute, Baltimore, MD, United States, ³Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁴Department of Electrical Engineering, Johns Hopkins University, Baltimore, MD, United States, ⁵Parkinson’s Disease and Movement Disorders Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁶Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁷Department of Neurology, University-Medical Center Schleswig-Holstein, Lübeck, Germany, ⁸Institute of Neurogenetics, University of Lübeck, Lübeck, Germany, ⁹Center for Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany

Synopsis

Keywords: Parkinson's Disease, Metabolism, Biomarkers

Motivation: Creatine (Cr) is a potential biomarker for Parkinson’s disease (PD), yet the relationship between PD severity and Cr levels in subcortical brain regions remains unclear.

Goal(s): To investigate the relationship between Cr-weighted CEST signals in subcortical regions and PD severity.

Approach: Guanidino chemical exchange saturation transfer (GuanCEST) MRI is a Cr-weighted metric. Reductions of GuanCEST intensity in thalamic subregions in PD patients versus healthy controls were correlated with disease duration and severity.

Results: Greater reduction in GuanCEST levels was observed with increasing PD severity, particularly in thalamic subregions. This is tentatively interpreted to be due to lower Cr levels in these regions.

Impact: Reductions in Cr-weighted GuanCEST MRI signal in several sensitive brain regions correlated to Parkinson’s severity, based on motor system scores, suggesting a potential biomarker to help identify responsive cohorts for targeted treatments and trial design.

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