CEST Contrasts Exhibit Significant Regional Variations in the Human Brain at 3 T

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging technique with established clinical relevance in neuro-oncology. While CEST contrast differences between gray matter (GM) and white matter (WM) are documented, brain region-specific contrast variations remain underexplored. This study investigates the regional variability of CEST contrasts in healthy brains to provide a baseline reference, which could enhance the detection of subtle pathological changes in clinical settings. Ten healthy volunteers (five female, mean age 25 ± 3.1 years) underwent 3D CEST imaging on a 3-T Siemens Prisma scanner. Using a custom segmentation tool, GM and WM regions of interest (ROIs) were automatically selected in the frontal, parietotemporal, and occipital regions and the calcarine sulcus to analyze regional contrast changes for the relaxation-compensated MTR_Rex and asymmetry-based APTw CEST contrasts. Individual and grouped analyses showed significant regional differences in GM and WM for all CEST contrasts. Globally, significant GM-WM differences were also detected for the APTw, MTR_Rex AMIDE, and MTR_Rex ssMT, which demonstrated higher GM contrast values for APTw and MTR_Rex AMIDE and lower GM contrast values for the MTR_Rex ssMT. Regionally, all contrasts showed reduced GM signals in the frontal lobe and increased signals in the calcarine sulcus when compared to the occipital and parietotemporal lobe; however, these differences were less pronounced for MTR_Rex rNOE and MTR_Rex ssMT. Relaxation-compensated CEST and APTw CEST contrast values exhibit significant regional variation in the healthy brain, highlighting the importance of consistent ROI placement in clinical studies. At the same time, low intersubject variability was observed, providing robust normative values for future comparisons. These regional reference values can aid in the detection of subtle pathological changes in CEST MRI by offering a reliable baseline for interpreting deviations in patient data.