MOTIVATION: Mass cytometry (Cytometry by Time-Of-Flight, CyTOF) is a single-cell technology that is able to quantify multiplex biomarker expressions and is commonly used in basic life science and translational research. However, the widely used Gadolinium (Gd)-based contrast agents (GBCAs) in magnetic resonance imaging (MRI) scanning in clinical practice can lead to signal contamination on the Gd channels in the CyTOF analysis. This Gd contamination greatly affects the characterization of the real signal from Gd-isotope-conjugated antibodies, severely impairing the CyTOF data quality and ruining downstream single-cell data interpretation. RESULTS: We first in-depth characterized the signals of Gd isotopes from a control sample that was not stained with Gd-labeled antibodies but was contaminated by Gd isotopes from GBCAs, and revealed the collinear intensity relationship across Gd contamination signals. We also found that the intensity ratios of detected Gd contamination signals to the reference Gd signal were highly correlated with the natural abundance ratios of corresponding Gd isotopes. We then developed a computational method named by GdClean to remove the Gd contamination signal at the single-cell level in the CyTOF data. We further demonstrated that the GdClean effectively cleaned up the Gd contamination signal while preserving the real Gd-labeled antibodies signal in Gd channels. All of these shed lights on the promising applications of the GdClean method in preprocessing CyTOF datasets for revealing the true single-cell information. AVAILABILITY AND IMPLEMENTATION: The R package GdClean is available on GitHub at https://github.com/JunweiLiu0208/GdClean. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.