AUTHOR=Liu Hao , Ye Zheng , Yang Ting , Xie Hongjun , Duan Ting , Li Mou , Wu Min , Song Bin TITLE=Predictive Value of Metabolic Parameters Derived From 18F-FDG PET/CT for Microsatellite Instability in Patients With Colorectal Carcinoma JOURNAL=Frontiers in Immunology VOLUME=Volume 12 - 2021 YEAR=2021 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2021.724464 DOI=10.3389/fimmu.2021.724464 ISSN=1664-3224 ABSTRACT=Background

Microsatellite instability (MSI) is one of the important factors that determine the effectiveness of immunotherapy in colorectal cancer (CRC) and serves as a prognostic biomarker for its clinical outcomes.

Purpose

To investigate whether the metabolic parameters derived from18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) can predict MSI status in patients with CRC.

Materials and Methods

A retrospective analysis was performed on CRC patients who underwent 18F-FDG PET/CT examination before surgery between January 2015 and April 2021. The metabolic 18F-FDG PET/CT parameters of the primary CRC lesion were calculated and recorded with different thresholds, including the maximum, peak, and mean standardized uptake value (SUVmax, SUVpeak, and SUVmean), as well as the metabolic tumor volume (MTV) and the total lesion glycolysis (TLG). The status of MSI was determined by immunohistochemical assessment. The difference of quantitative parameters between MSI and microsatellite stability (MSS) groups was assessed, and the receiver operating characteristic (ROC) analyses with area under ROC curves (AUC) was used to evaluate the predictive performance of metabolic parameters.

Results

A total of 44 patients (24 men and 20 women; mean ± standard deviation age: 71.1 ± 14.2 years) were included. There were 14 patients in the MSI group while there were 30 in the MSS group. MTV30%, MTV40%, MTV50%, and MTV60%, as well as TLG50% and TLG60% showed significant difference between two groups (all p-values <0.05), among which MTV50% demonstrated the highest performance in the prediction of MSI, with an AUC of 0.805 [95% confidence interval (CI): 0.657–0.909], a sensitivity of 92.9% (95% CI: 0.661–0.998), and a specificity of 66.7% (95% CI: 0.472–0.827). Patients’ age and MTV50% were significant predictive indicators of MSI in multivariate logistic regression.

Conclusion

The metabolic parameters derived from18F-FDG PET/CT were able to preoperatively predict the MSI status in CRC, with MTV50% demonstrating the highest predictive performance. PET/CT imaging could serve as a noninvasive tool in the guidance of immunotherapy and individualized treatment in CRC patients.