Exploring the association of glioma tumor residuals from incongruent [F]FET PET/MR imaging with tumor proliferation using a multiparametric MRI radiomics nomogram.

PURPOSE

The study aimed to using multiparametric MRI radiomics to predict glioma tumor residuals (TR) derived from incongruent [F]fluoroethyl-L-tyrosine ([F]FET) PET/MR imaging.

METHODS

One hundred ten patients with gliomas who underwent [F]FET PET/MR scanning were retrospectively analyzed. The TR was identified by the discrepancy-PET that the extent of resection (EOR) based on MRI subtracted the biological tumor volume on PET images. The MRI parameters and radiomics features were extracted based on EOR and selected by the least absolute shrinkage and selection operator to construct radiomics score (Rad-score). The correlation network analysis of all features was analyzed by Spearman's correlation tests. The methods for evaluating the clinical usefulness consisted of the receiver operating characteristic curve, the calibration curve, and decision curve analysis.

RESULTS

The Rad-score of the patients with the TR was significantly higher than those with the non TR (p < 0.001). The Rad-score was significantly correlated with the discrepancy-PET (r = 0.72, p < 0.001), Ki-67 level (r = 0.76, p < 0.001), and epidermal growth factor receptor (EGFR) of gliomas (r = 0.75, p < 0.001), respectively. Moreover, there was a difference of the correlation network analysis between the TR group and non TR group. The nomogram combing Rad-score and clinical features had the greatest performance in predicting TR (AUC = 0.90/0.87, training/testing). There was a significant difference in prognosis (median OS, 17 m vs. 43 m) between patients with TR and non TR based on nomogram prediction (p < 0.001).

CONCLUSION

The nomogram based on MRI radiomics would predict gliomas tumor residuals caused by the absence of F-PET PET examination and adjust EOR to improve prognosis.