Purpose:
We developed a
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C-Methionine positron emission tomography/computed tomography (
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C-MET PET/CT)-based nomogram model that uses easy-accessible imaging and clinical features to achieve reliable non-invasive isocitrate dehydrogenase (IDH)-mutant prediction with strong clinical translational capability.
Methods:
One hundred and ten patients with pathologically proven glioma who underwent pretreatment
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C-MET PET/CT were retrospectively reviewed. IDH genotype was determined by IDH1 R132H immunohistochemistry staining. Maximum, mean and peak tumor-to-normal brain tissue (TNRmax, TNRmean, TNRpeak), metabolic tumor volume (MTV), total lesion methionine uptake (TLMU), and standard deviation of SUV (SUV
SD
) of the lesions on MET PET images were obtained via a dedicated workstation (Siemens. syngo.via). Univariate and multivariate logistic regression models were used to identify the predictive factors for IDH mutation. Nomogram and calibration plots were further performed.
Results:
In the entire population, TNRmean, TNRmax, TNRpeak, and SUV
SD
of IDH-mutant glioma patients were significantly lower than these values of IDH wildtype. Receiver operating characteristic (ROC) analysis suggested SUV
SD
had the best performance for IDH-mutant discrimination (AUC = 0.731, cut-off ≤ 0.29,
p
< 0.001). All pairs of the
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C-MET PET metrics showed linear associations by Pearson correlation coefficients between 0.228 and 0.986. Multivariate analyses demonstrated that SUV
SD
(>0.29 vs. ≤ 0.29 OR: 0.053,
p
= 0.010), dichotomized brain midline structure involvement (no vs. yes OR: 26.52,
p
= 0.000) and age (≤ 45 vs. >45 years OR: 3.23,
p
= 0.023), were associated with a higher incidence of IDH mutation. The nomogram modeling showed good discrimination, with a C-statistics of 0.866 (95% CI: 0.796–0.937) and was well-calibrated.
Conclusions:
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C-Methionine PET/CT imaging features (SUV
SD
and the involvement of brain midline structure) can be conveniently used to facilitate the pre-operative prediction of IDH genotype. The nomogram model based on
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C-Methionine PET/CT and clinical age features might be clinically useful in non-invasive IDH mutation status prediction for untreated glioma patients.