Distributed parameter model of dynamic contrast-enhanced MRI in the identification of IDH mutation, 1p19q codeletion, and tumor cell proliferation in glioma patients

Objectives: To investigate the clinical value of hemodynamic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) in predicting glioma genotypes including isocitrate dehydrogenase (IDH) mutation, 1p/19q codeletion status and the tumor proliferation index (Ki-67) noninvasively. And to compare the diagnostic performance of parameters of distributed parameter (DP)model and extended Tofts (Ex-Tofts) model.

Materials and methods: Dynamic contrast-enhanced MRI (DCE-MRI) data of patients with glioma were prospectively enrolled from April 2021 to May 2023. The imaging data were analyzed using DP and Ex-Tofts model for evaluating the perfusion and permeability characteristics of glioma. Comparisons were performed according to IDH genotype in all glioma patients and 1p/19q codeletion in IDH mutation glioma patients. Receiver operating characteristic (ROC) curves were generated for DCE-MRI parameters. The Spearman rank correlation coefficients were calculated between DCE MRI parameters and Ki-67 index.

Results: In IDH-mutation gliomas, a higher blood flow (F) was found in 1p/19q codeletion gliomas than in 1p/19q intact gliomas. No parameter derived from Ex-Tofts model showed significant differences in predicting 1p/19q status. Fractional volume of interstitial space (V _e) derived from both the DP and Ex-Tofts models exhibited optimal performance in predicting IDH genotype (AUC = 0.818, 0.828, respectively). V _e also showed the highest correlations with Ki-67 LI within their respective models in all gliomas (ρ = 0.62, 0.61), indicating comparable moderate positive associations. Ki-67.

Conclusion: DP model showed a clear advantage in predicting 1p/19q status compared to Ex-Tofts model. The DP and Ex-Tofts models performed similarly in predicting IDH mutation and Ki-67 index.