REPOSITORY > RESULTS

Abstract

Background: Malignant pleural mesothelioma (MPM) is a rare and aggressive thoracic malignancy that is difficult to cure and is linked to asbestos exposure. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a functional imaging technique used to analyze tumor microvascular properties and to monitor therapy response. The purpose of this study was to compare two tracer kinetic models, the extended Tofts (ET) and the adiabatic approximation tissue homogeneity model (AATH), for analysis of DCE-MRI and to examine the value of the DCE parameters to predict the response to chemotherapy in patients with MPM.
Method: This was a prospective, longitudinal and single-center study conducted between October 2013 and July 2015. Patients underwent DCE-MRI studies at three time points: pre-, intra- and post-chemotherapy. Images were analyzed using ET and AATH models. After finishing the chemotherapy, patients were classified as having disease control or progressive disease according to modified response evaluation criteria in solid tumors (mRECIST) criteria. Receiver operating characteristic curve analysis was used to examine specificity and sensitivity of DCE parameters for predicting response to therapy. Comparison tests were used to analyze whether derived parameters are interchangeable between the two models.
Results: Nineteen patients form the study population. The results indicate that the derived parameters are not interchangeable between the models. Significant correlation with response to therapy was found for AATH-calculated median pre-treatment efflux rate (kep) with estimated sensitivity of 83% and specificity of 100% (cut-off of ≥ 0.13 /min, AUC 0.92). ET-calculated maximal pre-treatment kep values showed a significant predictive value of MPM response during treatment with estimated 100% sensitivity and specificity (cut-off of ≥ 0.89 /min, AUC 1), but were less predictive for MPM response to therapy with estimated sensitivity and specificity of 83.3% and 92.3%, respectively (P = 0.06; cut-off of ≥ 1.31 /min, AUC 0.81).
Conclusions: The results of our study showed that ET and AATH models for post-processing DCE-MRI datasets yield significantly different values of the DCE parameters which are not interchangeable. However, high pre-treatment kep values, calculated using both models, may serve as a prognostic marker in predicting better MPM response to chemotherapy. Therefore, the use of DCE-MRI may open up the possibility for patient-tailored treatment depending on tumor biology and provide a broader prospective of the treatment effect beyond the changes in tumor thickness.