ArticleCancer imaging : the official publication of the International Cancer Imaging Society2019
Dynamic contrast-enhanced MRI of malignant pleural mesothelioma: a comparative study of pharmacokinetic models and correlation with mRECIST criteria.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A signal model for fat-suppressed TNMR in biomedicine · 2025Article
- Pleural Neoplasms-What Could MRI Change?Cancers · 2023Review
- The Use of Chest Magnetic Resonance Imaging in Malignant Pleural Mesothelioma Diagnosis.Diagnostics (Basel, Switzerland) · 2022Review
- Article
- New Updates of the Imaging Role in Diagnosis, Staging, and Response Treatment of Malignant Pleural Mesothelioma.Cancers · 2021Review
- Enhancement degree of brain metastases: correlation analysis between enhanced T2 FLAIR and vascular permeability parameters of dynamic contrast-enhanced MRI.European radiology · 2021Article
- Clinical Implementation of a Free-Breathing, Motion-Robust Dynamic Contrast-Enhanced MRI Protocol to Evaluate Pleural Tumors.AJR. American journal of roentgenology · 2020Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundMalignant pleural mesothelioma (MPM) is a rare and aggressive thoracic malignancy that is difficult to cure. Dynamic contrast-enhanced (DCE) MRI is a functional imaging technique used to analyze tumor microvascular properties and to monitor therapy response. 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 examine the value of the DCE parameters to predict response to chemotherapy in patients with MPM.
methodThis prospective, longitudinal, single tertiary radiology center study was conducted between October 2013 and July 2015. Patient underwent DCE-MRI studies at three time points: prior to therapy, during and after cisplatin-based chemotherapy. The images were analyzed using ET and AATH models. In short-term follow-up, the 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.
resultsNineteen 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 (k
conclusionBoth models show potential in predicting response to therapy in MPM. High pre-treatment k
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