Imaging in pleural mesothelioma: A review of the 12th International Conference of the International Mesothelioma Interest Group. Issue 2 (November 2015) - Armato, Samuel G.; Coolen, Johan; Nowak, Anna K.; Robinson, Cleo; Gill, Ritu R.; Straus, Christopher; Khanwalkar, Ashoke
Highlights: A murine model for PET-based imaging of hypoxia in mesothelioma has been developed. DWI can be used to assess histologic composition and early response. CT-based tumor volume is only modestly correlated with surgical specimen volume. Volumetric tumor response criteria will differ from standard RECIST criteria. Pre-treatment tumor volume growth rate may be useful for tumor response assessment. Abstract: Imaging of malignant pleural mesothelioma is essential to patient management, prognostication, and response assessment. From animal models to clinical trials, the gamut of research activities and clinical standards relies on imaging to provide information on lesion morphology and the growing number of physiologic characteristics amenable to capture through imaging techniques. The complex morphology, growth pattern, and biological mechanisms of mesothelioma, however, present challenges for image acquisition and interpretation. Nevertheless, novel approaches to image acquisition and subsequent image analysis have expanded the opportunities for (as well as the need for) imaging in this disease. This paper summarizes the imaging-based research presented orally at the 2014 International Conference of the International Mesothelioma Interest Group (iMig) in Cape Town, South Africa, October 2014. Presented topics include the imaging of hypoxia in a murine model through positron emission tomography (PET), the use of diffusion-weighted magnetic resonance imaging (MRI) to assess the histologic composition of biphasic mesothelioma and to assess early response to chemotherapy, the correlation of CT-based tumor volume with the volume of the post-surgical tumor specimen, the development of volumetric tumor response criteria, and pre-treatment tumor volume growth considerations for tumor response assessment.