Detection and Characterization of Residual Masses in Lymphomas

Imaging biomarkers are important tools for the detection and characterization of cancers as well as for monitoring the response to therapy. "Whole-body" molecular imaging, in particular using 18-Fluorodeoxyglucose-PET, has been proven useful in the evaluation and management of lymphoma patients. FDG-PET has evolved as a valuable biomarker in aggressive lymphomas, which is the current state-of-the-art imaging technique for response assessment at the end of treatment. Additionally, the prognostic value of "interim" (during treatment) or early PET has been well established in Hodgkin lymphoma and diffuse large B-cell lymphoma, which together account for more than 50% of all lymphomas. Worldwide clinical trials are ongoing to evaluate risk-adapted individualized treatment strategy based on interim PET results. Therefore, uniform and evidence-based guidelines for the interpretation are warranted. International Workshop on Interim PET in Lymphoma recently proposed a 5-point score method and so far the results of validation studies are promising. However, one could speculate that the risk of false-positive studies due to a non-specific inflammatory effect will be greater when patients receiving more toxic regimens and the usefulness of imaging biomarkers would vary for different lymphoma subtypes. Meanwhile, thanks to rapid technical development, whole-body functional magnetic resonance imaging (MRI) in particular diffusion-weighted MRI (DWI) reflecting cell density is now feasible in the clinical setting. Quantitative parameters derived from DWI reflecting cell density may provide complementary information to current state-of-the-art FDG-PET imaging reflecting quantitatively glucose metabolism and prove to be helpful in patient management. Pilot studies have shown the potential of whole-body DWI in lymphomas for staging and response assessment on 1.5 Tesla MR system but larger-scaled prospective studies are required before this new imaging-based biomarker can ever be validated for routine clinical use. Besides, technical challenges remain especially when encountering higher-field clinical MR systems. Finally, a vast amount of information generated from whole-body parametric imaging data will require development of automated image analysis software, which may help in establishing a multi-parametric approach in characterizing residual lymphoma masses. Therefore, the present study aims to further optimize a whole-body DWI protocol on 3 Tesla MR and/or new system combining 3Tesla MR and PET, to develop and validate an automated whole-body parametric image analysis algorithm, and to determine the added value of whole-body DWI to FDG-PET for the management of lymphoma patients.