Time to Prepare for Risk Adaptation in Lymphoma by Standardizing Measurement of Metabolic Tumor Burden

Increased tumor burden is associated with inferior outcomes in many lymphoma subtypes. Surrogates of tumor burden that are easy to measure, such as the maximum tumor dimension of the bulkiest lesion on CT, have been used as prognostic indices for many years. Recently, total metabolic tumor volume (MTV) and tumor lesion glycolysis have emerged as promising and robust biomarkers of outcome in various lymphomas. The median MTV and the optimal cutoffs to separate patients into risk groups in a study population are, however, highly dependent on the population characteristics and the delineation method used to outline tumor on the PET image. This issue has precluded the use of MTV for risk stratification in trials and clinical practice. Standardization of the methodology is timely to allow the potential for risk adaptation to be explored in addition to response adaptation using PET. Meetings between representatives from research groups active in the field were held under the auspices of the PET International Lymphoma and Myeloma Workshop. A summary of those discussions, which included a review of the literature and a practical assessment of methods used for outlining, including various software options, is presented. Finally, a proposal is made to perform a technical validation of MTV measurement enabling benchmark reference ranges to be derived for published delineation approaches used for outlining with various software. This process would require collation of representative imaging data sets of the most common lymphoma subtypes; agreement on pragmatic criteria for the selection of lesions; generation of a range of MTVs, with consensus to be reached on final contours in a training set; and development of automated software solutions with a set of minimum functionalities to reduce measurement variability. Methods developed in the above training exercise could then be applied to another data set, with a final set of contours and values generated. This final data set would provide a benchmark against which end-users could test their ability to measure MTVs that are consistent with expected values. The data set and automated software solutions could be shared with manufacturers with the aim of including these in standard workflows to allow standardization of MTV measurement across the world.