Time to prepare for risk adaptation in lymphoma by standardising measurement of metabolic tumour burden

Abstract

Increased tumour burden is associated with inferior outcomes in many lymphoma subtypes. Surrogates of tumour burden that are easy to measure, such as the maximum tumour dimension of the ‘bulkiest’ lesion on CT have been used as prognostic indices for many years. Recently, the total metabolically (active) tumour volume (M(A)TV) and tumour lesion glycolysis (TLG) have emerged as promising and robust biomarkers of outcome in various lymphomas. The median MTV value and the optimal cut-off points 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 tumour in the PET image. This has precluded the use of MTV for risk stratification in trials and clinical practice. Standardisation 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 softwares. This process would require i) collation of representative imaging datasets of the most common lymphoma subtypes, ii) agreement on pragmatic criteria for the selection of lesions, iii) generating a range of MTV values with consensus to be reached on final contours in a training set, and iv) developing 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 dataset with a final set of contours and values generated. This final dataset would provide a benchmark against which end-users could test their ability to measure MTV consistent with expected values. The dataset and automated software solutions could be shared with manufacturers with the aim to include these in standard workflows to allow standardisation of MTV measurement across the world.