Page 105 - 18F-FDG PET as biomarker in aggressive lymphoma; technical and clinical validation

Workflow optimization of MTV in DLBCL
modification was necessary for some patients but reduced interobserver reliability which may need to be balanced against potential improvement on prognostic accuracy.
Key Words:
Diffuse large B cell lymphoma, Metabolic tumor volume, PET/CT, Total lesion Glycolysis
Introduction
In young patients with diffuse large B cell lymphoma (DLBCL), a large maximum tumor diameter is an indicator of poor prognosis [1]. Recent progress in lymphoma care has recommended exploration of the prognostic value of volumetric tumor bulk measured on staging 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/ CT, with methods combining metabolic activity and volume [2]. In lung cancer patients, studies have focused on finding the most reliable tumor segmentation method [3–5]. However, compared with lung cancer, lymphoma segmentation is more challenging due to higher number of lesions, multiple anatomical locations, and inter- and intratumoral [18F]FDG uptake heterogeneity.
Preliminary data suggest that baseline metabolic tumor volume (MTV) has a prognostic value in DLBCL [6–9] and predict outcome better than bulky disease measured by maximum tumor diameter [7]. Total lesion glycolysis (TLG)— defined as SUVmean in a volume multiplied by the corresponding MTV—seems to perform similarly [7] or inferiorly [6,8] in predicting outcome of DLBCL patients. Various segmentation methods to measure MTV and TLG are being used in clinical lymphoma studies [10]: most use a fixed SUV threshold (e.g., SUV≥2.5 [7,9] or SUV≥4.0 [11]) or a percentage of SUVmax (e.g., 41 % of SUVmax [6,8,12]) to define MTV. An important finding from earlier studies in DLBCL is that optimal cutoff values range widely (220–550 ml), probably because of using different methodologies, small patient cohorts, differences in patient risk factors, and therapies [13]. Moreover, these data-driven cutoff values should be interpreted with caution, as they depend highly on acquisition and reconstruction protocols.
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