PET-Based Prognostic Stratification in Primary Mediastinal B-Cell Lymphoma Using the SUV≥4 Segmentation Threshold: A Comparative Analysis of Contouring Methods in the IELSG37 Trial Cohort
Authors: Ceriani Luca , Milan Lisa , Pirosa Maria Cristina , Di Rocco Alice , Ruberto Teresa , Cascione Luciano , Johnson Peter , Davies Andrew J. , Martelli Maurizio , Zucca Emanuele 
Published: December 2024

Background: Metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG) on PET images are emerging as robust predictors for outcomes in various malignant lymphoma subtypes. However, their use in clinical practice and trials is limited due to the lack of standardized measurement procedures. While a 41% SUVmax threshold is commonly used for segmentation in lymphoma and solid cancers, it is suboptimal for primary mediastinal B-cell lymphoma (PMBCL). For PMBCL, a 25% SUVmax threshold has been identified as optimal for contouring bulky tumor lesions (Ceriani et al, Blood 2015). TLG estimated using this threshold has also proven to be the best prognostic marker in PMBCL.
A newly proposed SUV≥4 fixed threshold (Boellaard et al, J Nucl Med 2024, in press) might standardize MTV and TLG estimation and facilitate clinical application across various lymphomas, including follicular lymphoma, diffuse large B-cell lymphoma, and Hodgkin lymphoma. This new method reduces observer interaction and inter-operator variability but has not yet been tested in PMBCL.
Aim: To compare the prognostic value of TLG, estimated using both the current standard (25% of SUVmax) and the newly proposed segmentation thresholds (SUV≥4), in a large cohort of PMBCL patients.
Methods: Baseline 18FDG PET scans from 501 PMBCL patients enrolled in the IELSG37 study (NCT01599559) were evaluated. Lesion contouring was performed by a single operator using a dedicated commercial software with the two thresholds (SUV≥4 and 25% of SUVmax). PET-metrics were estimated with both thresholds.
Results: The SUV value used for segmentation with the 25% of SUVmax threshold was higher than 4 in over 75% of patients (median SUV 5.37, IQR 4.40-6.70). Consequently, the median MTV estimated with the 25% SUVmax threshold was lower than that obtained with the SUV≥4 threshold (331 ml, IQR 201-530 vs. 396 ml, IQR 229-635; p &lt; 0.0001). Similarly, the estimated TLG showed a difference (3387, IQR 1894-6070 vs. 3750, IQR 1953-6425; p &lt; 0.0001). Despite this, there were strong correlations between MTV values (r=0.95; p&lt;0.001) and even higher correlations for TLG (r=0.99; p&lt;0.001) calculated with each method. ROC analysis identified different optimal cutoff points for TLG estimated with the 25% of SUVmax threshold (3858, ROC-AUC 0.648, p=0.0008) and the SUV≥4 threshold (4225, ROC-AUC 0.649, p=0.0008), both effectively identifying patients with different outcomes. Univariate analysis showed significant differences in PFS between patients with low and high TLG, regardless of the method used (96% vs. 86%, log-rank test, p&lt;0.0001 with the 25% of SUVmax method, and 95% vs. 86%, log-rank test, p=0.0002 with the SUV≥4 method). Only 27 of 501 patients (5%) were categorized differently by the two methods. The comparable prognostic performance of TLG obtained using these two segmentation methods was then confirmed in the 103-patient cohort from the IELSG26 study, previously used to demonstrate the superiority of the 25% threshold in PMBCL. In this cohort, TLG's capacity to discriminate patients with significantly different progression-free survival (98% at 5 years for low TLG vs. 77% for high TLG, p=0.015) was maintained with the SUV≥4 method, even using the TLG cut-point generated by ROC curves in the IELSG37 study population.
Conclusions: Optimal cutoffs for distinguishing between high and low-risk patients depend on population characteristics and the segmentation method used on PET images. Our findings support the routine use of the SUV≥4 threshold for volumetric measurements in PMBCL. The prognostic utility of TLG is maintained with the new method, allowing its use in PMBCL similarly to other lymphoma subtypes.