Abstract
Total metabolic tumor volume (MTV) is a well-established prognostic biomarker in diffuse large B-cell lymphoma (DLBCL). Nonetheless, additional imaging parameters that are readily obtainable in routine clinical practice may further enhance prognostic accuracy. This study investigates two novel 18F-FDG PET/CT-derived metrics: Dmax/Volume lesion, a shape-related parameter, and TLG-inverse (the ratio of SUVmean to lesion volume), to determine if they improve risk stratification beyond MTV. Additionally, we evaluated the prognostic value of MTV rate (the ratio of the largest lesion volume to total MTV), a recently proposed metric.
Eighty-five patients diagnosed with DLBCL were included. Receiver operating characteristic (ROC) curves were generated to assess each parameter's capacity to predict disease progression at 24 months and to define optimal cut-off values. Kaplan-Meier survival analysis was conducted using these thresholds, with statistical significance evaluated via log-rank tests.
MTV demonstrated strong prognostic performance (AUC=0.845, p<0.001), consistent with its established role. The optimal MTV cut-off was identified as 412.9 cm³. Both Dmax/Volume lesion and TLG-inverse showed high AUC values (0.807 and 0.827, respectively) when predicting progression, however, with inverse correlation, indicating worse prognosis for lower values. Kaplan-Meier analyses confirmed that these parameters effectively discriminated clinically relevant low- and high-risk subgroups (p<0.001). Patients characterized by high MTV combined with low TLG-inverse had a progression rate of 78.6%, compared to 72.4% in the high-risk Dmax/Volume lesion group and 68.6% with high MTV alone. Notably, MTV rate did not enhance prognostication in this cohort (AUC=0.477, p=0.73).
Dmax/Volume lesion and TLG-inverse are novel, easily measurable imaging biomarkers that may augment prognostic precision when combined with MTV in DLBCL. While preliminary findings are encouraging, these results warrant cautious interpretation and require validation in larger, independent cohorts to confirm their added prognostic value.
