Role of novel PET-CT metabolic measures total lesion glycolysis (TLG) and total metabolic tumor volume (TMTV) in prediction of treatment response in hodgkin and non-hodgkin lymphoma patients
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Background
Advances in imaging have significantly enhanced the management of lymphoma, particularly through 18 F-FDG PET/CT, which combines metabolic and anatomical assessment. However, reliance on SUVmax alone provides a limited view of total disease burden. Recently, metabolic volumetric metrics such as total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) have emerged as promising tools, offering more robust prognostic information. This study aims to evaluate the predictive role of TMTV and TLG, as measured on an interim PET-CT scan (after three cycles of chemotherapy), and the change in these values on the end-of-treatment scan (after six cycles), in assessing theraputic response in patients with Hodgkin (HL) and non-Hodgkin lymphoma (NHL), and to correlate these measures with established prognostic indices.
Results
Ninety-one patients (HL: 38; NHL: 53) were analyzed. Comparison between interim and end-of-treatment scans showed significant reductions in TMTV and TLG in HL group, while reductions in NHL group did not reach statistical significance. For predicting complete metabolic response, ΔTLG demonstrated a diagnostic accuracy of 98.1% (at cut-off of > − 4.2) and ΔTMTV 96.2% (at cut-off of > − 1) in the NHL group, while in the HL group, ΔTLG achieved an accuracy of 92.1% (at cut-off of > − 7) and ΔMTV 89.5% (at cut-off of > − 5). In HL, TLG > 200 and MTV > 20 were associated with progressive disease, while in NHL, thresholds of TLG > 150 and MTV > 15 yielded AUCs of 0.768 and 0.761, respectively. Significant correlations were observed between end-of-treatment TMTV, TLG, and IPS in HL (r = 0.545 and 0.549; p < 0.05), but not with IPI in NHL.
Conclusions
TMTV and TLG are reliable PET/CT-derived biomarkers for early response prediction in lymphoma. Their dynamic changes outperform conventional SUVmax and correlate significantly with prognostic scores in HL. Incorporating these metabolic volumetric metrics may enhance individualized treatment strategies.
