The predictive and prognostic role of baseline 2-[18F]FDG PET/CT volumetric and dissemination features in classical Hodgkin lymphoma.

Albano, Domenico; Re, Alessandro; Daffini, Rosa; Tucci, Alessandra; Bertagna, Francesco · Eur J Nucl Med Mol Imaging · 2026

retrospective_cohort · Level III

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Abstract

This study aimed to evaluate whether baseline 2-deoxy-2-[18F]-fluoro-D-glucose (2-[<sup>18</sup>F]FDG) positron emission tomography/computed tomography (PET/CT) features reflecting tumor burden (Metabolic Tumor Volume [MTV] and Total Lesion Glycolysis [TLG]) and disease dissemination (Dmax) can predict treatment response and prognosis in patients with Hodgkin Lymphoma (HL). A retrospective single-center study was conducted on 361 classical HL consecutively diagnosed and treated with ABVD from January 2007 to June 2023. All patients underwent baseline, interim (iPET), and end-of-treatment (eotPET) PET/CT scans. Baseline MTV, TLG, and Dmax were calculated using specialized software (LIFEx 7.7). Treatment response was evaluated using Deauville scores and corresponding Lugano criteria. The primary endpoint was to evaluate the role of PET features in predicting progression-free survival (PFS). PFS was analyzed using Kaplan-Meier and Cox proportional hazards models. Baseline MTV, TLG, and Dmax were significantly higher in patients who failed to achieve a complete metabolic response at both interim and end-of-treatment assessments (<i>p</i> < 0.001). Multivariate analysis identified iPET metabolic response, eotPET metabolic response and baseline MTV, TLG, and Dmax as independent prognostic factors for PFS. Combining MTV and Dmax allowed for better risk stratification; Patients with both low MTV(≤ 111 cm<sup>3</sup>) and low Dmax (≤ 38 cm) had a median 5-year PFS of 90%, compared to 39% for those with both high MTV and high Dmax. Baseline 2-[18 F]FDG PET/CT metabolic parameters expressing tumor burden and dissemination are strong, independent predictors of treatment response and prognosis in HL. Integrating these features provides a robust method for early risk stratification. The online version contains supplementary material available at 10.1007/s00259-026-07862-x.