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. 2025 Jan;35(1):73-83.
doi: 10.1007/s00330-024-10955-6. Epub 2024 Jul 20.

Tumor response assessment in hepatocellular carcinoma treated with immunotherapy: imaging biomarkers for clinical decision-making

Rabea Sobirey  1   2 , Nickolai Matuschewski  1   2 , Moritz Gross  1   2 , MingDe Lin  1   3 , Tabea Kao  1   2 , Victor Kasolowsky  1   2 , Mario Strazzabosco  4 , Stacey Stein  5 , Lynn Jeanette Savic  2 , Bernhard Gebauer  2 , Ariel Jaffe  4 , James Duncan  1 , David C Madoff  1   5   6 , Julius Chapiro  7   8
Affiliations

Tumor response assessment in hepatocellular carcinoma treated with immunotherapy: imaging biomarkers for clinical decision-making

Rabea Sobirey et al. Eur Radiol. 2025 Jan.

Abstract

Objective: To compare the performance of 1D and 3D tumor response assessment for predicting median overall survival (mOS) in patients who underwent immunotherapy for hepatocellular carcinoma (HCC).

Methods: Patients with HCC who underwent immunotherapy between 2017 and 2023 and received multi-phasic contrast-enhanced MRIs pre- and post-treatment were included in this retrospective study. Tumor response was measured using 1D, RECIST 1.1, and mRECIST, and 3D, volumetric, and percentage quantitative EASL (vqEASL and %qEASL). Patients were grouped into disease control vs progression and responders vs non-responders. Kaplan-Meier curves analyzed with log-rank tests assessed the predictive value for mOS. Cox regression modeling evaluated the association of clinical baseline parameters with mOS.

Results: This study included 37 patients (mean age, 69.1 years [SD, 8.0]; 33 men). The mOS was 16.9 months. 3D vqEASL and %qEASL successfully stratified patients into disease control and progression (vqEASL: HR 0.21, CI: 0.55-0.08, p < 0.001; %qEASL: HR 0.18, CI: 0.83-0.04, p = 0.013), as well as responder and nonresponder (vqEASL: HR 0.25, CI: 0.08-0.74, p = 0.007; %qEASL: HR 0.17, CI: 0.04-0.72, p = 0.007) for predicting mOS. The 1D criteria, mRECIST stratified into disease control and progression only (HR 0.24, CI: 0.65-0.09, p = 0.002), and RECIST 1.1 showed no predictive value in either stratification. Multivariate Cox regression identified alpha-fetoprotein > 500 ng/mL as a predictor for poor mOS (p = 0.04).

Conclusion: The 3D quantitative enhancement-based response assessment tool qEASL can predict overall survival in patients undergoing immunotherapy for HCC and could identify non-responders.

Clinical relevance statement: Using 3D quantitative enhancement-based tumor response criteria (qEASL), radiologists' predictions of tumor response in patients undergoing immunotherapy for HCC can be further improved.

Key points: MRI-based tumor response criteria predict immunotherapy survival benefits in HCC patients. 3D tumor response assessment methods surpass current evaluation criteria in predicting overall survival during HCC immunotherapy. Enhancement-based 3D tumor response criteria are robust prognosticators of survival for HCC patients on immunotherapy.

Keywords: Hepatocellular carcinoma; Immune checkpoint inhibitors; Magnetic resonance imaging; Treatment outcome.

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Conflict of interest statement

Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is Julius Chapiro. Conflict of interest: M.L. is an employee and stockholder of Visage Imaging, Inc. and is a board member of the Tau Beta Pi engineering honor society. M.S. reports that he is an advisor for ENGITIX. S.S. reports serving as a Consultant for Genentech, QED Therapeutics, Exelixis, AstraZeneca, and Merck. D.C.M. reports consulting fees from Boston Scientific and participation in the data safety monitoring board of Sirtex. J.C. reports institutional grants from NIH, SIO, Guerbet, and Boston Scientific and consulting fees from and participation in data safety or advisory boards of AstraZeneca, Eisai, Bayer, Guerbet, and Genentech. D.C.M., J.D., and J.C. receive grants from the National Institute of Health (NIH/NCI R01 CA206180). The remaining authors declare no conflicts of interest. Statistics and biometry: No complex statistical methods were necessary for this paper. Informed consent: Written informed consent was waived by the Institutional Review Board. Ethical approval: Institutional Review Board approval was obtained. Methodology: This research was a retrospective single-institution study

References

    1. Sung H, Ferlay J, Siegel RL et al (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71:209–249 - DOI - PubMed
    1. El-Serag HB, Rudolph KL (2007) Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology 132:2557–2576 - DOI - PubMed
    1. Dimitroulis D, Damaskos C, Valsami S et al (2017) From diagnosis to treatment of hepatocellular carcinoma: an epidemic problem for both developed and developing world. World J Gastroenterol 23:5282–5294 - DOI - PubMed - PMC
    1. Reig M, Forner A, Rimola J et al (2022) BCLC strategy for prognosis prediction and treatment recommendation: the 2022 update. J Hepatol 76:681–693 - DOI - PubMed
    1. European Association for the Study of the Liver (2018) EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 69:182–236 - DOI

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