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Tumor response assessment in hepatocellular carcinoma treated with immunotherapy: imaging biomarkers for clinical decision-making.
Sobirey, Rabea; Matuschewski, Nickolai; Gross, Moritz; Lin, MingDe; Kao, Tabea; Kasolowsky, Victor; Strazzabosco, Mario; Stein, Stacey; Savic, Lynn Jeanette; Gebauer, Bernhard; Jaffe, Ariel; Duncan, James; Madoff, David C; Chapiro, Julius.
  • Sobirey R; Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
  • Matuschewski N; Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, Berlin, Germany.
  • Gross M; Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
  • Lin M; Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, Berlin, Germany.
  • Kao T; Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
  • Kasolowsky V; Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, Berlin, Germany.
  • Strazzabosco M; Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
  • Stein S; Visage Imaging Inc., San Diego, CA, USA.
  • Savic LJ; Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
  • Gebauer B; Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, Berlin, Germany.
  • Jaffe A; Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
  • Duncan J; Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, Berlin, Germany.
  • Madoff DC; Department of Medicine, Section of Digestive Diseases, Yale University School of Medicine, New Haven, CT, USA.
  • Chapiro J; Department of Medicine, Section of Medical Oncology, Yale University School of Medicine, New Haven, CT, USA.
Eur Radiol ; 2024 Jul 20.
Article en En | MEDLINE | ID: mdl-39033181
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.
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article