PET‐based radiomics signature can predict durable responses to CAR T‐cell therapy in patients with large B‐cell lymphoma

Author:

Ligero Marta1ORCID,Simó Marc2,Carpio Cecilia3ORCID,Iacoboni Gloria3,Balaguer‐Montero Maria1,Navarro Victor4,Sánchez‐Salinas Mario Andres3,Bobillo Sabela3,Marín‐Niebla Ana3,Iraola‐Truchuelo Josu3,Abrisqueta Pau3,Sala‐Llonch Roser56,Bosch Francesc3,Perez‐Lopez Raquel1ORCID,Barba Pere3

Affiliation:

1. Radiomics Group Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron Barcelona Hospital Campus (VHUH) Barcelona Spain

2. Nuclear Medicine Department Vall d'Hebron University Hospital, Autonomous University of Barcelona Barcelona Spain

3. Department of Hematology Experimental Hematology, Vall d’Hebron Institute of Oncology (VHIO), Vall d’Hebron University Hospital Barcelona Barcelona Spain

4. Oncology Data Science (ODysSey) Group Vall d'Hebron Institute of Oncology (VHIO) Barcelona Spain

5. Faculty of Medicine Department of Biomedicine Institute of Neurosciences, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) University of Barcelona Barcelona Spain

6. Centro de Investigación Biomédica en Red de Bioingeniería Biomateriales y Nanomedicina (CIBER‐BBN) Barcelona Spain

Abstract

AbstractChimeric antigen receptor (CAR) T‐cell therapy is a promising treatment option for relapsed or refractory (R/R) large B‐cell lymphoma (LBCL). However, only a subset of patients will present long‐term benefit. In this study, we explored the potential of PET‐based radiomics to predict treatment outcomes with the aim of improving patient selection for CAR T‐cell therapy. We conducted a single‐center study including 93 consecutive R/R LBCL patients who received a CAR T‐cell infusion from 2018 to 2021, split in training set (73 patients) and test set (20 patients). Radiomics features were extracted from baseline PET scans and clinical benefit was defined based on median progression‐free survival (PFS). Cox regression models including the radiomics signature, conventional PET biomarkers and clinical variables were performed for most relevant outcomes. A radiomics signature including 4 PET‐based parameters achieved an AUC = 0.73 for predicting clinical benefit in the test set, outperforming the predictive value of conventional PET biomarkers (total metabolic tumor volume [TMTV]: AUC = 0.66 and maximum standardized uptake value [SUVmax]: AUC = 0.59). A high radiomics score was also associated with longer PFS and OS in the multivariable analysis. In conclusion, the PET‐based radiomics signature predicted efficacy of CAR T‐cell therapy and outperformed conventional PET biomarkers in our cohort of LBCL patients.

Publisher

Wiley

Subject

General Earth and Planetary Sciences

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