Association between the tumor lesion spatial distribution shown in PET/CT and the prognosis of patients with DLBCL receiving CAR T cell therapy

Author:

Dang Xiuyong1,Li Ping1,Zhu Zeyv1,Zhang Min1,Qian Wenbin2ORCID,Liang Ai-Bin3,Zhang Wenjun4

Affiliation:

1. Tongji Hospital, Tongji University School of Medicine

2. Department of Hematology, the Second Affiliated Hospital, School of Medicine, Zhejiang University

3. Tongji University Hospital

4. Tongji Hospital of Tongji University

Abstract

Abstract Chimeric antigen receptor (CAR) T cell therapy improved the prognosis of patients with relapsed/refractory diffuse large B-cell lymphoma (DLBCL) significantly. Bulky disease and disease stage, as qualitative indicators of the spatial characteristic and distribution status of lymphoma lesions, have not been consistently confirmed to be associated with CAR T cell efficacy. Some researchers have proposed the conception of ‘tumor fragmentation’ and ‘lesion dissemination’, and suggested the association between those indicators and the prognosis of patients receiving chemotherapy. In this study, we reviewed and analysed the PET/CT of patients with DLBCL receiving CAR T cell therapy. We qualitatively described the tumor fragmentation using the tumor volume surface ratio (TVSR), which is the ratio of total metabolic tumor volume to total tumor surface, and we semi-quantitatively described the lesion dissemination using dissemination index (DI), which is the count of lesion invasion sites. We found that lower TVSR or lower DI indicates superior progression-free survival (PFS). Taking these two indicators into account at the same time, patients with lower TVSR and DI have the best prognosis, while patients with higher TVSR and DI have the worst. Overall, the tumor lesion spatial distribution shown in PET/CT before CAR T cell infusion are associated with the prognosis of patients with DLBCL receiving CAR T cell therapy. The lower the degree of tumor fragmentation or the higher the degree of lesion dissemination, the worse the prognosis of patients. They can jointly predict the prognosis.

Publisher

Research Square Platform LLC

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