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REVIEW article

Front. Oncol.
Sec. Cancer Immunity and Immunotherapy
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1530507

Innovative Applications and Future Trends of Multiparametric PET in the Assessment of Immunotherapy Efficacy

Provisionally accepted
Tingting Qiao Tingting Qiao 1,2*Yanhua Duan Yanhua Duan 1*Zhaoping Cheng Zhaoping Cheng 1*
  • 1 Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University, Jinan 250014, China
  • 2 Shandong First Medical University, Jinan 250117, China

The final, formatted version of the article will be published soon.

    The integration of multiparametric PET (Positron Emission Tomography.) imaging and multi-omics data has demonstrated significant clinical potential in predicting the efficacy of cancer immunotherapies.However, the specific predictive power and underlying mechanisms remain unclear.Objective This review systematically evaluates the application of multiparametric PET imaging metrics (such as SUVmax (Maximum Standardized Uptake Value), MTV (Metabolic Tumor Volume), and TLG (Total Lesion Glycolysis)) in predicting the efficacy of immunotherapies (including PD-1/PD-L1 inhibitors and CAR-T therapy), and explores their potential role in improving predictive accuracy when integrated with multi-omics data.Methods A systematic search of PubMed, Embase, and Web of Science databases identified studies evaluating the efficacy of immunotherapy using longitudinal PET/CT data and RECIST or iRECIST criteria. Only original prospective or retrospective studies were included for analysis. Review articles and meta-analyses were consulted for additional references but excluded from quantitative analysis. Studies lacking standardized efficacy evaluations were excluded to ensure data integrity and quality.Multiparametric PET imaging metrics exhibited high predictive capability for efficacy across various immunotherapies. Metabolic parameters such as SUVmax, MTV, and TLG were significantly correlated with treatment response rates, progression-free survival (PFS), and overall survival (OS). The integration of multi-omics data (including genomics and proteomics) with PET imaging enhanced the sensitivity and accuracy of efficacy prediction. Through integrated analysis, PET metabolic parameters demonstrated potential in predicting immune therapy response patterns, such as pseudo-progression and hyper-progression.The integration of multiparametric PET imaging and multi-omics data holds broad potential for predicting the efficacy of immunotherapies and may support the development of personalized treatment strategies.Future validation using large-scale, multicenter datasets is needed to further advance precision medicine in cancer immunotherapy.

    Keywords: Multiparametric Positron Emission Tomography, Immunotherapy, Tumor Microenvironment, Prognostic prediction, Multi-omics integration

    Received: 19 Nov 2024; Accepted: 23 Dec 2024.

    Copyright: © 2024 Qiao, Duan and Cheng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Tingting Qiao, Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University, Jinan 250014, China
    Yanhua Duan, Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University, Jinan 250014, China
    Zhaoping Cheng, Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University, Jinan 250014, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.