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Review
. 2025 Oct 31:12:2445-2457.
doi: 10.2147/JHC.S544565. eCollection 2025.

The Role of Nuclear Medicine in Predicting Treatment Response to Immunotherapy and Targeted Therapy in Hepatocellular Carcinoma: A Narrative Review

Haibin Tu  1 , Dingluan Lin  2 , Cailong Chen  2
Affiliations
Review

The Role of Nuclear Medicine in Predicting Treatment Response to Immunotherapy and Targeted Therapy in Hepatocellular Carcinoma: A Narrative Review

Haibin Tu et al. J Hepatocell Carcinoma. .

Abstract

Objective: Targeted and immunotherapy offer new treatment options for patients with advanced hepatocellular carcinoma (HCC); however, the proportion of patients who benefit from these therapies remains limited. Moreover, these treatments can involve complications and add financial burdens to patients, underscoring the need to identify those who are likely to benefit. As an advanced molecular imaging technique, nuclear medicine has the potential to predict treatment efficacy in targeted and immunotherapy, though its predictive accuracy remains uncertain. This narrative review aims to summarize existing research on nuclear medicine applications in this area, providing clinicians with new perspectives.

Materials and methods: We conducted a literature review across multiple medical databases, including PubMed, Embase, Cochrane Library, Web of Science, and Scopus. Relevant studies were identified, organized, and summarized to present findings in the field.

Results: The findings indicate that metrics such as maximum standardized uptake value (SUVmax) and metabolic tumor volume (MTV) correlate with the efficacy of targeted and immunotherapy. Additionally, emerging nuclear medicine techniques have shown promise in predicting PD-L1 expression.

Conclusion: Nuclear medicine holds potential for identifying patients who are likely to benefit from targeted and immunotherapy. However, further refinements are necessary to optimize its predictive capabilities.

Keywords: FDG PET/CT; hepatocellular carcinoma; immunotherapy; nuclear medicine; targeted therapy.

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Conflict of interest statement

The authors declare that there is no conflict of interest regarding the publication of this paper.

Figures

Figure 1
Figure 1
General workflow of nuclear medicine radiomics. Data is extracted from imaging, followed by data processing and construction of a predictive model. Green arrows indicate the sequential flow of steps (eg, from data extraction to processing); cross symbols denote potential decision points or exclusions during model validation.
See this image and copyright information in PMC

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