Evidence map›Paper›PMID 42016198›Full record

ArticleBioactive materials2026

Charge Au@Pt NPs combined with 3D STS-Net for adaptive and sensitized radiotherapy of hepatocellular carcinoma: Synergistic enhancement of therapeutic gain across physical and biological dimensions.

Ji-Gang Piao, Liting Chen, Weiyi Cheng, Lijuan Shen, Wenfan Deng, Yuan Yang, Yicun Li, Wenhao Lin, Jianjun Lai

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Article in Bioactive materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Ji-Gang PiaoSchool of Pharmaceutical Sciences, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 310008, China.
Liting ChenDepartment of Oncology, Zhejiang Hospital, Hangzhou, 310012, China.
Weiyi ChengSchool of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310051, China.
Lijuan ShenDepartment of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, 310008, China.
Wenfan DengDepartment of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, 310008, China.
Yuan YangDepartment of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, 310008, China.
Yicun LiDepartment of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, 310008, China.
Wenhao LinDepartment of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, 310008, China.
Jianjun LaiDepartment of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, 310008, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The therapeutic gain ratio (TGR) of radiotherapy for hepatocellular carcinoma (HCC) remains limited by two major barriers: insufficient precision in adaptive radiotherapy (ART) on the physical dimension and the lack of effective radiosensitization on the biological dimension. Although advances have been made separately in accurate dose delivery and tumor-sensitizing strategies, no approach has yet integrated both dimensions to achieve a coordinated improvement in TGR, representing a critical gap in current practice. In this study, we propose an integrated physical-biological strategy that combines nanomaterials with artificial intelligence (AI). We first constructed charge-engineered gold-platinum nanoparticles that respond to the acidic tumor microenvironment and enable prolonged, high-contrast computed tomography imaging of HCC. These enhanced images were then used to develop the first Transformer-convolutional neural network hybrid model (3D STS-Net) tailored for this scenario, enabling high-accuracy three-dimensional segmentation of small HCC for image-guided adaptive radiotherapy. In parallel, we systematically evaluated the nanoparticles' radiosensitizing effects in vitro and in vivo. The nanoparticles provided stable imaging enhancement for up to 120 h and markedly improved tumor-liver contrast. The 3D STS-Net achieved high segmentation accuracy, supporting more precise contouring for HCC ART. Moreover, the nanoparticles significantly increased radiation-induced reactive oxygen species and enhanced tumor control in animal models. Together, these findings demonstrate that the proposed strategy simultaneously strengthens radiotherapy performance in both physical and biological dimensions, leading to a coordinated improvement in TGR. This integrated "nanomaterial-AI" framework offers a systematic and generalizable approach for enhancing radiotherapy effectiveness in HCC.

Indexed as

Adaptive radiotherapyHepatocellular carcinomaNano-imagingRadiosensitizationTumor automatic segmentation

Identifiers

PMID42016198
PMCPMC13094426

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.