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

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.

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Publication Details

Journal
Bioactive Materials
Published
2026-04-14
DOI
https://doi.org/10.1016/j.bioactmat.2026.04.011
Primary Topic
Nanoplatforms for cancer theranostics
Type
article
Field-Weighted Citation Impact
0.00

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article

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, Y. J. Li, Wenfan Deng, Lijuan Shen et al.
Bioactive Materials
Nanoplatforms for cancer theranostics
article

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, Y. J. Li, Wenfan Deng, Lijuan Shen, Liting Chen, Weiyi Cheng, Yuan Yang, Wenhao Lin, Jianjun Lai
article en

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.

Bioactive MaterialsVol. 63
Zhejiang Chinese Medical University (CN), Zhejiang Hospital (CN), Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN), Hangzhou Cancer Hospital (CN)
Science and Technology Department of Zhejiang Province, Medical Science and Technology Project of Zhejiang Province
Openalex Percentile: Top 20%
Nanoplatforms for cancer theranostics
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