IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-59197-0.html
   My bibliography  Save this article

Vision transformer-based model can optimize curative-intent treatment for patients with recurrent hepatocellular carcinoma

Author

Listed:
  • Ke Zhang

    (Zhejiang University School of Medicine)

  • Jinyu Ru

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Wenbo Wang

    (Peking University Cancer Hospital & Institute)

  • Qiuping Ma

    (The Third Affiliated Hospital of Sun Yat-sen University)

  • Fengwei Gao

    (Sichuan University and Collaborative Innovation Center of Biotherapy)

  • Jiapeng Wu

    (Nankai University
    Fifth Medical Center of Chinese PLA General Hospital)

  • Zhifei Dai

    (Peking University)

  • Qingyun Xie

    (Sichuan University and Collaborative Innovation Center of Biotherapy)

  • Lei Mu

    (Zhejiang University School of Medicine)

  • Haoyan Zhang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Jinhua Pan

    (Zhejiang University School of Medicine)

  • Liting Xie

    (Zhejiang University School of Medicine)

  • Qiyu Zhao

    (Zhejiang University School of Medicine)

  • Jie Tian

    (Chinese Academy of Sciences
    Beihang University)

  • Jie Yu

    (Fifth Medical Center of Chinese PLA General Hospital)

  • Ping Liang

    (Fifth Medical Center of Chinese PLA General Hospital)

  • Hong Wu

    (Sichuan University and Collaborative Innovation Center of Biotherapy)

  • Kai Li

    (The Third Affiliated Hospital of Sun Yat-sen University)

  • Wei Yang

    (Peking University Cancer Hospital & Institute)

  • Kun Wang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Tianan Jiang

    (Zhejiang University School of Medicine)

Abstract

The treatment selection for recurrent hepatocellular carcinoma (rHCC) within Milan criteria after hepatectomy remains challenging. Here, we present HEROVision, a Vision Transformer-based model designed for personalized prognosis prediction and treatment optimization between thermal ablation (TA) and surgical resection (SR). HEROVision is trained on initial HCC cohorts (8492 images; 772 patients) and independently tested on rHCC cohorts (9163 images; 833 patients) from five centers. Propensity score matching (PSM) forms two groups of rHCC patients underwent TA and SR to fairly evaluate whether optimized treatment selection by HEROVision have clinical benefits. HEROVision significantly outperforms all six guideline staging systems in the external testing cohort, both in time-dependent concordance index and area under the curve (all P

Suggested Citation

  • Ke Zhang & Jinyu Ru & Wenbo Wang & Qiuping Ma & Fengwei Gao & Jiapeng Wu & Zhifei Dai & Qingyun Xie & Lei Mu & Haoyan Zhang & Jinhua Pan & Liting Xie & Qiyu Zhao & Jie Tian & Jie Yu & Ping Liang & Hon, 2025. "Vision transformer-based model can optimize curative-intent treatment for patients with recurrent hepatocellular carcinoma," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59197-0
    DOI: 10.1038/s41467-025-59197-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-59197-0
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-025-59197-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59197-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.