{
  "abstract": "The macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is associated with aggressive biology and poor prognosis. We aimed to develop a CT-based artificial intelligence model (DeepCT-MTM) for the noninvasive prediction of MTM-HCC and investigate its prognostic utilities as well as biological underpinnings. A total of 3118 patients with HCC were included from 20 tertiary-care hospitals. DeepCT-MTM was developed and validated among 832 patients with early-stage HCC undergoing resection (the resection set) and extrapolated to 2286 patients (including 480 prospectively-collected ones) with intermediate/advanced-stage HCC receiving IATs. DeepCT-MTM’s predictive performance for MTM-HCC was evaluated using the area under the receiver operating characteristic curve (AUC), and its prognostic values were investigated for progression-free survival (PFS) and overall survival (OS). In the external test cohort of the resection set, DeepCT-MTM predicted MTM-HCC with an AUC of 0.845. The DeepCT-MTM-predicted high-risk group had worse PFS and OS across all IAT sets (all P < 0.05).. DeepCT-MTM is effective for noninvasively predicting MTM-HCC and may help selecting patients who benefit from a combination of IAT with immunotherapy and anti-angiogenic therapy. However, prospective validations are warranted for these hypothesis-generating findings.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China",
    "Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China",
    "Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China",
    "State Key Laboratory of Oncology in South China, Guangzhou, China",
    "Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China",
    "Shcool of Electronic Information, Nortwest University, Xi’an, China",
    "Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou, China",
    "Department of Interventional Therapy, Guangdong Provincial Hospital of Chinese Medicine and Guangdong Provincial Academy of Chinese Medical Sciences, Guangdong, China",
    "Department of Interventional Radiology and Vascular Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, China",
    "Department of Oncology, Fifth Medical Center of Chinese PLA General Hospital, Beijing, China",
    "Interventional Radiology Department, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai’an, China",
    "Department of Interventional Therapy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China",
    "Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, China",
    "Department of Gastrointestinal Surgery, Xiang’an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China",
    "Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 18,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Ran Wei"
    },
    {
      "affs": [
        1
      ],
      "name": "Hanyu Jiang"
    },
    {
      "affs": [
        2,
        3,
        4
      ],
      "name": "Mengxuan Zuo"
    },
    {
      "affs": [
        5
      ],
      "name": "Xuelei He"
    },
    {
      "affs": [
        2,
        3,
        4
      ],
      "name": "Fei Cao"
    },
    {
      "affs": [
        1
      ],
      "name": "Bin Song"
    },
    {
      "affs": [
        3,
        4,
        6
      ],
      "name": "Shaolong Li"
    },
    {
      "affs": [
        2,
        3,
        4
      ],
      "name": "Wang Li"
    },
    {
      "affs": [
        7
      ],
      "name": "Wendao Liu"
    },
    {
      "affs": [
        8
      ],
      "name": "Chengzhi Li"
    },
    {
      "affs": [
        9
      ],
      "name": "Xin Li"
    },
    {
      "affs": [
        10
      ],
      "name": "Jianjun Han"
    },
    {
      "affs": [
        11
      ],
      "name": "Yan Fu"
    },
    {
      "affs": [
        12
      ],
      "name": "Dong Yan"
    },
    {
      "affs": [
        13
      ],
      "name": "Weiling He"
    },
    {
      "affs": [
        9
      ],
      "name": "Feng Duan"
    },
    {
      "affs": [
        14
      ],
      "name": "Xinya Zhao"
    },
    {
      "affs": [
        2,
        3,
        4,
        9
      ],
      "name": "Chao An"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bjf1z9dzea426.bib",
  "cited_by": 0,
  "doi": "10.1038/s41698-026-01607-7",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13737146/",
  "id": "bjf1z9dzea426",
  "issns": [
    "2397-768X"
  ],
  "landing_url": "https://doi.org/10.1038/s41698-026-01607-7",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Article"
    ],
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      "openalex",
      "2721|Hepatocellular Carcinoma Treatment and Prognosis"
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  "openalex": "W7168039876",
  "pdf_url": null,
  "pmcid": "PMC13737146",
  "pmid": "42436235",
  "published": "2026-07-11",
  "publisher": "Nature Publishing Group",
  "ris": "https://research.draconitic.com/paper/bjf1z9dzea426.ris",
  "sources": [
    {
      "first_seen": "2026-11-09T12:22:26Z",
      "native_id": "PMC13737146",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s41698-026-01607-7"
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  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2721|Hepatocellular Carcinoma Treatment and Prognosis",
      "subfield": "general"
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  ],
  "title": "AI in predicting the macrotrabecular-massive subtype of HCC and informing treatment selection: a multi-center and prospective validation study",
  "title_text": "AI in predicting the macrotrabecular-massive subtype of HCC and informing treatment selection: a multi-center and prospective validation study",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T12:22:26Z",
  "url": "https://research.draconitic.com/paper/bjf1z9dzea426",
  "venue": "NPJ Precision Oncology",
  "versions": []
}