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<p>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 <i>P</i> &lt; 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.</p>

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AI in predicting the macrotrabecular-massive subtype of HCC and informing treatment selection: a multi-center and prospective validation study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月11日

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  • Ran Wei,
  • Hanyu Jiang,
  • Mengxuan Zuo,
  • Xuelei He,
  • Fei Cao,
  • Bin Song,
  • Shaolong Li,
  • Wang Li,
  • Wendao Liu,
  • Chengzhi Li,
  • Xin Li,
  • Jianjun Han,
  • Yan Fu,
  • Dong Yan,
  • Weiling He,
  • Feng Duan,
  • Xinya Zhao,
  • Chao An

摘要

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.