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Predicting Survival Using Whole-Liver MRI Radiomics in Patients with Hepatocellular Carcinoma After TACE Refractoriness

  • Clinical Investigation
  • Imaging
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Abstract

Purpose

To develop a model based on whole-liver radiomics features of pre-treatment enhanced MRI for predicting the prognosis of hepatocellular carcinoma (HCC) patients undergoing continued transarterial chemoembolization (TACE) after TACE-resistance.

Materials and Methods

Data from 111 TACE-resistant HCC patients between January 2014 and March 2018 were retrospectively collected. At a ratio of 7:3, patients were randomly assigned to developing and validation cohorts. The whole-liver were manually segmented, and the radiomics signature was extracted. The tumor and liver radiomics score (TLrad-score) was calculated. Models were trained by machine learning algorithms and their predictive efficacies were compared.

Results

Tumor stage, tumor burden, body mass index, alpha-fetoprotein, and vascular invasion were revealed as independent risk factors for survival. The model trained by Random Forest algorithms based on tumor burden, whole-liver radiomics signature, and clinical features had the highest predictive efficacy, with c-index values of 0.85 and 0.80 and areas under the ROC curve of 0.96 and 0.83 in the developing cohort and validation cohort, respectively. In the high-rad-score group (TLrad-score > − 0.34), the median overall survival (mOS) was significantly shorter than in the low-rad-score group (17 m vs. 37 m, p < 0.001). A shorter mOS was observed in patients with high tumor burden compared to those with low tumor burden (14 m vs. 29 m, p = 0.007).

Conclusion

The combined radiomics model from whole-liver signatures may effectively predict survival for HCC patients continuing TACE after TACE refractoriness. The TLrad-score and tumor burden are potential prognostic markers for TACE therapy following TACE-resistance.

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Funding

This study was not supported by any funding.

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Author notes

  1. Chao Yang , Hong cai Yang, and Yin gen Luo have share first authorship.

Authors and Affiliations

  1. Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China

    Chao Yang

  2. 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, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China

    Hong-cai Yang, Yin-gen Luo, Tian-hao Cong, Yu-jie Li & Xiao Li

  3. Huiying Medical Technology (Beijing) Co., Ltd, Beijing, 100192, China

    Fu-tian Li

  4. Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Feng Ye

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Author Fu-tian Li was employed by Huiying Medical Technology (Beijing) Co., Ltd. The remaining authors declare that they have no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required. Ethics committee of National cancer center/Cancer hospital, Chinese academy of medical sciences and Peking union medical college approved this retrospective study (No. 22/448–3650), and waived all informed consents.

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Yang, C., Yang, Hc., Luo, Yg. et al. Predicting Survival Using Whole-Liver MRI Radiomics in Patients with Hepatocellular Carcinoma After TACE Refractoriness. Cardiovasc Intervent Radiol (2024). https://doi.org/10.1007/s00270-024-03730-z

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