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Computed tomography texture analysis combined with preoperative clinical factors serve as a predictor of early efficacy of transcatheter arterial chemoembolization in hepatocellular carcinoma

  • Special Section: Quantitative Imaging
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Aim

To investigate a pre-therapeutic radiomics nomogram to accurately predict hepatocellular carcinoma (HCC) lesion responses to transcatheter arterial chemoembolization (TACE).

Methods

This retrospective study from January 2012 to 2022 included 92 TACE-treated patients who underwent liver contrast-enhanced CT scan 7 days before treatment, having complete clinical information. We extracted quantitative texture parameters and clinical factors for the largest tumors on the baseline arterial and portal venous phase CT images. An adaptive least absolute shrinkage and selection operator (LASSO)-penalized logistic regression identified independent predictors of tumor activity after TACE.

Results

We fitted an adaptive LASSO regression model to narrow down the texture features and clinical risk factors of the tumor activity status. The selected texture features were used to construct radiomic scores (RadScore), which demonstrated superior performance in predicting tumor activity on both the training (area under the curve (AUC): 0.881, 95% CI: 0.799–0.963) and testing sets (AUC: 0.88, 95% CI: 0.726–1). A logistic regression-based nomogram was developed using RadScore and four selected clinical features. In the testing set, nomogram total points were significant predictors (P = 0.034), and the training set showed no departure from perfect fit (P = 0.833). Internal validation of the nomogram was obtained for the training (AUC: 0.91, 95% CI: 0.837–0.984) and testing (AUC: 0.889, 95% CI: 0.746–1) sets.

Conclusion

We propose a nomogram to predict the early response of HCC lesions to TACE treatment with high accuracy, which may serve as an additional criterion in multidisciplinary decision-making treatment.

Graphical Abstract

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Data availability

The raw data generated in this study are available in the article and its supplementary data files. Derived data supporting the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This work was supported by the Cancer Interventional Research Fund [NO. XM_2018_011_0006_01 and HRIRF-2019-C003] (B.H), the Fund of Health and Family Planning Commission of Jiangsu [No. ZD2021059] (B.H), the fifth round of the “Program 333” of Jiangsu [No. BRA2020198] (B.H), the Young Medical Talents Fund of Health and Family Planning Commission of Nantong (No. QA2020002) (B.H), the National Natural Science Foundation of China [No.81973145, No. 82273735] (F.Y.), and Key R&D Program of Jiangsu Province (Social Development) (BE2020694) (F.Y.).

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Author notes

  1. **ao Le Fan and Yu Hang Wang should be considered equally as first co-authors.

Authors and Affiliations

  1. Department of Radiology, The Second Affiliated Hospital of Nantong University, Nantong, Jiangsu, 226001, People’s Republic of China

    **ao Le Fan, Yu Hao Chen, Bai Xu Chen, Jia Nan Cai, Ju Shun Yang & Bo Sheng He

  2. State Key Laboratory of Natural Medicines, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nan**g, 211198, People’s Republic of China

    Yu Hang Wang & Fang Rong Yan

  3. Université Paris Cité, 75013, Paris, France

    Xu Sun

  4. Clinical Medicine Research Center, The Second Affiliated Hospital of Nantong University, Nantong, Jiangsu, 226001, People’s Republic of China

    Bo Sheng He

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  1. **ao Le Fan
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Contributions

Conceptualization: XF and BH, Methodology: XF, YW, FY, and BH, Software: XF and YW, Formal analysis: XF and YW, Investigation XF, YC, BC, JC, XS, and JY, Writing of the original draft: XF and YW, Funding acquisition: FY and BH, Supervision: BH.

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Correspondence to Bo Sheng He.

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Fan, X.L., Wang, Y.H., Chen, Y.H. et al. Computed tomography texture analysis combined with preoperative clinical factors serve as a predictor of early efficacy of transcatheter arterial chemoembolization in hepatocellular carcinoma. Abdom Radiol 48, 2008–2018 (2023). https://doi.org/10.1007/s00261-023-03868-3

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