Abstract
As a reliable preoperative predictor for microvascular invasion (MVI) and disease-free survival (DFS) is lacking, we developed a radiomics nomogram of [18F]FDG PET/CT to predict MVI status and DFS in patients with very-early- and early-stage (BCLC 0, BCLC A) hepatocellular carcinoma (HCC).
Methods
Patients (N = 80) with BCLC0-A HCC who underwent [18F]FDG PET/CT before surgery were enrolled in this retrospective study and were randomized to a training cohort and a validation cohort. Texture features from patients obtained using Lifex software in the training cohort were subjected to LASSO regression to select the most useful predictive features of MVI and DFS. Then, the radiomics nomogram was constructed using the radiomics signature and clinical features and further validated.
Results
To predict MVI, the [18F]FDG PET/CT radiomics signature consisted of five texture features from the PET and six texture features from CT. The signature was significantly associated with MVI status in the training cohort (P = 0.001). None of the clinical features was independent predictors for MVI status (P > 0.05). The area under the curve value of the M-PET/CT model was 0.891 (95% CI: 0.799–0.984) in the training cohort and showed good discrimination and calibration. To predict DFS, the [18F]FDG PET/CT radiomics nomogram (D-PET/CT model) and a clinicopathologic nomogram were built in the training cohort. The D-PET/CT model, which integrated the D-PET/CT radiomics signature with INR and TB, provided better predictive performance (C-index: 0.831, 95% CI: 0.761–0.900) and larger net benefits than the simple clinical model, as determined by decision curve analyses.
Conclusion
The newly developed [18F]FDG PET/CT radiomics signature was an independent biomarker for the estimation of MVI and DFS in patients with very-early- and early-stage HCC. Moreover, PET/CT nomogram, which incorporated the radiomics signature of [18F]FDG PET/CT and clinical risk factors in patients with very-early- and early-stage HCC, performed better for individualized DFS estimation, which might enable a step forward in precise medicine.
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Data availability
All data were transparent. The data used in the current study are available from the corresponding authors on reasonable request.
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Funding
This study was supported financially by the Science and Technology Program of Guangzhou (201604020094) and the Joint Logistic Support Force Project (CWH17J023).
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Conceptualization: Hubing Wu, Xinlu Wang
Methodology: Youcai Li, Yin Zhang
Formal analysis and investigation: Youcai Li, Yin Zhang, Qi Fang, Xiaoyao Zhang, Peng Hou, Hubing Wu, Xinlu Wang
Writing-original draft preparation: Youcai Li, Yin Zhang
Writing-review and editing: Hubing Wu, Xinlu Wang
Funding acquisition: Xinlu Wang
Supervision: Hubing Wu, Xinlu Wang
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Li, Y., Zhang, Y., Fang, Q. et al. Radiomics analysis of [18F]FDG PET/CT for microvascular invasion and prognosis prediction in very-early- and early-stage hepatocellular carcinoma. Eur J Nucl Med Mol Imaging 48, 2599–2614 (2021). https://doi.org/10.1007/s00259-020-05119-9
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DOI: https://doi.org/10.1007/s00259-020-05119-9