ArticleBMC cancer2024
Radiomics model based on contrast-enhanced computed tomography imaging for early recurrence monitoring after radical resection of AFP-negative hepatocellular carcinoma.
Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence for the prediction of posthepatectomy recurrence in hepatocellular carcinoma: a systematic review and meta-analysis.Annals of medicine · 2025Pooled it
- AI-Driven Predictive Models of Early Recurrence of HCC After Surgical Resection: A Systematic Review.Cancers · 2026Review
- Development of a CT radiomics and clinical feature combined model for predicting early recurrence of surgical resected hepatocellular carcinoma.Scientific reports · 2026Article
- Pre-treatment CEMRI habitat radiomics and deep learning for noninvasive prediction of the VETC pattern in hepatocellular carcinoma: an exploratory radiogenomic analysis.Frontiers in oncology · 2026Article
- Multiparametric dual-energy computed tomography radiomics for predicting microvascular invasion in hepatocellular carcinoma.BMC medical imaging · 2025Article
- A novel nomogram based on machine learning predicting overall survival for hepatocellular carcinoma patients with dynamic α‑fetoprotein level changes after local resection.Oncology letters · 2025Article
- Alpha-fetoprotein as a prognostic factor in alpha-fetoprotein-negative hepatocellular carcinoma - integration into post-resection prognostic nomograms.Contemporary oncology (Poznan, Poland) · 2025Article
- Multi-parameter MRI-based model for the prediction of early recurrence of hepatitis B-associated hepatocellular carcinoma after microwave ablation.Frontiers in cellular and infection microbiology · 2025Article
- Harnessing big data for precision medicine: radiomics based application of nanomaterials in MRI enhancement and multimodal therapy of hepatocellular carcinoma.Frontiers in immunology · 2025Review
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9 authors.
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Abstract
backgroundAlthough radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. Emerging radiomics can reveal subtle structural changes in tumors by analyzing preoperative contrast-enhanced computer tomography (CECT) imaging data and may provide new ways to predict early recurrence (recurrence within 2 years) in AFP-negative HCC. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC. PATIENTS AND
methodsPatients with AFP-negative HCC who underwent radical resection were included in this study. A computerized tool was used to extract radiomic features from the tumor region of interest (ROI), select the best radiographic features associated with patient's postoperative recurrence, and use them to construct the radiomics score (RadScore), which was then combined with clinical and follow-up information to comprehensively evaluate the reliability of the model.
resultsA total of 148 patients with AFP-negative HCC were enrolled in this study, and 1,977 radiographic features were extracted from CECT, 2 of which were the features most associated with recurrence in AFP-negative HCC. They had good predictive ability in both the training and validation cohorts, with an area under the ROC curve (AUC) of 0.709 and 0.764, respectively. Tumor number, microvascular invasion (MVI), AGPR and radiomic features were independent risk factors for early postoperative recurrence in patients with AFP-negative HCC. The AUCs of the integrated model in the training and validation cohorts were 0.793 and 0.791, respectively. The integrated model possessed the clinical value of predicting early postoperative recurrence in patients with AFP-negative HCC according to decision curve analysis, which allowed the classification of patients into subgroups of high-risk and low-risk for early recurrence.
conclusionThe nomogram constructed by combining clinical and imaging features has favorable performance in predicting the probability of early postoperative recurrence in AFP-negative HCC patients, which can help optimize the therapeutic decision-making and prognostic assessment of AFP-negative HCC patients.
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