ArticleEuropean journal of nuclear medicine and molecular imaging2021
An FDG PET/CT metabolic parameter-based nomogram for predicting the early recurrence of hepatocellular carcinoma after liver transplantation.
Article in European journal of nuclear medicine and molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 9 citations in OpenAlex.
- Artificial intelligence-based personalized treatment strategies for unresectable hepatocellular carcinoma: integrating HSP90α for prognosis and survival prediction.NPJ digital medicine · 2025Article
- Preoperative plasma ceramide profiling coupled with machine learning accurately predicts recurrence of hepatocellular carcinoma after resection.Lipids in health and disease · 2025Observational
- Prognostic nomogram for recurrence of hepatocellular carcinoma after liver transplantation for decision making on postoperative adjuvant therapy.Scientific reports · 2025Article
- Development of a nomogram for predicting liver transplantation prognosis in hepatocellular carcinoma.World journal of gastroenterology · 2024Article
- Metabolic Tumor Volume fromCancers · 2023Article
- Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy.European radiology · 2023Article
- Metabolic tumor volume predicts long-term survival after transplantation for unresectable colorectal liver metastases: 15 years of experience from the SECA study.Annals of nuclear medicine · 2022Article
- Predicting the Recurrence of Hepatocellular Carcinoma after Primary Living Donor Liver Transplantation Using Metabolic Parameters Obtained fromJournal of clinical medicine · 2022Article
- CT-Based Radiomics for the Recurrence Prediction of Hepatocellular Carcinoma After Surgical Resection.Journal of hepatocellular carcinoma · 2022Article
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11 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
purposeTo construct an FDG PET/CT metabolic parameter-based model to predict early recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT).
methodsA total of 62 patients with HCC after LT were enrolled with a follow-up period of 1 year. Basic clinical, pathology, and laboratory data, CT features (CPLC), and PET metabolic parameters (CPLCP) were collected for model construction. A CPLC nomogram without metabolic parameters and a CPLCP nomogram with metabolic parameters were established. The net reclassification index (NRI) and integrated discrimination improvement (IDI) of the two models were calculated. The constructed model was compared with Milan criteria and University of California San Francisco (UCSF) criteria. The time-dependent area under the receiver operating characteristic curve (time-AUC) was used to compare the efficiency of the models, and the bootstrap method was used to for verification. Harrell's concordance index (C-index) was used to evaluate the performance of these models. Decision curve analysis (DCA) was used to evaluate the clinical practicability of each model.
resultsThirty out of 62 patients experienced a recurrence during the 1-year follow-up. BCLC stage (P = 0.009), MVI (P = 0.032), AFP (P = 0.004), CTdmax (P = 0.033), and MTV (P = 0.039) were the independent predictors. The CPLC nomogram and the CPLCP nomogram were established. Compared with the CPLC nomogram, the NRI of the CPLCP nomogram increased by 38.98% (95% CI = -18.77-60.43%) and the IDI increased by 4.40% (95% CI = -1.00-16.62%). The AUC value of the CPLCP nomogram was higher than those of Milan criteria and UCSF criteria in the time-AUC curve. Moreover, the CPLCP nomogram had a higher C-index (0.774) than other models. Finally, the DCA curve showed that clinical practicability of the CPLCP nomogram outperformed the Milan criteria and UCSF criteria.
conclusionsThe CPLCP nomogram combining basic clinical data, pathology data, laboratory data, CT features, and PET metabolic parameters showed good efficacy and high clinical practicability in predicting the early recurrence of HCC after LT.
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