A Clinical-Radiomics Nomogram Predicts Early Tumor Necrosis After Transarterial Chemoembolization for Hepatocellular Carcinoma.
1/5 보강
IntroductionWe introduce a standardized necrosis rate-percent reduction in enhancing tumor diameter normalized by baseline tumor diameter-with a threshold of ≥30%.
- 표본수 (n) 29
- 95% CI 0.768-0.961
APA
Wu XL, Duan BZ, et al. (2026). A Clinical-Radiomics Nomogram Predicts Early Tumor Necrosis After Transarterial Chemoembolization for Hepatocellular Carcinoma.. Technology in cancer research & treatment, 25, 15330338261444986. https://doi.org/10.1177/15330338261444986
MLA
Wu XL, et al.. "A Clinical-Radiomics Nomogram Predicts Early Tumor Necrosis After Transarterial Chemoembolization for Hepatocellular Carcinoma.." Technology in cancer research & treatment, vol. 25, 2026, pp. 15330338261444986.
PMID
41999190 ↗
Abstract 한글 요약
IntroductionWe introduce a standardized necrosis rate-percent reduction in enhancing tumor diameter normalized by baseline tumor diameter-with a threshold of ≥30%. This endpoint is derived from the mRECIST partial response criteria but is normalized to mitigate tumor size-dependent bias. A clinical-radiomics model was developed to assess necrosis in hepatocellular carcinoma (HCC) patients treated with transarterial chemoembolization (TACE).MethodsRetrospectively, 95 HCC patients undergoing TACE were included. Radiomics features were selected via LASSO regression, and clinical variables via logistic regression. Separate radiomics and clinical models were developed, and a combined model was constructed using multivariable logistic regression. The cohort was randomly split into training (70%) and validation (30%) sets, with all preprocessing, feature selection, and model training confined to the training set to prevent data leakage. Model performance was evaluated using discrimination (AUC), calibration, clinical utility (decision curve analysis), and a nomogram.ResultsFrom 1,316 extracted radiomics features, six were retained for Rad-score calculation. Key clinical predictors included hepatitis group, standardized viable tumor ratio, and vascular invasion. The integrated model achieved AUCs of 0.865 (95% CI: 0.768-0.961) in training and 0.853 (95% CI: 0.716-0.990) in validation (n=29), outperforming the clinical model (AUCs: 0.808 (95% CI: 0.695-0.922) and 0.666 (95% CI: 0.465-0.866), respectively). Decision curve analysis and calibration plots confirmed the combined model's superior performance.ConclusionThe radiomics-clinical nomogram, based on a standardized necrosis rate, may enable early prediction of TACE response, offering potential insights for therapeutic decision-making, risk stratification, and liver transplantation management. External validation is warranted before clinical application.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
같은 제1저자의 인용 많은 논문 (2)
🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반
- A Phase I Study of Hydroxychloroquine and Suba-Itraconazole in Men with Biochemical Relapse of Prostate Cancer (HITMAN-PC): Dose Escalation Results.
- Self-management of male urinary symptoms: qualitative findings from a primary care trial.
- Clinical and Liquid Biomarkers of 20-Year Prostate Cancer Risk in Men Aged 45 to 70 Years.
- Diagnostic accuracy of Ga-PSMA PET/CT versus multiparametric MRI for preoperative pelvic invasion in the patients with prostate cancer.
- Clinical Presentation and Outcomes of Patients Undergoing Surgery for Thyroid Cancer.
- Association of patient health education with the postoperative health related quality of life in low- intermediate recurrence risk differentiated thyroid cancer patients.