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Aims: To develop multiple machine learning (ML) models based on the prognostic nutritional index (PNI) and determine the optimal model for predicting long‐term survival outcomes in hepatocellular carcinoma (HCC) patients after local ablation. Methods: From January 2009 to December 2019, we analyzed data from 848 primary HCC patients who underwent local ablation. ML models were constructed and evaluated using the concordance index (C‐index), concordance‐discordance area under curve (C/D AUC), and Brier scores. The optimal ML model was interpreted using the partial dependence plot (PDP) and SHapley Additive exPlanations (SHAP) framework. Additionally, the prognostic performance of our model was compared with other models. Results: Alkaline phosphatase, preoperation alpha‐fetoprotein level, PNI, tumor number, and tumor size were identified as independent prognostic factors for ML model construction. Among the 19 ML algorithms tested, the Aorsf model showed superior performance in both the training cohort (C/D AUC: 0.733; C‐index: 0.736; Brier score: 0.133) and validation cohort (C/D AUC: 0.713; C‐index: 0.793; Brier score: 0.117). The time‐dependent AUC of the Aorsf model for predicting overall survival was as follows: 1‐, 3‐, 5‐, 7‐, and 9‐year were 0.828, 0.765, 0.781, 0.817, and 0.812 in the training cohort, 0.846, 0.859, 0.824, 0.845, and 0.874 in the validation cohort, respectively. The PDP and SHAP algorithms were employed for visual interpretation. Furthermore, time‐AUC and decision curve analysis demonstrated that the Aorsf model provided superior clinical benefits compared to other models. Conclusion: The PNI‐based Aorsf model effectively predicts long‐term survival outcomes after ablation therapy, making a significant contribution to HCC research by improving surveillance, prevention, and treatment strategies. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the treatment outcomes of radiofrequency ablation (RFA) for patients with non-B non-C hepatocellular carcinoma (HCC) (NBNC-HCC) within Milan criteria, as well as to compare them with those of patients with hepatitis B virus (HBV)-related HCC (HBV-HCC). From January 2007 to February 2020, 303 patients with primary HCC who underwent RFA were retrospectively reviewed, including 259 patients with HBV-HCC (HBV-HCC group) and 44 patients with NBNC-HCC (NBNC-HCC group). The clinical characteristics and treatment survivals were evaluated and compared. Moreover, the propensity score matching was used to reduce selection bias. A significantly lower proportion of cirrhosis was observed in the NBNC-HCC group (p =.048). Before propensity score matching, local tumor progression, disease-free survival, and overall survival after RFA showed no significant differences between the two groups (all p >.05). After matching, the overall survival rates in the NBNC-HCC group were significantly better than those in the HBV-HCC group (p =.042). Moreover, for patients with NBNC-HCC, tumor size (hazard ratio = 8.749, 95% confidence interval, 1.599–47.849; p =.012) was the only independent predictor of local tumor progression. Patients with NBNC-HCC within the Milan criteria after RFA had better long-term survival than patients with HBV-HCC, although larger, prospective and multicenter trials are required to validate these results. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop prognostic scores, including the tumor burden score (TBS) and albumin-bilirubin (ALBI) grade, for evaluating the outcomes of hepatocellular carcinoma (HCC) patients after radiofrequency ablation (RFA). This retrospective study enrolled treatment-naïve HCC patients with BCLC 0-A who underwent RFA between January 2009 and December 2019. Regular follow-up was conducted after RFA to determine progression-free survival (PFS) and overall survival (OS). The patients were randomly allocated to the training or validation datasets in a 1:1 ratio. Preoperative prognostic scores were developed based on the results of multivariate analysis. The discriminatory ability of the scores was assessed using time-dependent AUC and compared with other models. Serum alpha-fetoprotein (AFP) level and TBS were identified as independent prognostic factors for PFS, while serum AFP, TBS, and ALBI were identified as independent prognostic factors for OS in HCC patients after RFA. The time-dependent AUCs of the AFP-TBS score for the 1-, 3-, and 5-year PFS were 0.651, 0.667, and 0.620, respectively, in the training set, and 0.657, 0.687, and 0.704, respectively, in the validation set. For the 1-, 3-, and 5-year OS, the time-dependent AUCs were 0.680, 0.712, and 0.666, respectively, in the training set, and 0.712, 0.706 and 0.726 in the validation set for the AFP-TBS-ALBI score (ATA). The C-indices and AIC demonstrated that the scores provided better clinical benefits compared to other models. The ATA/AT score, derived from clinical and objective laboratory variables, can assist in individually predicting the prognosis of HCC patients undergoing curative RFA. [ABSTRACT FROM AUTHOR]

Objectives: To analyze the contrast-enhanced ultrasound (CEUS) characteristics of pediatric patients with focal liver lesions (FLLs) and develop a pediatric liver CEUS criterion to improve the diagnostic performance of CEUS in differentiating pediatric benign and malignant liver lesions. Methods: Between March 2011 and May 2020, patients < 18 years who underwent CEUS were retrospectively evaluated. The CEUS characteristics of FLLs were analyzed. A pediatric liver CEUS criterion categorized as CEUS-1 to CEUS-5 was developed. The diagnostic performance of the criterion (i.e., sensitivity, specificity, PPV, and NPV) was assessed. Chi-square and Mann-Whitney tests were used. Results: After exclusion, the study included 130 lesions (mean diameter, 7.1 cm; range, 0.8–17.0 cm) from 130 patients (mean age, 36.0 months; range, 0.03–204.0 months; 74 boys). Hyperenhancement with washout in patients < 5 years or with early washout (≤ 45 s) was used to predict hepatoblastoma, with a sensitivity and specificity of 90.7% (95% confidence interval [CI]: 77.9%, 97.4%) and 93.6% (95% CI: 84.3%, 98.2%), respectively. Peripheral discontinuous globular hyperenhancement was used to diagnose hemangioma, with a sensitivity and specificity of 84.6% (95% CI: 65.1%, 95.6%) and 100% (95% CI: 95.4%, 100.0%), respectively. The rates of malignancies within the pediatric liver CEUS-1, CEUS-2, CEUS-3, CEUS-4, and CEUS-5 categories were 0.0%, 0.0%, 5.6%, 50.0%, and 96.1%, respectively. Besides, the incidences of hepatoblastoma in pediatric liver CEUS-3, CEUS-4, and CEUS-5 were 5.6%, 16.7%, and 67.5%, respectively. Conclusions: The pediatric liver CEUS criterion is useful in differentiating benign focal liver lesions from malignancies, especially hepatoblastoma from hemangioma. Key Points: • Hyperenhancement with washout in patients

Background: We aimed to evaluate the performance of a deep learning (DL)-based Radiomics strategy designed for analyzing contrast-enhanced ultrasound (CEUS) to not only predict the progression-free survival (PFS) of radiofrequency ablation (RFA) and surgical resection (SR) but also optimize the treatment selection between them for patients with very-early or early-stage hepatocellular carcinoma (HCC). Methods: We retrospectively enrolled 419 patients examined by CEUS within 1 week before receiving RFA or SR (RFA: 214, SR: 205) from January 2008 to 2016. Two Radiomics signatures were constructed by the Radiomics model R-RFA and R-SR to stratify PFS of different treatment groups. Then, RFA and SR nomograms were built by incorporating Radiomics signatures and significant clinical variables to achieve individualized 2-year PFS prediction. Finally, we applied both Radiomics models and both nomograms to each enrolled patient to investigate whether there were space for treatment optimization and how much prognostic improvement could be expected. Results: R-RFA and R-SR showed remarkable discrimination (C-index: 0.726 for RFA, 0.741 for SR). RFA and SR nomograms provided good 2-year PFS prediction accuracy and good calibrations. We identified 17.3% RFA patients and 27.3% SR patients should swap their treatment, so their average probability of 2-year PFS would increase 12 and 15%, respectively. Conclusions: The proposed Radiomics models and nomograms achieved accurate preoperative prediction of PFS for RFA and SR, and they could facilitate the optimized treatment selection between them for patients with very-early or early-stage HCC. [ABSTRACT FROM AUTHOR]