The impact of COVID-19 on the diagnosis and treatment of HCC: analysis of a nationwide registry for advanced liver diseases (REAL).

The number of cancer cases diagnosed during the coronavirus disease 2019 (COVID-19) pandemic has decreased. This study investigated the impact of the pandemic on the clinical practice of hepatocellular carcinoma (HCC) using a novel nationwide REgistry for Advanced Liver diseases (REAL) in Japan. We retrieved data of patients initially diagnosed with HCC between January 2018 and December 2021. We adopted tumor size as the primary outcome measure and compared it between the pre-COVID-19 (2018 and 2019) and COVID-19 eras (2020 and 2021). We analyzed 13,777 patients initially diagnosed with HCC (8074 in the pre-COVID-19 era and 5703 in the COVID-19 era). The size of the maximal intrahepatic tumor did not change between the two periods (mean [SD] = 4.3 [3.6] cm and 4.4 [3.6] cm), whereas the proportion of patients with a single tumor increased slightly from 72.0 to 74.3%. HCC was diagnosed at a similar Barcelona Clinic Liver Cancer stage. However, the proportion of patients treated with systemic therapy has increased from 5.4 to 8.9%. The proportion of patients with a non-viral etiology significantly increased from 55.3 to 60.4%. Although the tumor size was significantly different among the etiologies, the subgroup analysis showed that the tumor size did not change after stratification by etiology. In conclusion, the characteristics of initially diagnosed HCC remained unchanged during the COVID-19 pandemic in Japan, regardless of differences in etiology. A robust surveillance system should be established particularly for non-B, non-C etiology to detect HCC in earlier stages.

Development of a transformer model for predicting the prognosis of patients with hepatocellular carcinoma after radiofrequency ablation.

INTRODUCTION: Radiofrequency ablation (RFA) is a widely accepted, minimally invasive treatment modality for patients with hepatocellular carcinoma (HCC). Accurate prognosis prediction is important to identify patients at high risk for cancer progression/recurrence after RFA. Recently, state-of-the-art transformer models showing improved performance over existing deep learning-based models have been developed in several fields. This study was aimed at developing and validating a transformer model to predict the overall survival in HCC patients with treated by RFA. METHODS: We enrolled a total of 1778 treatment-naïve HCC patients treated by RFA as the first-line treatment. We developed a transformer-based machine learning model to predict the overall survival in the HCC patients treated by RFA and compared its predictive performance with that of a deep learning-based model. Model performance was evaluated by determining the Harrel's c-index and validated externally by the split-sample method. RESULTS: The Harrel's c-index of the transformer-based model was 0.69, indicating its better discrimination performance than that of the deep learning model (Harrel's c-index, 0.60) in the external validation cohort. The transformer model showed a high discriminative ability for stratifying the external validation cohort into two or three different risk groups (p < 0.001 for both risk groupings). The model also enabled output of a personalized cumulative recurrence prediction curve for each patient. CONCLUSIONS: We developed a novel transformer model for personalized prediction of the overall survival in HCC patients after RFA treatment. The current model may offer a personalized survival prediction schema for patients with HCC undergoing RFA treatment.

Proton Beam Therapy versus Radiofrequency Ablation for Patients with Treatment-Naïve Single Hepatocellular Carcinoma: A Propensity Score Analysis.

Introduction: Proton beam therapy (PBT) is known to be an effective locoregional treatment for hepatocellular carcinoma (HCC). However, few comparative studies in treatment-naïve cases have been reported. The aim of this study was to compare the survival outcomes of PBT with those of radiofrequency ablation (RFA) in patients with treatment-naïve solitary HCC. Methods: Ninety-five consecutive patients with treatment-naïve HCC, a single nodule measuring ≤5 cm in diameter, and a Child-Pugh score of ≤8 who were treated with PBT at the University of Tsukuba Hospital between 2001 and 2013 were enrolled in the study. In addition, 836 patients with treatment-naïve HCC treated by RFA at the University of Tokyo Hospital during the same period were analyzed as controls. Recurrence-free survival (RFS) and overall survival (OS) were compared in 83 patient pairs after propensity score matching. Results: The 1-year, 3-year, and 5-year RFS rates were 86.6%, 49.5%, and 35.5%, respectively, in the PBT group and 59.5%, 34.0%, and 20.9% in the RFA group (p = 0.058); the respective OS rates were 97.6%, 77.8%, and 57.1% in the PBT group and 95.1%, 81.7%, and 67.7% in the RFA group (p = 0.16). Regarding adverse effects, no grade 3 or higher adverse events were noted in the PBT; however, two grade 3 adverse events occurred within 30 days of RFA in the RFA group: one hemoperitoneum and one hemothorax. Discussion: After propensity score matching, PBT showed no significant difference in RFS and OS compared to RFA. PBT can be an alternative for patients with solitary treatment-naïve HCC.

Machine learning for individualized prediction of hepatocellular carcinoma development after the eradication of hepatitis C virus with antivirals.

BACKGROUND AND AIMS: Accurate risk stratification for hepatocellular carcinoma (HCC) after achieving a sustained viral response (SVR) is necessary for optimal surveillance. We aimed to develop and validate a machine learning (ML) model to predict the risk of HCC after achieving an SVR in individual patients. METHODS: In this multicenter cohort study, 1742 patients with chronic hepatitis C who achieved an SVR were enrolled. Five ML models were developed including DeepSurv, gradient boosting survival analysis, random survival forest (RSF), survival support vector machine, and a conventional Cox proportional hazard model. Model performance was evaluated using Harrel' c-index and was externally validated in an independent cohort (977 patients). RESULTS: During the mean observation period of 5.4 years, 122 patients developed HCC (83 in the derivation cohort and 39 in the external validation cohort). The RSF model showed the best discrimination ability using seven parameters at the achievement of an SVR with a c-index of 0.839 in the external validation cohort and a high discriminative ability when the patients were categorized into three risk groups (P <0.001). Furthermore, this RSF model enabled the generation of an individualized predictive curve for HCC occurrence for each patient with an app available online. CONCLUSIONS: We developed and externally validated an RSF model with good predictive performance for the risk of HCC after an SVR. The application of this novel model is available on the website. This model could provide the data to consider an effective surveillance method. Further studies are needed to make recommendations for surveillance policies tailored to the medical situation in each country. IMPACT AND IMPLICATIONS: A novel prediction model for HCC occurrence in patients after hepatitis C virus eradication was developed using machine learning algorithms. This model, using seven commonly measured parameters, has been shown to have a good predictive ability for HCC development and could provide a personalized surveillance system.

Clinical utility of postablation liver tumor biopsy and possibility of gene mutation analysis.

AIM: Radiofrequency ablation (RFA) is regarded as a first-line treatment for hepatocellular carcinoma (HCC) at an early stage. When treated with RFA, tumor biopsy may not be performed due to the risk of neoplastic seeding. We previously revealed that the risk of neoplastic seeding is significantly reduced by performing biopsies after RFA. In this study, we investigated the possibility of pathological evaluation and gene mutation analysis of post-RFA tumor specimens. METHODS: Radiofrequency ablation was undertaken on diethylnitrosamine-induced mouse liver tumor, and tumor samples with or without RFA were subjected to whole exome sequencing. Post-RFA human liver tumor specimens were used for detection of TERT promoter mutations and pathological assessment. RESULTS: The average somatic mutation rate, sites of mutation, and small indels and base transition patterns were comparable between the nontreated and post-RFA tumors. We identified 684 sites of nonsynonymous somatic substitutions in the nontreated tumor and 704 sites of nonsynonymous somatic substitutions in the post-RFA tumor, with approximately 85% in common. In the human post-RFA samples, the TERT promoter mutations were successfully detected in 40% of the cases. Pathological evaluation was possible with post-RFA specimens, and in one case, the diagnosis of adenocarcinoma was made. CONCLUSION: Our findings suggest that post-RFA liver tumor biopsy is a useful and safe method for obtaining tumor samples that can be used for gene mutation analysis and for pathological assessment.

Treatment and outcome of hepatorenal syndrome in Japan: a retrospective cohort study using a national inpatient database.

BACKGROUND: Hepatorenal syndrome (HRS) is a life-threatening complication of end-stage liver disease. This study aimed to clarify the status of HRS in Japan by analyzing the Japanese Diagnosis Procedure Combination database. METHODS: Patients hospitalized for cirrhosis and HRS from July 2010 to March 2019 were sampled. They were divided into two groups according to their prognosis upon discharge: the transplant-free survival group and the death or liver transplantation group. The two groups' baseline patient characteristics and treatments were compared. RESULTS: The mean age of the 1,412 participants was 67.3 years (standard deviation: 12.3 years), and 65.4% were male. The Child-Pugh grades was B and C in 18.8% and 81.2%, respectively. Hepatocellular carcinoma was present in 27.1% of the patients, and the proportion of spontaneous bacterial peritonitis was 2.3%. Albumin, noradrenaline, and dopamine were administered to 57.9%, 8.0%, and 14.9% of the patients, respectively; 7.0% of the patients underwent renal replacement therapy; and 5.0% were admitted to the intensive care unit. Intravenous antibiotics were administered to 30.8% of the patients. A total of 925 patients (65.5%) died or underwent liver transplantation. In addition to a higher proportion of patients with poor baseline liver function, the death or liver transplantation group included more males, patients with hepatocellular carcinoma, and those with spontaneous bacterial peritonitis. CONCLUSIONS: HRS in Japan has a high mortality rate. Albumin was administered to over 50% of participants. Although noradrenaline is recommended in Japanese clinical guidelines, dopamine was more frequently used as a vasoconstrictor in clinical practice.

Impact of a Novel Digital Therapeutics System on Nonalcoholic Steatohepatitis: The NASH App Clinical Trial.

INTRODUCTION: Management of nonalcoholic steatohepatitis (NASH) is a currently unmet clinical need. Digital therapeutics (DTx) is an emerging class of medicine that delivers evidence-based therapeutic interventions. This study was aimed at investigating the efficacy of DTx in patients with NASH. METHODS: We conducted a multicenter, single-arm, 48-week trial in 19 patients with biopsy-confirmed NASH. All patients received a DTx intervention with a newly developed smartphone application. The primary endpoint was change in the nonalcoholic fatty liver disease activity score (NAS) without worsening of liver fibrosis. The secondary endpoints included improvement of the NAS by ≥2 points without worsening of liver fibrosis, change in the body weight, and regression of fibrosis. RESULTS: After the 48-week DTx intervention, improvement of the NAS was observed in 68.4% (13/19) of patients. The mean change in the NAS from baseline to the end of the intervention was -2.05 ± 1.96 ( P < 0.001 when compared with the threshold of -0.7). A decrease in the NAS by ≥ 2 points was achieved in 11 (57.9%). The average weight loss at the end of the intervention was 8.3% ( P < 0.001). Reduction of the fibrosis stage was observed in 58.3% when the analysis was limited to patients with stage F2/3 fibrosis. There were no serious adverse events that could be considered as being related to the DTx intervention. DISCUSSION: DTx for NASH was found to be highly efficacious and well-tolerated. Further evaluation of the DTx intervention for NASH in a phase 3 trial is warranted.

Current status of primary liver cancer and decompensated cirrhosis in Japan: launch of a nationwide registry for advanced liver diseases (REAL).

BACKGROUND: We developed a nationwide database that stores data of patients with primary liver cancer (PLC) and decompensated cirrhosis (DC) on an admission basis. METHODS: A database was constructed using the National Clinical Database, a nationwide registry platform for various diseases in Japan. Mutual data exchange was possible with the Nationwide Follow-up Survey of Primary Liver Cancer in Japan by the Liver Cancer Study Group of Japan. The stored data on the admission of patients with PLC, DC, or both, included treatment details as well as patient characteristics. RESULTS: A total of 37,705 admissions (29,489 PLC, 10,077 DC, and 1862 for both) in 21,376 patients from 224 hospitals were analyzed. The proportions of patients with hepatitis B, hepatitis C, and non-viral etiology were 11.9%, 36.2%, and 42.6%, respectively, in PLC, and 7.5%, 23.8%, and 55.0%, respectively, in DC. The mean ages (± standard deviation) on admission with PLC and DC were 73 ± 10 and 68 ± 13 years, respectively. The Barcelona Clinic Liver Cancer (BCLC) stage for PLC was 0, A, B, C, and D in 22.0%, 17.1%, 29.6%, 15.1%, and 5.1%, respectively. Treatment modalities for PLC were resection, ablation, transarterial chemoembolization, and systemic therapy in 18.4%, 22.8%, 33.7%, and 11.4%, respectively. A vasopressin receptor V2 antagonist was used in 38.2% in addition to conventionally used loop diuretics and aldosterone antagonists for DC. CONCLUSIONS: The distribution of treatment options for PLC on admission differed from that of the initial treatment. Newly introduced drugs are widely used in patients with DC.

Improved prognosis of hepatitis C-related hepatocellular carcinoma in the era of direct-acting antivirals.

The prognostic impact of direct-acting antivirals (DAAs) on patients with hepatitis C-related hepatocellular carcinoma (C-HCC) is still unclear. This study aimed to evaluate the prognosis of C-HCC in the DAA era. We enrolled 1237 consecutive patients with treatment-naive C-HCC who underwent radical radiofrequency ablation between 1999 and 2019. We also enrolled 350 patients with nonviral HCC as controls. We divided these patients into three groups according to the year of initial treatment: 1999-2005 (cohort 1), 2006-2013 (cohort 2), and 2014-2019 (cohort 3). The use of antiviral agents and their effect in patients with C-HCC was investigated. Overall survival was evaluated for each cohort using the Kaplan-Meier method and a multivariable Cox proportional hazards regression model. Sustained virologic response (SVR) was achieved in 52 (10%), 157 (26%), and 102 (74%) patients with C-HCC in cohorts 1-3, respectively. The 3- and 5-year survival rates of patients with C-HCC were 82% and 59% in cohort 1; 80% and 64% in cohort 2; and 86% and 78% in cohort 3, respectively (p = 0.003). Multivariable analysis adjusted for age, liver function, and tumor extension showed that the prognosis of C-HCC improved in cohort 3 compared to cohort 1 (adjusted hazard ratio [aHR], 0.49; 95% confidence interval [CI], 0.32-0.73; p < 0.001), whereas the prognosis of nonviral HCC did not improve significantly (aHR, 0.96; 95% CI, 0.59-1.57; p = 0.88). The prognosis of C-HCC drastically improved with the advent of DAAs.

Inhibiting SCAP/SREBP exacerbates liver injury and carcinogenesis in murine nonalcoholic steatohepatitis.

Enhanced de novo lipogenesis mediated by sterol regulatory element-binding proteins (SREBPs) is thought to be involved in nonalcoholic steatohepatitis (NASH) pathogenesis. In this study, we assessed the impact of SREBP inhibition on NASH and liver cancer development in murine models. Unexpectedly, SREBP inhibition via deletion of the SREBP cleavage-activating protein (SCAP) in the liver exacerbated liver injury, fibrosis, and carcinogenesis despite markedly reduced hepatic steatosis. These phenotypes were ameliorated by restoring SREBP function. Transcriptome and lipidome analyses revealed that SCAP/SREBP pathway inhibition altered the fatty acid (FA) composition of phosphatidylcholines due to both impaired FA synthesis and disorganized FA incorporation into phosphatidylcholine via lysophosphatidylcholine acyltransferase 3 (LPCAT3) downregulation, which led to endoplasmic reticulum (ER) stress and hepatocyte injury. Supplementation with phosphatidylcholines significantly improved liver injury and ER stress induced by SCAP deletion. The activity of the SCAP/SREBP/LPCAT3 axis was found to be inversely associated with liver fibrosis severity in human NASH. SREBP inhibition also cooperated with impaired autophagy to trigger liver injury. Thus, excessively strong and broad lipogenesis inhibition was counterproductive for NASH therapy; this will have important clinical implications in NASH treatment.

Artificial intelligence (AI) models for the ultrasonographic diagnosis of liver tumors and comparison of diagnostic accuracies between AI and human experts.

BACKGROUND: Ultrasonography (US) is widely used for the diagnosis of liver tumors. However, the accuracy of the diagnosis largely depends on the visual perception of humans. Hence, we aimed to construct artificial intelligence (AI) models for the diagnosis of liver tumors in US. METHODS: We constructed three AI models based on still B-mode images: model-1 using 24,675 images, model-2 using 57,145 images, and model-3 using 70,950 images. A convolutional neural network was used to train the US images. The four-class liver tumor discrimination by AI, namely, cysts, hemangiomas, hepatocellular carcinoma, and metastatic tumors, was examined. The accuracy of the AI diagnosis was evaluated using tenfold cross-validation. The diagnostic performances of the AI models and human experts were also compared using an independent test cohort of video images. RESULTS: The diagnostic accuracies of model-1, model-2, and model-3 in the four tumor types are 86.8%, 91.0%, and 91.1%, whereas those for malignant tumor are 91.3%, 94.3%, and 94.3%, respectively. In the independent comparison of the AIs and physicians, the percentages of correct diagnoses (accuracies) by the AIs are 80.0%, 81.8%, and 89.1% in model-1, model-2, and model-3, respectively. Meanwhile, the median percentages of correct diagnoses are 67.3% (range 63.6%-69.1%) and 47.3% (45.5%-47.3%) by human experts and non-experts, respectively. CONCLUSION: The performance of the AI models surpassed that of human experts in the four-class discrimination and benign and malignant discrimination of liver tumors. Thus, the AI models can help prevent human errors in US diagnosis.

Machine learning-based personalized prediction of gastric cancer incidence using the endoscopic and histologic findings at the initial endoscopy.

BACKGROUND AND AIMS: Accurate risk stratification for gastric cancer is required for optimal endoscopic surveillance in patients with chronic gastritis. We aimed to develop a machine learning (ML) model that incorporates endoscopic and histologic findings for an individualized prediction of gastric cancer incidence. METHODS: We retrospectively evaluated 1099 patients with chronic gastritis who underwent EGD and biopsy sampling of the gastric mucosa. Patients were randomly divided into training and test sets (4:1). We constructed a conventional Cox proportional hazard model and 3 ML models. Baseline characteristics, endoscopic atrophy, and Operative Link on Gastritis-Intestinal Metaplasia Assessment (OLGIM)/Operative Link on Gastritis Assessment (OLGA) stage at initial EGD were comprehensively assessed. Model performance was evaluated using Harrel's c-index. RESULTS: During a mean follow-up of 5.63 years, 94 patients (8.55%) developed gastric cancer. The gradient-boosting decision tree (GBDT) model achieved the best performance (c-index from the test set, .84) and showed high discriminative ability in stratifying the test set into 3 risk categories (P < .001). Age, OLGIM/OLGA stage, endoscopic atrophy, and history of malignant tumors other than gastric cancer were important predictors of gastric cancer incidence in the GBDT model. Furthermore, the proposed GBDT model enabled the generation of a personalized cumulative incidence prediction curve for each patient. CONCLUSIONS: We developed a novel ML model that incorporates endoscopic and histologic findings at initial EGD for personalized risk prediction of gastric cancer. This model may lead to the development of effective and personalized follow-up strategies after initial EGD.

Development of novel deep multimodal representation learning-based model for the differentiation of liver tumors on B-mode ultrasound images.

BACKGROUND AND AIM: Recently, multimodal representation learning for images and other information such as numbers or language has gained much attention. The aim of the current study was to analyze the diagnostic performance of deep multimodal representation model-based integration of tumor image, patient background, and blood biomarkers for the differentiation of liver tumors observed using B-mode ultrasonography (US). METHOD: First, we applied supervised learning with a convolutional neural network (CNN) to 972 liver nodules in the training and development sets to develop a predictive model using segmented B-mode tumor images. Additionally, we also applied a deep multimodal representation model to integrate information about patient background or blood biomarkers to B-mode images. We then investigated the performance of the models in an independent test set of 108 liver nodules. RESULTS: Using only the segmented B-mode images, the diagnostic accuracy and area under the curve (AUC) values were 68.52% and 0.721, respectively. As the information about patient background and blood biomarkers was integrated, the diagnostic performance increased in a stepwise manner. The diagnostic accuracy and AUC value of the multimodal DL model (which integrated B-mode tumor image, patient age, sex, aspartate aminotransferase, alanine aminotransferase, platelet count, and albumin data) reached 96.30% and 0.994, respectively. CONCLUSION: Integration of patient background and blood biomarkers in addition to US image using multimodal representation learning outperformed the CNN model using US images. We expect that the deep multimodal representation model could be a feasible and acceptable tool for the definitive diagnosis of liver tumors using B-mode US.

Infectious complications related to radiofrequency ablation of liver tumors: The role of antibiotics.

BACKGROUND AND AIM: Prophylactic administration of antibiotics within 24 hours of surgery is recommended to reduce the risk of infection. We conducted a prospective study to compare the efficacy of single administration of antibiotics with a historical control of continuous administration of antibiotics for radiofrequency ablation (RFA) of malignant liver tumors. METHODS: Between February 1, 1999 and November 30, 2010, a total of 6,763 RFA treatments were performed in 2,355 patients, using a protocol with continuous administration of prophylactic antibiotics. On December 1, 2010, we began using a revised protocol with a single administration of prophylactic antibiotics, while continuing to use the old continuous administration protocol for patients who declined the new protocol. Interim analysis was performed to assess the safety of the single administration protocol. Thereafter, from April 1, 2012, all patients were treated using the new protocol. Risk factors for infectious complications of RFA were assessed using logistic regression. RESULTS: From December 2010 to March 2012, 766 RFA treatments were performed in 663 patients using the new antibiotic protocol. Infectious complications were observed following 4 of these treatments (0.52%). As the upper limit of the confidence interval (CI) resulting from a one-sided binomial test was exactly the prespecified limit of 1.0%, from April 2012 onwards, we treated all patients using the new protocol with single administration of prophylactic antibiotics. A total of 3,547 RFA treatments were performed using the single administration protocol. Univariable logistic regression indicated that prior transcatheter arterial chemoembolization (TACE) and maximal tumor diameter were significant risk factors for infectious complications (P = 0.04 and P < 0.001, respectively). Multivariable analysis indicated that the adjusted hazard ratio of single vs. continuous administration of antibiotics was 1.20 (95% CI: 0.53-2.75; P = 0.66). CONCLUSIONS: The rate of infectious complications related to RFA was acceptably low. Single administration of prophylactic antibiotics did not significantly increase the rate of infectious complications related to RFA, compared with a more intensive antibiotic protocol.

Impact of Obesity and Heavy Alcohol Consumption on Hepatocellular Carcinoma Development after HCV Eradication with Antivirals.

BACKGROUND AND AIMS: It remains unclear whether obesity increases the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis C who achieved a sustained virological response (SVR) with antiviral therapy. METHODS: In this multicenter cohort study, we enrolled patients with chronic hepatitis C who achieved SVR with interferon (IFN)-based therapy (IFN group) or direct-acting antiviral (DAA) therapy (DAA group) between January 1, 1990, and December 31, 2018. The patients underwent regular surveillance for HCC. Cumulative incidence of and the risk factors for HCC development after SVR were assessed using the Kaplan-Meier method and Cox proportional hazard regression analysis, respectively. RESULTS: Among 2,055 patients (840 in the IFN group and 1,215 in the DAA group), 75 developed HCC (41 in the IFN group and 34 in the DAA group) during the mean observation period of 4.1 years. The incidence rates of HCC at 1, 2, and 3 years were 1.2, 1.9, and 3.0%, respectively. Multivariate analysis revealed that in addition to older age, lower albumin level, lower platelet count, higher alpha-fetoprotein level, and absence of dyslipidemia, obesity (body mass index ≥25 kg/m2) and heavy alcohol consumption (≥60 g/day) were independent risk factors for HCC development, with adjusted hazard ratio (HR) of 2.53 (95% confidence interval [CI]: 1.51-4.25) and 2.56 (95% CI: 1.14-5.75), respectively. The adjusted HR was not significant between the 2 groups (DAA vs. IFN; HR 1.19, 95% CI: 0.61-2.33). CONCLUSIONS: Obesity and heavy alcohol consumption increased the risk of HCC development after SVR.

Artificial intelligence in the diagnosis and management of hepatocellular carcinoma.

Despite recent improvements in therapeutic interventions, hepatocellular carcinoma is still associated with a poor prognosis in patients with an advanced disease at diagnosis. Recently, significant progress has been made in image recognition through advances in the field of artificial intelligence (AI) (or machine learning), especially deep learning. AI is a multidisciplinary field that draws on the fields of computer science and mathematics for developing and implementing computer algorithms capable of maximizing the predictive accuracy from static or dynamic data sources using analytic or probabilistic models. Because of the multifactorial and complex nature of liver diseases, the machine learning approach to integrate multiple factors would appear to be an advantageous approach to improve the likelihood of making a precise diagnosis and predicting the response of treatment and prognosis of liver diseases. In this review, we attempted to summarize the potential use of AI in the diagnosis and management of liver diseases, especially hepatocellular carcinoma.

Radiofrequency Ablation of Liver Tumors in Patients on Antithrombotic Therapy: A Case-Control Analysis of over 10,000 Treatments.

PURPOSE: To evaluate the safety of radiofrequency ablation (RFA) for liver tumors in patients on antithrombotic therapy. MATERIALS AND METHODS: A total of 10,653 consecutive RFA treatments in 3,485 patients with liver tumors were analyzed. The incidence of complications was analyzed on a treatment basis. The treatments for patients who had received antithrombotic medication up to 1 week prior to RFA comprised the antithrombotic therapy group (n = 806), and the others comprised the control group (n = 9,847). Antithrombotic agents were ceased prior to RFA (aspirin, ticlopidine, clopidogrel, and prasugrel ceased 7 days before RFA; cilostazol, 2 or 3 days before RFA; warfarin, 3 days before RFA; and direct oral anticoagulants, 1 day before RFA) and resumed as soon as possible after RFA. Logistic regression analysis was performed to assess whether the antithrombotic therapy increased the risk of hemorrhagic complications. RESULTS: Hemorrhagic complications were diagnosed after 6 treatments (0.7%) in the antithrombotic group and 48 (0.5%) in the control group, and there was no significant difference between the groups (P = .30). In 3 treatments, hemorrhage was diagnosed on or after 8 days of RFA, all of which were in the antithrombotic group. Thrombotic complications were diagnosed after 2 treatments (0.2%) in the antithrombotic group and after 5 (0.1%) in the control group. In a multivariate analysis, receiving antithrombotic therapy was not an independent risk factor for hemorrhagic complications (adjusted odds ratio, 1.52; 95% confidence interval, 0.60-3.87; P = .38). CONCLUSIONS: RFA of liver tumors in patients on antithrombotic therapy is generally safe with appropriate cessation and resumption. Late-onset hemorrhage should be noted in the patients on antithrombotic therapy.

Post-treatment cell-free DNA as a predictive biomarker in molecular-targeted therapy of hepatocellular carcinoma.

BACKGROUND: Liquid biopsies, particularly those involving circulating tumor DNA (ctDNA), are rapidly emerging as a non-invasive alternative to tumor biopsies. However, clinical applications of ctDNA analysis in hepatocellular carcinoma (HCC) have not been fully elucidated. METHODS: We measured the amount of plasma-derived cell-free DNA (cfDNA) in HCC patients before (n = 100) and a few days after treatment (n = 87), including radiofrequency ablation, transarterial chemoembolization, and molecular-targeted agents (MTAs), and prospectively analyzed their associations with clinical parameters and prognosis. TERT promoter mutations in cfDNA were analyzed using droplet digital PCR. Furthermore, we performed a comprehensive mutational analysis of post-treatment cfDNA via targeted ultra-deep sequencing (22,000× coverage) in a panel of 275 cancer-related genes in selected patients. RESULTS: Plasma cfDNA levels increased significantly according to HCC clinical stage, and a high cfDNA level was independently associated with a poor prognosis. TERT promoter mutations were detected in 45% of all cases but were not associated with any clinical characteristics. cfDNA levels increased significantly a few days after treatment, and a greater increase in post-treatment cfDNA levels was associated with a greater therapeutic response to MTAs. The detection rate of TERT mutations increased to 57% using post-treatment cfDNA, suggesting that the ctDNA was enriched. Targeted ultra-deep sequencing using post-treatment cfDNA after administering lenvatinib successfully detected various gene mutations and obtained promising results in lenvatinib-responsive cases. CONCLUSIONS: Post-treatment cfDNA analysis may facilitate the construction of biomarkers for predicting MTA treatment effects.

Analysis of vasovagal syncope in the blood collection room in patients undergoing phlebotomy.

Vasovagal syncope (VVS) is well-known to occur in patients undergoing phlebotomy, however, there have been no large-scale studies of the incidence of VVS in the blood collection room. The aim of our present retrospective study was to investigate the conditions of phlebotomy and determine the incidence/factors predisposing to the development of VVS. We investigated 677,956 phlebotomies performed in outpatients in the blood collection room, to explore factors predisposing to the development of VVS. Our analysis revealed an overall incidence of VVS of 0.004% and suggested that use of more than 5 blood collection tubes and a waiting time of more than 15 min were associated with a higher risk of VVS. The odds ratios of these factors were 8.10 (95% CI 3.76-17.50) and 3.69 (95% CI 0.87-15.60), respectively. This is the large-scale study to analyze factors of the development of VVS in the blood collection room, and according to our results, use of a large number of blood collection tubes and a prolonged waiting time for phlebotomy may be risk factors for the development of VVS.

Improved liver function in patients with cirrhosis due to chronic hepatitis C virus who achieve sustained virologic response is not accompanied by increased liver volume.

BACKGROUND: Serum albumin level improves in patients with chronic hepatitis C virus (HCV) infection who achieve sustained virologic response (SVR) with antiviral therapy. However, it remains controversial whether liver volume increases along with SVR. METHODS: Patients with chronic HCV infection with a history of hepatocellular carcinoma (HCC) who achieved SVR with anti-HCV treatment from March 2003 to November 2017 were enrolled. Patients were followed up with periodic computed tomography (CT) scans to detect HCC recurrence. Patients who underwent treatment for HCC recurrence within 1 year after initiation of anti-HCV treatment were excluded. Laboratory data, including alanine aminotransferase (ALT) level, serum albumin level, and platelet count, were collected at baseline and timepoints after treatment initiation. Liver volume was evaluated at baseline and 24 and 48 weeks after treatment initiation using a CT volume analyzer. A linear mixed-effects model was applied to analyze the chronologic change in liver volume. The correlations between changes in ALT level, albumin level, and liver volume were also evaluated. RESULTS: Of 108 enrolled patients, 78 had cirrhosis. Serum albumin level continued to increase through 48 weeks after treatment initiation. A significant increase in liver volume was observed only in patients without cirrhosis (P = 0.005). There was a significant correlation between ALT level decrease and albumin level increase (P = 0.018). CONCLUSIONS: Improved liver albumin production with SVR was contributed by improved liver cell function rather than increased liver volume in patients with cirrhosis.