Diagnostic performance of two-dimensional shear wave elastography and attenuation imaging for fibrosis and steatosis assessment in chronic liver disease.

PURPOSE: We investigated the diagnostic performance of two-dimensional shear wave elastography (2D-SWE) and attenuation imaging (ATI) in detecting fibrosis and steatosis in patients with chronic liver disease (CLD), comparing them with established methods. METHODS: In 190 patients with CLD, 2D-SWE and vibration-controlled transient elastography (VCTE) were used for liver stiffness measurement (LSM), and ATI and controlled attenuation parameter (CAP) were used for steatosis quantification. The correlations between these new and established methods were analyzed. RESULTS: Significant correlations were found between 2D-SWE and VCTE (r = 0.78, P < 0.001), and between ATI and CAP (r = 0.70, P < 0.001). Liver stiffness tended to be lower with 2D-SWE compared with that with VCTE, especially in cases with higher LSM, and ATI was less influenced by skin-capsular distance than CAP. Area under the receiver-operating characteristics curves (AUCs) and optimal cut-offs of 2D-SWE for diagnosing liver fibrosis stages F2, F3, and F4 were 0.73 (8.7 kPa), 0.79 (9.1 kPa), and 0.88 (11.6 kPa), respectively. The AUCs and optimal cut-offs of ATI for diagnosing hepatic steatosis grades S1, S2, and S3 were 0.91 (0.66 dB/cm/MHz), 0.80 (0.79 dB/cm/MHz), and 0.88 (0.86 dB/cm/MHz), respectively. A subgroup analysis of 86 patients with metabolic dysfunction-associated steatotic liver disease also demonstrated good performance for 2D-SWE and ATI. CONCLUSION: 2D-SWE and ATI performed comparably with conventional VCTE and CAP in evaluating CLD, offering reliable alternatives for diagnosing liver fibrosis and steatosis.

Integrated policy of medical expense subsidies and clinical registry for patients with liver cancer and decompensated cirrhosis in Japan.

Chronic hepatitis B and C are among the most significant infectious diseases worldwide, and are major risk factors for liver cirrhosis and liver cancer. In Japan, comprehensive hepatitis measures are implemented for the testing and treatment of viral hepatitis, thus enabling the early diagnosis of liver cancer. Nevertheless, patients with decompensated cirrhosis and liver cancer often have unfavorable prognoses and require repetitive long-term treatment. In fiscal year 2018, an integrated policy of medical expense subsidies and research was established in Japan that aimed to alleviate patients' financial burden and launch the clinical registry of advanced liver disease. Over time, updates to the eligibility for the subsidy increased access to patients and has led to an increased number of beneficiaries. Additionally, the accumulation of clinical data in the registry has revealed the treatment choices for these diseases. However, the disparities in efforts across prefectures have also become evident. Raising public awareness of the policy and tightening the multisector healthcare network are keys to success in supporting qualifying patients with advanced liver disease.

Deep learning and digital pathology powers prediction of HCC development in steatotic liver disease.

BACKGROUND AND AIMS: Identifying patients with steatotic liver disease who are at a high risk of developing HCC remains challenging. We present a deep learning (DL) model to predict HCC development using hematoxylin and eosin-stained whole-slide images of biopsy-proven steatotic liver disease. APPROACH AND RESULTS: We included 639 patients who did not develop HCC for ≥7 years after biopsy (non-HCC class) and 46 patients who developed HCC <7 years after biopsy (HCC class). Paired cases of the HCC and non-HCC classes matched by biopsy date and institution were used for training, and the remaining nonpaired cases were used for validation. The DL model was trained using deep convolutional neural networks with 28,000 image tiles cropped from whole-slide images of the paired cases, with an accuracy of 81.0% and an AUC of 0.80 for predicting HCC development. Validation using the nonpaired cases also demonstrated a good accuracy of 82.3% and an AUC of 0.84. These results were comparable to the predictive ability of logistic regression model using fibrosis stage. Notably, the DL model also detected the cases of HCC development in patients with mild fibrosis. The saliency maps generated by the DL model highlighted various pathological features associated with HCC development, including nuclear atypia, hepatocytes with a high nuclear-cytoplasmic ratio, immune cell infiltration, fibrosis, and a lack of large fat droplets. CONCLUSIONS: The ability of the DL model to capture subtle pathological features beyond fibrosis suggests its potential for identifying early signs of hepatocarcinogenesis in patients with steatotic liver disease.

Etiological changes of liver cirrhosis and hepatocellular carcinoma-complicated liver cirrhosis in Japan: Updated nationwide survey from 2018 to 2021.

AIM: A nationwide survey in 2018 showed decreasing involvement of viral hepatitis and increasing involvement of nonviral liver diseases in the etiology of liver cirrhosis (LC) in Japan. An updated nationwide survey was undertaken in 2023. METHODS: Cases of LC diagnosed between 2018 and 2021 were collected from 75 institutions, and the etiologies of LC were investigated. In addition, the data obtained were compared with the results of previous studies. RESULTS: Among the 15 517 cases, alcohol-related liver disease (ALD)-associated LC was the most frequent cause (n = 5,487, 35.4%). Hepatitis C virus-associated LC, nonalcoholic steatohepatitis (NASH)-associated LC, and hepatitis B virus-associated LC were ranked as second, third, and fourth, respectively. In comparison to the previous survey, the ratios of viral hepatitis-associated LC decreased (HBV: from 11.5% to 8.1%; HCV: from 48.2% to 23.4%), while the ratios of ALD-associated LC and NASH-associated LC increased (from 19.9% to 35.4% and from 6.3% to 14.6%, respectively). Regarding cases of LC with hepatocellular carcinoma (n = 5906), HCV-associated LC (1986 cases, 33.6%) was the most frequent cause. Alcohol-related liver disease-associated LC, NASH-associated LC, and HBV-associated LC were the second-, third-, and fourth-ranked causes, respectively. In comparison to the previous survey, as the cause of hepatocellular carcinoma-complicated LC, HCV-associated LC decreased from 60.3% to 33.6%, while the ratios of ALD-associated LC and NASH-associated LC increased from 14.2% to 28.6% and from 4.2% to 14.0%, respectively. CONCLUSIONS: The major causes of LC in Japan are suggested to have been shifting from viral hepatitis to nonviral chronic liver diseases.

Serum MYCN as a predictive biomarker of prognosis and therapeutic response in the prevention of hepatocellular carcinoma recurrence.

The proto-oncogene MYCN expression marked a cancer stem-like cell population in hepatocellular carcinoma (HCC) and served as a therapeutic target of acyclic retinoid (ACR), an orally administered vitamin A derivative that has demonstrated promising efficacy and safety in reducing HCC recurrence. This study investigated the role of MYCN as a predictive biomarker for therapeutic response to ACR and prognosis of HCC. MYCN gene expression in HCC was analyzed in the Cancer Genome Atlas and a Taiwanese cohort (N = 118). Serum MYCN protein levels were assessed in healthy controls (N = 15), patients with HCC (N = 116), pre- and post-surgical patients with HCC (N = 20), and a subset of patients from a phase 3 clinical trial of ACR (N = 68, NCT01640808). The results showed increased MYCN gene expression in HCC tumors, which positively correlated with HCC recurrence in non-cirrhotic or single-tumor patients. Serum MYCN protein levels were higher in patients with HCC, decreased after surgical resection of HCC, and were associated with liver functional reserve and fibrosis markers, as well as long-term HCC prognosis (>4 years). Subgroup analysis of a phase 3 clinical trial of ACR identified serum MYCN as the risk factor most strongly associated with HCC recurrence. Patients with HCC with higher serum MYCN levels after a 4-week treatment of ACR exhibited a significantly higher risk of recurrence (hazard ratio 3.27; p = .022). In conclusion, serum MYCN holds promise for biomarker-based precision medicine for the prevention of HCC, long-term prognosis of early-stage HCC, and identification of high-response subgroups for ACR-based treatment.

Skeletal muscle status and survival among patients with advanced biliary tract cancer.

BACKGROUND: Studies have demonstrated a prognostic role of sarcopenia (i.e., loss of skeletal muscle volume and functionality) in patients with various cancer types. In patients with biliary tract cancer, the quantity and quality of skeletal muscles and their serial changes have not been fully investigated in relation to survival outcomes. METHODS: We identified 386 patients with unresectable or recurrent biliary tract cancer and calculated skeletal muscle index (SMI) and skeletal muscle density (SMD) to estimate muscular quantity and quality, respectively, based on computed tomography images. Using the Cox regression model with adjustment for potential confounders, we calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for progression-free survival (PFS) and overall survival (OS) according to skeletal muscle status and its serial change. RESULTS: Compared to patients without sarcopenia, patients with sarcopenia were associated with shorter PFS (multivariable HR, 1.60; 95% CI, 1.15-2.22; P = 0.005), but not with OS (P = 0.027) at the adjusted α level of 0.013. SMD at baseline was associated with OS (multivariable HR comparing the extreme quartiles, 1.52; 95% CI, 1.07-2.14; Ptrend = 0.012), but not with PFS (Ptrend = 0.13). A reduction in SMI rather than that in SMD was associated with OS. Progressive disease was a risk factor for reductions in SMI and SMD. CONCLUSIONS: Skeletal muscle quantity and quality and their serial changes were associated with survival outcomes in patients with advanced biliary tract cancer. Our data highlight the importance of designing nutritional and physical interventions for improvements in skeletal muscle status.

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.

Increased expression of TNFRSF14 and LIGHT in biliary epithelial cells of patients with primary sclerosing cholangitis.

BACKGROUND AND AIMS: There is a lack of biliary epithelial molecular markers for primary sclerosing cholangitis (PSC). We analyzed candidates from disease susceptibility genes identified in recent genome-wide association studies (GWAS). METHODS: Expression levels of GWAS genes were analyzed in archival liver tissues of patients with PSC and controls. Immunohistochemical analysis was performed to evaluate expression levels in the biliary epithelia of PSC (N = 45) and controls (N = 12). Samples from patients with primary biliary cholangitis (PBC) were used as disease controls (N = 20). RESULTS: Hepatic expression levels of ATXN2, HHEX, PRDX5, MST1, and TNFRSF14 were significantly altered in the PSC group. We focused on the immune-related receptor, TNFRSF14. Immunohistochemistry revealed that high expression of TNFRSF14 in biliary epithelial cells was observed only in the PSC group. In addition, the expression of LIGHT, which encodes a TNFRSF14-activating ligand, was increased in PSC liver. Immunohistochemistry showed that high expression of LIGHT was more common in PSC biliary epithelia (53%) than in the PBC (15%) or control (0%) groups; moreover, it was positively associated with fibrotic progression, although it was not an independent prognostic factor. CONCLUSIONS: TNFRSF14 and LIGHT are promising candidate markers for PSC.

Diagnostic accuracy of AGILE 3+ score for advanced fibrosis in patients with NAFLD: A systematic review and meta-analysis.

BACKGROUND AND AIMS: A simple noninvasive score, the Agile 3+ score, combining liver stiffness measurement, aspartate aminotransferase/alanine aminotransferase ratio, platelet count, diabetes status, sex, and age, has been proposed for the identification of advanced fibrosis in patients with suspected NAFLD. We performed a systematic review and meta-analysis of observational studies to evaluate the diagnostic accuracy of the Agile 3+ score in identifying patients with NAFLD and advanced fibrosis. Recently, an International consensus changed the nomenclature of NAFLD into metabolic-associated steatotic liver disease, so currently, the two terms are interchangeable. APPROACH AND RESULTS: We systematically searched MEDLINE, Ovid Embase, Scopus, and Cochrane Library electronic databases for full-text published articles in any language from the inception to the April 24, 2023. We included original articles reporting data on the sensitivity and specificity of the Agile 3+ score, according to previously described rule-out (≤ 0.451) and rule-in (≥ 0.679) cutoffs. We included 6 observational studies (total of 6955 participants) with biopsy-proven NAFLD [mean age 53 (SE 4) years, mean body mass index 30.9 (SE 2.3) kg/m 2 , 54.0% men, prevalence of diabetes 59.6%]. The pooled prevalence of advanced fibrosis (≥ F3) was 42.1%. By the rule-out cutoff, the overall sensitivity and specificity were 88% (95% CI: 81-93%; I2 = 89.2%) and 65% (95% CI: 54-75%; I2 = 97.6%), respectively. By the rule-in cutoff, the overall sensitivity and specificity were 68% (95% CI: 57-78%; I2 =91.1%) and 87% (95% CI: 80%-92%; I2 =96.7%), respectively. Meta-regression analyses reported that the diagnostic accuracy was partly mediated by age ( p < 0.01), body mass index ( p < 0.01), and, although not statistically significant, sex ( p = 0.06). CONCLUSIONS: Our systematic review and meta-analysis suggests that Agile 3+ accurately diagnoses NAFLD with advanced fibrosis and can identify patients eligible for biopsy and emerging pharmacotherapies.

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.

Posttreatment liver function, but not baseline liver function stratifies patient survival after direct-acting antiviral treatment in decompensated cirrhosis with hepatitis C virus.

BACKGROUND: The prognosis of cirrhosis is clearly stratified by liver function. Although direct-acting antiviral (DAA) has recently been used to eliminate hepatitis C virus (HCV), it is not clear whether liver function stratifies the prognosis of decompensated cirrhotic patients treated with DAA. METHODS: A total of 206 HCV-associated decompensated cirrhotic patients who started DAA from February 2019 to December 2021 at 31 Japanese hospitals were prospectively registered. RESULTS: The median age was 68, and the proportions of patients with Child-Pugh class A (CP-A), CP-B and CP-C were 10% (20/206), 76% (156/206) and 15% (30/206), respectively. Twenty-six patients died, and two patients underwent liver transplantation (LT); the 2- and 3-year LT-free survival rates were 90.0% and 83.2%, respectively. We examined factors associated with LT-free survival using 2 models including either CP class (Model 1) or MELD score (Model 2). In multivariate Cox proportional hazard analysis, CP class at 12 weeks after the end of treatment (EOT) in Model 1 and MELD score at 12 weeks after the EOT in Model 2 were significant factors, while baseline CP class or MELD score was not. Two-year LT-free survival rates were 100%, 91.6% and 60.4% for patients with CP-A, CP-B and CP-C at 12 weeks after the EOT and 95.2% and 69.6% for patients with MELD < 15 and MELD ≥ 15 at 12 weeks after the EOT, respectively. CONCLUSIONS: The prognosis of decompensated cirrhotic patients receiving DAA was stratified by liver function at 12 weeks after the EOT, not by baseline liver function.

Gut insulin action protects from hepatocarcinogenesis in diabetic mice comorbid with nonalcoholic steatohepatitis.

Diabetes is known to increase the risk of nonalcoholic steatohepatitis (NASH) and hepatocellular carcinoma (HCC). Here we treat male STAM (STelic Animal Model) mice, which develop diabetes, NASH and HCC associated with dysbiosis upon low-dose streptozotocin and high-fat diet (HFD), with insulin or phlorizin. Although both treatments ameliorate hyperglycemia and NASH, insulin treatment alone lead to suppression of HCC accompanied by improvement of dysbiosis and restoration of antimicrobial peptide production. There are some similarities in changes of microflora from insulin-treated patients comorbid with diabetes and NASH. Insulin treatment, however, fails to suppress HCC in the male STAM mice lacking insulin receptor specifically in intestinal epithelial cells (ieIRKO), which show dysbiosis and impaired gut barrier function. Furthermore, male ieIRKO mice are prone to develop HCC merely on HFD. These data suggest that impaired gut insulin signaling increases the risk of HCC, which can be countered by restoration of insulin action in diabetes.

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.

Report of the 23rd nationwide follow-up survey of primary liver cancer in Japan (2014-2015).

For the 23rd Nationwide Follow-up Survey of Primary Liver Cancer in Japan, data from 20 889 newly registered patients and 42 274 previously registered follow-up patients were compiled from 516 institutions over a 2-year period from January 1, 2014 to December 31, 2015. Basic statistics compiled for patients newly registered in the 23rd survey were cause of death, past medical history, clinical diagnosis, imaging diagnosis, treatment-related factors, pathological diagnosis, recurrence status, and autopsy findings. Compared with the previous 22nd survey, the population of patients with hepatocellular carcinoma (HCC) was older at the time of clinical diagnosis, had more female patients, had more patients with non-B non-C HCC, had smaller tumor diameter, and was more frequently treated with hepatectomy. Cumulative survival rates were calculated for HCC, intrahepatic cholangiocarcinoma, and combined hepatocellular cholangiocarcinoma (combined HCC and intrahepatic cholangiocarcinoma) by treatment type and background characteristics for patients newly registered between 2004 and 2015 whose final outcome was survival or death. The median overall survival and cumulative survival rates for HCC were calculated by dividing patients by combinations of background factors (number of tumors, tumor diameter, Child-Pugh grade, or albumin-bilirubin grade) and by treatment type (hepatectomy, radiofrequency ablation therapy, transcatheter arterial chemoembolization, hepatic arterial infusion chemotherapy, and systemic therapy). The same values were also calculated according to registration date by dividing patients newly registered between 1978 and 2015 into five time period groups. The data obtained from this nationwide follow-up survey are expected to contribute to advancing clinical research and treatment of primary liver cancer in the world.