ASARA, a prediction model based on Child-Pugh class in hepatocellular carcinoma patients undergoing transarterial chemoembolization.

BACKGROUND: Due to the high heterogeneity among hepatocellular carcinoma (HCC) patients receiving transarterial chemoembolization (TACE), the prognosis of patients varies significantly. The decision-making on the initiation and/or repetition of TACE under different liver functions is a matter of concern in clinical practice. Thus, we aimed to develop a prediction model for TACE candidates using risk stratification based on varied liver function. METHODS: A total of 222 unresectable HCC patients who underwent TACE as their only treatment were included in this study. Cox proportional hazards regression was performed to select the independent risk factors and establish a predictive model for the overall survival (OS). The model was validated in patients with different Child-Pugh class and compared to previous TACE scoring systems. RESULTS: The five independent risk factors, including alpha-fetoprotein (AFP) level, maximal tumor size, the increase of albumin-bilirubin (ALBI) grade score, tumor response, and the increase of aspartate aminotransferase (AST), were used to build a prognostic model (ASARA). In the training and validation cohorts, the OS of patients with ASARA score ≤ 2 was significantly higher than that of patients with ASARA score > 2 (P < 0.001, P = 0.006, respectively). The ASARA model and its modified version "AS(ARA)" can effectively distinguish the OS (P < 0.001, P = 0.004) between patients with Child-Pugh class A and B, and the C-index was 0.687 and 0.706, respectively. For repeated TACE, the ASARA model was superior to Assessment for Retreatment with TACE (ART) and ALBI grade, maximal tumor size, AFP, and tumor response (ASAR) among Child-Pugh class A patients. For the first TACE, the performance of AS(ARA) was better than that of modified hepatoma arterial-embolization prognostic (mHAP), mHAP3, and ASA(R) models among Child-Pugh class B patients. CONCLUSIONS: The ASARA scoring system is valuable in the decision-making of TACE repetition for HCC patients, especially Child-Pugh class A patients. The modified AS(ARA) can be used to screen the ideal candidate for TACE initiation in Child-Pugh class B patients with poor liver function.

Liver cirrhosis in a patient with hepatic hereditary hemorrhagic telangiectasia and Budd-Chiari syndrome: a case report.

BACKGROUND: Hereditary hemorrhagic telangiectasia (HHT) often involves the liver, and belongs to abnormal blood vessel disease. The etiology of Budd-Chiari syndrome (BCS) is not clear, but congenital vascular dysplasia is considered to be one of the causes. Liver cirrhosis due to hepatic hereditary hemorrhagic telangiectasia concomitant with BCS has not been reported. Here, we report a case of cirrhosis with hepatic hereditary hemorrhagic telangiectasia (HHHT) and BCS. CASE PRESENTATION: A 58-year-old woman with hepatic hereditary hemorrhagic telangiectasia showed decompensated liver cirrhosis, and abdominal imaging revealed Budd-Chiari syndrome. Disease has progressed considerably during 2.5 years after hospital discharge despite subsequent transjugular intrahepatic portosystemic shunting (TIPS). One hypothesis that might explain the coexistence of hepatic hereditary hemorrhagic telangiectasia and Budd-Chiari syndrome in this patient is ischemia and thrombosis of hepatic veins. CONCLUSIONS: Further studies are required to evaluate the relationship between HHHT and BCS. Our observations already challenged the TIPS therapeutic strategy in BCS secondary to HHHT patients.

Simplified liver imaging reporting and data system for the diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced magnetic resonance imaging.

BACKGROUND: The liver imaging reporting and data system (LI-RADS) diagnostic table has 15 cells and is too complex. The diagnostic performance of LI-RADS for hepatocellular carcinoma (HCC) is not satisfactory on gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI). AIM: To evaluate the ability of the simplified LI-RADS (sLI-RADS) to diagnose HCC on EOB-MRI. METHODS: A total of 331 patients with 356 hepatic observations were retrospectively analysed. The diagnostic performance of sLI-RADS A-D using a single threshold was evaluated and compared with LI-RADS v2018 to determine the optimal sLI-RADS. The algorithms of sLI-RADS A-D are as follows: The single threshold for sLI-RADS A and B was 10 mm, that is, classified observations ≥ 10mm using an algorithm of 10-19 mm observations (sLI-RADS A) and ≥ 20 mm observations (sLI-RADS B) in the diagnosis table of LI-RADS v2018, respectively, while the classification algorithm remained unchanged for observations < 10 mm; the single threshold for sLI-RADS C and D was 20 mm, that is, for < 20 mm observations, the algorithms for < 10 mm observations (sLI-RADS C)and 10-19 mm observations (sLI-RADS D) were used, respectively, while the algorithm remained unchanged for observations ≥ 20 mm. With hepatobiliary phase (HBP) hypointensity as a major feature (MF), the final sLI-RADS (F-sLI-RADS) was formed according to the optimal sLI-RADS, and its diagnostic performance was evaluated. The times needed to classify the observations according to F-sLI-RADS and LI-RADS v2018 were compared. RESULTS: The optimal sLI-RADS was sLI-RADS D (with a single threshold of 20 mm), because its sensitivity was greater than that of LI-RADS v2018 (89.8% vs 87.0%, P = 0.031), and its specificity was not lower (89.4% vs 90.1%, P > 0.999). With HBP hypointensity as an MF, the sensitivity of F-sLI-RADS was greater than that of LI-RADS v2018 (93.0% vs 87.0%, P < 0.001) and sLI-RADS D (93.0% vs 89.8%, P = 0.016), without a lower specificity (86.5% vs 90.1%, P = 0.062; 86.5% vs 89.4%, P = 0.125). Compared with that of LI-RADS v2018, the time to classify lesions according to F-sLI-RADS was shorter (51 ± 21 s vs 73 ± 24 s, P < 0.001). CONCLUSION: The use of sLI-RADS with HBP hypointensity as an MF may improve the sensitivity of HCC diagnosis and reduce lesion classification time.