Malnutrition and sarcopenia are common complications of liver cirrhosis. This study compares the performance of different nutritional assessment techniques in detecting malnourished patients. Data from 156 patients with liver cirrhosis were collected. We assessed the nutritional status of these patients according to: Subjective Global Assessment (SGA); Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT), skinfold thickness (TSF), mid-upper arm circumference (MUAC), mid-upper arm muscle circumference (MUMC), handgrip strength (HGS), body mass index (BMI), and skeletal muscle index (SMI) evaluated by Contrast-Enhanced Computed Tomography (CT). According to EWGSOP2 criteria, combining low HGS with low SMI, the prevalence of malnutrition/sarcopenia was 60.2%. RFH-NPT, MUAC, MAMC, and HGS were excellent tests for detecting malnourished patients. Combining RFH-NPT with MUAC or MUMC increased diagnosis accuracy, AUC = 0.89, p < 0.0001. Age, Child-Pugh class C, albumin level, vitamin D deficiency, male gender, and alcoholic etiology were significantly associated with malnutrition. In conclusion, the prevalence of malnutrition among patients with cirrhosis was relatively high. Our study highlights the potential use of a simpler and inexpensive alternative that can be used as a valuable tool in daily practice, the combination between RFH-NPT and MUAC.

Aims: to evaluate the accuracy of LR-5 category from the latest Contrast-Enhanced Ultrasound algorithm (ACR CEUS LI-RADSv 2017) for the noninvasive diagnosis of hepatocellular carcinoma (HCC), in a real-life cohort of high-risk patients. Material and methods: We retrospectively re-analysed the CEUS studies of 464 focal liver lesions (FLL) in 382 patients at high-risk for HCC (liver cirrhosis of any aetiology, chronic B or C hepatitis with severe fibrosis) using the ACR CEUS LI-RADSv 2017 algorithm. CEUS LI-RADS categories used for the diagnosis of HCC were: CEUS LR-5 (definitely HCC) and CEUS LR-TIV (HCC with macrovascular invasion). Contrast-enhanced CT, contrast-enhanced MRI, or histology were used as diagnostic reference methods to evaluate the CEUS LI-RADS classification of the 464 lesions. Results: According to the reference method, the 464 lesions were classified as follows: 359 HCCs, 68 non-HCC-non-malignant lesions and 37 non-HCC malignant lesions. The diagnostic accuracy of LR-5 category for the diagnosis of hepatocellular carcinoma was 76.9%. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 71.9%, 94.3 %, 97.7% and 49.5%, respectively. Conclusions: LR-5 category from ACR CEUS LI-RADSv 2017 algorithm, has good sensitivity, excellent specificity, and PPV for the diagnosis of HCC. The HCC rate increases from LR-3 to LR-5.

Sarcopenia and sarcopenic obesity are frequent complications of cirrhosis, and the dietary patterns of patients with these diseases significantly impact the development of both conditions. This study aims to evaluate the adequacy of the dietary intake of patients with liver cirrhosis. A total of 201 patients with liver cirrhosis were included in this analysis. We evaluated the nutritional status of the patients as stated by EWGSOP2 criteria. Subjects were divided into three groups: non-sarcopenic, sarcopenic, and with sarcopenic obesity. We conducted a dietary assessment three times over nonconsecutive 24 h periods within a month. According to EWGSOP2 criteria, combining low handgrip strength with low skeletal muscle index, the prevalence of sarcopenia was 57.2%. Sarcopenic obesity was found in 25.3% of patients. In the sarcopenic group of patients, the energy intake was lower than the current recommendations. Regarding protein intake, the consumption was relatively low in both sarcopenia and sarcopenic obesity samples of patients (0.85 g/kg body weight and 0.77 g/kg BW, p < 0.0001). Patients had a median of 2–3 eating episodes daily, and they often missed late-evening snacks. In conclusion, diet quality in cirrhotic patients was relatively poor, and energy and protein intakes were lower than suggested.

Background: Multiparametric ultrasound (MPUS) is a concept whereby the examiner is encouraged to use the latest features of an ultrasound machine. The aim of this study was to reanalyze inconclusive focal liver lesions (FLLs) that had been analyzed via contrast enhanced ultrasound (CEUS) using the MPUS approach with the help of a tree-based decision classifier. Materials and methods: We retrospectively analyzed FLLs that were inconclusive upon CEUS examination in our department, focusing our attention on samples taken over a period of two years (2017−2018). MPUS reanalysis followed a three-step algorithm, taking into account the liver stiffness measurement (LSM), time–intensity curve analysis (TIC), and parametric imaging (PI). After processing all steps of the algorithm, a binary decision tree classifier (BDTC) was used to achieve a software-assisted decision. Results: Area was the only TIC-CEUS parameter that showed a significant difference between malign and benign lesions with a cutoff of >−19.3 dB for washout phenomena (AUROC = 0.58, Se = 74.0%, Sp = 45.7%). Using the binary decision tree classifier (BDTC) algorithm, we correctly classified 71 out of 91 lesions according to their malignant or benignant status, with an accuracy of 78.0% (sensitivity = 62%, specificity = 45%, and precision = 80%). Conclusions: By reevaluating inconclusive FLLs that had been analyzed via CEUS using MPUS, we managed to determine that 78% of the lesions were malignant and, in 28% of them, we established the lesion type.

Liver biopsy is the gold standard method for staging liver fibrosis, but it is an invasive procedure that is associated with some complications. There are also non-invasive techniques for assessing liver fibrosis, such as elastography and biological tests, but these techniques can fail in detection or generate false measurements depending on the subject’s condition. This study aimed to determine whether liver fibrosis can be evaluated using contrast-enhanced ultrasonography with arrival time parametric imaging using the ultrasound machine’s parametric image software, the method being called (CEUS-PAT). CEUS-PAT was performed on each subject using SonoVue as a contrast agent, and images showing liver parenchyma and the right kidney on a single screen were used for analysis in parametric imaging, which was performed using the proprietary software of the ultrasound system. The ratio between the kidney and liver arrival times was calculated. The study included 64 predominantly male (56.3%) subjects, 37 cirrhotic patients, and 27 healthy volunteers, with a mean age of 58.98 ± 8.90 years. Significant differences were found between the liver cirrhosis and healthy groups regarding CEUS-PAT, 0.83 ± 0.09 vs. 0.49 ± 0.11, p < 0.0001. The correlation between CEUS-PAT and VCTE was r = 0.81. The optimal cut-off value for detecting liver cirrhosis was >0.7, with an AUC of 0.98, p < 0.001, Se = 89.19%, Sp = 100%, PPV = 100%, and NPV = 87.1%. We demonstrate that CEUS-PAT achieves excellent performance in diagnosing liver cirrhosis and is a fast method for diagnosing liver cirrhosis that can even be applied in situations where the use of other methods is excluded.

This study aims to evaluate the performance of contrast-enhanced ultrasound (CEUS) and biological tests to characterize portal vein thrombosis (PVT). We retrospectively analyzed 101 patients with PVT, liver cirrhosis, and hepatocellular carcinoma (HCC). In all patients, demographic, biologic, imaging, and endoscopic data were collected. All patients underwent CEUS and a second line imaging technique (CE-CT/MRI) to characterize PVT. Of the 101 cirrhotic subjects, 77 (76.2%) had HCC. CEUS had 98.6% sensitivity (Se) and 89.3% specificity (Sp) for the characterization of PVT type. A significant correlation was found between alpha-fetoprotein (AFP) levels and the PVT characterization at CEUS (r = 0.28, p = 0.0098) and CT/MRI (r = 0.3, p = 0.0057). Using the AFP rule-out cutoff values for HCC (AFP < 20 ng/dL), 78% of the subjects were correctly classified as having benign PVT, while 100% of the subjects were correctly classified as tumor-in-vein (TIV) when the rule-in cutoff value was used (AFP ≥ 200 ng/dL). Using multiple regression analysis, we obtained a score for classifying PVT. The PVT score performed better than CEUS (AUC—0.99 vs. AUC—0.93, p = 0.025) or AFP serum levels (AUC—0.99 vs. AUC—0.96, p = 0.047) for characterizing PVT. In conclusion, CEUS is a sensitive method for the characterization of PVT. The PVT score had the highest performance for PVT characterization.