Classification Of Liver Cirrhosis Research Articles

Multiscale Feature Fusion Method for Liver Cirrhosis Classification

ABSTRACTLiver cirrhosis is one of the most common liver diseases in the world, posing a threat to people's daily lives. In advanced stages, cirrhosis can lead to severe symptoms and complications, making early detection and treatment crucial. This study aims to address this critical healthcare challenge by improving the accuracy of liver cirrhosis classification using ultrasound imaging, thereby assisting medical professionals in early diagnosis and intervention. This article proposes a new multiscale feature fusion network model (MSFNet), which uses the feature extraction module to capture multiscale features from ultrasound images. This approach enables the neural network to utilize richer information to accurately classify the stage of cirrhosis. In addition, a new loss function is proposed to solve the class imbalance problem in medical datasets, which makes the model pay more attention to the samples that are difficult to classify and improves the performance of the model. The effectiveness of the proposed MSFNet was evaluated using ultrasound images from 61 subjects. Experimental results demonstrate that our method achieves high classification accuracy, with 98.08% on convex array datasets and 97.60% on linear array datasets. Our proposed method can classify early, middle, and late cirrhosis very accurately. It provides valuable insights for the clinical treatment of liver cirrhosis and may be helpful for the rehabilitation of patients.

Clinical classification of liver cirrhosis - a way to plan individual definitive treatment.

Aim: To develop clinical classification of liver cirrhosis, which can aid individualization and planning definitive treatment for this group of patients. Materials and Methods: Computerized search of the literature was performed via PubMed using the following medical subject headings or keywords: "liver", "cirrhosis" and "classification"; or "liver", "cirrhosis" and "complications"; or "liver", "cirrhosis" and "treatment"; or "portal" ", "hypertension" and "complications". Articles were independently evaluated by each author, the etiological, morphological and current clinical classifications of LC were analyzed, their advantages and disadvantages identified, and after discussion classification of LC was developed by consensus. Conclusions: The developed clinical classification of liver cirrhosis will facilitate the planning of therapeutic tactics for each patient, allow to personalize the treatment of patients with this pathology.

The Clinical Value of Thyroid Hormone Levels and Correlation with Severity of Liver Cirrhosis.

Background The aims of this study were to expound the effect of thyroid hormone on the occurrence of liver cirrhosis and the severity classification of liver cirrhosis with meta-analysis. Methods A comprehensive search of PubMed, EMbase, The Cochrane Library, Web of Science, Google Scholar, CNKI, and WanFang Data databases and reference lists of retrieved articles was performed since the inception of each database until September 2021. Two reviewers independently screened literature, extracted data, and assessed the risk of bias by RevMan 5.3 software. In continuous variable analysis, the standardized mean difference (SMD) and 95% confidence interval (95% CI) were calculated through a random-effect model. Results Eighteen case-control studies involving 3336 subjects were included for review. The results of the meta-analysis showed free triiodothyronine (FT3) and free thyroxine (FT4) levels in the liver cirrhosis group were lower than the control group (SMD = −1.29, 95% CI [−1.85, −0.74], P < 0.001), (SMD = −0.61, 95% CI [−0.96, −0.26], P < 0.001), thyroid-stimulating hormone (TSH) levels in liver cirrhosis group were higher than the control group (SMD = 0.34, 95%CI [0.06, 0.63], P < 0.001) and that FT3 levels in Child-Pugh A VS B and Child-Pugh B VS C group were higher than the control group (SMD = 1.08, 95%CI [0.80, 1.37], P = 0.008), (SMD = 0.68, 95%CI [0.38, 0.98], P < 0.001). Conclusions Cirrhosis has decreased FT3 and FT4 levels and increased TSH levels. FT3 levels correlate negatively with the Child-Pugh score, and it is a measure of the severity of liver cirrhosis dysfunction. FT3 serum levels of thyroid hormones are a prognostic marker in liver cirrhosis.

Image Correction Methods for Regions of Interest in Liver Cirrhosis Classification on CNNs.

The average error rate in liver cirrhosis classification on B-mode ultrasound images using the traditional pattern recognition approach is still too high. In order to improve the liver cirrhosis classification performance, image correction methods and a convolution neural network (CNN) approach are focused on. The impact of image correction methods on region of interest (ROI) images that are input into the CNN for the purpose of classifying liver cirrhosis based on data from B-mode ultrasound images is investigated. In this paper, image correction methods based on tone curves are developed. The experimental results show positive benefits from the image correction methods by improving the image quality of ROI images. By enhancing the image contrast of ROI images, the image quality improves and thus the generalization ability of the CNN also improves.

A Meta-Analysis of the Influence of Tumor Necrosis Factor-α-308 Gene Polymorphism on Liver Cirrhosis.

Cirrhosis is an active hepatic inflammation process of the liver considered as the serious phase of different liver injuries. Epidemiological studies have evaluated the possible association between TNF-α-308G/A gene polymorphism and liver cirrhosis. In this study, we have furthered the study to assess the exact association of TNF-α-308G/A gene polymorphism with liver cirrhosis susceptibility by integrating all available data. Eligible case-control studies were carried out from the establishment of the project to September 2021. Published literature from multiple databases was retrieved, collected, and analyzed by two investigators independently. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for every study. Review Manager 5.2 and Stata 15.0 software were used for meta-analysis and stability was assessed by both subgroup analysis and sensitivity analysis. Begg's funnel plot and Egger's regression across the studies were also explored. We examined 22 case-control studies with 2683 cirrhosis patients and 2905 normal controls in four genetic models (GA vs. GG: OR = 0.95, 95%CI: (0.70, 1.30); AA vs. GG: OR = 1.11, 95% CI: (0.66, 1.85), GA + AA vs. GG: OR = 1.00, 95% CI: (0.73, 1.37); AA vs. GA + GG: OR = 1.07, 95%CI: (0.70,1.63)). TNF-α-308G/A gene polymorphism was relatively independent, and the results did not show a significant difference between the two groups. In the subgroup analysis by etiological classification of liver cirrhosis, cirrhosis after HCV infection was positively associated with the risk of TNF-α-308G/A polymorphism (AA vs. GG: OR = 3.02, 95% CI: (1.15, 7.88), AA vs. GA + GG: OR = 2.68, 95% CI: (1.04, 6.95)). The meta-analysis showed TNF-α-308G/A gene polymorphism might not have affected susceptibility for liver cirrhosis. Nevertheless, further and well-designed studies were needed to confirm the findings.

Identification of Molecular Subgroups in Liver Cirrhosis by Gene Expression Profiles

Background: Liver cirrhosis is characterized by high mortality, bringing a serious health and economic burden to the world. The clinical manifestations of liver cirrhosis are complex and heterogeneous. According to subgroup characteristics, identifying cirrhosis has become a challenge. Objectives: The purpose of this study was to evaluate the difference between different subgroups of cirrhosis. The ultimate goal of research on these different phenotypes was to discover groups of patients with unique treatment characteristics, and formulate targeted treatment plans that improve the prognosis of the disease and improve the patients’ quality of life. Methods: We obtained the relevant gene chip by searching the gene expression omnibus (GEO) database. According to the gene expression profile, 79 patients with liver cirrhosis were divided into four subgroups, which showed different expression patterns. Therefore, we used weighted gene coexpression network analysis (WGCNA) to find differences between subgroups. Results: The characteristics of the WGCNA module indicated that subjects in subgroup I might exhibit inflammatory characteristics; subjects in subgroup II might exhibit metabolically active characteristics; arrhythmogenic right ventricular cardiomyopathy and neuroactive ligand-receptive somatic interaction pathways were significantly enriched in subgroup IV. We did not find a significantly upregulated pathway in the third subgroup. Conclusions: In this study, a new type of clinical phenotype classification of liver cirrhosis was derived by consensus clustering. This study found that patients in different subgroups may have unique gene expression patterns. This new classification method helps researchers explore new treatment strategies for cirrhosis based on clinical phenotypic characteristics.

Frequency of severe liver cirrhosis and hepatocellular carcinoma caused by hepatitis B and C in a tertiary care hospital.

Objective: Liver cirrhosis is one of the most widespread diseases in underdeveloped countries. Study Design: Cross Sectional Study. Setting: Nishtar Hospital Multan. Period: January 2020 to March 2020. Material &amp; Methods: Three hundred and ninety seven of admitted patients were included and patients falling in class C of child Turcotte Pugh classification of liver cirrhosis were determined. Prevalence of hepatocellular carcinoma and cause of cirrhosis in these patients was also determined. Statistical Package for Social Sciences (SPSS 23.0) was used for analysis. Results: Out of 397 patients included in the study 25.4 % or 101 had class C cirrhosis, out of these 5.94% or 6 also had hepatocellular carcinoma. With respect to age of initial diagnosis of the illness 25.7% or 26 were in age interval 31-40yrs, 24.8% or 25 in interval 41-50yrs, 20.8% or 21 in interval 51-60 yrs. Hepatitis C (67.3%) comes out to be the commonest of all causes of chronic liver disease, followed by other causes (18.8%), then both hepatitis C and B (7.9%) and hepatitis B alone (5.9%). Conclusion: Our study concluded that approximately 1 in every 4 patients admitted in medical wards of a tertiary care hospital have severe liver cirrhosis caused most commonly by hepatitis C with most common age of presentation being 30-60 years. Approximately 6 out of 100 of these patients also had hepatocellular carcinoma.

Classification of Liver cirrhosis via data mining algorithm: A new tool to detect disease

Liver cirrhosis or hepatic cirrhosis is termed as condition in which the liver of patient not working properly owing to damage by various factors. In a present day, data mining in the field of medical is an important tool to explore the sign patterns in term of medical data sets. The aim of current study is to investigate a method for the classification system of liver cirrhosis in data findings in databases utilizing data mining method which are used in present time. In the data mining system and research work, the Tanagra data mining device, an accurate classifier algorithm and an open source project is used. By using different classification algorithms, we find a pattern which is formed in it. Fischer filtering was good feature in feature selection algorithm. Limited number of attributes in filtering algorithm along with better classification system were chosen and executed. The architecture model flow includes: training dataset, feature relevance analysis, classification process i.e. classification and regression tree, random tree binary logistic regression, support vector machine accuracy analysis. The research work was accomplished on the basis classification algorithms including training and test datsets along with well obtained characterized data. The classification process categorized the liver cirrhosis in dataset and provides better results. The feature relevance analysis displays the different important characteristics which are intended for. The experiment is projected to prove the efficiency of the presentation of numerous classifiers to the liver cirrhosis and dataset used in it. Primary diagnosis of any.

Liver Cirrhosis: Modern Approach to the Problem

Liver Cirrhosis: Modern Approach to the Problem

Classification of Liver Cirrhosis on m-Mode Ultrasound Images by Extended Higher Order Local Autocorrelation Features

Classification of Liver Cirrhosis on m-Mode Ultrasound Images by Extended Higher Order Local Autocorrelation Features

The frequency of complications and the etiology of disease in patients with liver cirrhosis in erzurum.

This study included 100 patients diagnosed with liver cirrhosis who presented at Atatürk University Faculty of Medicine Gastroenterology clinic and polyclinic. The etiology of liver cirrhosis and the incidence of its complications have been investigated. The etiological classification of liver cirrhosis in our patients was as follows: 47 hepatitis B virus hepatitis, 11 hepatitis C virus hepatitis, 5 HBV+HDV hepatitis, 4 Budd Chiari syndrome, 2 chronic alcohol abuse, 2 ischemic heart disease, 1 autoimmune hepatitis, 1 sclerosing cholangitis, 1 hydatid cyst. In 26 patients we could not find any etiological condition. These patients were called cryptogenic cirrhosis patients.When we examined the complications of liver cirrhosis, it appeared that there were ascites in 83 patient. In 56 patients, esophageal variceal bleeding occurred. There was spontaneous bacterial peritonitis in 42 patients. Hepatorenal syndrome occurred in 26 patients. Finally, in 3 patients we detected hepatorenal syndrome. The most common causes in the etiology of liver cirrhosis are viral, especially HBV. Many of the patients were in decompensated phase when diagnosed. We found that there was a close relation between the frequency of complications and mortality in liver cirrhosis.

Identifying Hepatitis B Carriers at Low Risk for Hepatocellular Carcinoma

Identifying Hepatitis B Carriers at Low Risk for Hepatocellular Carcinoma

Spectral CT: Preliminary Studies in the Liver Cirrhosis

ObjectiveTo investigate the value of spectral CT imaging in the diagnosis and classification of liver cirrhosis during the arterial phase (AP) and portal venous phase (PVP).Materials and MethodsThirty-eight patients with liver cirrhosis (Child-Pugh class A/B/C: n = 10/14/14), and 43 patients with healthy livers, participated in this study. The researchers used abdominal spectral CT imaging during AP and PVP. Iodine concentration, derived from the iodine-based material-decomposition image and the iodine concentration ratio (ICratio) between AP and PVP, were obtained. Statistical analyses {two-sample t test, One-factor analysis of variance, and area under the receiver operating characteristic curve (A [z])} were performed.ResultsThe mean normalized iodine concentration (NIC) (0.5 ± 0.12) during PVP in the control group was significantly higher than that in the study group (0.4 ± 0.10 on average, 0.4 ± 0.08 for Class A, 0.4 ± 0.15 for Class B, and 0.4 ± 0.06 for Class C) (All p < 0.05). Within the cirrhotic liver group, the mean NIC for Class C during the AP (0.1 ± 0.05) was significantly higher than NICs for Classes A (0.1 ± 0.06) and B (0.1 ± 0.03) (Both p < 0.05). The ICratio in the study group (0.4 ± 0.15), especially for Class C (0.5 ± 0.14), was higher than that in the control group (0.3 ± 0.15) (p < 0.05).The combination of NIC and ICratio showed high sensitivity and specificity for differentiating healthy liver from cirrhotic liver, especially in Class C cirrhotic liver.ConclusionSpectral CT Provides a quantitative method with which to analyze the cirrhotic liver, and shows the potential value in the classification of liver cirrhosis.

Microvascular head and neck reconstruction in patients with liver cirrhosis

The aim of this retrospective case series was to review the safety, complications, and outcomes of free-tissue transfer in head and neck cancer reconstruction in patients with liver cirrhosis. A retrospective review of all microvascular head and neck reconstruction cases with concomitant liver cirrhosis treated in our institution from 1994 to 2005 was performed. Data collected included patient demographics, etiology, and severity of liver cirrhosis, defect site, choice of free flap, complications, and clinical follow-up. Seven patients were identified. They were all males and underwent microvascular head and neck reconstruction due to ablative cancer surgery. Their Child-Pugh classification of liver cirrhosis was graded as follows: Child A (n = 3); Child B (n = 3); and Child C (n = 1). Eight free flaps were transferred (1 patient received 2), including anterolateral thigh (n = 4); radial forearm (n = 3); and fibula (n = 1). All flaps survived without the need for any microvascular revision procedures. Two patients died within postoperative 30 days due to hepatic decompensation. Other complications included neck hematoma (n = 1), neck wound infection (n = 2), and donor site dehiscence (n = 1). Only 2 patients with Child A cirrhosis remained free from complications and survived more than 1 year after the surgery. Microvascular head and neck reconstruction may be performed in patients with liver cirrhosis with a certain degree of technical success. However, the procedure is associated with significant mortality and morbidity in Child class B and C patients. Therefore, we recommend avoiding free-tissue transfer in patients with head and neck cancer with advanced liver cirrhosis.

Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics.

Liver cirrhosis is a worldwide health problem. Reliable, noninvasive methods for early detection of liver cirrhosis are not available. Using a three-step approach, we classified sera from rats with liver cirrhosis following different treatment insults. The approach consisted of: (i) protein profiling using surface-enhanced laser desorption/ionization (SELDI) technology; (ii) selection of a statistically significant serum biomarker set using machine learning algorithms; and (iii) identification of selected serum biomarkers by peptide sequencing. We generated serum protein profiles from three groups of rats: (i) normal (n=8), (ii) thioacetamide-induced liver cirrhosis (n=22), and (iii) bile duct ligation-induced liver fibrosis (n=5) using a weak cation exchanger surface. Profiling data were further analyzed by a recursive support vector machine algorithm to select a panel of statistically significant biomarkers for class prediction. Sensitivity and specificity of classification using the selected protein marker set were higher than 92%. A consistently down-regulated 3495 Da protein in cirrhosis samples was one of the selected significant biomarkers. This 3495 Da protein was purified on-chip and trypsin digested. Further structural characterization of this biomarkers candidate was done by using cross-platform matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) peptide mass fingerprinting (PMF) and matrix-assisted laser desorption/ionization time of flight/time of flight (MALDI-TOF/TOF) tandem mass spectrometry (MS/MS). Combined data from PMF and MS/MS spectra of two tryptic peptides suggested that this 3495 Da protein shared homology to a histidine-rich glycoprotein. These results demonstrated a novel approach to discovery of new biomarkers for early detection of liver cirrhosis and classification of liver diseases.

Improvement of prognostic power of the Child–Pugh classification of liver cirrhosis by hyaluronan

Background/Aims : Modifications of the Child–Pugh classification of liver cirrhosis by incorporation of hyaluronan were tested to improve the prognostic power for long term evaluation of liver cirrhosis in 126 patients observed over a period of 10 years. Methods : Serum concentrations of HA were determined at study entry. Statistical analysis included Kaplan–Meier life tables and stepwise multivariant Cox-regression analysis for each parameter of Child–Pugh classification and hyaluronan. Prognostic models were developed by exchanging prothrombin time, albumin and encephalopathy by HA in different combinations. Results : Based on a good single correlation between hyaluronan (0.62) and clinical course ( P<0.01) we conclude that models with hyaluronan instead of albumin or encephalopathy and with or without shifted threshold values of bilirubin and albumin are superior for the prediction of the long term prognosis. In Cox-regression analysis, apart from hyaluronan and bilirubin, no other parameters contributed to an improvement. Conclusions : We conclude that a modification of the Child–Pugh classification of liver cirrhosis by inclusion of HA significantly improves the predictive power of CP, especially in alcoholic etiology. A prospective validation of the newly defined scores needs to be done in the future.

Quantitative morphology of human cirrhotic livers. Part II: The statistically adequate morphological classification of liver cirrhosis. Multivariate analysis from quantified data of form.

In a previous report, we developed methods by which to quantify various patterns of cirrhosis. A set of parameters were used: (i) the mean nodular radius; (ii) the coarseness; (iii) the mean septal thickness; and (iv) the degree of nodular separation. This was applied to 70 cirrhotic livers in an attempt to establish a reproducible classification, and the data were subjected to four-dimensional cluster analysis (Ward method) using a mainframe computer. Five clusters appeared: cluster A, fine nodules, thin septa; cluster B, coarse nodules, relatively thin septa; cluster C, fine nodules, thick septa; cluster D, extremely coarse nodules; and cluster E, coarse nodules, thin septa and incomplete nodulation. Of these, cluster A was considered to correspond to the nutritional type of Gall, cluster B to posthepatitic type (Nagayo's Type B), cluster C to postnecrotic type (Nagayo's Type A) and cluster E to the subtype of posthepatitic cirrhosis with incomplete nodulation (Miyake's Type BI). Cluster D comprised cases with extremely coarsened nodules. The reproducibility of this clustering was fully ensured by linear discriminant analysis. Another discriminant analysis, the canonical, allowed us to visualize the separation of clusters in a two-dimensional (2-D) scatter diagram. We thus managed to establish a most adequate classification from a geometric and statistical point of view.

Classification of liver cirrhosis based on parenchymal echo patterns and its clinical usefulness for diagnosis of liver cirrhosis

Classification of liver cirrhosis based on parenchymal echo patterns and its clinical usefulness for diagnosis of liver cirrhosis

Morphological classification of liver cirrhosis based upon measurement of per cent of interstitial tissue in liver biopsy specimens.

Per cent of interstitial tissue was measured in liver biopsy specimens of 62 patients with liver cirrhosis. The frequency curve of the per cent of interstitial tissue showed two peaks in 10-19 per cent and in 40-49 per cent, a dell being observed at 30 per cent. Therefore, liver cirrhosis could be classified into two groups, i. e., the group with less than 30 per cent of interstitial tissue and the group with 30 per cent or more of interstitial tissue. Edema, liver enlargement, abnormalities in thymol flocculation test, in cephalin cholesterol flocculation test, and in serum γ-globulin concentration, and deformity of the hepatic veins in hepatic venograms were all significantly more frequently observed in the group with 30 per cent or more of interstitial tissue than in the group with less than 30 per cent of interstitial tissue. There was significant correlation between the per cent of interstitial tissue and the per cent of intrahepatic shunt.

HISTOMETRICAL STUDIES OF LIVER CIRRHOSIS BY MATHEMATICAL TREATMENTS OF LINEAR INTERCEPTS ON A SMALL NUMBER OF RANDOM HISTOLOGICAL SECTIONS.

Cirrhotic nodules were assumed to be a mixture of ellipsoids of different sizes and eccentricities, and mathematical derivations were discussed to estimate the distribution, the mean and the standard deviation of their sizes with only a small number of random histological sections. Logarithms of the largest axes of nodules approximately formed a normal distribution. With intermediate results, the total nodule volume in an unit volume of the liver and the mean thickness of internodular septa could be estimated. None of the above estimates from 87 autopsy cases of Laonnec's cirrhosis of various types revealed discon-tinuity in its frequency distribution. Consequently, a classification of liver cirrhosis based on the difference of the above quantities was regarded to be an unsuccessful attempt. Characterization of individual cirrhotic livers with the above estimates was proposed instead of “classification”, to ensure unbiased correlations of anatomical properties to other quantities of clinical, functional and etiological implications.