scholarly journals Evaluation of the effectiveness of ultrasound shear elastography and liver steatometry

2020 ◽  
Vol 92 (4) ◽  
pp. 17-22
Author(s):  
O. I. Tarasova ◽  
E. I. Kuhareva ◽  
S. K. Krasnitskaya ◽  
N. V. Mazurchik ◽  
M. Ya. Ngameni ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Comparative Analysis ◽  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Liver Steatosis ◽  
Diagnostic System ◽  
Ultrasound Elastography ◽  
Cross Sectional ◽  
Ultrasonic Diagnostic System ◽  
Diagnostic Criterion

Detection of liver fibrosis and steatosis at early stages is a difficult task for clinical practice, due to the lack of early signs in routine radiation diagnostics. Aim. To evaluate the efficacy of ultrasound shear elastography and ultrasound steatometry of the liver with the use of domestic ultrasonic diagnostic system Angiodin-Sono/N-Ultra. Materials and methods. 264 people held ultrasound elastography and ultrasound steatometry. 38 patients underwent percutaneous puncture liver biopsy and subsequent pathophysiological examination. Results. High correlation of fibrosis obtained at the Angiodin-Sono/N-Ultra and the leading ultrasonic systems with shear elastography was revealed. Cross-sectional comparative analysis of elasticity with the results of liver steatometry was conducted. Conclusions. Results obtained in all groups correlate with the data obtained in studies on Fibroscan. When working with system Angiodin we got a simultaneous comparative analysis of elasticity with the results of liver steatosis. Results appear to be much more stable and compact than those obtained in studies on the Fibroscan. A new diagnostic criterion was revealed the phenomenon of independence of fibrosis and steatosis indices.

Lysosomal Acid Lipase: Can it be a New Non-Invasive Serum Biomarker of Cryptogenic Liver Fibrosis and Cirrhosis?

2018 ◽  
Vol 17 (5) ◽  
pp. 0-10
Author(s):  
Marta Gravito-Soares ◽  
Elisa Gravito-Soares ◽  
Dário Gomes ◽  
Luis Tomé
Keyword(s):  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Liver Steatosis ◽  
Acid Lipase ◽  
Cross Sectional ◽  
Lysosomal Acid ◽  
Significant Fibrosis ◽  
Non Invasive ◽  
Lysosomal Acid Lipase ◽  
Elevated Liver Enzymes

Introduction and aim. The association between lysosomal acid lipase (LAL) activity and liver steatosis or fibrosis is poorly studied. The aim of our study was to determine the predictive power of LAL for cryptogenic liver steatosis and cryptogenic significant fibrosis/ cirrhosis. Material and methods. Cross-sectional observational study of 101 adult patients with unexplained elevated liver enzymes/hepatomegaly with or without dyslipidemia submitted to the determination of LAL activity and LIPA gene (E8SJMC. 894G→A) mutation. Seventy-one patients underwent liver biopsy or FibroScan®. Patients with an identifiable liver dysfunction cause and well-stablished NAFLD/NASH risk factors were excluded. Predictors for liver steatosis, significant fibrosis (≥ F2) or cirrosis (F4) were evaluated. Results. Liver steatosis and fibrosis were mainly assessed by liver biopsy (74.6%; n = 53). Steatosis was present in 62.0% (n = 44), significant fibrosis in 47.9% (n = 34) and cirrhosis in 39.4% (n = 28). The median LAL was 0.36 (0.21-0.46)nmol/spot/h (vs. 0.29 (0.20-0.47); p = 0.558) for liver steatosis, 0.22 (0.11-0.29) nmol/spot/h (vs. 0.40 (0.34-0.51); p < 0.001) for significant fibrosis and 0.21 (0.11-0.27) nmol/spot/h (vs. 0.40 (0.32-0.52); p < 0.001) for cirrhosis. No LIPA gene mutations were found. LAL activity was the strongest predictor of significant fibrosis (AUROC: 0.833; p < 0.001) with a cut-off of 0.265 (sensitivity: 85.9%; specificity: 75.0%) and cirrhosis (AUROC: 0.859; p < 0.001) with a cut-off of 0.235 (sensitivity: 86.2%; specificity: 75.0%), being higher than FIB4, GUCI or APRI. However, LAL activity was not associated with liver steatosis (AUROC: 0.536; p = 0.558). Conclusion. LAL activity can be considered a non-invasive new marker of cryptogenic liver fibrosis with higher accuracy than other known biomarkers. LAL activity < 0.265 nmol/spot/h was strongly associated with cryptogenic significant fibrosis and < 0.235 nmol/spot/h with cryptogenic cirrhosis. LAL activity was not associated with cryptogenic liver steatosis.

Longitudinal Analysis of Serial Liver Biopsies in Chronically Transfused Sickle Cell Disease

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1052-1052
Author(s):  
Jaime L Wolfe ◽  
Robert Anders ◽  
Shirley Reddoch ◽  
Kathleen Schwarz ◽  
William Savage
Keyword(s):  
Sickle Cell Disease ◽  
Liver Fibrosis ◽  
Liver Injury ◽  
Liver Biopsy ◽  
Red Cell ◽  
Cell Disease ◽  
Likelihood Ratios ◽  
Cross Sectional ◽  
Liver Biopsies ◽  
Over Time

Abstract Abstract 1052 Background: Chronic red cell transfusions are commonly used for the treatment and prevention of complications in sickle cell disease (SCD). Liver injury from transfusional iron overload is a recognized morbidity of chronic transfusion therapy, but little is known about the progression of liver injury over time in SCD. Methods: We conducted a retrospective cohort study of all chronically transfused people with SCD who had 2 or more serial liver biopsies at a single academic hospital. Subjects with viral hepatitis were excluded. Serum ferritin, serum ALT, chelation status, and transfusion volumes were extracted from the electronic record and validated against paper records in all subjects. Quantitative liver iron concentration (LIC) was determined at the time of biopsy by inductively coupled plasma-mass spectrometry. Core liver biopsy slides stained for iron and fibrosis were retrieved and scored in a blinded fashion by a hepatopathologist (RA) for total iron score (TIS, Deugnier, 2007) and fibrosis score (Ishak, 1995). Analyses evaluated how liver fibrosis changed over the first 2 biopsies and how changes in biomarkers correlated with changes in fibrosis. Cross sectional analyses assessed the relationship of biomarkers to the presence or absence of fibrosis. Ferritin was analyzed as an average of the 3 closest values ± 6 weeks of liver biopsy. Area under receiver operator characteristic curve (AUC) analysis, likelihood ratios for positive tests (LR+), and summary statistics were calculated using Stata v11.2. Results: 26 people had at least 2 serial core liver biopsies for evaluation (n=70 biopsies total, range 2–7 biopsies per subject). Fibrosis was Ishak grade 0 or 1 in all biopsies. Median age at first biopsy was 13.3 years and median total transfusion duration was 9.4 years. The first 2 biopsies were obtained a median of 2.3 years apart. Evaluation of the first 2 biopsies showed that fibrosis was present in 7/26 initial biopsies and 3/26 second biopsies: fibrosis regressed in 6 subjects, developed in 2 subjects and persisted in 1 subject. Among non-chelated subjects at the time of first biopsy, 2/11 had fibrosis, as compared to 5/15 subjects who had received a mean of 3.7 years of chelation at the time of first biopsy (18% vs 33%, P=0.6). Eleven subjects had 3 or more serial biopsies performed during a median of 9.2 years of chronic transfusion. There was no consistent pattern of fibrosis development, nor was there an apparent association of fibrosis with LIC over time (Figure, asterisks indicate presence of fibrosis). On a cross-sectional basis, ALT performed better than ferritin in classifying fibrosis, with ALT having an AUC of 0.80 (95% CI 0.66–0.94) and ferritin having an AUC of 0.63 (95% CI 0.38–0.87). LIC performed poorly at discriminating fibrosis from no fibrosis (AUC 0.30; 95%CI 0.0–0.82). The highest positive likelihood ratios for fibrosis were for a ferritin cutoff of 5000 ng/mL (LR+ 5.7) and an ALT cutoff of 65 U/L (LR+ 5.2). Longitudinal analysis did not reveal any statistically significant relationship between changes in fibrosis status and changes in ferritin, ALT, LIC, TIS, and cumulative red cell transfusion volume. Summary: Among chronically transfused people with SCD, liver fibrosis most often does not persist or progress, as detected by serial core liver biopsies. On a cross-sectional basis, serum ALT >65 U/L and serum ferritin >5000 ng/mL are cutoffs associated with the highest likelihood of liver fibrosis. Cross-sectional or longitudinal measurements of LIC are not associated with fibrosis. Conclusion: The progression of liver fibrosis is minimal among people with SCD who receive chronic red cell transfusions for up to 17 years. Serum biomarkers may be used to inform when investigations for fibrosis are warranted. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Application of artificial intelligence in chronic liver diseases: a systematic review and meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pakanat Decharatanachart ◽  
Roongruedee Chaiteerakij ◽  
Thodsawit Tiyarattanachai ◽  
Sombat Treeprasertsuk
Keyword(s):  
Artificial Intelligence ◽  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Liver Steatosis ◽  
Diagnostic Tools ◽  
Summary Receiver Operating Characteristic ◽  
Subgroup Analyses ◽  
Sensitivity Specificity

Abstract Background The gold standard for the diagnosis of liver fibrosis and nonalcoholic fatty liver disease (NAFLD) is liver biopsy. Various noninvasive modalities, e.g., ultrasonography, elastography and clinical predictive scores, have been used as alternatives to liver biopsy, with limited performance. Recently, artificial intelligence (AI) models have been developed and integrated into noninvasive diagnostic tools to improve their performance. Methods We systematically searched for studies on AI-assisted diagnosis of liver fibrosis and NAFLD on MEDLINE, Scopus, Web of Science and Google Scholar. The pooled sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic odds ratio (DOR) with their 95% confidence intervals (95% CIs) were calculated using a random effects model. A summary receiver operating characteristic curve and the area under the curve was generated to determine the diagnostic accuracy of the AI-assisted system. Subgroup analyses by diagnostic modalities, population and AI classifiers were performed. Results We included 19 studies reporting the performances of AI-assisted ultrasonography, elastrography, computed tomography, magnetic resonance imaging and clinical parameters for the diagnosis of liver fibrosis and steatosis. For the diagnosis of liver fibrosis, the pooled sensitivity, specificity, PPV, NPV and DOR were 0.78 (0.71–0.85), 0.89 (0.81–0.94), 0.72 (0.58–0.83), 0.92 (0.88–0.94) and 31.58 (11.84–84.25), respectively, for cirrhosis; 0.86 (0.80–0.90), 0.87 (0.80–0.92), 0.85 (0.75–0.91), 0.88 (0.82–0.92) and 37.79 (16.01–89.19), respectively; for advanced fibrosis; and 0.86 (0.78–0.92), 0.81 (0.77–0.84), 0.88 (0.80–0.93), 0.77 (0.58–0.89) and 26.79 (14.47–49.62), respectively, for significant fibrosis. Subgroup analyses showed significant differences in performance for the diagnosis of fibrosis among different modalities. The pooled sensitivity, specificity, PPV, NPV and DOR were 0.97 (0.76–1.00), 0.91 (0.78–0.97), 0.95 (0.87–0.98), 0.93 (0.80–0.98) and 191.52 (38.82–944.81), respectively, for the diagnosis of liver steatosis. Conclusions AI-assisted systems have promising potential for the diagnosis of liver fibrosis and NAFLD. Validations of their performances are warranted before implementing these AI-assisted systems in clinical practice. Trial registration: The protocol was registered with PROSPERO (CRD42020183295).

scholarly journals Enhanced Liver Fibrosis Test as a Reliable Tool for Assessing Fibrosis in Nonalcoholic Fatty Liver Disease in a Clinical Setting

2017 ◽  
Vol 32 (4) ◽  
pp. 397-402 ◽  
Author(s):  
Luca Miele ◽  
Teresa De Michele ◽  
Giuseppe Marrone ◽  
Maria Antonietta Isgrò ◽  
Umberto Basile ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Liver Disease ◽  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Fatty Liver ◽  
Nonalcoholic Fatty Liver Disease ◽  
Predictive Value ◽  
Fatty Liver Disease ◽  
Nonalcoholic Fatty Liver ◽  
Severe Fibrosis

Background Liver fibrosis is the main determinant and predictor of the clinical course of nonalcoholic fatty liver disease (NAFLD). To date, a liver biopsy is still considered the gold standard for staging fibrosis. The aim of this study was to investigate the diagnostic accuracy of the commercial enhanced liver fibrosis (ELF) test manufacturer's cutoff value (≥9.8) in identifying severe fibrosis for adult patients with histologically confirmed NAFLD. Methods We tested the ELF test in a clinical practice, prospective cohort of 82 consecutive patients who consecutively underwent percutaneous liver biopsy. Results All stages of liver fibrosis were represented in our cohort, and severe fibrosis was present in 15 of 82 patients (18.3%). The stage of fibrosis was significantly associated with ELF score (Spearman's rho = 0.483, p<0.001). The commercial ELF test manufacturer's cutoff identified severe fibrosis with good sensitivity (86.7%; 95% confidence interval [95% CI], 0.69-1.04) and high specificity (92.5%; 95% CI, 0.86-0.99), with a positive predictive value of 72% and negative predictive value of 97%. Conclusions Our data could support the use of the ELF test in clinical practice.

scholarly journals Ability of a Combined FIB4/miRNA181a Score to Predict Significant Liver Fibrosis in NAFLD Patients

Biomedicines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1751
Author(s):  
Rodrigo Vieira Costa Lima ◽  
José Tadeu Stefano ◽  
Fernanda de Mello Malta ◽  
João Renato Rebello Pinho ◽  
Flair José Carrilho ◽  
...  
Keyword(s):  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Roc Curve ◽  
Phenotypic Expression ◽  
Multivariate Logistic Regression Analysis ◽  
Serum Levels ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Non Invasive ◽  
Significant Liver Fibrosis

Liver biopsy is the gold standard for assessing fibrosis, but there is a need to seek non-invasive biomarkers for this purpose. The aim of this study was to evaluate the correlation between the serum levels of the microRNAs miR-21, miR-29a, miR-122, miR-155 and miR-181a and the phenotypic expression of NAFLD. A cross-sectional study was carried out on 108 NAFLD patients diagnosed by liver biopsy. FIB-4 and NAFLD fibrosis scores were calculated. The comparison between the distributions of microRNA values according to the presence or absence of histological fibrosis (F2–F4) was performed. A multivariate logistic regression analysis was performed to build a score for predicting fibrosis using FIB-4 and Ln (miR-181a) as independent variables. Only miR-181a showed a statistical difference between patients with significant liver fibrosis (>F2) and those without (F0–F1) (p = 0.017). FIB-4 revealed an AUC on the ROC curve of 0.667 to predict clinically significant fibrosis (F2–F4). When assessed using the score in association with Ln (miR-181a), there was an improvement in the ROC curve, with an AUC of 0.71. miR-181a can be used as a non-invasive method of predicting fibrosis in NAFLD, and an association with FIB-4 has the potential to increase the accuracy of each method alone.

scholarly journals Strain Elastography (SE) for liver fibrosis estimation – which elastic score to calculate?

2016 ◽  
Vol 18 (4) ◽  
pp. 481 ◽  
Author(s):  
Mariana M. Gersak ◽  
Monica Lupșor-Platon ◽  
Radu Badea ◽  
Anca Ciurea ◽  
Sorin M Dudea
Keyword(s):  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Quantitative Method ◽  
Estimation Method ◽  
Daily Practice ◽  
Ultrasound Elastography ◽  
Fibrosis Score ◽  
Strain Elastography ◽  
Non Invasive ◽  
Similar Accuracy

Liver fibrosis scoring by liver biopsy has become a rarity in daily practice mainly because many non-invasive methods with similar accuracy have been developed. Among all ultrasound elastography imaging methods, Strain Elastography (SE) is the most widely available. Although SE is a qualitative and semi-quantitative method, there is reliable applicability for liver fibrosis estimation and multiple ways to transform SE into a quantitative method, in order to obtain a fibrosis score. The aim of this review is to briefly introduce all these methods and to offer support in choosing the best estimation method for liver fibrosis, with SE.

scholarly journals THE DEGREE OF LIVER FIBROSIS ANALYSIS WITH APRI SCORE AND FIB4 INDEX ON PATIENTS WITH NON-ALCOHOLIC FATTY LIVER

2019 ◽  
Vol 26 (2) ◽  
Author(s):  
Gillian Elvira Seipalla ◽  
Nurahmi Nurahmi ◽  
Ibrahim Abd Samad
Keyword(s):  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Fatty Liver ◽  
Matrix Protein ◽  
Pearson Correlation ◽  
Extracellular Matrix Protein ◽  
Cross Sectional ◽  
Alcoholic Fatty Liver ◽  
Gold Standard Method ◽  
Apri Score

Background - Liver fibrosis is the accumulation of extracellular matrix protein (MES) scar tissue after acute or chronic liver injury. Liver biopsy is the gold standard method for evaluating liver fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). This diagnostic method is invasive, painful, and complicated in rare cases, hence the noninvasive method like laboratory tests and radiology had been proposed to assess liver fibrosis in NAFLD and can overcome the limitations of liver biopsy. This method consists of aspartate aminotransferase to platelet index ratio (APRI) and fibrosis 4 (FIB-4).Methods - This retrospective cross sectional study was conducted at Wahidin Sudirohusodo Hospital Makassar by taking a total sample of 63 people from January to June 2018. The correlated variables were made in categorical and numerical using Pearson Correlation statistical test, to assess the compatibility of APRI Score and FIB4 Index with Fibroscan result in patients with NAFLD.Results - A highly significant positive correlation (p <0.001) was found between APRI score and fibroscan (correlation value = 45,8%), APRI Score and FIB4 index (correlation value = 91,8%), FIB4 index and fibroscan (correlation value = 47,6%).Conclusion - APRI Score and FIB-4 Index can be an alternative method instead of liver biopsy to predict the degree of fibrosis in patients with NAFLD.

scholarly journals Application of Artificial Intelligence in Chronic Liver Diseases: A Systematic Review and Meta-analysis

2020 ◽  
Author(s):  
Pakanat Decharatanachart ◽  
Roongruedee Chaiteerakij ◽  
Thodsawit Tiyarattanachai ◽  
Sombat Treeprasertsuk
Keyword(s):  
Artificial Intelligence ◽  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Liver Steatosis ◽  
Diagnostic Tools ◽  
Summary Receiver Operating Characteristic ◽  
Subgroup Analyses ◽  
Sensitivity Specificity

Abstract Background: The gold standard for the diagnosis of liver fibrosis and nonalcoholic fatty liver disease (NAFLD) is liver biopsy. Various noninvasive modalities, e.g., ultrasonography, elastography and clinical predictive scores, have been used as alternatives to liver biopsy, with limited performance. Recently, artificial intelligence (AI) models have been developed and integrated into noninvasive diagnostic tools to improve their performance. Methods: We systematically searched for studies on AI-assisted diagnosis of liver fibrosis and NAFLD on MEDLINE, Scopus, Web of Science and Google Scholar. The pooled sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic odds ratio (DOR) with their 95% confidence intervals (95%CIs) were calculated using a random effects model. A summary receiver operating characteristic curve and the area under the curve was generated to determine the diagnostic accuracy of the AI-assisted system. Subgroup analyses by diagnostic modalities were performed.Results: We included 17 studies reporting the performances of AI-assisted ultrasonography, elastrography, computed tomography (CT), magnetic resonance imaging (MRI) and clinical parameters for the diagnosis of liver fibrosis and steatosis. For the diagnosis of liver fibrosis, the pooled sensitivity, specificity, PPV, NPV and DOR were 0.78 (0.70 – 0.84), 0.88 (0.79 – 0.94), 0.73 (0.58 – 0.84), 0.91 (0.88 – 0.94) and 29.57 (10.65 – 82.10), respectively, for cirrhosis; 0.86 (0.80 – 0.91), 0.87 (0.79 – 0.92), 0.85 (0.74 – 0.91), 0.88 (0.82 – 0.92) and 37.95 (15.52 – 92.77), respectively; for advanced fibrosis; and 0.86 (0.78 – 0.92), 0.81 (0.77 – 0.84), 0.88 (0.80 – 0.93), 0.77 (0.58 – 0.89) and 26.79 (14.47 – 49.62), respectively, for significant fibrosis. Subgroup analyses showed significant differences in performance for the diagnosis of fibrosis among different modalities. The pooled sensitivity, specificity, PPV, NPV and DOR were 0.97 (0.76 – 1.00), 0.91 (0.78 – 0.97), 0.95 (0.87 – 0.98), 0.93 (0.80 – 0.98) and 191.52 (38.82 – 944.81), respectively, for the diagnosis of liver steatosis. Conclusions: AI-assisted systems have promising potential for the diagnosis of liver fibrosis and NAFLD. Validations of their performances are warranted before implementing these AI-assisted systems in clinical practice.Trial registration: The protocol was registered with PROSPERO (CRD42020183295).

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