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Villani R, Lupo P, Sangineto M, Romano AD, Serviddio G. Liver Ultrasound Elastography in Non-Alcoholic Fatty Liver Disease: A State-of-the-Art Summary. Diagnostics (Basel) 2023; 13:diagnostics13071236. [PMID: 37046454 PMCID: PMC10093430 DOI: 10.3390/diagnostics13071236] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/21/2023] [Accepted: 03/23/2023] [Indexed: 03/29/2023] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a chronic disease which is currently the most common hepatic disorder affecting up to 38% of the general population with differences according to age, country, ethnicity and sex. Both genetic and acquired risk factors such as a high-calorie diet or high intake of saturated fats have been associated with obesity, diabetes and, finally, NAFLD. A liver biopsy has always been considered essential for the diagnosis of NAFLD; however, due to several limitations such as the potential occurrence of major complications, sampling variability and the poor repeatability in clinical practice, it is considered an imperfect option for the evaluation of liver fibrosis over time. For these reasons, a non-invasive assessment by serum biomarkers and the quantification of liver stiffness is becoming the new frontier in the management of patients with NAFLD and liver fibrosis. We present a state-of-the-art summary addressing the methods for the non-invasive evaluation of liver fibrosis in NAFLD patients, particularly the ultrasound-based techniques (transient elastography, ARFI techniques and strain elastography) and their optimal cut-off values for the staging of liver fibrosis.
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Cardoso AC, Tovo CV, Leite NC, El Bacha IA, Calçado FL, Coral GP, Sammarco GN, Cravo C, Carvalho Filho RJ, de Mello Perez R, Luiz RR, Parise ER, Villela-Nogueira CA. Validation and Performance of FibroScan®-AST (FAST) Score on a Brazilian Population with Nonalcoholic Fatty Liver Disease. Dig Dis Sci 2022; 67:5272-5279. [PMID: 35091842 DOI: 10.1007/s10620-021-07363-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 12/07/2021] [Indexed: 01/05/2023]
Abstract
BACKGROUND AND AIM FAST score has a good performance for diagnosing the composite of NASH + NAS ≥ 4 + F ≥ 2. However, it has not been evaluated in Latin American individuals with nonalcoholic fatty liver disease (NAFLD). We aimed to analyze the performance of the FAST score in a Brazilian NAFLD population. METHODS Cross-sectional study was held in ≥ 18 years NAFLD patients diagnosed by ultrasonography and submitted to liver biopsy (LB). Liver stiffness (LSM) and CAP measurements were performed with FibroScan®, using M (BMI < 32 kg/m2) or XL probes. Area under receiver operating characteristic (AUROC) curves were calculated as well as sensitivity (S), specificity (Spe), positive predictive value (VPP) and negative predictive value (NPV) for the previously established FAST score cut-offs. RESULTS Among 287 patients included (75% female; mean age 55 ± 10 years), NASH + NAS ≥ 4 + F ≥ 2 was reported in 30% of LB. For the FAST cut-off of 0.35, the S and NPV to rule out NASH + NAS ≥ 4 + F ≥ 2 were 78.8% and 87.8%, respectively. Regarding the cut-off of 0.67, the Spe and PPV to rule-in NASH + NAS ≥ 4 + F ≥ 2 were 89.1%, 61.8%, respectively. The AUROC of FAST for all included patients was 0.78 (95% CI 0.72-0.84) and for those with ≥ 32 kg/m2 was 0.81 (95% CI 0.74-0.88). CONCLUSION FAST score has a good performance in a Brazilian NAFLD population, even in patients with higher BMI when the XL probe is adopted. Therefore, FAST can be used as a noninvasive screening tool mainly for excluding the diagnosis of progressive NASH, reducing the number of unnecessary liver biopsies.
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Affiliation(s)
- Ana Carolina Cardoso
- Hepatology Unit - Clementino Fraga Filho University Hospital - School of Medicine, Federal University of Rio de Janeiro, Rua Professor Rodolpho Paulo Rocco 255 - Room 9E16, Rio de Janeiro, 29913-941, Brazil
| | - Cristiane Valle Tovo
- Gastroenterology and Hepatology Unit, Department of Internal Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Brazil
| | - Nathalie Carvalho Leite
- Hepatology Unit - Clementino Fraga Filho University Hospital - School of Medicine, Federal University of Rio de Janeiro, Rua Professor Rodolpho Paulo Rocco 255 - Room 9E16, Rio de Janeiro, 29913-941, Brazil
| | - Ibrahim A El Bacha
- Division of Gastroenterology, Hepatology Section, Federal University of São Paulo, São Paulo, Brazil
| | - Fernanda Luiza Calçado
- Hepatology Unit - Clementino Fraga Filho University Hospital - School of Medicine, Federal University of Rio de Janeiro, Rua Professor Rodolpho Paulo Rocco 255 - Room 9E16, Rio de Janeiro, 29913-941, Brazil
| | - Gabriela Perdomo Coral
- Gastroenterology and Hepatology Unit, Department of Internal Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Brazil
| | - Glauco Navas Sammarco
- Division of Gastroenterology, Hepatology Section, Federal University of São Paulo, São Paulo, Brazil
| | - Claudia Cravo
- Hepatology Unit - Clementino Fraga Filho University Hospital - School of Medicine, Federal University of Rio de Janeiro, Rua Professor Rodolpho Paulo Rocco 255 - Room 9E16, Rio de Janeiro, 29913-941, Brazil
| | | | - Renata de Mello Perez
- Hepatology Unit - Clementino Fraga Filho University Hospital - School of Medicine, Federal University of Rio de Janeiro, Rua Professor Rodolpho Paulo Rocco 255 - Room 9E16, Rio de Janeiro, 29913-941, Brazil
| | - Ronir Raggio Luiz
- Institute of Public Health Studies, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Edison Roberto Parise
- Division of Gastroenterology, Hepatology Section, Federal University of São Paulo, São Paulo, Brazil
| | - Cristiane A Villela-Nogueira
- Hepatology Unit - Clementino Fraga Filho University Hospital - School of Medicine, Federal University of Rio de Janeiro, Rua Professor Rodolpho Paulo Rocco 255 - Room 9E16, Rio de Janeiro, 29913-941, Brazil.
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Cao YT, Xiang LL, Qi F, Zhang YJ, Chen Y, Zhou XQ. Accuracy of controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) for assessing steatosis and fibrosis in non-alcoholic fatty liver disease: A systematic review and meta-analysis. EClinicalMedicine 2022; 51:101547. [PMID: 35844772 PMCID: PMC9284399 DOI: 10.1016/j.eclinm.2022.101547] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 06/16/2022] [Accepted: 06/20/2022] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease, and among the non-invasive tests, controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) have shown better diagnostic performance in NAFLD. This meta-analysis aimed to evaluate the performance of CAP and LSM for assessing steatosis and fibrosis in NAFLD. METHODS We searched the PubMed, Web of Science, Cochrane Library, and Embase databases for relevant articles published up to February 13th, 2022, and selected studies that met the inclusion and exclusion criteria, and evaluated the quality of evidence. Then we pooled sensitivity (SE), specificity (SP), and area under receiver operating characteristic (AUROC) curves. A random effect model was applied regardless of heterogeneity. Meta-regression analysis and subgroup analysis were performed to explore heterogeneity, and Fagan plot analysis was used to evaluate clinical utility. This meta-analysis was completed in Nanjing, Jiangsu and registered on PROSPERO (CRD42022309965). FINDINGS A total of 10537 patients from 61 studies were included in our meta-analysis. The AUROC of CAP were 0·924, 0·794 and 0·778 for steatosis grades ≥ S1, ≥ S2 and = S3, respectively, and the AUROC of LSM for detecting fibrosis stages ≥ F1, ≥ F2, ≥ F3, and = F4 were 0·851, 0·830, 0·897 and 0·925, respectively. Subgroup analysis revealed that BMI ≥ 30 kg/m² had lower accuracy for diagnosing S ≥ S1, ≥ S2 than BMI<30 kg/m². For the mean cut-off values, significant differences were found in CAP values among different body mass index (BMI) populations and LSM values among different regions. For diagnosing S ≥ S1, ≥ S2 and = S3, the mean CAP cut-off values for BMI ≥ 30 kg/m² were 30·7, 28·2, and 27·9 dB/m higher than for BMI < 30 kg/m² (P = 0·001, 0·001 and 0·018, respectively). For diagnosing F ≥ F2 and = F4, the mean cut-off values of Europe and America were 0·96 and 2·03 kPa higher than Asia (P = 0·027, P = 0·034), respectively. In addition, the results did not change significantly after sensitivity analysis and the trim and fill method to correct for publication bias, proving that the conclusions are robust. INTERPRETATION The good performance of CAP and LSM for the diagnosis of mild steatosis (S ≥ S1), advanced liver fibrosis (F ≥ F3), and cirrhosis (F = F4) can be used to screen for NAFLD in high-risk populations. Of note, the accuracy of CAP for the detection of steatosis in patients with obesity is reduced and requires specific diagnostic values. For LSM, the same diagnostic values can be used when the appropriate probes are selected based on BMI and the automated probe selection tool. The performance of CAP and LSM in assessing steatosis in patients with obesity, moderate to severe steatosis, and low-grade fibrosis should be further validated and improved in the future. FUNDING The study was funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).
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Affiliation(s)
- Yu-tian Cao
- The first clinical medical college of Nanjing University of Chinese Medicine, Nanjing, China
- Department of Endocrinology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Liu-lan Xiang
- The first clinical medical college of Nanjing University of Chinese Medicine, Nanjing, China
- Department of Endocrinology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Fang Qi
- The first clinical medical college of Nanjing University of Chinese Medicine, Nanjing, China
- Department of Endocrinology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Yu-juan Zhang
- The first clinical medical college of Nanjing University of Chinese Medicine, Nanjing, China
- Department of Endocrinology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Yi Chen
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xi-qiao Zhou
- Department of Endocrinology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
- Corresponding author at: Department of Endocrinology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing 210029, China.
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Le MH, Henry L, Cheung R, Nguyen MH. Transient Elastography and Serum-Based Tests for Diagnosis of Fatty Liver and Advanced Fibrosis in a Community Cohort: A Cross-Sectional Analysis. Dig Dis 2022; 41:767-779. [PMID: 35973400 PMCID: PMC10614275 DOI: 10.1159/000526503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 06/13/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Noninvasive tests (NITs) are necessary for knowing the true prevalence of fatty liver (FL) and advanced fibrosis. NITs for diagnosis of FL and fibrosis were compared. METHODS Data were obtained from the National Health and Examination Survey (2017-2018). Participants were excluded with other liver diseases, missing data for NIT calculation, and/or excessive alcohol use. Area under the receiver operating characteristic (AUROC) compared the accuracy of 4 FL NITs (CAP, HSI, FLI, USFLI) among themselves and to CAP value of 285 dB/m and 5 fibrosis NITs (transient elastography, APRI, NFS, FIB-4, HEPAmet) among themselves and to LSM ≥8.7 kPa. RESULTS Among 2,051 participants (average age 47 (±17.7), 48% males, 62% white, 73% overweight/obese, 39% metabolic syndrome), demographics were similar among NIT groups (CAP = 812; HSI = 1,234; FLI = 935; USFLI-824). FL prevalence by NIT: 39% CAP, 58% HSI, 47% FLI, 37% USFLI. Advanced fibrosis prevalence by test: LSM (≥8.7 kPa) 10-14%; FIB-4 (≥2.67) and APRI (≥0.7) 1.3-2.7%; HEPAmet (>0.47) 14-21%. Compared to CAP ≥285, FLI (AUROC = 0.823) and USFLI (AUROC = 0.833) performed better than HSI (AUROC: 0.798). Compared to LSM ≥8.7 kPa, only NFS (AUROC = 0.722) performed well (FIB-4 AUROC = 0.606; APRI = 0.647; HEPAmet = 0.629). Among the CAP cohort, the strongest FL predictor was obesity (OR: 15.2, 95% CI: 7.97-28.9, p < 0.001); the only fibrosis predictor was elevated AST (OR: 1.06, 95% CI: 1.00-1.12, p = 0.04). The addition of CAP or LSM as a second NIT reduced the number of indeterminate patients especially for FL. CONCLUSIONS Regardless of diagnostic method in 2017-2018, the prevalence of NAFLD was >35%. NITs for FL performed well but not for advanced fibrosis. CAP and LSM as a second NIT reduced those considered indeterminate.
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Affiliation(s)
- Michael H. Le
- Division of Gastroenterology and Hepatology, Stanford University Medical Center, Palo Alto, CA, USA
- The Robert Larner, M.D. College of Medicine, The University of Vermont, Burlington, VT, USA
| | - Linda Henry
- Division of Gastroenterology and Hepatology, Stanford University Medical Center, Palo Alto, CA, USA
| | - Ramsey Cheung
- Division of Gastroenterology and Hepatology, Stanford University Medical Center, Palo Alto, CA, USA
- Division of Gastroenterology and Hepatology, Department of Medicine, Palo Alto Veterans Affairs Medical Center, Palo Alto, CA, USA
| | - Mindie H. Nguyen
- Division of Gastroenterology and Hepatology, Stanford University Medical Center, Palo Alto, CA, USA
- Department of Epidemiology and Population Health, Stanford University, Palo Alto, CA, USA
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Brazilian Society of Hepatology and Brazilian College of Radiology practice guidance for the use of elastography in liver diseases. Ann Hepatol 2021; 22:100341. [PMID: 33737252 DOI: 10.1016/j.aohep.2021.100341] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 02/21/2021] [Accepted: 03/01/2021] [Indexed: 02/07/2023]
Abstract
In 2015 the European Association for the Study of Liver Diseases (EASL) and the Asociación Latinoamericana para el Estudio del Hígado (ALEH) published a guideline for the use of non-invasive markers of liver disease. At that time, this guideline focused on the available data regarding ultrasonic-related elastography methods. Since then, much has been published, including new data about XL probe use in transient elastography, magnetic resonance elastography, and non-invasive liver steatosis evaluation. In order to draw evidence-based guidance concerning the use of elastography for non-invasive assessment of fibrosis and steatosis in different chronic liver diseases, the Brazilian Society of Hepatology (SBH) and the Brazilian College of Radiology (CBR) sponsored a single-topic meeting on October 4th, 2019, at São Paulo, Brazil. The aim was to establish specific recommendations regarding the use of imaging-related non-invasive technology to diagnose liver fibrosis and steatosis based on the discussion of evidence-based topics by an organizing committee of experts. It was submitted online to all SBH and CBR members. The present document is the final version of the manuscript that supports the use of this new technology as an alternative to liver biopsy.
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Selvaraj EA, Mózes FE, Jayaswal ANA, Zafarmand MH, Vali Y, Lee JA, Levick CK, Young LAJ, Palaniyappan N, Liu CH, Aithal GP, Romero-Gómez M, Brosnan MJ, Tuthill TA, Anstee QM, Neubauer S, Harrison SA, Bossuyt PM, Pavlides M. Diagnostic accuracy of elastography and magnetic resonance imaging in patients with NAFLD: A systematic review and meta-analysis. J Hepatol 2021; 75:770-785. [PMID: 33991635 DOI: 10.1016/j.jhep.2021.04.044] [Citation(s) in RCA: 125] [Impact Index Per Article: 41.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 03/15/2021] [Accepted: 04/25/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND AND AIMS Vibration-controlled transient elastography (VCTE), point shear wave elastography (pSWE), 2-dimensional shear wave elastography (2DSWE), magnetic resonance elastography (MRE), and magnetic resonance imaging (MRI) have been proposed as non-invasive tests for patients with non-alcoholic fatty liver disease (NAFLD). This study evaluated their diagnostic accuracy for liver fibrosis and non-alcoholic steatohepatitis (NASH). METHODS PubMED/MEDLINE, EMBASE and the Cochrane Library were searched for studies examining the diagnostic accuracy of these index tests, against histology as the reference standard, in adult patients with NAFLD. Two authors independently screened and assessed methodological quality of studies and extracted data. Summary estimates of sensitivity, specificity and area under the curve (sAUC) were calculated for fibrosis stages and NASH, using a random effects bivariate logit-normal model. RESULTS We included 82 studies (14,609 patients). Meta-analysis for diagnosing fibrosis stages was possible in 53 VCTE, 11 MRE, 12 pSWE and 4 2DSWE studies, and for diagnosing NASH in 4 MRE studies. sAUC for diagnosis of significant fibrosis were: 0.83 for VCTE, 0.91 for MRE, 0.86 for pSWE and 0.75 for 2DSWE. sAUC for diagnosis of advanced fibrosis were: 0.85 for VCTE, 0.92 for MRE, 0.89 for pSWE and 0.72 for 2DSWE. sAUC for diagnosis of cirrhosis were: 0.89 for VCTE, 0.90 for MRE, 0.90 for pSWE and 0.88 for 2DSWE. MRE had sAUC of 0.83 for diagnosis of NASH. Three (4%) studies reported intention-to-diagnose analyses and 15 (18%) studies reported diagnostic accuracy against pre-specified cut-offs. CONCLUSIONS When elastography index tests are acquired successfully, they have acceptable diagnostic accuracy for advanced fibrosis and cirrhosis. The potential clinical impact of these index tests cannot be assessed fully as intention-to-diagnose analyses and validation of pre-specified thresholds are lacking. LAY SUMMARY Non-invasive tests that measure liver stiffness or use magnetic resonance imaging (MRI) have been suggested as alternatives to liver biopsy for assessing the severity of liver scarring (fibrosis) and fatty inflammation (steatohepatitis) in patients with non-alcoholic fatty liver disease (NAFLD). In this study, we summarise the results of previously published studies on how accurately these non-invasive tests can diagnose liver fibrosis and inflammation, using liver biopsy as the reference. We found that some techniques that measure liver stiffness had a good performance for the diagnosis of severe liver scarring.
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Affiliation(s)
- Emmanuel Anandraj Selvaraj
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
| | - Ferenc Emil Mózes
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Arjun Narayan Ajmer Jayaswal
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Mohammad Hadi Zafarmand
- Department of Epidemiology and Data Science, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Yasaman Vali
- Department of Epidemiology and Data Science, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Jenny A Lee
- Department of Epidemiology and Data Science, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Christina Kim Levick
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Liam Arnold Joseph Young
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Naaventhan Palaniyappan
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
| | - Chang-Hai Liu
- UCM Digestive Diseases. Virgen del Rocio University Hospital. Institute of Biomedicine of Seville, University of Seville, Sevilla, Spain; Center for Infectious Diseases, West China Hospital of Sichuan University; Division of Infectious Diseases, State Key Laboratory of Biotherapy and Center of Infectious Disease, West China Hospital, Sichuan University, Chengdu, China
| | - Guruprasad Padur Aithal
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
| | - Manuel Romero-Gómez
- UCM Digestive Diseases. Virgen del Rocio University Hospital. Institute of Biomedicine of Seville, University of Seville, Sevilla, Spain
| | - M Julia Brosnan
- Internal Medicine Research Unit, Pfizer Inc, Cambridge, MA, USA
| | | | - Quentin M Anstee
- Liver Research Group, Translational & Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals, NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Stefan Neubauer
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Stephen A Harrison
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Patrick M Bossuyt
- Department of Epidemiology and Data Science, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Michael Pavlides
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK.
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Effect of skin-capsular distance on controlled attenuation parameter for diagnosing liver steatosis in patients with nonalcoholic fatty liver disease. Sci Rep 2021; 11:15641. [PMID: 34341368 PMCID: PMC8329228 DOI: 10.1038/s41598-021-94970-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Accepted: 07/19/2021] [Indexed: 12/16/2022] Open
Abstract
The effect of the skin–capsular distance (SCD) on the controlled attenuation parameter (CAP) for diagnosis of liver steatosis in patients with nonalcoholic fatty liver disease (NAFLD) remains unclear. The SCD was measured using B-mode ultrasound, and the CAP was measured using the M probe of FibroScan®. According to the indications of the M probe, 113 patients with an SCD of ≤ 25 mm were included in the present study. The association between the SCD and CAP was investigated, and the diagnostic performance of the SCD-adjusted CAP was tested. The SCD showed the most significant positive correlation with the CAP (ρ = 0.329, p < 0.001). In the multiple regression analysis, the SCD and serum albumin concentration were associated with the CAP, independent of pathological liver steatosis. According to the multivariate analysis, two different formulas were developed to obtain the adjusted CAP using the SCD and serum albumin concentration as follows: adjusted CAP (dB/m) = CAP − (5.26 × SCD) and adjusted CAP (dB/m) = CAP − (5.35 × SCD) − (25.77 × serum albumin concentration). The area under the receiver operating characteristic curve for diagnosis of a steatosis score ≥ 2 of adjusted CAP was 0.678 and 0.684 respectively, which were significantly greater than the original CAP (0.621: p = 0.030 and p = 0.024). The SCD is associated with the CAP independent of liver steatosis. Adjustment of the CAP using the SCD improves the diagnostic performance of the CAP in NAFLD.
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Yu CS, Chang SS, Lin CH, Lin YJ, Wu JL, Chen RJ. Identify the Characteristics of Metabolic Syndrome and Non-obese Phenotype: Data Visualization and a Machine Learning Approach. Front Med (Lausanne) 2021; 8:626580. [PMID: 33898478 PMCID: PMC8058220 DOI: 10.3389/fmed.2021.626580] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 03/08/2021] [Indexed: 12/16/2022] Open
Abstract
Introduction: A third of the world's population is classified as having Metabolic Syndrome (MetS). Traditional diagnostic criteria for MetS are based on three or more of five components. However, the outcomes of patients with different combinations of specific metabolic components are undefined. It is challenging to be discovered and introduce treatment in advance for intervention, since the related research is still insufficient. Methods: This retrospective cohort study attempted to establish a method of visualizing metabolic components by using unsupervised machine learning and treemap technology to discover the relations between predicting factors and different metabolic components. Several supervised machine-learning models were used to explore significant predictors of MetS and to construct a powerful prediction model for preventive medicine. Results: The random forest had the best performance with accuracy and c-statistic of 0.947 and 0.921, respectively, and found that body mass index, glycated hemoglobin, and controlled attenuation parameter (CAP) score were the optimal primary predictors of MetS. In treemap, high triglyceride level plus high fasting blood glucose or large waist circumference group had higher CAP scores (>260) than other groups. Moreover, 32.2% of patients with high CAP scores during 3 years of follow-up had metabolic diseases are observed. This reveals that the CAP score may be used for detecting MetS, especially for the non-obese MetS phenotype. Conclusions: Machine learning and data visualization can illustrate the complicated relationships between metabolic components and potential risk factors for MetS.
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Affiliation(s)
- Cheng-Sheng Yu
- Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan.,Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.,Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Shy-Shin Chang
- Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan.,Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Chang-Hsien Lin
- Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan.,Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Yu-Jiun Lin
- Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan.,Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Jenny L Wu
- Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan.,Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Ray-Jade Chen
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Division of General Surgery, Department of Surgery, Taipei Medical University Hospital, Taipei, Taiwan.,Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
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Gu Q, Cen L, Lai J, Zhang Z, Pan J, Zhao F, Yu C, Li Y, Chen C, Chen W, Shen Z. A meta-analysis on the diagnostic performance of magnetic resonance imaging and transient elastography in nonalcoholic fatty liver disease. Eur J Clin Invest 2021; 51:e13446. [PMID: 33128454 DOI: 10.1111/eci.13446] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 10/15/2020] [Accepted: 10/27/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Noninvasive methods have been used for the assessment of hepatic steatosis in patients with nonalcoholic fatty liver disease (NAFLD). The aim was to assess the efficacy and accuracy of both magnetic resonance imaging(MRI) and transient elastography(TE) for the evaluation of hepatic steatosis. MATERIALS AND METHODS The PubMed, Cochrane Library, Embase, MEDLINE and Web of Science databases were searched to retrieve studies examining the accuracy of MRI-proton density fat fraction(PDFF) and TE-controlled attenuation parameter(CAP) for evaluating the grading of steatosis(S0-S3) diagnosed by liver biopsy in NAFLD. We compared the sensitivity, specificity, hierarchical summary receiver operating characteristic curves(HSROC) and clinical utility of these methods. RESULTS Twenty-four articles with a total of 2979 patients with NAFLD were included. The steatosis distribution was 8.1%/35.1%/32.2%/24.6% for S0/S1/S2/S3. For the diagnostic accuracy of MRI-PDFF, the HSROCs were 0.97 for ≥S1, 0.91 for ≥S2 and 0.90 for ≥S3. For the diagnostic accuracy of TE-based CAP, the HSROCs were 0.85 for ≥S1, 0.83 for ≥S2 and 0.79 for ≥S3. Following a 'positive' measurement (over the threshold value) for ≥S1, the corresponding post-test probabilities of PDFF and CAP for the presence of steatosis were 82% and 61%, respectively, when the pretest probability was 24%. If the values were below these thresholds ('negative' results), the post-test probabilities were 3% and 7%. CONCLUSION MRI-PDFF and TE-CAP both provide highly accurate noninvasive approaches for quantifying and staging hepatic steatosis in NAFLD. Compared with TE-CAP, MRI-PDFF is significantly more accurate for evaluating dichotomized grades of steatosis.
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Affiliation(s)
- Qing Gu
- Center of Endoscopy, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Li Cen
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Jiawei Lai
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China.,Department of Emergency, The First People's Hospital of Xiaoshan District, Hangzhou, China
| | - Zhongchen Zhang
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Jiaqi Pan
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Feng Zhao
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Chaohui Yu
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Youming Li
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Chunxiao Chen
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Weixing Chen
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
| | - Zhe Shen
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, Zhejiang Province, 310003, China
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10
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Petroff D, Blank V, Newsome PN, Shalimar, Voican CS, Thiele M, de Lédinghen V, Baumeler S, Chan WK, Perlemuter G, Cardoso AC, Aggarwal S, Sasso M, Eddowes PJ, Allison M, Tsochatzis E, Anstee QM, Sheridan D, Cobbold JF, Naveau S, Lupsor-Platon M, Mueller S, Krag A, Irles-Depe M, Semela D, Wong GLH, Wong VWS, Villela-Nogueira CA, Garg H, Chazouillères O, Wiegand J, Karlas T. Assessment of hepatic steatosis by controlled attenuation parameter using the M and XL probes: an individual patient data meta-analysis. Lancet Gastroenterol Hepatol 2021; 6:185-198. [PMID: 33460567 DOI: 10.1016/s2468-1253(20)30357-5] [Citation(s) in RCA: 125] [Impact Index Per Article: 41.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 10/13/2020] [Accepted: 10/27/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Diagnostic tools for liver disease can now include estimation of the grade of hepatic steatosis (S0 to S3). Controlled attenuation parameter (CAP) is a non-invasive method for assessing hepatic steatosis that has become available for patients who are obese (FibroScan XL probe), but a consensus has not yet been reached regarding cutoffs and its diagnostic performance. We aimed to assess diagnostic properties and identify relevant covariates with use of an individual patient data meta-analysis. METHODS We did an individual patient data meta-analysis, in which we searched PubMed and Web of Science for studies published from database inception until April 30, 2019. Studies reporting original biopsy-controlled data of CAP for non-invasive grading of steatosis were eligible. Probe recommendation was based on automated selection, manual assessment of skin-to-liver-capsule distance, and a body-mass index (BMI) criterion. Receiver operating characteristic methods and mixed models were used to assess diagnostic properties and covariates. Patients with non-alcoholic fatty liver disease (NAFLD) were analysed separately because they are the predominant patient group when using the XL probe. This study is registered with PROSPERO, CRD42018099284. FINDINGS 16 studies reported histology-controlled CAP including the XL probe, and individual data from 13 papers and 2346 patients were included. Patients with a mean age of 46·5 years (SD 14·5) were recruited from 20 centres in nine countries. 2283 patients had data for BMI; 673 (29%) were normal weight (BMI <25 kg/m2), 530 (23%) were overweight (BMI ≥25 to <30 kg/m2), and 1080 (47%) were obese (BMI ≥30 kg/m2). 1277 (54%) patients had NAFLD, 474 (20%) had viral hepatitis, 285 (12%) had alcohol-associated liver disease, and 310 (13%) had other liver disease aetiologies. The XL probe was recommended in 1050 patients, 930 (89%) of whom had NAFLD; among the patients with NAFLD, the areas under the curve were 0·819 (95% CI 0·769-0·869) for S0 versus S1 to S3 and 0·754 (0·720-0·787) for S0 to S1 versus S2 to S3. CAP values were independently affected by aetiology, diabetes, BMI, aspartate aminotransferase, and sex. Optimal cutoffs differed substantially across aetiologies. Risk of bias according to QUADAS-2 was low. INTERPRETATION CAP cutoffs varied according to cause, and can effectively recognise significant steatosis in patients with viral hepatitis. CAP cannot grade steatosis in patients with NAFLD adequately, but its value in a NAFLD screening setting needs to be studied, ideally with methods beyond the traditional histological reference standard. FUNDING The German Federal Ministry of Education and Research and Echosens.
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Affiliation(s)
- David Petroff
- Clinical Trial Centre, University of Leipzig, Leipzig, Germany; Faculty of Medicine, Integrated Research and Treatment Center AdiposityDiseases, University of Leipzig, Leipzig, Germany
| | - Valentin Blank
- Faculty of Medicine, Integrated Research and Treatment Center AdiposityDiseases, University of Leipzig, Leipzig, Germany; Division of Gastroenterology, Department of Medicine II, Leipzig University Medical Center, Leipzig, Germany
| | - Philip N Newsome
- National Institute for Health Research, Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham, UK; Centre for Liver Research, Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Liver Unit, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Shalimar
- Department of Gastroenterology, All India Institute of Medical Sciences, New Delhi, India
| | - Cosmin Sebastian Voican
- Faculté de Médecine Paris-Sud, Université Paris-Sud, Université Paris-Saclay, Le Kremlin-Bicêtre, France; Service d'Hépato-Gastroentérologie et Nutrition, Hôpital Antoine-Béclère, Hôpitaux Universitaires Paris-Sud, Assistance Publique-Hôpitaux de Paris, Clamart, France; INSERM U996, DHU Hepatinov, Labex LERMIT, Clamart, France
| | - Maja Thiele
- Department of Gastroenterology and Hepatology, Odense University Hospital, University of Southern Denmark, Odense, Denmark
| | - Victor de Lédinghen
- Centre d'Investigation de la Fibrose Hépatique, Bordeaux University Hospital, Pessac, France; INSERM U1053, Bordeaux University, Bordeaux, France
| | - Stephan Baumeler
- Department of Gastroenterology and Hepatology, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Wah Kheong Chan
- Gastroenterology and Hepatology Unit, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Gabriel Perlemuter
- Faculté de Médecine Paris-Sud, Université Paris-Sud, Université Paris-Saclay, Le Kremlin-Bicêtre, France; Service d'Hépato-Gastroentérologie et Nutrition, Hôpital Antoine-Béclère, Hôpitaux Universitaires Paris-Sud, Assistance Publique-Hôpitaux de Paris, Clamart, France; INSERM U996, DHU Hepatinov, Labex LERMIT, Clamart, France
| | - Ana-Carolina Cardoso
- Hepatology Unit, Hospital Universitário Clementino Fraga Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Sandeep Aggarwal
- Department of Surgical Disciplines, All India Institute of Medical Sciences, New Delhi, India
| | - Magali Sasso
- Research and Development Department, Echosens, Paris, France
| | - Peter J Eddowes
- National Institute for Health Research, Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham, UK; Centre for Liver Research, Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Liver Unit, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK; University of Nottingham, Nottingham, UK
| | - Michael Allison
- Liver Unit, Addenbrooke's Hospital, Cambridge Biomedical Research Centre, Cambridge, UK
| | - Emmanuel Tsochatzis
- University College London Institute for Liver and Digestive Health, Royal Free Hospital, London, UK
| | - Quentin M Anstee
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; Newcastle National Institute for Health Research Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - David Sheridan
- Institute of Translational and Stratified Medicine, Faculty of Medicine and Dentistry, University of Plymouth, Plymouth, UK
| | - Jeremy F Cobbold
- Department of Gastroenterology and Hepatology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Sylvie Naveau
- Faculté de Médecine Paris-Sud, Université Paris-Sud, Université Paris-Saclay, Le Kremlin-Bicêtre, France; Service d'Hépato-Gastroentérologie et Nutrition, Hôpital Antoine-Béclère, Hôpitaux Universitaires Paris-Sud, Assistance Publique-Hôpitaux de Paris, Clamart, France; INSERM U996, DHU Hepatinov, Labex LERMIT, Clamart, France
| | - Monica Lupsor-Platon
- Department of Medical Imaging, Iuliu Hatieganu University of Medicine and Pharmacy, Regional Institute of Gastroenterology and Hepatology, Cluj-Napoca, Romania
| | - Sebastian Mueller
- Department of Medicine and Liver Diseases, Salem Medical Center, University of Heidelberg, Heidelberg, Germany
| | - Aleksander Krag
- Department of Gastroenterology and Hepatology, Odense University Hospital, University of Southern Denmark, Odense, Denmark
| | - Marie Irles-Depe
- Centre d'Investigation de la Fibrose Hépatique, Bordeaux University Hospital, Pessac, France; INSERM U1053, Bordeaux University, Bordeaux, France
| | - David Semela
- Department of Gastroenterology and Hepatology, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Grace Lai-Hung Wong
- Institute of Digestive Disease, The Chinese University of Hong Kong, Sha Tin, Hong Kong; Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Vincent Wai-Sun Wong
- Institute of Digestive Disease, The Chinese University of Hong Kong, Sha Tin, Hong Kong; Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Cristiane A Villela-Nogueira
- Hepatology Unit, Hospital Universitário Clementino Fraga Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Harshit Garg
- Department of Surgical Disciplines, All India Institute of Medical Sciences, New Delhi, India
| | - Olivier Chazouillères
- Hepatology Department, Saint-Antoine Hospital, Assistance Publique-Hôpitaux de Paris, Centre de Recherche Saint-Antoine, Sorbonne University, Paris, France
| | - Johannes Wiegand
- Division of Hepatology, Department of Medicine II, Leipzig University Medical Center, Leipzig, Germany
| | - Thomas Karlas
- Division of Gastroenterology, Department of Medicine II, Leipzig University Medical Center, Leipzig, Germany.
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11
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Oeda S, Tanaka K, Oshima A, Matsumoto Y, Sueoka E, Takahashi H. Diagnostic Accuracy of FibroScan and Factors Affecting Measurements. Diagnostics (Basel) 2020; 10:diagnostics10110940. [PMID: 33198092 PMCID: PMC7696616 DOI: 10.3390/diagnostics10110940] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 11/10/2020] [Accepted: 11/11/2020] [Indexed: 12/12/2022] Open
Abstract
Evaluating liver steatosis and fibrosis is important for patients with non-alcoholic fatty liver disease. Although liver biopsy and pathological assessment is the gold standard for these conditions, this technique has several disadvantages. The evaluation of steatosis and fibrosis using ultrasound B-mode imaging is qualitative and subjective. The liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) determined using FibroScan are the evidence-based non-invasive measures of liver fibrosis and steatosis, respectively. The LSM and CAP measurements are carried out simultaneously, and the median values of more than ten valid measurements are used to quantify liver fibrosis and steatosis. Here, we demonstrate that the reliability of the LSM depends on the interquartile range to median ratio (IQR/Med), but CAP values do not depend on IQR/Med. In addition, the LSM is affected by inflammation, congestion, and cholestasis in addition to fibrosis, while CAP values are affected by the body mass index in addition to steatosis. We also show that the M probe provides higher LSM values but lower CAP values than the XL probe in the same population. However, there was no statistically significant difference between the diagnostic accuracies of the two probes. These findings are important to understand the reliability of FibroScan measurements and the factors influencing measurement values for all patients.
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Affiliation(s)
- Satoshi Oeda
- Liver Center, Saga University Hospital, 5-1-1 Nabeshima, Saga 849-8501, Japan;
- Department of Laboratory Medicine, Saga University Hospital, 5-1-1 Nabeshima, Saga 849-8501, Japan; (A.O.); (Y.M.); (E.S.)
- Correspondence:
| | - Kenichi Tanaka
- Department of Internal Medicine, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan;
| | - Ayaka Oshima
- Department of Laboratory Medicine, Saga University Hospital, 5-1-1 Nabeshima, Saga 849-8501, Japan; (A.O.); (Y.M.); (E.S.)
| | - Yasue Matsumoto
- Department of Laboratory Medicine, Saga University Hospital, 5-1-1 Nabeshima, Saga 849-8501, Japan; (A.O.); (Y.M.); (E.S.)
| | - Eisaburo Sueoka
- Department of Laboratory Medicine, Saga University Hospital, 5-1-1 Nabeshima, Saga 849-8501, Japan; (A.O.); (Y.M.); (E.S.)
- Department of Clinical Laboratory Medicine, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Hirokazu Takahashi
- Liver Center, Saga University Hospital, 5-1-1 Nabeshima, Saga 849-8501, Japan;
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12
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Parente DB, Perazzo H, Paiva FF, Campos CFF, Saboya CJ, Pereira SE, Silva FDE, Rodrigues RS, Perez RDM. Higher cut-off values of non-invasive methods might be needed to detect moderate-to-severe steatosis in morbid obese patients: a pilot study. Sci Rep 2020; 10:15007. [PMID: 32929103 PMCID: PMC7490697 DOI: 10.1038/s41598-020-71723-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 08/17/2020] [Indexed: 12/19/2022] Open
Abstract
To evaluate the diagnostic value of described thresholds of controlled attenuation parameter (CAP) and biomarker scores for liver steatosis and to evaluate new cut-offs to detect moderate-to-severe steatosis (S2-3) in patients with morbid obesity. In this prospective study, 32 patients with morbid obesity with indications for bariatric surgery (15 women and 17 men, mean age = 36 years, median BMI = 40.2 kg/m2) underwent CAP, magnetic resonance spectroscopy (MRS), three biomarker scores (Steato-ELSA, Fatty Liver Index (FLI), and Hepatic Steatosis Index (HSI)), and liver biopsy. Subjects were divided into an exploratory cohort (reliable CAP and liver biopsy) and a confirmatory cohort (reliable CAP and MRS) to evaluate new thresholds for CAP and biomarker scores to detect S2-3. Receiver operator characteristic (ROC) curves analyses were performed and the optimal cut-off points were identified using the maximal Youden index. A total of 22 patients had CAP measure and liver biopsy (exploratory cohort) and 24 patients had CAP measure with MRS (confirmatory cohort). New cut-offs were identified for detection of S2-3 by the non-invasive tests using liver biopsy as the reference standard (exploratory cohort). Considering the new proposed cut-offs for detection of S2-3 for CAP (≥ 314 dB/m), Steato-ELSA (≥ 0.832), FLI (≥ 96), and HSI (≥ 53), for the exploratory and confirmatory cohorts sensitivities were: 71-75%, 86-81%, 85-81%, and 71-69% and specificities were: 94-89%, 75-63%, 63-63%, and 75-88%, respectively. Higher cut-offs for CAP and biomarker scores may be better to diagnose moderate-to-severe steatosis in patients with morbid obesity.
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Affiliation(s)
- Daniella Braz Parente
- D'Or Institute for Research and Education, Rua Diniz Cordeiro 30, 3º andar, Botafogo, Rio de Janeiro, CEP 22281-100, Brazil. .,Federal University of Rio de Janeiro, Av. Professor Rodolpho Paulo Rocco 255, Cidade Universitária, Ilha Do Fundão, Rio de Janeiro, Rio de Janeiro, CEP 21941-913, Brazil.
| | - Hugo Perazzo
- Oswaldo Cruz Foundation - National Institute of Infectious Diseases Evandro Chagas, Av. Brasil, 4365, Manguinhos, Rio de Janeiro, CEP 21040-360, Brazil
| | - Fernando Fernandes Paiva
- Institute of Physics of São Carlos, University of São Paulo, Av. Trabalhador São-Carlense 400, Pq. Arnold Schimidt, São Carlos, São Paulo, CEP 13566-590, Brazil
| | - Carlos Frederico Ferreira Campos
- University of the State of Rio de Janeiro, R. S Francisco Xavier, 524, Maracanã, Rio de Janeiro, Rio de Janeiro, CEP 20550-013, Brazil
| | - Carlos José Saboya
- Clinica Cirúrgica Carlos Saboya, Rua Dona Mariana 143/F11, Botafogo, Rio de Janeiro, CEP 22280-020, Brazil
| | - Silvia Elaine Pereira
- Clinica Cirúrgica Carlos Saboya, Rua Dona Mariana 143/F11, Botafogo, Rio de Janeiro, CEP 22280-020, Brazil
| | - Felipe d'Almeida E Silva
- D'Or Institute for Research and Education, Rua Diniz Cordeiro 30, 3º andar, Botafogo, Rio de Janeiro, CEP 22281-100, Brazil
| | - Rosana Souza Rodrigues
- D'Or Institute for Research and Education, Rua Diniz Cordeiro 30, 3º andar, Botafogo, Rio de Janeiro, CEP 22281-100, Brazil.,Federal University of Rio de Janeiro, Av. Professor Rodolpho Paulo Rocco 255, Cidade Universitária, Ilha Do Fundão, Rio de Janeiro, Rio de Janeiro, CEP 21941-913, Brazil
| | - Renata de Mello Perez
- D'Or Institute for Research and Education, Rua Diniz Cordeiro 30, 3º andar, Botafogo, Rio de Janeiro, CEP 22281-100, Brazil.,Federal University of Rio de Janeiro, Av. Professor Rodolpho Paulo Rocco 255, Cidade Universitária, Ilha Do Fundão, Rio de Janeiro, Rio de Janeiro, CEP 21941-913, Brazil.,University of the State of Rio de Janeiro, R. S Francisco Xavier, 524, Maracanã, Rio de Janeiro, Rio de Janeiro, CEP 20550-013, Brazil
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13
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Usefulness of Different Imaging Modalities in Evaluation of Patients with Non-Alcoholic Fatty Liver Disease. Biomedicines 2020; 8:biomedicines8090298. [PMID: 32839409 PMCID: PMC7556032 DOI: 10.3390/biomedicines8090298] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 08/13/2020] [Accepted: 08/19/2020] [Indexed: 12/14/2022] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are becoming some of the major health problems in well-developed countries, together with the increasing prevalence of obesity, metabolic syndrome, and all of their systemic complications. As the future prognoses are even more disturbing and point toward further increase in population affected with NAFLD/NASH, there is an urgent need for widely available and reliable diagnostic methods. Consensus on a non-invasive, accurate diagnostic modality for the use in ongoing clinical trials is also required, particularly considering a current lack of any registered drug for the treatment of NAFLD/NASH. The aim of this narrative review was to present current information on methods used to assess liver steatosis and fibrosis. There are several imaging modalities for the assessment of hepatic steatosis ranging from simple density analysis by computed tomography or conventional B-mode ultrasound to magnetic resonance spectroscopy (MRS), magnetic resonance imaging proton density fat fraction (MRI-PDFF) or controlled attenuation parameter (CAP). Fibrosis stage can be assessed by magnetic resonance elastography (MRE) or different ultrasound-based techniques: transient elastography (TE), shear-wave elastography (SWE) and acoustic radiation force impulse (ARFI). Although all of these methods have been validated against liver biopsy as the reference standard and provided good accuracy, the MRS and MRI-PDFF currently outperform other methods in terms of diagnosis of steatosis, and MRE in terms of evaluation of fibrosis.
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