AIMS: To provide a narrative review on the performance and limitations of non-invasive tests, with a special emphasis on the impact of diabetes and obesity.
METHODS: We searched PubMed and Cochrane databases for articles published from 1990 to August 2023.
RESULTS: Abdominal ultrasonography remains the primary method to diagnose hepatic steatosis, while magnetic resonance imaging proton density fat fraction is currently the gold standard to quantify steatosis. Simple fibrosis scores such as the Fibrosis-4 index are well suited as initial assessment in primary care and non-hepatology settings to rule out advanced fibrosis and future risk of liver-related complications. However, because of its low positive predictive value, an abnormal test should be followed by specific blood (e.g. Enhanced Liver Fibrosis score) or imaging biomarkers (e.g. vibration-controlled transient elastography and magnetic resonance elastography) of fibrosis. Some non-invasive tests of fibrosis appear to be less accurate in patients with diabetes. Obesity also affects the performance of abdominal ultrasonography and transient elastography, whereas magnetic resonance imaging may not be feasible in some patients with severe obesity.
CONCLUSIONS: This article highlights issues surrounding the clinical application of non-invasive tests for MASLD in patients with type 2 diabetes and obesity.
METHODS: Consecutive NAFLD patients who underwent liver biopsy were enrolled in this study and had two sets each of pSWE and TE examinations by a nurse and a doctor on the same day of liver biopsy procedure. The medians of the four sets of pSWE and TE were used for evaluation of diagnostic accuracy using area under receiver operating characteristic curve (AUROC). Intra-observer and inter-observer variability was analyzed using intraclass correlation coefficients.
RESULTS: Data for 100 NAFLD patients (mean age 57.1 ± 10.2 years; male 46.0%) were analyzed. The AUROC of TE for diagnosis of fibrosis stage ≥ F1, ≥ F2, ≥ F3, and F4 was 0.89, 0.83, 0.83, and 0.89, respectively. The corresponding AUROC of pSWE was 0.80, 0.72, 0.69, and 0.79, respectively. TE was significantly better than pSWE for the diagnosis of fibrosis stages ≥ F2 and ≥ F3. The intra-observer and inter-observer variability of TE and pSWE measurements by the nurse and doctor was excellent with intraclass correlation coefficient > 0.96.
CONCLUSION: Transient elastography was significantly better than pSWE for the diagnosis of fibrosis stage ≥ F2 and ≥ F3. Both TE and pSWE had excellent intra-observer and inter-observer variability when performed by healthcare personnel of different backgrounds.
AIM: To determine how to use CAP in interpreting liver stiffness measurements.
METHODS: This is a secondary analysis of data from an individual patient data meta-analysis on CAP. The main exclusion criteria for the current analysis were unknown aetiology, unreliable elastography measurement and data already used for the same research question. Aetiology-specific liver stiffness measurement cut-offs were determined and used to estimate positive and negative predictive values (PPV/NPV) with logistic regression as functions of CAP.
RESULTS: Two thousand and fifty eight patients fulfilled the inclusion criteria (37% women, 18% NAFLD/NASH, 42% HBV, 40% HCV, 51% significant fibrosis ≥ F2). Youden optimised cut-offs were only sufficient for ruling out cirrhosis (NPV of 98%). With sensitivity and specificity-optimised cut-offs, NPV for ruling out significant fibrosis was moderate (70%) and could be improved slightly through consideration of CAP. PPV for significant fibrosis and cirrhosis were 68% and 55% respectively, despite specificity-optimised cut-offs for cirrhosis.
CONCLUSIONS: Liver stiffness measurement values below aetiology-specific cut-offs are very useful for ruling out cirrhosis, and to a lesser extent for ruling out significant fibrosis. In the case of the latter, Controlled Attenuation Parameter can improve interpretation slightly. Even if cut-offs are very high, liver stiffness measurements are not very reliable for ruling in fibrosis or cirrhosis.
METHODS: Patients with solid pancreatic lesions ≤ 15 mm in size and a definite diagnosis were included. Lesion stiffness relative to the surrounding pancreatic parenchyma, as qualitatively assessed and documented at the time of EUS elastography, was retrospectively compared with the final diagnosis obtained by fine-needle aspiration/biopsy or surgical resection.
RESULTS: 218 patients were analyzed. The average size of the lesions was 11 ± 3 mm; 23 % were ductal adenocarcinoma, 52 % neuroendocrine tumors, 8 % metastases, and 17 % other entities; 66 % of the lesions were benign. On elastography, 50 % of lesions were stiffer than the surrounding pancreatic parenchyma (stiff lesions) and 50 % were less stiff or of similar stiffness (soft lesions). High stiffness of the lesion had a sensitivity of 84 % (95 % confidence interval 73 % - 91 %), specificity of 67 % (58 % - 74 %), positive predictive value (PPV) of 56 % (50 % - 62 %), and negative predictive value (NPV) of 89 % (83 % - 93 %) for the diagnosis of malignancy. For the diagnosis of pancreatic ductal adenocarcinoma, the sensitivity, specificity, PPV, and NPV were 96 % (87 % - 100 %), 64 % (56 % - 71 %), 45 % (40 % - 50 %), and 98 % (93 % - 100 %), respectively.
CONCLUSIONS: In patients with small solid pancreatic lesions, EUS elastography can rule out malignancy with a high level of certainty if the lesion appears soft. A stiff lesion can be either benign or malignant.
METHODS: Retrospective analysis of prospectively collected data on adult NAFLD patients who had two FibroScan examination within 6 months prior to liver biopsy. F3-F4 fibrosis was excluded using LSM cut-off of 7.9 kPa.
RESULTS: A total of 136 patients were recruited. Eighty-five percent (115/136) of patients had high baseline LSM (≥ 7.9 kPa). Among them, 25% (29/115) had low repeat LSM (
METHODS: This is a cross-sectional study of consecutive adult T2DM patients attending the Diabetes Clinic of a university hospital. Significant hepatic steatosis and advanced fibrosis was diagnosed based on transient elastography if the controlled attenuation parameter was ≥ 263 dB/m, and the liver stiffness measurement was ≥ 9.6 kPa using the M probe or ≥ 9.3 kPa using the XL probe, respectively. Patients with liver stiffness measurement ≥ 8 kPa were referred to the Gastroenterology and Hepatology Clinic for further assessment, including liver biopsy.
RESULTS: The data of 557 patients were analyzed (mean age 61.4 ± 10.8 years, male 40.6%). The prevalence of NAFLD and advanced fibrosis based on transient elastography was 72.4% and 21.0%, respectively. On multivariate analysis, independent factors associated with NAFLD were central obesity (OR 4.856, 95% confidence interval [CI] 2.749-8.577, P = 0.006), serum triglyceride (OR 1.585, 95% CI 1.056-2.381, P = 0.026), and alanine aminotransferase levels (OR 1.047, 95% CI 1.025-1.070, P
Methods: A cross-sectional study of government officers and their family members attending a health screening at a public healthcare facility was conducted. All subjects underwent clinical evaluation, biochemical testing, anthropometry, ultrasound carotid Doppler, and Fibroscan examination.
Results: Data for 251 subjects were analyzed (mean age 47.1 ± 12.4 years, 74.1% male). Prevalence of NAFLD and advanced fibrosis were 57.4 and 17.5%, respectively. Independent factors associated with NAFLD were waist circumference (odds ratio [OR] = 1.077, 95% confidence interval [CI] 1.038-1.118, P < 0.001) and serum alanine aminotransferase (ALT) (OR = 1.039, 95% CI 1.005-1.074, P = 0.024). Independent factors associated with advanced fibrosis were male gender (OR = 4.847, 95% CI 1.369-17.155, P = 0.014) and serum aspartate aminotransferase (AST) (OR = 1.057, 95% CI 1.003-1.113, P = 0.036). Prevalence of increased CIMT was 29.0%. Independent factor associated with increased CIMT was older age (OR = 1.146, 95% CI 1.067-1.231, P < 0.001). Of the subjects, 34.5% with NAFLD had increased CIMT compared to 19.1% of the subjects without NAFLD (P = 0.063). Advanced fibrosis was not associated with increased CIMT.
Conclusions: Prevalence of NAFLD, advanced liver fibrosis, and increased CIMT were high. NAFLD and advanced liver fibrosis appeared not to be associated with increased CIMT. However, a larger sample size is needed to demonstrate whether there is any association.
METHODS: This prospective study included a derivation cohort before validation in multiple international cohorts. The derivation cohort was a cross-sectional, multicentre study of patients aged 18 years or older, scheduled to have a liver biopsy for suspicion of NAFLD at seven tertiary care liver centres in England. This was a prespecified secondary outcome of a study for which the primary endpoints have already been reported. Liver stiffness measurement (LSM) by vibration-controlled transient elastography and controlled attenuation parameter (CAP) measured by FibroScan device were combined with aspartate aminotransferase (AST), alanine aminotransferase (ALT), or AST:ALT ratio. To identify those patients with NASH, an elevated NAS, and significant fibrosis, the best fitting multivariable logistic regression model was identified and internally validated using boot-strapping. Score calibration and discrimination performance were determined in both the derivation dataset in England, and seven independent international (France, USA, China, Malaysia, Turkey) histologically confirmed cohorts of patients with NAFLD (external validation cohorts). This study is registered with ClinicalTrials.gov, number NCT01985009.
FINDINGS: Between March 20, 2014, and Jan 17, 2017, 350 patients with suspected NAFLD attending liver clinics in England were prospectively enrolled in the derivation cohort. The most predictive model combined LSM, CAP, and AST, and was designated FAST (FibroScan-AST). Performance was satisfactory in the derivation dataset (C-statistic 0·80, 95% CI 0·76-0·85) and was well calibrated. In external validation cohorts, calibration of the score was satisfactory and discrimination was good across the full range of validation cohorts (C-statistic range 0·74-0·95, 0·85; 95% CI 0·83-0·87 in the pooled external validation patients' cohort; n=1026). Cutoff was 0·35 for sensitivity of 0·90 or greater and 0·67 for specificity of 0·90 or greater in the derivation cohort, leading to a positive predictive value (PPV) of 0·83 (84/101) and a negative predictive value (NPV) of 0·85 (93/110). In the external validation cohorts, PPV ranged from 0·33 to 0·81 and NPV from 0·73 to 1·0.
INTERPRETATION: The FAST score provides an efficient way to non-invasively identify patients at risk of progressive NASH for clinical trials or treatments when they become available, and thereby reduce unnecessary liver biopsy in patients unlikely to have significant disease.
FUNDING: Echosens and UK National Institute for Health Research.
DISCUSSION: This paper presents comprehensive report on breast carcinoma disease and its modalities available for detection and diagnosis, as it delves into the screening and detection modalities with special focus placed on the non-invasive techniques and its recent advancement work done, as well as a proposal on a novel method for the application of early breast carcinoma detection.
CONCLUSION: This paper aims to serve as a foundation guidance for the reader to attain bird's eye understanding on breast carcinoma disease and its current non-invasive modalities.
METHODS: The NFS was calculated and LSM obtained for consecutive adult NAFLD patients scheduled for liver biopsy. The accuracy of predicting advanced fibrosis using either modality and in combination were assessed. An algorithm combining the NFS and LSM was developed from a training cohort and subsequently tested in a validation cohort.
RESULTS: There were 101 and 46 patients in the training and validation cohort, respectively. In the training cohort, the percentages of misclassifications using the NFS alone, LSM alone, LSM alone (with grey zone), both tests for all patients and a 2-step approach using LSM only for patients with indeterminate and high NFS were 5.0, 28.7, 2.0, 2.0 and 4.0 %, respectively. The percentages of patients requiring liver biopsy were 30.7, 0, 36.6, 36.6 and 18.8 %, respectively. In the validation cohort, the percentages of misclassifications were 8.7, 28.3, 2.2, 2.2 and 8.7 %, respectively. The percentages of patients requiring liver biopsy were 28.3, 0, 41.3, 43.5 and 19.6 %, respectively.
CONCLUSIONS: The novel 2-step approach further reduced the number of patients requiring a liver biopsy whilst maintaining the accuracy to predict advanced fibrosis. The combination of NFS and LSM for all patients provided no apparent advantage over using either of the tests alone.
METHODS: The proposed method uses a 2D contourlet transform and a set of texture features that are efficiently extracted from the transformed image. Then, the combination of a kernel discriminant analysis (KDA)-based feature reduction technique and analysis of variance (ANOVA)-based feature ranking technique was used, and the images were then classified into various stages of liver fibrosis.
RESULTS: Our 2D contourlet transform and texture feature analysis approach achieved a 91.46% accuracy using only four features input to the probabilistic neural network classifier, to classify the five stages of liver fibrosis. It also achieved a 92.16% sensitivity and 88.92% specificity for the same model. The evaluation was done on a database of 762 ultrasound images belonging to five different stages of liver fibrosis.
CONCLUSIONS: The findings suggest that the proposed method can be useful to automatically detect and classify liver fibrosis, which would greatly assist clinicians in making an accurate diagnosis.
METHODS: This is a cross-sectional study on T2DM patients. Modest alcohol intake was defined as alcohol intake ≤ 21 units/week in men and ≤ 14 units/week in women. Significant hepatic steatosis was diagnosed on the basis of controlled attenuation parameter > 263 dB/m, while advanced fibrosis was diagnosed on the basis of liver stiffness measurement ≥ 9.6 kPa using M probe or ≥ 9.3 kPa using XL probe. Patients with liver stiffness measurement ≥ 8.0 kPa were offered liver biopsy.
RESULTS: Five hundred fifty-seven patients underwent transient elastography, and 71 patients underwent liver biopsy. The prevalence of modest drinking was 16.5%. Modest drinking was equally prevalent among ethnic Indians and Chinese at 22.9% and 23.3%, respectively, but uncommon among ethnic Malays at 1.7%. Modest drinkers were more likely to be male, smoked, and had significantly lower glycated hemoglobin, total cholesterol, low-density lipoprotein cholesterol, alkaline phosphatase, and platelet count. There was no significant difference in the prevalence of significant hepatic steatosis or advanced fibrosis based on transient elastography and steatohepatitis or advanced fibrosis between modest drinkers and nondrinkers. The prevalence of significant hepatic steatosis was higher among ethnic Malays and Indians compared with ethnic Chinese, but the Chinese did not have a lower prevalence of more severe liver disease.
CONCLUSION: Modest alcohol intake is not associated with higher prevalence of significant hepatic steatosis or more severe liver disease among patients with T2DM.
METHODS: Six hundred and thirty-six adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from two independent Asian cohorts were enrolled in our study. Liver stiffness measurement (LSM) was assessed by vibration-controlled transient elastography (Fibroscan). Fibrotic NASH was defined as NASH with a NAFLD activity score (NAS) ≥ 4 and F ≥ 2 fibrosis.
RESULTS: Metabolic syndrome (MetS), platelet count and MACK-3 were independent predictors of fibrotic NASH. On the basis of their regression coefficients, we developed a novel nomogram showing a good discriminatory ability (area under receiver operating characteristic curve [AUROC]: 0.79, 95% confidence interval [CI 0.75-0.83]) and a high negative predictive value (NPV: 94.7%) to rule out fibrotic NASH. In the validation set, this nomogram had a higher AUROC (0.81, 95%CI 0.74-0.87) than that of MACK-3 (AUROC: 0.75, 95%CI 0.68-0.82; P