AGILE SCORES IN MASLD AND ALD: EXTERNAL VALIDATION AND THEIR UTILITY IN CLINICAL ALGORITHMS.

BACKGROUND: Agile scores, including liver stiffness measurements (LSM) and routine clinical/laboratory biomarkers, have been developed for advanced fibrosis (F≥3) and cirrhosis, respectively, in patients with metabolic-associated steatotic liver disease (MASLD). We independently validated the diagnostic accuracy of these scores in MASLD, alcohol-related liver disease (ALD) and chronic hepatitis B or C (CHB/C) and assessed them in clinical algorithms with FIB-4 and LSM. METHODS: We included 4,243 patients (MASLD:912, ALD:386, CHB:597, CHC:2348) with LSM, liver biopsy and laboratory tests within 6 months. FIB-4, Agile 3+ and Agile 4 scores were calculated. RESULTS: For F≥3, diagnostic accuracy of Agile 3+ and LSM were similar in MASLD (AUC: 0.86 vs 0.86, P=0.831) and ALD (0.92 vs 0.94, P=0.123). For cirrhosis, Agile 4 was similar to LSM in MASLD (0.89 vs 0.90, P=0.412) and ALD (0.94 vs 0.95, P=0.513). Agile 3+/4 performed worse than LSM in CHB/C. Using predefined dual thresholds of 90% Se/Sp, correct classification rates in MASLD were 66% vs 61% using Agile 3+ vs LS dual cut-offs and 71% vs 67% in ALD. When using Agile 3+ or LSM as a second step after FIB-4>1.3, correct classification rates were higher with Agile 3+ than LSM, both for MASLD (75% vs 71%) and for ALD patients (76% vs 72%) with fewer indeterminate results. Positive agreement of LSM and Agile 3+/4 significantly increased the specificity of a diagnosis of advanced fibrosis/cirrhosis. CONCLUSION: Agile 3+ and Agile 4 have equal diagnostic accuracy with LSM in both MASLD and ALD but result in fewer indeterminate results. Sequential use of FIB-4 and Agile 3+/4 or concurrent Agile 3+/4 and LSM can be used to further optimize F≥3 diagnosis.

Noninvasive assessment of liver disease severity in patients with nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes.

BACKGROUND AND AIMS: We evaluated the diagnostic accuracy of simple, noninvasive tests (NITs) in NAFLD patients with type 2 diabetes (T2D). METHODS AND RESULTS: This was an individual patient data meta-analysis of 1780 patients with biopsy-proven NAFLD and T2D. The index tests of interest were FIB-4, NAFLD Fibrosis Score (NFS), aspartate aminotransferase-to-platelet ratio index, liver stiffness measurement (LSM) by vibration-controlled transient elastography, and AGILE 3+. The target conditions were advanced fibrosis, NASH, and fibrotic NASH(NASH plus F2-F4 fibrosis). The diagnostic performance of noninvasive tests. individually or in sequential combination, was assessed by area under the receiver operating characteristic curve and by decision curve analysis. Comparison with 2278 NAFLD patients without T2D was also made. In NAFLD with T2D LSM and AGILE 3+ outperformed, both NFS and FIB-4 for advanced fibrosis (area under the receiver operating characteristic curve:LSM 0.82, AGILE 3+ 0.82, NFS 0.72, FIB-4 0.75, aspartate aminotransferase-to-platelet ratio index 0.68; p < 0.001 of LSM-based versus simple serum tests), with an uncertainty area of 12%-20%. The combination of serum-based with LSM-based tests for advanced fibrosis led to a reduction of 40%-60% in necessary LSM tests. Decision curve analysis showed that all scores had a modest net benefit for ruling out advanced fibrosis at the risk threshold of 5%-10% of missing advanced fibrosis. LSM and AGILE 3+ outperformed both NFS and FIB-4 for fibrotic NASH (area under the receiver operating characteristic curve:LSM 0.79, AGILE 3+ 0.77, NFS 0.71, FIB-4 0.71; p < 0.001 of LSM-based versus simple serum tests). All noninvasive scores were suboptimal for diagnosing NASH. CONCLUSIONS: LSM and AGILE 3+ individually or in low availability settings in sequential combination after FIB-4 or NFS have a similar good diagnostic accuracy for advanced fibrosis and an acceptable diagnostic accuracy for fibrotic NASH in NAFLD patients with T2D.

Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques.

Hepatocellular Carcinoma (HCC) is the most frequent malignant liver tumor and the third cause of cancer-related deaths worldwide. For many years, the golden standard for HCC diagnosis has been the needle biopsy, which is invasive and carries risks. Computerized methods are due to achieve a noninvasive, accurate HCC detection process based on medical images. We developed image analysis and recognition methods to perform automatic and computer-aided diagnosis of HCC. Conventional approaches that combined advanced texture analysis, mainly based on Generalized Co-occurrence Matrices (GCM) with traditional classifiers, as well as deep learning approaches based on Convolutional Neural Networks (CNN) and Stacked Denoising Autoencoders (SAE), were involved in our research. The best accuracy of 91% was achieved for B-mode ultrasound images through CNN by our research group. In this work, we combined the classical approaches with CNN techniques, within B-mode ultrasound images. The combination was performed at the classifier level. The CNN features obtained at the output of various convolution layers were combined with powerful textural features, then supervised classifiers were employed. The experiments were conducted on two datasets, acquired with different ultrasound machines. The best performance, above 98%, overpassed our previous results, as well as representative state-of-the-art results.

Refining the Baveno VI elastography criteria for the definition of compensated advanced chronic liver disease.

BACKGROUND: The Baveno VI consensus proposed a dual liver stiffness (LS) by transient elastography threshold of <10 and >15 kPa for excluding and diagnosing compensated advanced chronic liver disease (cACLD) in the absence of other clinical signs. Herein, we aimed to validate these criteria in a real-world multicentre study. METHODS: We included 5,648 patients (mean age 51 ± 13 years, 53% males) from 10 European liver centres who had a liver biopsy and LS measurement within 6 months. We included patients with chronic hepatitis C (n = 2,913, 52%), non-alcoholic fatty liver disease (NAFLD, n = 1,073, 19%), alcohol-related liver disease (ALD, n = 946, 17%) or chronic hepatitis B (n = 716, 13%). cACLD was defined as fibrosis stage ≥F3. RESULTS: Overall, 3,606 (66%) and 987 (18%) patients had LS <10 and >15 kPa, respectively, while cACLD was histologically confirmed in 1,772 (31%) patients. The cut-offs of <10 and >15 kPa showed 75% sensitivity and 96% specificity to exclude and diagnose cACLD, respectively. Examining the ROC curve, a more optimal dual cut-off at <7 and >12 kPa, with 91% sensitivity and 92% specificity for excluding and diagnosing cACLD (AUC 0.87; 95% CI 0.86-0.88; p <0.001) was derived. Specifically, for ALD and NAFLD, a low cut-off of 8 kPa can be used (sensitivity=93%). For the unclassified patients, we derived a risk model based on common patient characteristics with better discrimination than LS alone (AUC 0.74 vs. 0.69; p <0.001). CONCLUSIONS: Instead of the Baveno VI proposed <10 and >15 kPa dual cut-offs, we found that the <8 kPa (or <7 kPa for viral hepatitis) and >12 kPa dual cut-offs have better diagnostic accuracy in cACLD. LAY SUMMARY: The term compensated advanced chronic liver disease (cACLD) was introduced in 2015 to describe the spectrum of advanced fibrosis and cirrhosis in asymptomatic patients. It was also suggested that cACLD could be diagnosed or ruled out based on specific liver stiffness values, which can be non-invasively measured by transient elastography. Herein, we assessed the suggested cut-off values and identified alternative values that offered better overall accuracy for diagnosing or ruling out cACLD.

Liver Stiffness Assessed by Ultrasound Shear Wave Elastography from General Electric Accurately Predicts Clinically Significant Portal Hypertension in Patients with Advanced Chronic Liver Disease.

PURPOSE: Clinically significant portal hypertension (CSPH) is responsible for most of the complications in patients with cirrhosis. Liver stiffness (LS) measurement by vibration-controlled transient elastography (VCTE) is currently used to evaluate CSPH. Bi-dimensional shear wave elastography from General Electric (2D-SWE.GE) has not yet been validated for the diagnosis of PHT. Our aims were to test whether 2D-SWE.GE-LS is able to evaluate CSPH, to determine the reliability criteria of the method and to compare its accuracy with that of VCTE-LS in this clinical setting. MATERIALS AND METHODS: Patients with chronic liver disease referred to hepatic catheterization (HVPG) were consecutively enrolled. HVPG and LS by both VCTE and 2D-SWE.GE were performed on the same day. The diagnostic performance of each LS method was compared against HVPG and between each other. RESULTS: 2D-SWE.GE-LS was possible in 123/127 (96.90 %) patients. The ability to record at least 5 LS measurements by 2D-SWE.GE and IQR < 30 % were the only features associated with reliable results. 2D-SWE.GE-LS was highly correlated with HVPG (r = 0.704; p < 0.0001), especially if HVPG < 10 mmHg and was significantly higher in patients with CSPH (15.52 vs. 8.14 kPa; p < 0.0001). For a cut-off value of 11.3 kPa, the AUROC of 2D-SWE.GE-LS to detect CSPH was 0.91, which was not inferior to VCTE-LS (0.92; p = 0.79). The diagnostic accuracy of LS by 2D-SWE.GE-LS to detect CSPH was similar with the one of VCTE-LS (83.74 % vs. 85.37 %; p = 0.238). The diagnostic accuracy was not enhanced by using different cut-off values which enhanced the sensitivity or the specificity. However, in the subgroup of compensated patients with alcoholic liver disease, 2D-SWE.GE-LS classified CSPH better than VCTE-LS (93.33 % vs. 85.71 %, p = 0.039). CONCLUSION: 2D-SWE.GE-LS has good accuracy, not inferior to VCTE-LS, for the diagnosis of CSPH.

Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images.

The emergence of deep-learning methods in different computer vision tasks has proved to offer increased detection, recognition or segmentation accuracy when large annotated image datasets are available. In the case of medical image processing and computer-aided diagnosis within ultrasound images, where the amount of available annotated data is smaller, a natural question arises: are deep-learning methods better than conventional machine-learning methods? How do the conventional machine-learning methods behave in comparison with deep-learning methods on the same dataset? Based on the study of various deep-learning architectures, a lightweight multi-resolution Convolutional Neural Network (CNN) architecture is proposed. It is suitable for differentiating, within ultrasound images, between the Hepatocellular Carcinoma (HCC), respectively the cirrhotic parenchyma (PAR) on which HCC had evolved. The proposed deep-learning model is compared with other CNN architectures that have been adapted by transfer learning for the ultrasound binary classification task, but also with conventional machine-learning (ML) solutions trained on textural features. The achieved results show that the deep-learning approach overcomes classical machine-learning solutions, by providing a higher classification performance.

Individual patient data meta-analysis of controlled attenuation parameter (CAP) technology for assessing steatosis.

BACKGROUND & AIMS: The prevalence of fatty liver underscores the need for non-invasive characterization of steatosis, such as the ultrasound based controlled attenuation parameter (CAP). Despite good diagnostic accuracy, clinical use of CAP is limited due to uncertainty regarding optimal cut-offs and the influence of covariates. We therefore conducted an individual patient data meta-analysis. METHODS: A review of the literature identified studies containing histology verified CAP data (M probe, vibration controlled transient elastography with FibroScan®) for grading of steatosis (S0-S3). Receiver operating characteristic analysis after correcting for center effects was used as well as mixed models to test the impact of covariates on CAP. The primary outcome was establishing CAP cut-offs for distinguishing steatosis grades. RESULTS: Data from 19/21 eligible papers were provided, comprising 3830/3968 (97%) of patients. Considering data overlap and exclusion criteria, 2735 patients were included in the final analysis (37% hepatitis B, 36% hepatitis C, 20% NAFLD/NASH, 7% other). Steatosis distribution was 51%/27%/16%/6% for S0/S1/S2/S3. CAP values in dB/m (95% CI) were influenced by several covariates with an estimated shift of 10 (4.5-17) for NAFLD/NASH patients, 10 (3.5-16) for diabetics and 4.4 (3.8-5.0) per BMI unit. Areas under the curves were 0.823 (0.809-0.837) and 0.865 (0.850-0.880) respectively. Optimal cut-offs were 248 (237-261) and 268 (257-284) for those above S0 and S1 respectively. CONCLUSIONS: CAP provides a standardized non-invasive measure of hepatic steatosis. Prevalence, etiology, diabetes, and BMI deserve consideration when interpreting CAP. Longitudinal data are needed to demonstrate how CAP relates to clinical outcomes. LAY SUMMARY: There is an increase in fatty liver for patients with chronic liver disease, linked to the epidemic of the obesity. Invasive liver biopsies are considered the best means of diagnosing fatty liver. The ultrasound based controlled attenuation parameter (CAP) can be used instead, but factors such as the underlying disease, BMI and diabetes must be taken into account. Registration: Prospero CRD42015027238.

Non-invasive ménage à trois for the prediction of high-risk varices: stepwise algorithm using lok score, liver and spleen stiffness.

BACKGROUND & AIMS: Liver stiffness (LS), spleen stiffness (SS) and serum markers have been proposed to non-invasively assess portal hypertension or oesophageal varices (EV) in cirrhotic patients. We aimed to evaluate the performance of a stepwise algorithm that combines Lok score with LS and SS for diagnosing high-risk EV (HREV) and to compare it with other already-validated non-invasive methods. METHODS: We performed a cross-sectional study including 136 consecutive compensated cirrhotic patients with various aetiologies, divided into training (90) and validation (46) set. Endoscopy was performed within 6 months from inclusion for EV screening. Spleen diameter was assessed by ultrasonography. LS and SS were measured using Fibroscan. Lok score, platelet count/spleen diameter ratio, LSM-spleen diameter to platelet ratio score and oesophageal varices risk score (EVRS) were calculated and their diagnostic accuracy for HREV was assessed. The algorithm classified patients as having/not-having HREV. Its performance was tested and compared in both groups. RESULTS: In the training set, all variables could select patients with HREV with moderate accuracy, the best being LSPS (AUROC = 0.818; 0.93 sensitivity; 0.63 specificity). EVRS, however, was the only independent predictor of HREV (OR = 1.521; P = 0.032). The algorithm correctly classified 69 (76.66%) patients in the training set (P < 0.0001) and 36 (78.26%) in the validation one. In the validation group, the algorithm performed slightly better than LSPS and EVRS, showing 100% sensitivity and negative predicted value. CONCLUSION: The stepwise algorithm combining Lok score, LS and SS could be used to select patients at low risk of having HREV and who may benefit from more distanced endoscopic evaluation.

Liver stiffness is influenced by a standardized meal in patients with chronic hepatitis C virus at different stages of fibrotic evolution.

UNLABELLED: Transient elastography (TE) is increasingly employed in clinical practice for the noninvasive detection of tissue fibrosis in patients with chronic liver disease (CLD), and particularly chronic hepatitis C virus (HCV)-related hepatitis. The present study was designed to provide a definitive characterization of the "confounding" increase in liver stiffness (LS) following a standardized meal in a consecutive population of 125 patients with chronic HCV infection at different stages of fibrotic evolution. LS values were obtained after overnight fasting and 15, 30, 45, 60, and 120 minutes following the onset of a standardized liquid meal (400 mL, 600 Kcal, 16.7% protein, 53.8% carbohydrates, 29.5% fat). An evident increase in LS values was observed 15 to 45 minutes after the onset of the meal with return to baseline premeal levels within 120 minutes in all patients. The peak postmeal delta increase in LS was progressively more marked with increasing stages of fibrosis (P < 0.001), becoming maximal in patients with cirrhosis. However, the probability of identifying the Metavir stage of fibrosis, the Child-Pugh class, or the presence/absence of esophageal varices with the postmeal delta increase in LS was inferior to that obtained with baseline LS values. CONCLUSION: The results of the present study provide definitive evidence of the confounding effect of a meal on the accuracy of LS measurements for the prediction of fibrosis stage in patients with chronic HCV hepatitis and suggest that a fasting period of 120 minutes should be observed before the performance of TE.

Multiparametric ultrasound evaluation of liver fibrosis, steatosis, and viscosity in patients with chronic liver disease.

AIMS: This study assessed the effectiveness of three ultrasound-based techniques (2D-SWE.PLUS, Att.PLUS, Vi.PLUS) for non-invasive evaluation of liver fibrosis, steatosis, and inflammation in chronic liver disease (CLD) patients.Materials and methods: Involving 209 consecutive compensated CLD patients, the study compared these ultrasound methods from Aixplorerwith standard Vibration-controlled Transient Elastography (VCTE) and Controlled Attenuation Parameter (CAP) from Fibroscan, alongside non-invasive serological markers. RESULTS: High validity rates were observed in measurements: 99% for VCTE, 89% for 2D-SWE.PLUS/Vi.PLUS, and 96.6% for Att.PLUS. 2D-SWE.PLUS showed a strong correlation with VCTE (R=0.91) and excelled at a lower Stability Index (80%), with optimal cut-offs for moderate and severe fibrosis at 8 kPa and 10 kPa, respectively. 2D-SWE.PLUS was superior to Fib4, eLIFT, APRI, BARD, and NFS in detecting advanced CLD. Att.PLUS moderately correlated with CAP (R=0.47) for steatosis grades, while Viscosity was highly effective in identifying significant fibrosis (AUC=0.87) but less so for inflammation. CONCLUSIONS: 2D-SWE.PLUS demonstrated superior diagnostic precision in liver fibrosis, exceeding other non-invasive markers. Att.PLUS was relatively accurate for liver steatosis, and viscosity more effectively indicated fibrosis stages than inflammation in CLD patients.

FAST and Agile-the MASLD drift: Validation of Agile 3+, Agile 4 and FAST scores in 246 biopsy-proven NAFLD patients meeting MASLD criteria of prevalent caucasian origin.

BACKGROUND: MASLD is a prevalent chronic liver condition with substantial clinical implications. This study aimed to assess the effectiveness of three new, elastography-based, scoring systems for advanced fibrosis ≥F3 (Agile 3+), cirrhosis F4 (Agile 4), and fibrotic NASH: NASH + NAS ≥4 + F≥2 (FAST score), in a cohort of biopsy-proven NAFLD meeting MASLD criteria. Our secondary aim was to compare their diagnostic performances with those of other fibrosis prediction tools: LSM-VCTE alone, and common, easily available scores (FIB-4 or APRI). METHODS: Single-center, retrospective study, on consecutive patients with baseline laboratory tests, liver biopsy, and reliable LSM-VCTE measurements. The discrimination between tests was evaluated by analyzing the AUROCs. Dual cut-off approaches were applied to rule-out and rule-in ≥F3, F4 and fibrotic NASH. We tested previously reported cut-off values and provided our best thresholds to achieve Se ≥85%, Se ≥90%, and Sp ≥90%, Sp ≥95%. RESULTS: Among 246 patients, 113 (45.9%) were women, and 75 (30.5%) presented diabetes. Agile 3+ and Agile 4 demonstrated excellent performance in identifying ≥F3 and F4, achieving AUROCs of 0.909 and 0.968, while the FAST score yielded acceptable results in distinguishing fibrotic NASH. When compared to FIB-4 and LSM-VCTE, both Agile 3+ and Agile 4 performed better than FIB-4 and had a similar performance to LSM-VCTE, but with higher diagnostic accuracy, hence reducing the grey zone. CONCLUSION: Agile 3+ and Agile 4 are reliable, non-invasive tests for identifying advanced fibrosis or cirrhosis in MASLD patients, while FAST score demonstrates moderate performance in identifying fibrotic NASH.

A global survey on the use of the international classification of diseases codes for metabolic dysfunction-associated fatty liver disease.

BACKGROUND: With the implementation of the 11th edition of the International Classification of Diseases (ICD-11) and the publication of the metabolic dysfunction-associated fatty liver disease (MAFLD) nomenclature in 2020, it is important to establish consensus for the coding of MAFLD in ICD-11. This will inform subsequent revisions of ICD-11. METHODS: Using the Qualtrics XM and WJX platforms, questionnaires were sent online to MAFLD-ICD-11 coding collaborators, authors of papers, and relevant association members. RESULTS: A total of 890 international experts in various fields from 61 countries responded to the survey. We also achieved full coverage of provincial-level administrative regions in China. 77.1% of respondents agreed that MAFLD should be represented in ICD-11 by updating NAFLD, with no significant regional differences (77.3% in Asia and 76.6% in non-Asia, p = 0.819). Over 80% of respondents agreed or somewhat agreed with the need to assign specific codes for progressive stages of MAFLD (i.e. steatohepatitis) (92.2%), MAFLD combined with comorbidities (84.1%), or MAFLD subtypes (i.e., lean, overweight/obese, and diabetic) (86.1%). CONCLUSIONS: This global survey by a collaborative panel of clinical, coding, health management and policy experts, indicates agreement that MAFLD should be coded in ICD-11. The data serves as a foundation for corresponding adjustments in the ICD-11 revision.

An international multidisciplinary consensus on pediatric metabolic dysfunction-associated fatty liver disease.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent in children and adolescents, particularly those with obesity. NAFLD is considered a hepatic manifestation of the metabolic syndrome due to its close associations with abdominal obesity, insulin resistance, and atherogenic dyslipidemia. Experts have proposed an alternative terminology, metabolic dysfunction-associated fatty liver disease (MAFLD), to better reflect its pathophysiology. This study aimed to develop consensus statements and recommendations for pediatric MAFLD through collaboration among international experts. METHODS: A group of 65 experts from 35 countries and six continents, including pediatricians, hepatologists, and endocrinologists, participated in a consensus development process. The process encompassed various aspects of pediatric MAFLD, including epidemiology, mechanisms, screening, and management. FINDINGS: In round 1, we received 65 surveys from 35 countries and analyzed these results, which informed us that 73.3% of respondents agreed with 20 draft statements while 23.8% agreed somewhat. The mean percentage of agreement or somewhat agreement increased to 80.85% and 15.75%, respectively, in round 2. The final statements covered a wide range of topics related to epidemiology, pathophysiology, and strategies for screening and managing pediatric MAFLD. CONCLUSIONS: The consensus statements and recommendations developed by an international expert panel serve to optimize clinical outcomes and improve the quality of life for children and adolescents with MAFLD. These findings emphasize the need for standardized approaches in diagnosing and treating pediatric MAFLD. FUNDING: This work was funded by the National Natural Science Foundation of China (82070588, 82370577), the National Key R&D Program of China (2023YFA1800801), National High Level Hospital Clinical Research Funding (2022-PUMCH-C-014), the Wuxi Taihu Talent Plan (DJTD202106), and the Medical Key Discipline Program of Wuxi Health Commission (ZDXK2021007).

Exploring Opportunities to Enhance the Screening and Surveillance of Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease (NAFLD) through Risk Stratification Algorithms Incorporating Ultrasound Elastography.

Non-alcoholic fatty liver disease (NAFLD), with its progressive form, non-alcoholic steatohepatitis (NASH), has emerged as a significant public health concern, affecting over 30% of the global population. Hepatocellular carcinoma (HCC), a complication associated with both cirrhotic and non-cirrhotic NAFLD, has shown a significant increase in incidence. A substantial proportion of NAFLD-related HCC occurs in non-cirrhotic livers, highlighting the need for improved risk stratification and surveillance strategies. This comprehensive review explores the potential role of liver ultrasound elastography as a risk assessment tool for HCC development in NAFLD and highlights the importance of effective screening tools for early, cost-effective detection and improved management of NAFLD-related HCC. The integration of non-invasive tools and algorithms into risk stratification strategies could have the capacity to enhance NAFLD-related HCC screening and surveillance effectiveness. Alongside exploring the potential advancement of non-invasive tools and algorithms for effectively stratifying HCC risk in NAFLD, we offer essential perspectives that could enable readers to improve the personalized assessment of NAFLD-related HCC risk through a more methodical screening approach.

How to Identify Advanced Fibrosis in Adult Patients with Non-Alcoholic Fatty Liver Disease (NAFLD) and Non-Alcoholic Steatohepatitis (NASH) Using Ultrasound Elastography-A Review of the Literature and Proposed Multistep Approach.

Non-alcoholic fatty liver disease (NAFLD), and its progressive form, non-alcoholic steatohepatitis (NASH), represent, nowadays, real challenges for the healthcare system. Liver fibrosis is the most important prognostic factor for NAFLD, and advanced fibrosis is associated with higher liver-related mortality rates. Therefore, the key issues in NAFLD are the differentiation of NASH from simple steatosis and identification of advanced hepatic fibrosis. We critically reviewed the ultrasound (US) elastography techniques for the quantitative characterization of fibrosis, steatosis, and inflammation in NAFLD and NASH, with a specific focus on how to differentiate advanced fibrosis in adult patients. Vibration-controlled transient elastography (VCTE) is still the most utilized and validated elastography method for liver fibrosis assessment. The recently developed point shear wave elastography (pSWE) and two-dimensional shear wave elastography (2D-SWE) techniques that use multiparametric approaches could bring essential improvements to diagnosis and risk stratification.

MRI-Based Radiomics in Bladder Cancer: A Systematic Review and Radiomics Quality Score Assessment.

(1): Background: With the recent introduction of vesical imaging reporting and data system (VI-RADS), magnetic resonance imaging (MRI) has become the main imaging method used for the preoperative local staging of bladder cancer (BCa). However, the VI-RADS score is subject to interobserver variability and cannot provide information about tumor cellularity. These limitations may be overcome by using a quantitative approach, such as the new emerging domain of radiomics. (2) Aim: To systematically review published studies on the use of MRI-based radiomics in bladder cancer. (3) Materials and Methods: We performed literature research using the PubMed MEDLINE, Scopus, and Web of Science databases using PRISMA principles. A total of 1092 papers that addressed the use of radiomics for BC staging, grading, and treatment response were retrieved using the keywords "bladder cancer", "magnetic resonance imaging", "radiomics", and "textural analysis". (4) Results: 26 papers met the eligibility criteria and were included in the final review. The principal applications of radiomics were preoperative tumor staging (n = 13), preoperative prediction of tumor grade or molecular correlates (n = 9), and prediction of prognosis/response to neoadjuvant therapy (n = 4). Most of the developed radiomics models included second-order features mainly derived from filtered images. These models were validated in 16 studies. The average radiomics quality score was 11.7, ranging between 8.33% and 52.77%. (5) Conclusions: MRI-based radiomics holds promise as a quantitative imaging biomarker of BCa characterization and prognosis. However, there is still need for improving the standardization of image preprocessing, feature extraction, and external validation before applying radiomics models in the clinical setting.

An international multidisciplinary consensus statement on MAFLD and the risk of CVD.

BACKGROUND: Fatty liver disease in the absence of excessive alcohol consumption is an increasingly common condition with a global prevalence of ~ 25-30% and is also associated with cardiovascular disease (CVD). Since systemic metabolic dysfunction underlies its pathogenesis, the term metabolic (dysfunction)-associated fatty liver disease (MAFLD) has been proposed for this condition. MAFLD is closely intertwined with obesity, type 2 diabetes mellitus and atherogenic dyslipidemia, which are established cardiovascular risk factors. Unlike CVD, which has received attention in the literature on fatty liver disease, the CVD risk associated with MAFLD is often underestimated, especially among Cardiologists. METHODS AND RESULTS: A multidisciplinary panel of fifty-two international experts comprising Hepatologists, Endocrinologists, Diabetologists, Cardiologists and Family Physicians from six continents (Asia, Europe, North America, South America, Africa and Oceania) participated in a formal Delphi survey and developed consensus statements on the association between MAFLD and the risk of CVD. Statements were developed on different aspects of CVD risk, ranging from epidemiology to mechanisms, screening, and management. CONCULSIONS: The expert panel identified important clinical associations between MAFLD and the risk of CVD that could serve to increase awareness of the adverse metabolic and cardiovascular outcomes of MAFLD. Finally, the expert panel also suggests potential areas for future research.

More than Meets the Eye: Using Textural Analysis and Artificial Intelligence as Decision Support Tools in Prostate Cancer Diagnosis-A Systematic Review.

(1) Introduction: Multiparametric magnetic resonance imaging (mpMRI) is the main imagistic tool employed to assess patients suspected of harboring prostate cancer (PCa), setting the indication for targeted prostate biopsy. However, both mpMRI and targeted prostate biopsy are operator dependent. The past decade has been marked by the emerging domain of radiomics and artificial intelligence (AI), with extended application in medical diagnosis and treatment processes. (2) Aim: To present the current state of the art regarding decision support tools based on texture analysis and AI for the prediction of aggressiveness and biopsy assistance. (3) Materials and Methods: We performed literature research using PubMed MeSH, Scopus and WoS (Web of Science) databases and screened the retrieved papers using PRISMA principles. Articles that addressed PCa diagnosis and staging assisted by texture analysis and AI algorithms were included. (4) Results: 359 papers were retrieved using the keywords "prostate cancer", "MRI", "radiomics", "textural analysis", "artificial intelligence", "computer assisted diagnosis", out of which 35 were included in the final review. In total, 24 articles were presenting PCa diagnosis and prediction of aggressiveness, 7 addressed extracapsular extension assessment and 4 tackled computer-assisted targeted prostate biopsies. (5) Conclusions: The fusion of radiomics and AI has the potential of becoming an everyday tool in the process of diagnosis and staging of the prostate malignancies.

Noninvasive Assessment of Hepatitis C Virus Infected Patients Using Vibration-Controlled Transient Elastography.

Chronic infection with hepatitis C virus (HCV) is one of the leading causes of cirrhosis and hepatocellular carcinoma (HCC). Surveillance of these patients is an essential strategy in the prevention chain, including in the pre/post-antiviral treatment states. Ultrasound elastography techniques are emerging as key methods in the assessment of liver diseases, with a number of advantages such as their rapid, noninvasive, and cost-effective characters. The present paper critically reviews the performance of vibration-controlled transient elastography (VCTE) in the assessment of HCV patients. VCTE measures liver stiffness (LS) and the ultrasonic attenuation through the embedded controlled attenuation parameter (CAP), providing the clinician with a tool for assessing fibrosis, cirrhosis, and steatosis in a noninvasive manner. Moreover, standardized LS values enable proper staging of the underlying fibrosis, leading to an accurate identification of a subset of HCV patients that present a high risk for complications. In addition, VCTE is a valuable technique in evaluating liver fibrosis prior to HCV therapy. However, its applicability in monitoring fibrosis regression after HCV eradication is currently limited and further studies should focus on extending the boundaries of VCTE in this context. From a different perspective, VCTE may be effective in identifying clinically significant portal hypertension (CSPH). An emerging prospect of clinical significance that warrants further study is the identification of esophageal varices. Our opinion is that the advantages of VCTE currently outweigh those of other surveillance methods.