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.

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.

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.

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.

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.

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.

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.

Performance of Ultrasound Techniques and the Potential of Artificial Intelligence in the Evaluation of Hepatocellular Carcinoma and Non-Alcoholic Fatty Liver Disease.

Global statistics show an increasing percentage of patients that develop non-alcoholic fatty liver disease (NAFLD) and NAFLD-related hepatocellular carcinoma (HCC), even in the absence of cirrhosis. In the present review, we analyzed the diagnostic performance of ultrasonography (US) in the non-invasive evaluation of NAFLD and NAFLD-related HCC, as well as possibilities of optimizing US diagnosis with the help of artificial intelligence (AI) assistance. To date, US is the first-line examination recommended in the screening of patients with clinical suspicion of NAFLD, as it is readily available and leads to a better disease-specific surveillance. However, the conventional US presents limitations that significantly hamper its applicability in quantifying NAFLD and accurately characterizing a given focal liver lesion (FLL). Ultrasound contrast agents (UCAs) are an essential add-on to the conventional B-mode US and to the Doppler US that further empower this method, allowing the evaluation of the enhancement properties and the vascular architecture of FLLs, in comparison to the background parenchyma. The current paper also explores the new universe of AI and the various implications of deep learning algorithms in the evaluation of NAFLD and NAFLD-related HCC through US methods, concluding that it could potentially be a game changer for patient care.

Assessment of hepatic steatosis by controlled attenuation parameter using the M and XL probes: an individual patient data meta-analysis.

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.

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.

Hepatocellular Carcinoma and Non-Alcoholic Fatty Liver Disease: A Step Forward for Better Evaluation Using Ultrasound Elastography.

The increasing prevalence of non-alcoholic fatty liver disease (NAFLD) in the general population prompts for a quick response from physicians. As NAFLD can progress to liver fibrosis, cirrhosis, and even hepatocellular carcinoma (HCC), new non-invasive, rapid, cost-effective diagnostic methods are needed. In this review, we explore the diagnostic performance of ultrasound elastography for non-invasive assessment of NAFLD and NAFLD-related HCC. Elastography provides a new dimension to the conventional ultrasound examination, by adding the liver stiffness quantification in the diagnostic algorithm. Whilst the most efficient elastographic techniques in staging liver fibrosis in NAFLD are vibration controlled transient elastography (VCTE) and 2D-Shear wave elastography (2D-SWE), VCTE presents the upside of assessing steatosis through the controlled attenuation parameter (CAP). Hereby, we have also critically reviewed the most important elastographic techniques for the quantitative characterization of focal liver lesions (FLLs), focusing on HCC: Point shear wave elastography (pSWE) and 2D-SWE. As our paper shows, elastography should not be considered as a substitute for FLL biopsy because of the stiffness values overlap. Furthermore, by using non-invasive, disease-specific surveillance tools, such as US elastography, a subset of the non-cirrhotic NAFLD patients at risk for developing HCC can be detected early, leading to a better outcome. A recent ultrasomics study exemplified the wide potential of 2D-SWE to differentiate benign FLLs from malignant ones, guiding the clinician towards the next steps of diagnosis and contributing to better long-term disease surveillance.

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.

Ultrasonographic elastography, no longer for the "select few".

.

Good performance of liver stiffness measurement in the prediction of postoperative hepatic decompensation in patients with cirrhosis complicated with hepatocellular carcinoma.

The evaluation of patients with early hepatocellular carcinoma (HCC) referred for liver resection is still a matter of debate. Aims: 1) to compare liver stiffness measurement (LSM) by transient elastography with hepatic venous pressure gradient (HVPG) in the prediction of decompensation after liver resection in patients with cirrhosis and early HCC; 2) to identify which definition for posthepatectomy liver failure is better associated with survival. MATERIAL AND METHODS: Fifty-one patients (MELD score of 10±3) were included. In this group, 34 patients underwent HVPG measurement, of which 13 (38%) had clinically significant portal hypertension (CSPH) and 35 patients underwent LSM (21.8±17.9 kPa). The study's end-points were: posthepatectomy liver failure (PHLF) defined according to International Study Group of Liver Surgery criteria and 3-month decompensation defined as de novo ascites, variceal bleeding, jaundice, hepatic encephalopathy and acute kidney injury. The performance of LSM compared to HVPG in predicting the end-points were assessed by AUROC curves and accuracy. RESULTS: Twenty (39%) patients developed PHLF and 15 (29%) developed decompensationat 3 months. Three-month decompensation tended to be better correlated with survival. LSM performed well in predicting decompensation at 3 months (AUROC=0.78, 95%CI: 0.63-0.94; p=0.01), comparable with HVPG (AUROC=0.89, 95%CI: 0.79-1.00; p<0.01) (DeLong test p=0.21). LSM was not sufficiently accurate to predict PHLF. CONCLUSION: LSM has a similar performance to HVPG in predicting decompensation at 3 months in patients with early HCC submitted to liver resection. Three-month decompensation is better associated with survival.

The pursuit of normal reference values of pancreas stiffness by using Acoustic Radiation Force Impulse (ARFI) elastography.

AIM: The purpose of this study is to evaluate pancreatic stiffness by ARFI abdominal elastography. In the current literature, there are relatively few studies that have assessed the clinical utility of this technique. MATERIAL AND METHOD: A number of 37 healthy subjects were included. The data were collected in a prospective manner and afterwards included in an observational, analytical and longitudinal study. Subsequently viewing the pancreatic parenchyma in bidimensional mode (2D-US) mode, 10 shear wave velocity (SWV) measurements for each segment: head, body and tail were performed. Statistical analysis by regression models targeted also the possible influence of other factors in assessing SWV. A comparative analysis was performed regarding the statistical significance of 5 versus 10 SWV measurements for each segment. RESULTS: The pancreas was entirely evaluated in all subjects. The mean SWV from the entire parenchyma was 1.216 m/s±0.36 and between the three segments SWV were similar (head: 1.224 m/s, body: 1.227 m/s and tail: 1.191 m/s). A ratio of the IQR/Median >0.4 was interpreted as statistically invalid, relevant data being highlighted in the percentage of 83.78% for the head of the pancreas, 78.37% for the body, and 67.56% at the caudal level. Significant correlations were observed between the data (mean and median SWV) provided by the group with 5 measurements of the SWV versus the standard group: 93.9% for the head, 96.6% for the body, and 98.7% accordingly to the tail. CONCLUSIONS: SWV determination by percutaneous approach represents a useful imaging method for evaluating pancreatic stiffness, of course within these limitations. Because we did not observe statistically significant differences between the results obtained by 5 or 10 measurements, we suggest that it would be sufficient to perform only five measurements of the SWV per pancreatic segment. The data obtained in the normal pancreas could be used in future comparative assessments regarding the inflammatory or tumoral pathology of the pancreas.

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.

Noninvasive assessment of liver steatosis using ultrasound methods.

Hepatic steatosis is a condition frequently encountered in clinical practice, with potential progression towards chirrhosis and hepatocellular carcinoma. Ultrasonography (US) is one of the noninvasive imaging techniques used in the diagnosis of steatosis. We will review the US diagnostic criteria, the US performance in the diagnosis and grading of hepatic steatosis, the US steatosis models, but also its limitations in the diagnosis of steatosis. In addition, we will discuss 2 modern methods of assessing hepatic steatosis using ultrasounds, namely the computerized processing of data forming the US image and the controlled attenuation parameter measured with unidimensional transient elastography.

Transient elastography for the detection of hepatocellular carcinoma in viral C liver cirrhosis. Is there something else than increased liver stiffness?

BACKGROUND & AIMS: Liver stiffness (LS) is increased in liver cirrhosis, higher values being associated with complications, among them the development of hepatocellular carcinoma (HCC). However, LS values alone cannot accurately differentiate patients with HCC. Therefore, our aim was to study the performance of LS measurement data and common biomarkers for the detection of HCC in HCV related liver cirrhosis. METHODS: We performed a case matching study comparing HCV cirrhotic patients with and without HCC (72 in each group) that were identical in terms of sex, age, BMI and duration of HCV infection. All patients underwent LS measurement, endoscopy, liver imaging and liver function tests. A multiple regression analysis was performed and a HCC detection model was calculated, which was further validated in another group of 40 HCV infected cirrhotics, of whom 52% had HCC. RESULTS: In the HCC group, LS was significantly higher (42 vs 27 kPa, p<0.0001). In the multivariate analysis higher values of LS, alanine-aminotransferase (ALAT), alpha-fetoprotein (AFP) and interquartile range (IQR) of LS measurements were independently associated with the presence of HCC (p<0.0001 for all parameters; Odds Ratios of 8.27, 1.01, 1.04 and 1.16, respectively). The detection model combining the four variables showed a good diagnostic performance in both training and validation groups, with AUROCs of 0.86 and 0.8, respectively. All variables were also positively correlated with tumor size. CONCLUSION: In HCV related cirrhosis, HCC is associated with increased LS and IQR values and high ALAT and AFP levels. By combining these four parameters into a regression model, liver cancer may be noninvasively predicted with good accuracy.

ARFI quantitative elastography of the submandibular glands. Normal measurements and the diagnosis value of the method in radiation submaxillitis.

OBJECTIVES: Evaluation of Acoustic Radiation Force Impulse Imaging (ARFI) elastography performance in predicting the elasticity of the submandibular glands in normal situations and after radiation therapy. MATERIAL AND METHOD: A number of 54 normal submandibular glands from 27 voluntary subjects and 33 pathological submandibular glands (radiation submaxillities) from 18 patients who had undergone radiation therapy for various cervical and facial oncological conditions were included in study. All the patients had undergone a B mode ultrasonography (Tissue Harmonic Imaging, 8-14 MHz) while the submandibular volume was determined and subsequently an ARFI examination while the shear wave velocity (SWV) was measured (in the central, peripheral and subcapsular areas, with the results expressed in m/s). RESULTS: In the volunteers' group the mean value of the SWV of the left submandibular gland was 1.68 ± 0.46 m/s, determined in the centre of the gland, 1.88 ± 0.4 m/s in the periphery (corresponding to the subcapsular parenchyma) and the SWV of the right submandibular gland was 1.74 ± 0.35 m/s (centrally) and 1.84 ± 0.43 m/s in the periphery. The mean value of all measurements was 1.82 ± 0.41 m/s. The mean volume of the glands was 7.97 ± 2.63 cm3. In the group of patients who had underwent radiation therapy (at least 35Gy), the mean value of the SWV was 2.24 ± 0.49 m/s centrally and 2.1 ± 0.58 m/s in the periphery on the left and 1.99 ± 0.5 m/s centrally and 2.21 ± 0.52 m/s in the periphery on the right. The mean value of all the measurements was 2.13 ± 0.52 m/s and the mean volume of the gland was 5.95 ± 4.16 cm3. CONCLUSIONS: Elastography using ARFI technique is a valid examination in the evaluation of the normal and pathological submandibular gland stiffness. The values of the shear wave velocities that correspond to a normal stiffness, determined through the ARFI technique, are similar in the two glands. After cervical and facial radiation therapy the values of the SWV are increased, indicating a change in the consistency of the gland thus implying a structural transformation. The ARFI technique can be used in the evaluation of the salivary glands pathology.