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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.
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Classificação Internacional de Doenças , Hepatopatia Gordurosa não Alcoólica , Humanos , Hepatopatia Gordurosa não Alcoólica/epidemiologia , Hepatopatia Gordurosa não Alcoólica/classificação , Inquéritos e Questionários , Saúde GlobalRESUMO
BACKGROUND & AIMS: Agile scores, including liver stiffness measurements (LSM) and routine clinical/laboratory biomarkers, have been developed for advanced fibrosis (F≥3) and cirrhosis (F4), respectively, in patients with metabolic dysfunction-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: 2,348) with LSM, liver biopsy and laboratory tests within 6 months. FIB-4, Agile 3+ and Agile 4 scores were calculated. RESULTS: For F≥3, the 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% sensitivity/specificity, correct classification rates in MASLD were 66% vs. 61% using Agile 3+ vs. LS dual cut-offs and 71% vs. 67% in ALD, respectively. 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 ALD (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. IMPACT AND IMPLICATIONS: As of today, it is accepted that there will be no single non-invasive test or an isolated cut-off for identifying patients with advanced chronic liver disease. Here, we confirmed that Agile 3+ and Agile 4 scores are useful alternatives to simple liver stiffness measurement in diagnosing advanced fibrosis/cirrhosis in steatotic liver disease, but they do not perform as well in chronic viral hepatitis. Agile scores can help optimize the diagnosis of advanced fibrosis/cirrhosis in a dual cut-off strategy by reducing the number of indeterminate results either alone or in a sequential strategy after FIB-4. The combination of Agile scores and liver stiffness measurement can further increase our confidence in a positive diagnosis of advanced fibrosis/cirrhosis. These novel combination strategies can be useful tools to predict the likelihood of advanced stages of liver disease with the highest possible accuracy in a secondary/tertiary healthcare setting.
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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.
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Técnicas de Imagem por Elasticidade , Cirrose Hepática , Hepatopatia Gordurosa não Alcoólica , Humanos , Hepatopatia Gordurosa não Alcoólica/patologia , Hepatopatia Gordurosa não Alcoólica/diagnóstico , Feminino , Masculino , Pessoa de Meia-Idade , Biópsia/métodos , Técnicas de Imagem por Elasticidade/métodos , Estudos Retrospectivos , Cirrose Hepática/patologia , Cirrose Hepática/diagnóstico , Adulto , Fígado/patologia , População Branca , Índice de Gravidade de Doença , IdosoRESUMO
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).
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Consenso , Hepatopatia Gordurosa não Alcoólica , Humanos , Hepatopatia Gordurosa não Alcoólica/epidemiologia , Hepatopatia Gordurosa não Alcoólica/terapia , Hepatopatia Gordurosa não Alcoólica/metabolismo , Hepatopatia Gordurosa não Alcoólica/diagnóstico , Criança , Adolescente , Síndrome Metabólica/epidemiologia , Síndrome Metabólica/diagnóstico , Síndrome Metabólica/terapia , Síndrome Metabólica/metabolismoRESUMO
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.
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Técnicas de Imagem por Elasticidade , Fígado Gorduroso , Cirrose Hepática , Humanos , Feminino , Masculino , Técnicas de Imagem por Elasticidade/métodos , Cirrose Hepática/diagnóstico por imagem , Pessoa de Meia-Idade , Viscosidade , Fígado Gorduroso/diagnóstico por imagem , Reprodutibilidade dos Testes , Doença Crônica , Fígado/diagnóstico por imagem , Adulto , Idoso , Ultrassonografia/métodos , Hepatopatias/diagnóstico por imagemRESUMO
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.
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(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.
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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.
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Doenças Cardiovasculares , Diabetes Mellitus Tipo 2 , Hepatopatias , Hepatopatia Gordurosa não Alcoólica , Humanos , Doenças Cardiovasculares/epidemiologia , Doenças Cardiovasculares/etiologia , Diabetes Mellitus Tipo 2/complicações , Diabetes Mellitus Tipo 2/epidemiologia , Ásia , ConsensoRESUMO
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.
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Carcinoma Hepatocelular , Aprendizado Profundo , Neoplasias Hepáticas , Humanos , Neoplasias Hepáticas/patologia , Ultrassonografia/métodos , Redes Neurais de ComputaçãoRESUMO
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.
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Diabetes Mellitus Tipo 2 , Hepatopatia Gordurosa não Alcoólica , Humanos , Hepatopatia Gordurosa não Alcoólica/complicações , Hepatopatia Gordurosa não Alcoólica/diagnóstico , Diabetes Mellitus Tipo 2/complicações , Cirrose Hepática/diagnóstico , Cirrose Hepática/etiologia , Índice de Gravidade de Doença , Fígado/diagnóstico por imagem , Fígado/patologia , Fibrose , Gravidade do Paciente , Curva ROC , Biópsia , Aspartato AminotransferasesRESUMO
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.
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(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.
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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.
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INTRODUCTION: Telemedicine has emerged as a critical technology to mitigate SARS-CoV-2 infection. We aim in this work to explore how general practitioners (GPs) perceived the use of telemedicine, recently recognized and reimbursed by the Public Health Insurance House (PHIH) for primary care (PC) provision. METHODS: A cross-sectional study was performed in 2020 in one county of Romania using an anonymous questionnaire that assessed physicians' perceptions regarding teleconsultation, reliability in tele-decision, remote pathology management, pregnant women's surveillance, patients' satisfaction with telemedicine, the need for its further reimbursement. Bivariate correlation was used to measure associations between the investigated issues. RESULTS: More than a quarter of GPs (28.6%) found it easier to address patients' healthcare needs remotely, while 60.7% considered time-consuming teleconsultations compared to face-to-face visits. Tele-diagnostic uncertainty was expressed by 64.3% of physicians, and a quarter were confident in tele-decisions. Almost half of GPs (43%) observed patients' satisfaction with tele-visits, while half said patients encountered difficulties using technology. A large percentage of doctors (62.5%) perceived that patients felt as well treated by virtual as in-person visit and 91.1% suggested post-pandemic reimbursement. The results of the bivariate correlation showed that physicians who perceived positive patient feedback on telemedicine were more supportive of subsequent reimbursement. CONCLUSION: This study showed the GPs' positive perception of the use of telemedicine. Its adoption in PC has shed light on the shadows of the pandemic. The time-consuming nature of teleconsultations, uncertainty in tele-decisions, patients' difficulties in using technology were seen as shadows of telecare. However, most of the GPs surveyed agreed with the need for further reimbursement. Future work should focus on innovative solutions for integrating telemedicine as complementary form of PC, the need for telemedicine-based training for GPs to improve capacity building, and patients' perceptions of virtual care, helping to build trust and satisfaction.
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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.
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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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Técnicas de Imagem por Elasticidade/métodos , Fígado/patologia , Hepatopatia Gordurosa não Alcoólica/diagnóstico por imagem , Adulto , Área Sob a Curva , Biópsia , Índice de Massa Corporal , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Hepatopatia Gordurosa não Alcoólica/etiologia , Curva ROC , Índice de Gravidade de DoençaRESUMO
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.
Assuntos
Técnicas de Imagem por Elasticidade , Hepatite B Crônica , Hepatite Alcoólica , Cirrose Hepática , Fígado , Hepatopatia Gordurosa não Alcoólica , Biópsia , Precisão da Medição Dimensional , Elasticidade , Técnicas de Imagem por Elasticidade/métodos , Técnicas de Imagem por Elasticidade/normas , Técnicas de Imagem por Elasticidade/estatística & dados numéricos , Europa (Continente)/epidemiologia , Feminino , Hepatite B Crônica/complicações , Hepatite B Crônica/epidemiologia , Hepatite B Crônica/patologia , Hepatite Alcoólica/complicações , Hepatite Alcoólica/epidemiologia , Hepatite Alcoólica/patologia , Humanos , Fígado/diagnóstico por imagem , Fígado/patologia , Cirrose Hepática/diagnóstico , Cirrose Hepática/epidemiologia , Cirrose Hepática/etiologia , Masculino , Pessoa de Meia-Idade , Hepatopatia Gordurosa não Alcoólica/complicações , Hepatopatia Gordurosa não Alcoólica/epidemiologia , Hepatopatia Gordurosa não Alcoólica/patologia , Gravidade do Paciente , Sensibilidade e EspecificidadeRESUMO
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.
RESUMO
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.
Assuntos
Carcinoma Hepatocelular , Aprendizado Profundo , Neoplasias Hepáticas , Aprendizado de Máquina , Ultrassonografia , Carcinoma Hepatocelular/diagnóstico por imagem , Humanos , Processamento de Imagem Assistida por Computador , Neoplasias Hepáticas/diagnóstico por imagem , Redes Neurais de ComputaçãoRESUMO
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