ReviewClinical and molecular hepatology2017
Imaging evaluation of non-alcoholic fatty liver disease: focused on quantification.
Review in Clinical and molecular hepatology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
80 citing papers in PubMed, 2 syntheses or guidelines pooled it, 162 citations in OpenAlex.
- Liver Fat Quantification and Steatosis Grading in Fatty Liver Disease by Magnetic Resonance Imaging: Systematic Review and Meta-Analysis.Journal of gastroenterology and hepatology · 2025Pooled it
- The association of metabolic dysfunction-associated steatotic liver disease (MASLD) with the risk of myocardial infarction: a systematic review and meta-analysis.Annals of medicine · 2024Pooled it
- Trial
- Attenuation imaging and hepatorenal index composite score for the noninvasive assessment of hepatic steatosis in chronic liver disease: a prospective multicenter study.Journal of medical ultrasonics (2001) · 2026Article
- Efficacy of CPAP Therapy on Liver Steatosis and Insulin Resistance in Fatty Liver Patients With Obstructive Sleep Apnea: A 4-Year Follow-Up Cohort Study.The Kaohsiung journal of medical sciences · 2026Article
- Article
- Prevalence and risk factors for metabolic dysfunction-associated steatotic liver disease in Sweden: Insights from the SCAPIS cohort.Journal of internal medicine · 2026Article
- Dose-response association between metabolic syndrome component count and metabolic dysfunction-associated fatty liver disease, and independent graded association of visceral fat area: a cross-sectional study in a health-checkup population.Frontiers in public health · 2026Article
- A novel liver image classification network for accurate diagnosis of liver diseases.Scientific reports · 2025Article
- 3D multiparametric ultrasound imaging of steatotic liver disease in a study with male rats.Nature communications · 2025Article
- Attenuation Based Quantitative Evaluation of Hepatic Steatosis Using US: Current Status and Future Perspective.Journal of the Korean Society of Radiology · 2025Review
- Correlation between ultrasound-based hepatic steatosis grade and thyroid hormone levels.Gland surgery · 2025Article
- Use of Metabolic Scores and Lipid Ratios to Predict Metabolic Dysfunction-Associated Steatotic Liver Disease Onset in Patients with Inflammatory Bowel Diseases.Journal of clinical medicine · 2025Article
- The Management of Cardiometabolic Risk in MAFLD: Therapeutic Strategies to Modulate Deranged Metabolism and Cholesterol Levels.Medicina (Kaunas, Lithuania) · 2025Review
- Triglyceride-glucose index and related parameters in the diagnosis and predictive efficacy for older adults with NAFLD/MASLD: a prospective cohort study.Frontiers in medicine · 2025Article
- Inter- and Intraobserver variability of attenuation coefficient measurement in innovative ultrasound diagnosis of metabolic dysfunction-associated steatotic liver disease: a cross-sectional study.Frontiers in medicine · 2025Article
- Exploring Biomarkers in Nonalcoholic Fatty Liver Disease Among Individuals With Type 2 Diabetes Mellitus.Journal of clinical gastroenterology · 2025Review
- Ultrasound Versus Elastography in the Diagnosis of Hepatic Steatosis: Evaluation of Traditional Machine Learning Versus Deep Learning.Sensors (Basel, Switzerland) · 2024Article
- The Development of a Non-Invasive Screening Method Based on Serum microRNAs to Quantify the Percentage of Liver Steatosis.Biomolecules · 2024Article
- Utilizing fully-automated 3D organ segmentation for hepatic steatosis assessment with CT attenuation-based parameters.European radiology · 2024Article
20 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-alcoholic fatty liver disease (NAFLD) has been an emerging major health problem, and the most common cause of chronic liver disease in Western countries. Traditionally, liver biopsy has been gold standard method for quantification of hepatic steatosis. However, its invasive nature with potential complication as well as measurement variability are major problem. Thus, various imaging studies have been used for evaluation of hepatic steatosis. Ultrasonography provides fairly good accuracy to detect moderate-to-severe degree hepatic steatosis, but limited accuracy for mild steatosis. Operator-dependency and subjective/qualitative nature of examination are another major drawbacks of ultrasonography. Computed tomography can be considered as an unsuitable imaging modality for evaluation of NAFLD due to potential risk of radiation exposure and limited accuracy in detecting mild steatosis. Both magnetic resonance spectroscopy and magnetic resonance imaging using chemical shift technique provide highly accurate and reproducible diagnostic performance for evaluating NAFLD, and therefore, have been used in many clinical trials as a non-invasive reference of standard method.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.