ArticleIEEE journal of translational engineering in health and medicine2020
Ultrasound-Based Attenuation Imaging for the Non-Invasive Quantification of Liver Fat - A Pilot Study on Feasibility and Inter-Observer Variability.
Article in IEEE journal of translational engineering in health and medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.
- Assessment of the Diagnostic Performance and Clinical Impact of AI in Hepatic Steatosis: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Accuracy of the ultrasound attenuation coefficient for the evaluation of hepatic steatosis: a systematic review and meta-analysis of prospective studies.Ultrasonography (Seoul, Korea) · 2022Pooled it
- Quantitative Ultrasound for Hepatic Steatosis: A Systematic Review Highlighting the Diagnostic Performance of Ultrasound-Derived Fat Fraction.Diagnostics (Basel, Switzerland) · 2025Review
- Ultrasound derived fat fraction indicates reduction of liver fat content after lifestyle modification in obese patients.Clinical hemorheology and microcirculation · 2025Article
- Depth-Dependent Variability in Ultrasound Attenuation Imaging for Hepatic Steatosis: A Pilot Study of ATI and HRI in Healthy Volunteers.Journal of imaging · 2025Article
- Application of Quantitative Ultrasonography and Artificial Intelligence for Assessing Severity of Fatty Liver: A Pilot Study.Diagnostics (Basel, Switzerland) · 2024Article
- Comparison of Ultrasound Attenuation Imaging Using a Linear versus a Conventional Convex Probe: A Volunteer Study.Diagnostics (Basel, Switzerland) · 2024Article
- Confounders of Ultrasound Attenuation Imaging in a Linear Probe Using the Canon Aplio i800 System: A Phantom Study.Diagnostics (Basel, Switzerland) · 2024Article
- Noninvasive assessment of paediatric hepatic steatosis by using attenuation imaging.European radiology · 2023Article
- Impact of Breathing Phase, Liver Segment, and Prandial State on Ultrasound Shear Wave Speed, Shear Wave Dispersion, and Attenuation Imaging of the Liver in Healthy Volunteers.Diagnostics (Basel, Switzerland) · 2023Article
- Detection and quantification of a focal fat deposition in a liver undergoing multiple operations for neuroendocrine tumor disease using attenuation imaging: a case report.Journal of medical case reports · 2023Article
- Ultrasound-Based Diagnostic Methods: Possible Use in Fatty Liver Disease Area.Diagnostics (Basel, Switzerland) · 2022Review
- Quantitative Evaluation of Hepatic Steatosis Using Advanced Imaging Techniques: Focusing on New Quantitative Ultrasound Techniques.Korean journal of radiology · 2022Review
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Attenuation imaging is a novel, ultrasound-based technique to objectively detect and quantify liver steatosis. In this study, we evaluated the performance and inter-observer variability of attenuation imaging and compared it to a known quantification method of liver fat, the hepatorenal index (HRI). Two observers measured attenuation coefficients (AC) in an attenuation phantom, 20 healthy volunteers and 27 patients scheduled for biopsy for suspected diffuse liver disease. Results were compared with the HRI and histological findings. Both observers were blinded to the results of the biopsy and the measurements of the other observer. Our results showed that patients with moderate (S2, 33-66%) and severe fatty infiltration of the liver (S3, >66%) showed significantly higher ACs in comparison to patients with a liver fat fraction of less than 33% (S0/1). There was no significant difference in AC-values of patients with fatty infiltration of less than 5% (S0) and 5-32% (S1). In the Receiver Operating Characteristic (ROC)-analysis, the area under the curve (AUC)-values for the detection of moderate and severe steatosis were excellent at 0.98. Cut-off values were 0.64 dB/cm/MHz for the detection of S2- and 0.68 dB/cm/MHz for the detection of S3-steatosis. The inter-observer agreement of attenuation imaging was very good with an intraclass correlation coefficient (ICC) of 0.92 in patient and 0.96 in phantom measurements. The ICC decreased with depth in the phantom measurements. In summary, attenuation imaging showed very good inter-observer agreement and is a promising tool for the detection and quantification of moderate and severe hepatic steatosis.
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