US Attenuation for Liver Fat Quantification: An AIUM-RSNA QIBA                     Pulse-Echo Quantitative Ultrasound Initiative

Ferraioli, Giovanna; Kumar, Viksit; Ozturk, Arinc; Nam, Kibo; Korte, Chris L. de; Barr, Richard G.

doi:10.1148/radiol.210736

Cited by 78 publications

(83 citation statements)

References 57 publications

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“…Guidelines on what a quality IQR/M for attenuation coefficient estimation has not been published. Although a cut‐off recommendation for IQR/M for quality has not been made, the suggestion of <15% has been suggested 13 . Further work is needed to determine the appropriate IQR/M for attenuation imaging.…”

Section: Discussionmentioning

confidence: 99%

“…However, the limits of agreements indicate that the difference between values obtained with software from different vendors is still clinically relevant. In this regard, the AIUM/PEGUS group is working toward a standardization of US fat quantification with the various techniques 13 …”

Section: Discussionmentioning

confidence: 99%

“…Although a cut-off recommendation for IQR/M for quality has not been made, the suggestion of <15% has been suggested. 13 Further work is needed to determine the appropriate IQR/M for attenuation imaging. The IQR/M between the 2 systems was significantly different but both have a mean IQR/M of <15%.…”

Section: Discussionmentioning

confidence: 99%

“…Quantifying the energy loss while taking the frequency into account can quantify the liver fat content. There are different approaches used to estimate attenuation, which is described elsewhere 12–14 …”

mentioning

confidence: 99%

“…There are different approaches used to estimate attenuation, which is described elsewhere. [12][13][14] To improve the clinical use of attenuation imaging, various US vendor systems should provide similar attenuation coefficients (AC) and have similar cut-off values. In this paper, we compare the attenuation coefficient estimate for liver fat fraction from 2 different US systems, one of which has pre-released software.…”

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confidence: 99%

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A Pre‐Release Algorithm With a Confidence Map for Estimating the Attenuation Coefficient for Liver Fat Quantification

Barr

Cestone²,

Silvestri

2021

J of Ultrasound Medicine

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Objectives-To compare the estimates of attenuation coefficient (AC) for liver fat quantification between 2 Ultrasound systems and to evaluate the quality measure of a pre-released software.Methods-AC were obtained in 30 participants in this single-center IRBapproved, HIPAA compliant study. Images were obtained on the Philips Epiq Elite system using experimental software and the Canon Medical Systems Aplio i800 with released software. Five AC measurements were taken and the median and IQR/M were calculated. Region of interest placement was based on a confidence map. ROI was at the same depth and size for each system. The concordance was estimated using the Lin's concordance correlation coefficient (CCC), the r Pearson's correlation coefficient, the bias-correction factor (Cb), and the Bland-Altman method.Results-The ACs varied from 0.45 to 1.0 dB/cm/MHz for the Philips system and 0.30 to 0.96 dB/cm/MHz for the Canon system. The CCC (95% CI) was 0.792 (0.666-0.918), Pearson's r was 0.839 with Cb of 0.944, and the mean difference was 0.03 (À0.101; 0.162) suggesting the 2 methods are considered to be in agreement. Based on a Philips confidence map to determine the best location for performing the measurements, a depth of 3.5 to 4.0 cm from the liver capsule was determined, which might be significantly different than that of the Canon system.Conclusions-Estimation of the AC of the 2 systems showed a high agreement, that is, a similar trend. Assessment of the placement of the measurement box based on the quality of the measurement might be different between the 2 systems.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A Pre‐Release Algorithm With a Confidence Map for Estimating the Attenuation Coefficient for Liver Fat Quantification

Barr

Cestone²,

Silvestri

2021

J of Ultrasound Medicine

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Non‐invasive assessment of hepatic steatosis by ultrasound‐derived fat fraction in individuals at high‐risk for metabolic dysfunction‐associated steatotic liver disease

Tavaglione,

Flagiello,

Terracciani

et al. 2024

Diabetes Metabolism Res

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AimsGiven the increasing number of individuals developing metabolic dysfunction‐associated steatotic liver disease (MASLD) and the low rate of those with progressive liver disease, there is a pressing need to conceive affordable biomarkers to assess MASLD in general population settings. Herein, we aimed to investigate the performance of the ultrasound‐derived fat fraction (UDFF) for hepatic steatosis in high‐risk individuals.MethodsA total of 302 Europeans with obesity, type 2 diabetes, or a clinical history of hepatic steatosis were included in the analyses. Clinical, laboratory, and imaging data were collected using standardized procedures during a single screening visit in Rome, Italy. Hepatic steatosis was defined by controlled attenuation parameter (CAP) or ultrasound‐based Hamaguchi's score. UDFF performance for hepatic steatosis was estimated by the area under the receiver operating characteristic curve (AUC).ResultsOverall, median (IQR) UDFF was 12% (7–20). UDFF was positively correlated with CAP (ρ = 0.73, p < 0.0001) and Hamaguchi's score (ρ = 0.79, p < 0.0001). Independent predictors of UDFF were circulating triglycerides, alanine aminotransferase (ALT), and ultrasound‐measured visceral adipose tissue (VAT). UDFF AUC was 0.89 (0.85–0.93) and 0.92 (0.88–0.95) for CAP‐ and ultrasound‐diagnosed hepatic steatosis, respectively. UDFF AUC for hepatic steatosis was higher than those of fatty liver index (FLI), hepatic steatosis index (HSI), CAP‐score (CAPS), and ALT (p < 0.0001). Lower age, ALT, and VAT were associated with discordance between UDFF and ultrasound.ConclusionsUDFF may be a simple and accurate imaging biomarker to assess hepatic steatosis and monitor changes in hepatic fat content over time or in response to therapeutic interventions beyond clinical trials.

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Interobserver Variability in Ultrasound‐Based Liver Fat Quantification

Şendur

Cerit

Ibrahimkhanli

et al. 2022

J of Ultrasound Medicine

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Objectives-To assess interobserver variability in ultrasound-based quantitative liver fat content measurements and to determine how much time these quantitative ultrasound (QUS) techniques require.Methods-One hundred patients with known or suspected of having nonalcoholic fatty liver disease were included in this prospective study. Two observers who were blinded to each other measurements performed tissue attenuation imaging (TAI) and tissue scatter distribution imaging (TSI) techniques independently. Both observers assessed hepatic steatosis visually and obtained 5 measurements for each QUS technique and the median values of the measurements were recorded. Spearman's correlation test was used to assess the correlation between QUS measurements and visual hepatic stetaosis grades. Intraclass correlation coefficient (ICC) test was used to assess interobserver variability in QUS measurements.Results-The median values of TAI measurements for the observers 1 and 2 were 0.75 and 0.74 dB/cm/MHz, respectively. The median values of TSI measurements for the observers 1 and 2 were 93.53 and 92.58, respectively. The interobserver agreement in TAI (ICC: 0.970) and TSI (ICC: 0.938) measurements were excellent. The mean of the required time period for TAI technique were 55.1 AE 7.8 and 59.9 AE 6.6 seconds for the observers 1 and 2, respectively. The mean of the required time period for TSI technique were 49.1 AE 5.8 and 54.1 AE 5.4 seconds for the observers 1 and 2, respectively. Conclusion-The current study revealed that both TAI and TSI techniques are highly reproducible and can be implemented into daily practice with little additional time requirement.

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US Attenuation for Liver Fat Quantification: An AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative

Cited by 78 publications

References 57 publications

A Pre‐Release Algorithm With a Confidence Map for Estimating the Attenuation Coefficient for Liver Fat Quantification

A Pre‐Release Algorithm With a Confidence Map for Estimating the Attenuation Coefficient for Liver Fat Quantification

Non‐invasive assessment of hepatic steatosis by ultrasound‐derived fat fraction in individuals at high‐risk for metabolic dysfunction‐associated steatotic liver disease

Interobserver Variability in Ultrasound‐Based Liver Fat Quantification

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