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Intersystem and Interoperator Agreement of US Attenuation Coefficient for Quantifying Liver Steatosis
Giovanna Ferraioli1, Davide Roccarina1, Richard G Barr1
1From the Department of Clinical-Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Division of Internal Medicine and Hepatology, Azienda Ospedaliero Universitaria Careggi, Firenze, Italy (D.R.); Sherlock Liver Unit and UCL Institute for Liver and Digestive Health, Royal Free Hospital, London, England (D.R.); Department of Radiology, Northeast Ohio Medical University, Rootstown, Ohio (R.G.B.); and Southwoods Imaging, 7623 Market St, Youngstown, OH 44512 (R.G.B.).
None:
Background The extent of liver steatosis can be assessed using US attenuation coefficient (AC) algorithms currently implemented in several US systems. However, little is known about intersystem and interoperator variability in measurements. Purpose To assess intersystem and interoperator agreement in US AC measurements for fat quantification in individuals with varying degrees of liver steatosis and to assess the correlation of each manufacturer's AC algorithm results with MRI proton density fat fraction (PDFF). Materials and Methods This prospective study was conducted at Southwoods Imaging, Youngstown, Ohio, September 30-October 1, 2023. Two operators independently obtained AC measurements using eight US systems equipped with an AC algorithm from different manufacturers. On the same day, MRI PDFF measurement was performed by a different operator. Correlation between US AC and MRI PDFF was assessed using a mixed-effects model. Agreement between systems and operators was evaluated using the intraclass correlation coefficient (ICC). Results Twenty-six individuals (mean age, 55.4 years ± 10.7 [SD]; 16 female participants) were evaluated. The correlation of US AC with MRI PDFF was high for five AC algorithms (r range, 0.70-0.86), moderate for two (r = 0.62 for both), and poor for one (r = 0.47). In pairwise comparisons, none of the pairs of systems achieved excellent agreement (overall ICC = 0.33 [95% CI: 0.15, 0.52]). One pair showed good agreement (ICC = 0.79 [95% CI: 0.66, 0.87]), eight pairs showed moderate agreement (ICC range, 0.50 [95% CI: 0.22, 0.69] to 0.73 [95% CI: 0.49, 0.85]), and 19 pairs showed poor agreement (ICC range, 0.11 [95% CI: -0.06, 0.37] to 0.48 [95% CI: 0.20, 0.67]). Interoperator agreement on AC value was excellent for the Samsung Medison algorithm (ICC = 0.90 [95% CI: 0.80, 0.96]), good for the Siemens Healthineers (ICC = 0.76 [95% CI: 0.54, 0.89]) and Canon Medical Systems (ICC = 0.76 [95% CI: 0.16, 0.92]) algorithms, and moderate for the remaining algorithms (ICC range, 0.50 [95% CI: 0.16, 0.73] to 0.74 [95% CI: 0.51, 0.88]). The mean AC value obtained by the two operators did not differ for any system except the system from Canon Medical Systems. Conclusion There was substantial variability in AC values obtained with different US systems, precluding interchangeability between systems for liver steatosis diagnosis and follow-up imaging. Interoperator agreement ranged from moderate to excellent. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Han in this issue.
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