Standardized ultrasound hepatic/renal ratio and hepatic attenuation rate to quantify liver fat content: an improvement method

Abstract

Accurate measures of liver fat content are essential for investigating the role of hepatic steatosis in the pathophysiology of multiple metabolic disorders. No traditional imaging methods can accurately quantify liver fat content. [(1)H]-magnetic resonance spectroscopy (MRS) is restricted in large-scale studies because of the practical and technological issues. Previous attempts on computer-aided ultrasound quantification of liver fat content varied in method, and the ultrasound quantitative parameters measured from different ultrasound machines were hardly comparable. We aimed to establish and validate a simple and propagable method for quantitative assessment of liver fat content based on the combination of standardized ultrasound quantitative parameters, using [(1)H]-MRS as gold standard. Totally 127 participants were examined with both ultrasonography (US) and [(1)H]-MRS. Ultrasound hepatic/renal echo-intensity ratio (H/R) and ultrasound hepatic echo-intensity attenuation rate (HA) were obtained from ordinary ultrasound images using computer program. Both parameters were standardized using a tissue-mimicking phantom before analysis. Standardized ultrasound H/R and HA were positively correlated with the liver fat content by [(1)H]-MRS (r = 0.884, P < 0.001 and r = 0.711, P < 0.001, respectively). Linear regression analysis showed ultrasound H/R could modestly predict the amount of liver fat (adjusted explained variance 78.0%, P < 0.001). The addition of ultrasound HA slightly improved the adjusted explained variance to 79.8%. Difference of estimated liver fat contents between different ultrasound machines and operators was reasonably well. Thus, computer-aided US is a valid method to estimate liver fat content and can be applied extensively after standardization of ultrasound quantitative parameters.

Figure 1

Ultrasound images of liver in (a) sagittal liver/right kidney view and (b) right intercostals view in a 53-year-old man show graphic representation of region of interest (ROI) rectangles. ROI-1, ROI-2, ROI-3, and ROI-4 show the gray scale distribution of the pixels in the selected liver, right kidney cortex, liver near-field, and liver far-field region, respectively. The linear distance between the top left corners of near-field and far-field liver ROIs was also measured.

Figure 2

(a) Linear correlation between liver fat contents by [¹H]-MRS and (a) US hepatic/renal ratio (r = 0.884, P < 0.001) and (b) US hepatic attenuation rate (r = 0.711, P < 0.001).

Figure 3

Bland–Altman analysis for agreement of US quantitative parameters between measurements with different ultrasound machines (a,b) and by different operators (c,d). (a) measurement of US hepatic/renal ratio from GE Vivid7 US machine minus measurement from GE Logiq P5 US machine; (b) measurement of US hepatic attenuation rate from GE Vivid7 US machine minus measurement from GE Logiq P5 machine; (c) measurement of US hepatic/renal ratio by operator 1 minus measurement by operator 2; and (d) measurement of US hepatic attenuation rate by operator 1 minus measurement by operator 2. LP5, Logiq P5.

Figure 4

Bland–Altman analysis for agreement of liver fat content estimated with US quantitative parameters measured from (a) different ultrasound machines and (b) different operators. In a, 18 of 26 (69.2%) points fall within the range of ± 5% liver fat content; in b, 21 of 23 (91.3%) points fall within the range of ± 5% liver fat content.