B-Mode Ultrasound With Algorithm Based on Statistical Analysis of Signals: Evaluation of Liver Fibrosis in Patients With Chronic Hepatitis C

Toyoda, Hidenori; Kumada, Takashi; Kamiyama, Naohisa; Shiraki, Katsuya; Takase, Kojiro; Yamaguchi, Tadashi; Hachiya, Hiroyuki

doi:10.2214/ajr.07.4047

Cited by 92 publications

(80 citation statements)

References 20 publications

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“…The method is based on statistical analysis of the difference between theoretical and real echo amplitude distribution (21,22). Theoretical echo amplitude distribution indicates that a speckle pattern in a certain liver region is approximated by a function of a Reyleigh distribution based on the assumption that the speckle pattern is generated only by ultrasonic interference of very small scattering objects that are located closer than the wavelength of US.…”

Section: Study Populationmentioning

confidence: 99%

Hepatic Steatosis: Assessment with Acoustic Structure Quantification of US Imaging

Son

Lee

et al. 2016

Radiology

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).q RSNA, 2015 Purpose:To investigate the diagnostic performance of acoustic structure quantification (ASQ) for the assessment of hepatic steatosis by using hydrogen 1 ( 1 H) magnetic resonance (MR) spectroscopy as the reference standard and to compare ASQ with hepatorenal ratio. Materials andMethods:This prospective study was approved by an institutional review board, and informed written consent was obtained from all participants. ASQ and MR spectroscopy were performed in 89 participants (mean age, 41.48 years 6 14.16; 35 men, 54 women) without history of chronic liver disease. Obtained were focal disturbance (FD) ratio by using ASQ, hepatic fat fraction (HFF) by using MR spectroscopy, and hepatorenal ratio by using a histogram. Correlation coefficient, intraclass correlation coefficient, and receiver operating curve analyses were performed. Results:FD ratio measured with ASQ had a strong linear correlation with HFF measured with MR spectroscopy after logarithmic transformation of both variables (r = 20.87; P , .001). By using HFF of 5.79% as a cutoff value of 10% hepatic steatosis, 29 of 89 participants (32.6%) were categorized into the group with hepatic steatosis of 10% or greater (mean HFF, 13.18% 6 4.89). The area under curve of the FD ratio for diagnosing hepatic steatosis 10% or greater was 0.959 (95% confidence interval: 0.895, 0.990) with sensitivity of 86.2% (95% confidence interval: 68.3%, 96.0%) and specificity of 100% (95% confidence interval: 94.0%, 100.0%) by using a cutoff value of 0.1; the area under curve and specificity of the FD ratio were significantly higher than those of the hepatorenal ratio (respectively, 0.772 and 73.3%; respective P values, .001 and ,.001). Conclusion:This pilot study in a cohort of patients with hepatic steatosis without other parenchymal disease suggested ASQ may be valuable for the quantification of hepatic steatosis and detection of hepatic steatosis 10% or greater in living liver donors.q RSNA, 2015

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Section: Study Populationmentioning

confidence: 99%

Hepatic Steatosis: Assessment with Acoustic Structure Quantification of US Imaging

Son

Lee

et al. 2016

Radiology

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“…18,19) On the other hand, the PDF of echo envelope amplitude from an inhomogeneous tissue such as a fibrotic liver deviates from the RA distribution; therefore, the deviation of the PDF from the RA distribution was quantified. [20][21][22] As a probability distribution model of a fibrotic liver, we proposed a multi-Rayleigh (MRA) model, which is a combination of several RA distributions with different variances. [23][24][25] Using the MRA model, liver fibrosis parameters such as the amount of fibrotic tissue and the fibrosis progressive ratio can be quantitatively estimated.…”

Section: Introductionmentioning

confidence: 99%

Quantitative evaluation method for liver fibrosis based on multi-Rayleigh model with estimation of number of tissue components in ultrasound B-mode image

Mori

Hirata

Yamaguchi

et al. 2018

Jpn. J. Appl. Phys.

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The development of a quantitative diagnostic method for liver fibrosis using an ultrasound B-mode image is highly required. In our previous study, a multi-Rayleigh model was proposed to express a probability distribution of echo envelope amplitude from a fibrotic liver. Using the multi-Rayleigh model, a structure of fibrotic tissue can be quantitatively estimated. In this study, a method of estimating the number of tissue components was proposed to improve the accuracy of estimating a fibrotic tissue structure. Using threshold processing for a squared Mahalanobis distance of moments, which is a statistical property of echo envelope amplitude, the number of tissue components could be quantitatively estimated. The results of evaluation of clinical ultrasound B-mode images using the multi-Rayleigh model with estimation of the number of tissue components well reflected the tissue structural changes caused by liver fibrosis. It was concluded that our proposed method of estimating the number of tissue components improves the accuracy of liver fibrosis evaluation based on the multi-Rayleigh model.

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“…For example, the attenuation [11,12] and backscatter coefficient [12] can be used to quantify the degree of fatty liver. Previous studies have shown that changes in the microstructures of liver parenchyma alter the speckle pattern and image texture of a B-mode image [13,14]. Therefore, the texture analysis of the B-mode image has also been explored for fatty liver evaluations [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Effects of Fatty Infiltration of the Liver on the Shannon Entropy of Ultrasound Backscattered Signals

Tsui

Wan

2016

Entropy

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This study explored the effects of fatty infiltration on the signal uncertainty of ultrasound backscattered echoes from the liver. Standard ultrasound examinations were performed on 107 volunteers. For each participant, raw ultrasound image data of the right lobe of liver were acquired using a clinical scanner equipped with a 3.5-MHz convex transducer. An algorithmic scheme was proposed for ultrasound B-mode and entropy imaging. Fatty liver stage was evaluated using a sonographic scoring system. Entropy values constructed using the ultrasound radiofrequency (RF) and uncompressed envelope signals (denoted by H R and H E , respectively) as a function of fatty liver stage were analyzed using the Pearson correlation coefficient. Data were expressed as the median and interquartile range (IQR). Receiver operating characteristic (ROC) curve analysis with 95% confidence intervals (CIs) was performed to obtain the area under the ROC curve (AUC). The brightness of the entropy image typically increased as the fatty stage varied from mild to severe. The median value of H R monotonically increased from 4.69 (IQR: 4.60-4.79) to 4.90 (IQR: 4.87-4.92) as the severity of fatty liver increased (r = 0.63, p < 0.0001). Concurrently, the median value of H E increased from 4.80 (IQR: 4.69-4.89) to 5.05 (IQR: 5.02-5.07) (r = 0.69, p < 0.0001). In particular, the AUCs obtained using H E (95% CI) were 0. 93 (0.87-0.99), 0.88 (0.82-0.94), and 0.76 (0.65-0.87) for fatty stages ≥mild, ≥moderate, and ≥severe, respectively. The sensitivity, specificity, and accuracy were 93.33%, 83.11%, and 86.00%, respectively (≥mild). Fatty infiltration increases the uncertainty of backscattered signals from livers. Ultrasound entropy imaging has potential for the routine examination of fatty liver disease.

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B-Mode Ultrasound With Algorithm Based on Statistical Analysis of Signals: Evaluation of Liver Fibrosis in Patients With Chronic Hepatitis C

Cited by 92 publications

References 20 publications

Hepatic Steatosis: Assessment with Acoustic Structure Quantification of US Imaging

Hepatic Steatosis: Assessment with Acoustic Structure Quantification of US Imaging

Quantitative evaluation method for liver fibrosis based on multi-Rayleigh model with estimation of number of tissue components in ultrasound B-mode image

Effects of Fatty Infiltration of the Liver on the Shannon Entropy of Ultrasound Backscattered Signals

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