Texture analysis with a new method in which the region of interest is segmented into multiple layers for radiofrequency amplitude histogram analysis of fibrous rat livers

Abstract

These results make it possible to predict the severity of liver fibrosis from data obtained without resorting to biopsy. The data, obtained from our earlier study on rats, may be used to evaluate human hepatitis quantitatively by measuring these three values. The method may make it possible to estimate the degree of severity of chronic liver disease noninvasively.

Proposal of a parametric imaging method for quantitative diagnosis of liver fibrosis

“…Possibility of false-positive reduction In many recent analytic methods used to estimate tissue properties [4,12,15,18], many false-positive determinations occurred (i.e., a normal liver was often misclassified as fibrotic). In the liver, in particular, a speckle pattern slightly changes because of the echoes from portal veins and hepatic veins.…”

“…Our group also quantified liver fibrosis by analyzing the echo amplitude envelope [18][19][20][21][22][23][24]. Envelope statistics are often used for tissue characterization using ultrasound [13,15]. It is possible to roughly estimate the progress of fibrosis by previous research results including our research.…”

“…In ultrasound tissue characterization based on the characteristics of the echo signal such as power spectrum, texture parameters, local attenuation, and statistical characteristics, it is assumed that changes in tissue properties such as attenuation and elasticity are uniform in the liver, and a single evaluation index is therefore used in many methods [10][11][12][13][14][15][16][17]. Our group also quantified liver fibrosis by analyzing the echo amplitude envelope [18][19][20][21][22][23][24].…”

Basic concept and clinical applications of quantitative ultrasound (QUS) technologies

“…Focusing on the fact that the deviation from the Rayleigh distribution in living tissue indicates inhomogeneity of the tissue, several attempts have been made to realize QUS by indexing the degree of non-Rayleigh distribution. Representative examples of this work include techniques that use signal-to-noise ratio (SNR) as the index, as proposed by Shankar [ 53 , 54 ] and Fujii [ 55 ]; and methods that use variance as the index, as proposed by Kamiyama, which have been implemented in clinical devices [ 56 ]. Yamaguchi and Hachiya have proposed multi-Rayleigh distributions that combine two or three Rayleigh distributions to eliminate the constraint of expressing the amplitude envelope characteristics of the echo signal only by the Rayleigh distribution [ 57 , 58 ].…”

Liver tissue characterization for each pixel in ultrasound image using multi-Rayleigh model

“…Several investigators have reported ultrasound tissue characterization based on the characteristics of echo signals. [1][2][3][4][5][6][7][8] We have also examined methods of analyzing echo signals to realize the quantitative evaluation of liver fibrosis in a series of "quantitative diagnostic ultrasound" studies. We measured the acoustical property of liver tissue accurately [9][10][11] and developed a tissue structure model to investigate the relationship between the progress of liver fibrosis and ultrasound images.…”