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

Purpose

The aim of this study was to estimate the severity of fibrosis without a biopsy.

Methods

The signal-to-noise ratio (SNR), skewness, and kurtosis were measured using a 10-MHz transducer with the texture analysis in conjunction with an alternative method for evaluating fibrous rat livers. This method segments the region of interest (ROI) into multiple layers (sub-ROIs). In each sub-ROI of a homogeneous medium, the histogram of enveloped amplitude of radiofrequency (RF) backscattered echoes resembles a Rayleigh distribution. In theory, SNR, skewness, and kurtosis for Rayleigh statistics are constant and independent of the mean scattering intensity, which is enhanced by such undesirable effects as tissue attenuation, beam diffraction, and incident waveforms. Thus, these values, which are averages of the corresponding sub-ROI values, constitute an unbiased estimator. All fibrous liver specimens were induced using the dimethylnitrosamine method. Fiber content was estimated quantitatively as the fibrosis index by computer processing of pathological images obtained by light microscopy.

Results

The SNR, skewness and kurtosis, expressed as averages of corresponding values from each sub-ROI, correlated closely with the fibrosis index.

Conclusion

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.