Characterization of in vitro healthy and pathological human liver tissue periodicity using backscattered ultrasound signals

This work studied the periodicity of in vitro healthy and pathologic liver tissue, using backscattered ultrasound (US) signals. It utilized the mean scatterer spacing (MSS) as a parameter of tissue characterization, estimated by three methods: the spectral autocorrelation (SAC), the singular spectrum analysis (SSA) and the quadratic transformation method (SIMON). The liver samples were classified in terms of tissue status using the METAVIR scoring system. Twenty tissue samples were classified in four groups: F0, F1, F3 and F4 (five samples for each). The Kolmogorov-Smirnov test (applied on group pairs) resulted as nonsignificant (p > 0.05) for two pairs only: F1/F3 (for SSA) and F3/F4 (for SAC). A discriminant analysis was applied using as parameters the MSS mean (MSS) and standard deviation (sigmaMSS), the estimates histogram mode (mMSS), and the speed of US (mc(foie)) in the medium, to evaluate the degree of discrimination among healthy and pathologic tissues. The better accuracy (Ac) with SAC (80%) was with parameter group (MSS, sigmaMSS, mc(foie)), achieving a sensitivity (Ss) of 92.3% and a specificity (Sp) of 57.1%. For SSA, the group with all four parameters showed an Ac of 75%, an Ss of 78.6% and an Sp of 66.70%. SIMON obtained the best Ac of all (85%) with group (MSS, mMSS, mc(foie)), an Ss of 100%, but with an Sp of 50%.