The effects of digitization on the elastographic signal-to-noise ratio

In elastography, the tissue under investigation is compressed and the resulting strain is estimated from the gradient of the displacement (time-delay) estimates. The displacements are typically estimated by cross-correlating the radiofrequency (RF) ultrasound signals of the pre- and postcompressed tissue. One of the parameters used to quantify the resulting quality of the elastogram is the elastographic signal-to-noise ratio (SNR(e)). For a uniformly elastic target (a single elastic modulus), the dependence of the SNR(e) on the applied strain has a bandpass characteristic that has been termed the strain filter. Theoretical expressions for the upper bound on the strain filter were developed earlier. Yet, simulated as well as experimental strain filters derived from uniformly elastic phantoms deviate from these upper bounds. The failure to achieve the upper bounds could be partially attributed to the fact that, in both simulations and experiments, the RF signals used to compute the TDEs are sampled and quantized. Using simulated models of uniformly elastic phantoms, a study of the dependence of the strain filter on the quantization and sampling rates was performed. The results indicated that the strain filter improves with both the sampling rate and the quantization, as expected. A theoretical analysis was done to incorporate quantization as a derating factor to the strain filter.