A new high-resolution spectral approach to noninvasively evaluate wall deformations in arteries

Abstract

By locally measuring changes on arterial wall thickness as a function of pressure, the related Young modulus can be evaluated. This physical magnitude has shown to be an important predictive factor for cardiovascular diseases. For evaluating those changes, imaging segmentation or time correlations of ultrasonic echoes, coming from wall interfaces, are usually employed. In this paper, an alternative low-cost technique is proposed to locally evaluate variations on arterial walls, which are dynamically measured with an improved high-resolution calculation of power spectral densities in echo-traces of the wall interfaces, by using a parametric autoregressive processing. Certain wall deformations are finely detected by evaluating the echoes overtones peaks with power spectral estimations that implement Burg and Yule Walker algorithms. Results of this spectral approach are compared with a classical cross-correlation operator, in a tube phantom and "in vitro" carotid tissue. A circulating loop, mimicking heart periods and blood pressure changes, is employed to dynamically inspect each sample with a broadband ultrasonic probe, acquiring multiple A-Scans which are windowed to isolate echo-traces packets coming from distinct walls. Then the new technique and cross-correlation operator are applied to evaluate changing parietal deformations from the detection of displacements registered on the wall faces under periodic regime.

Figure 1

Schematic flow chart of the procedure for PSD calculation.

Figure 2

Circulating loop showing the artificial heart with a pneumatic pump, a perfusion line with the organ chamber, and a reservoir. Pressure inside the sample is obtained by using a solid state transducer. The echoes reflected from the wall faces are evaluated with a broadband ultrasonic probe (as it is explained in [24, 25]).

Figure 3

Schematic representation of the setup used for displacement measurements. Four echoes per A-scan appear, corresponding to the sample-fluid interfaces.

Figure 4

Windowing process and cross-correlation computation.

Figure 5

Echoes from a healthy arterial segment acquired during pump-simulated heart beats (with an acquisition interval of 9.8 s), from anterior and posterior walls.

Figure 6

PSD's estimated using the Burg option for the first analysis window, in the signals acquired in a healthy artery wall.

Figure 7

Results of dynamic thickness deformation in the two walls of a latex tube obtained with two PSD methods for (a) anterior and (b) posterior face; and with TCC processing for (c) anterior and (d) posterior face.

Figure 8

Results of dynamic thickness deformation in anterior wall face of a carotid segment with two PSD processing (a) and with TCC processing (b).

Figure 9

Wall deformation estimates obtained by means of TCC method before removing the linear trend.

Figure 10

Behaviour of wall thickness (a) and 7th overtone frequency (b) for the latex tube.

Figure 11

Resulting wall thickness values of the anterior wall of carotid artery (a) calculated from 6th harmonic values (b).

Figure 12

Resulting wall thickness values of the posterior wall of carotid artery (a) calculated from 6th harmonic values (b).

Figure 13

Pressure variations during an acquisition interval of 2 seconds, for latex tube (a) and carotid artery (b).