On the Relationship between Dynamic Contrast-Enhanced Ultrasound Parameters and the Underlying Vascular Architecture Extracted from Acoustic Angiography

Abstract

Dynamic contrast-enhanced ultrasound (DCE-US) has been proposed as a powerful tool for cancer diagnosis by estimation of perfusion and dispersion parameters reflecting angiogenic vascular changes. This work was aimed at identifying which vascular features are reflected by the estimated perfusion and dispersion parameters through comparison with acoustic angiography (AA). AA is a high-resolution technique that allows quantification of vascular morphology. Three-dimensional AA and 2-D DCE-US bolus acquisitions were used to monitor the growth of fibrosarcoma tumors in nine rats. AA-derived vascular properties were analyzed along with DCE-US perfusion and dispersion to investigate the differences between tumor and control and their evolution in time. AA-derived microvascular density and DCE-US perfusion exhibited good agreement, confirmed by their spatial distributions. No vascular feature was correlated with dispersion. Yet, dispersion provided better cancer classification than perfusion. We therefore hypothesize that dispersion characterizes vessels that are smaller than those visible with AA.

Keywords: Acoustic angiography; Cancer; Dispersion; Dynamic contrast-enhanced ultrasound; Perfusion; Ultrasound contrast agents.

Figure 1:

DCE-US and AA images of the same plane, and maps of the extracted features. a: maximum intensity projection of the DCE-US video. The tumor is encircled by a red contour, while the region outside the blue contour belongs to the control, separated by a margin which was not included in the analysis. Regions with power below the threshold of −22 dBs of the maximum intensity are displayed in black. b-c: perfusion and dispersion colormaps, respectively. Regions with power below −22 dBs of the maximum intensity are displayed in white. d: Selected AA slice. e-f: vascular skeleton, colorcoded according to the values of the microvascular desity, and mean radius, respectively (yellow indicates low values, while red inicates high values). The numbers in b and d illustate the vessels identified in the perfusion maps, used as markers to locate the right plane in AA volumes.

Figure 2:

A typical preprocessed indicator dilution curve. T1 shows the appearance time, T0 is taken 3 seconds before appearance time. The interval from T0 to T2 shows the interval of the IDC used for dispersion analysis. The tangens of the angle alpha of the line fitted to the indicator dilution curve in the 2 seconds after appearance time is the wash-in-rate.

Figure 3:

AA maximum intensity projection. The tumor region is indicated by the red contour, surrounded by the control region.

Figure 4:

Boxplots of tumor and control parameters, binned together from all time points. a: dispersion, b: perfusion, c: distance metric, d: sum of angles metric, e: vessel length, f: vessel radius, g: microvascular density, h: volume vascular density. Cohen’s d measure is indicated above the plots.

Figure 5:

Boxplots of tumor (T1, T2, T3, T4) and control (C1, C2, C3, C4) parameters, binned together at different time points. a: dispersion, b: perfusion, c: volume vascular density, d: microvascular density, e: vessel radius, f: vessel length, g: sum of angles metric.

Figure 6:

Results of the Tukey’s post hoc test performed on tumor and control parameters at four time points (indicated by T1, T2, T3, T4 and by C1, C2, C3, C4, respectively). The colors of the rows indicate whether the distribution is significantly different from the others, green and yellow representing different significance levels. a: dispersion, b: perfusion, c: volume vascular density, d: microvascular density, e: vessel radius, f: vessel length, g: sum of angles metric.