Evaluation of the Accuracy of Liver Lesion DCEUS Quantification With Respiratory Gating.

Confidence in the accuracy of dynamic contrast enhanced ultrasound (DCEUS) quantification parameters is imperative for the correct diagnosis of liver lesion perfusion characteristics. An important source of uncertainty in liver DCEUS acquisitions is artifacts introduced by respiratory motion. The objective of this study is to construct a respiratory motion simulation model (RMSM) of dual contrast imaging mode acquisitions of liver lesions in order to evaluate an algorithm for automatic respiratory gating (ARG). The respiratory kinetics as well as the perfusion models of the liver lesion and parenchyma used by the RMSM were solely derived from clinical data. The quality of fit (of the DCEUS data onto the bolus kinetics model) depends on the respiration amplitude. Similar trends in terms of quality of fit as a function of respiration amplitude were observed from RMSM and clinical data. The errors introduced on the DCEUS quantification under the influence of respiration were evaluated. The RMSM revealed that the error in the liver lesion DCEUS quantification parameters significantly decreased (p < 0.001) from a maximum of 32.3% to 6.2% when ARG was used. The use of RMSM clearly demonstrates the capability of the ARG algorithm in significantly reducing errors introduced from both in-plane and out-of-plane respiratory motion.

Improvement of the accuracy of liver lesion DCEUS quantification with the use of automatic respiratory gating.

OBJECTIVES: To evaluate the efficiency of automatic respiratory gating (ARG) in reducing respiratory motion-induced artefacts from dynamic contrast-enhanced ultrasound (DCEUS) acquisitions and to assess the impact of ARG on DCEUS quantification parameters in patients with liver malignancies. METHODS: Twenty-five patients with liver metastasis were imaged with DCEUS. The lognormal indicator dilution model was fitted on time-intensity curves extracted from hepatic lesions with and without the use of ARG and DCEUS quantification parameters were extracted. The goodness of fit was assessed using the coefficient of determination (R (2) LN ). The effect respiration had on the data was assessed using the respiration amplitude (RA) metric. Pearson's correlation coefficient (r) was used to assess the correlation between R (2) LN and RA with and without the use of ARG. RESULTS: The RA parameter was strongly correlated with R (2) LN (r = -0.96, P = 7.412 × 10(-15)) and this correlation became weaker with ARG (r = -0.64, P = 5.449 × 10(-4)). ARG significantly influenced the values of the quantification parameters extracted (P ≤ 0.05). The RA was significantly decreased when ARG was used (P = 1.172 × 10(-6)). CONCLUSIONS: ARG has a significant impact on the quantification parameters extracted and it has been shown to improve the accuracy of liver lesion DCEUS. KEY POINTS: • ARG has a significant impact on DCEUS quantification parameters. • ARG can improve the modelling of liver lesion haemodynamics using DCEUS quantification. • ARG significantly reduces the respiration amplitude of DCEUS lesion time-intensity curves.

Automatic respiratory gating for contrast ultrasound evaluation of liver lesions.

Dynamic contrast-enhanced ultrasound (DCEUS) has been used in radiology for many years for lesion detection and characterization. In recent years, more emphasis has been placed on tumor perfusion quantification with DCEUS. To ensure accuracy in both quantitative and qualitative evaluation of liver tumors with DCEUS, sources of noise in clinical data must be identified and, if possible, removed. One of the major sources of such noise is respiratory motion. A new automatic respiratory gating (ARG) algorithm is presented and evaluated with clinical data. The results of the evaluation demonstrate the potential of the ARG algorithm for clinical use as a fast and easy-to-implement method for removing respiratory motion from DCEUS loops.