Contrast-enhanced ultrasonography of the pancreas shows impaired perfusion in pancreas insufficient cystic fibrosis patients.

BACKGROUND: Perfusion assessment of the pancreas is challenging and poorly evaluated. Pancreatic affection is a prevalent feature of cystic fibrosis (CF). Little is known about pancreatic perfusion in CF. We aimed to assess pancreatic perfusion by contrast-enhanced ultrasound (CEUS) analysed in the bolus-and-burst model and software. METHODS: We performed contrast enhanced ultrasound of the pancreas in 25 CF patients and 20 healthy controls. Perfusion data was analysed using a dedicated perfusion model providing the mean capillary transit-time (MTT), blood flow (BF) and blood-volume (BV). CF patients were divided according to exocrine function. RESULTS: The pancreas insufficient CF patients had longer MTT (p ≤ 0.002), lower BF (p < 0.001) and lower BV (p < 0.05) compared to the healthy controls and sufficient CF patients. Interrater analysis showed substantial agreement for the analysis of mean transit time. CONCLUSION: The bolus-and-burst method used on pancreatic CEUS-examinations demonstrates reduced perfusion in CF patients with pancreas affection. The perfusion model and software requires further optimization and standardization to be clinical applicable for the assessment of pancreatic perfusion.

Interobserver Variation of the Bolus-and-Burst Method for Pancreatic Perfusion with Dynamic - Contrast-Enhanced Ultrasound.

PURPOSE: Dynamic contrast-enhanced ultrasound (DCE-US) can be used for calculating organ perfusion. By combining bolus injection with burst replenishment, the actual mean transit time (MTT) can be estimated. Blood volume (BV) can be obtained by scaling the data to a vessel on the imaging plane. The study aim was to test interobserver agreement for repeated recordings using the same ultrasound scanner and agreement between results on two different scanner systems. MATERIALS AND METHODS: Ten patients under evaluation for exocrine pancreatic failure were included. Each patient was scanned two times on a GE Logiq E9 scanner, by two different observers, and once on a Philips IU22 scanner, after a bolus of 1.5 ml Sonovue. A 60-second recording of contrast enhancement was performed before the burst and the scan continued for another 30 s for reperfusion. We performed data analysis using MATLAB-based DCE-US software. An artery in the same depth as the region of interest (ROI) was used for scaling. The measurements were compared using the intraclass correlation coefficient (ICC) and Bland Altman plots. RESULTS: The interobserver agreement on the Logiq E9 for MTT (ICC=0.83, confidence interval (CI) 0.46-0.96) was excellent. There was poor agreement for MTT between the Logiq E9 and the IU22 (ICC=-0.084, CI -0.68-0.58). The interobserver agreement for blood volume measurements was excellent on the Logiq E9 (ICC=0.9286, CI 0.7250-0.98) and between scanners (ICC=0.86, CI=0.50-0.97). CONCLUSION: Interobserver agreement was excellent using the same scanner for both parameters and between scanners for BV, but the comparison between two scanners did not yield acceptable agreement for MTT. This was probably due to incomplete bursting of bubbles in some of the recordings on the IU22.

Absolute ultrasound perfusion parameter quantification of a tissue-mimicking phantom using bolus tracking [Correspondence].

This study presents three methods for absolute quantification in ultrasound perfusion analysis based on bolus tracking. The first two methods deconvolve the perfusion time sequence with a measured AIF, using a nonparametric or a parametric model of the tissue residue function, respectively. The third method is a simplified approach avoiding deconvolution by assuming a narrow AIF. A phantom with a dialyzer filter as a tissue-mimicking model was used for evaluation. Estimated mean transit times and blood volumes were compared with the theoretical values. A match with a maximum error of 12% was achieved.

Semi-automatic motion compensation of contrast-enhanced ultrasound images from abdominal organs for perfusion analysis.

This paper presents a system for correcting motion influences in time-dependent 2D contrast-enhanced ultrasound (CEUS) images to assess tissue perfusion characteristics. The system consists of a semi-automatic frame selection method to find images with out-of-plane motion as well as a method for automatic motion compensation. Translational and non-rigid motion compensation is applied by introducing a temporal continuity assumption. A study consisting of 40 clinical datasets was conducted to compare the perfusion with simulated perfusion using pharmacokinetic modeling. Overall, the proposed approach decreased the mean average difference between the measured perfusion and the pharmacokinetic model estimation. It was non-inferior for three out of four patient cohorts to a manual approach and reduced the analysis time by 41% compared to manual processing.

Blind deconvolution in dynamic contrast-enhanced MRI and ultrasound.

This paper is focused on quantitative perfusion analysis using MRI and ultrasound. In both MRI and ultrasound, most approaches allow estimation of rate constants (Ktrans, kep for MRI) and indices (AUC, TTP) that are only related to the physiological perfusion parameters of a tissue (e.g. blood flow, vessel permeability) but do not allow their absolute quantification. Recent methods for quantification of these physiological perfusion parameters are shortly reviewed. The main problem of these methods is estimation of the arterial input function (AIF). This paper summarizes and extends the current blind-deconvolution approaches to AIF estimation. The feasibility of these methods is shown on a small preclinical study using both MRI and ultrasound.

Quantitative contrast-enhanced ultrasound comparison between inflammatory and fibrotic lesions in patients with Crohn's disease.

The aim of this study was to determine whether there are differences in absolute blood flow between patients with Crohn's disease with inflammation or fibrosis using contrast-enhanced ultrasound. Eighteen patients with fibrotic disease and 19 patients with inflammation were examined. Video sequences of contrast data were analyzed using a pharmacokinetic model to extract the arterial input and tissue residue functions with a custom software, enabling calculation of the absolute values for mean transit time, blood volume and flow. Feasibility of the examination was 89%. The fibrosis group had lower blood volume (0.9 vs. 3.4 mL per 100 mL tissue; p = 0.001) and flow (22.6 vs. 45.3 mL/min per 100 mL tissue; p = 0.003) compared with the inflammation group. There was no significant difference in mean transit time (3.9 vs. 5.5 s). In conclusion, absolute perfusion measurement in the gastrointestinal wall using contrast-enhanced ultrasound is feasible. There seems to be reduced blood volume and blood flow in patients with fibrotic disease.

Ultrasound perfusion analysis combining bolus-tracking and burst-replenishment.

A new signal model and processing method for quantitative ultrasound perfusion analysis is presented, called bolus-and-burst. The method has the potential to provide absolute values of blood flow, blood volume, and mean transit time. Furthermore, it provides an estimate of the local arterial input function which characterizes the arterial tree, allowing accurate estimation of the bolus arrival time. The method combines two approaches to ultrasound perfusion analysis: bolus-tracking and burst-replenishment. A pharmacokinetic model based on the concept of arterial input functions and tissue residue functions is used to model both the bolus and replenishment parts of the recording. The pharmacokinetic model is fitted to the data using blind deconvolution. A preliminary assessment of the new perfusion-analysis method is presented on clinical recordings.

Comparison and evaluation of indicator dilution models for bolus of ultrasound contrast agents.

Dynamic contrast-enhanced ultrasound (DCE-US) imaging is a promising diagnostic method, which enables the evaluation of tissue perfusion via different parameters. The mean transit time and time-to-peak parameters are the main time parameters and their values depend on the model used for the approximation of the noisy perfusion curves. In this paper, we described a new comparison of different perfusion models using a tissue mimicking phantom. The following models were compared: log-normal, lagged, Erlang, Gamma and the local density random walk model. We discovered that the mean-square error is not the best criterion for model evaluation. More important is the comparison between the estimated time perfusion parameters and the physical parameters of the developed tissue mimicking phantom. Based on the statistical analysis, we can suggest that for the DCE-US perfusion analysis more models should be used, excluding the log-normal model, which gives the highest error of mean transit time value.