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

A Comprehensive and Repeatable Contrast-Enhanced Ultrasound Quantification Approach for Clinical Evaluations of Tumor Blood Flow

OBJECTIVE

The aim of this study is to define a comprehensive and repeatable contrast-enhanced ultrasound (CEUS) imaging protocol and analysis method to quantitatively assess lesional blood flow. Easily repeatable CEUS evaluations are essential for longitudinal treatment monitoring. The quantification method described here aims to provide a structure for future clinical studies.

MATERIALS AND METHODS

This retrospective analysis study included liver CEUS studies in 80 patients, 40 of which contained lesions (primarily hepatocellular carcinoma, n = 28). Each patient was given at least 2 injections of a microbubble contrast agent, and 60-second continuous loops were acquired for each injection to enable evaluation of repeatability. For each bolus injection, 1.2 mL of contrast was delivered, whereas continuous, stationary scanning was performed. Automated respiratory gating and motion compensation algorithms dealt with breathing motion. Similar in size regions of interest were drawn around the lesion and liver parenchyma, and time-intensity curves (TICs) with linearized image data were generated. Four bolus transit parameters, rise time (RT), mean transit time (MTT), peak intensity (PI), and area under the curve (AUC), were extracted either directly from the actual TIC data or from a lognormal distribution curve fitted to the TIC. Interinjection repeatability for each parameter was evaluated with coefficient of variation. A 95% confidence interval was calculated for all fitted lognormal distribution curve coefficient of determination (R2) values, which serves as a data quality metric. One-sample t tests were performed between values obtained from injection pairs and between the fitted lognormal distribution curve and direct extraction from the TIC calculation methods to establish there were no significant differences between injections and measurement precision, respectively.

RESULTS

Average interinjection coefficient of variation with both the fitted curve and direct calculation of RT and MTT was less than 21%, whereas PI and AUC were less than 40% for lesion and parenchyma regions of interest. The 95% confidence interval for the R2 value of all fitted lognormal curves was [0.95, 0.96]. The 1-sample t test for interinjection value difference showed no significant differences, indicating there was no relationship between the order of the repeated bolus injections and the resulting parameters. The 1-sample t test between the values from the fitted lognormal distribution curve and the direct extraction from the TIC calculation found no statistically significant differences (α = 0.05) for all perfusion-related parameters except lesion and parenchyma PI and lesion MTT.

CONCLUSIONS

The scanning protocol and analysis method outlined and validated in this study provide easily repeatable quantitative evaluations of lesional blood flow with bolus transit parameters in CEUS data that were not available before. With vital features such as probe stabilization ideally performed with an articulated arm and an automated respiratory gating algorithm, we were able to achieve interinjection repeatability of blood flow parameters that are comparable or surpass levels currently established for clinical 2D CEUS scans. Similar values and interinjection repeatability were achieved between calculations from a fitted curve or directly from the data. This demonstrated not only the strength of the protocol to generate TICs with minimal noise, but also suggests that curve fitting might be avoided for a more standardized approach. Utilizing the imaging protocol and analysis method defined in this study, we aim for this methodology to potentially assist clinicians to assess true perfusion changes for treatment monitoring with CEUS in longitudinal studies.

Quantification of Hepatocellular Carcinoma Vascular Dynamics With Contrast-Enhanced Ultrasound for LI-RADS Implementation

OBJECTIVE

The aim of this study is to describe a comprehensive contrast-enhanced ultrasound (CEUS) imaging protocol and analysis method to implement CEUS LI-RADS (Liver Imaging Reporting and Data System) in a quantifiable manner. The methods that are validated with a prospective single-center study aim to simplify CEUS LI-RADS evaluation, remove observer bias, and potentially improve the sensitivity of CEUS LI-RADS.

MATERIALS AND METHODS

This prospective single-center study enrolled patients with hepatocellular carcinoma (April 2021-June 2022; N = 31; mean age ± SD, 67 ± 6 years; 24 men/7 women). For each patient, at least 2 CEUS loops spanning over 5 minutes were collected for different lesion scan planes using an articulated arm to hold the transducer. Automatic respiratory gating and motion compensation algorithms removed errors due to breathing motion. The long axis of the lesion was measured in the contrast and fundamental images to capture nodule size. Parametric processing of time-intensity curve analysis on linearized data provided quantifiable information of the wash-in and washout dynamics via rise time ( RT ) and degree of washout ( DW ) parameters extracted from the time-intensity curve, respectively. A Welch t test was performed between lesion and parenchyma RT for each lesion to confirm statistically significant differences. P values for bootstrapped 95% confidence intervals of the relative degree of washout ( rDW ), ratio of DW between the lesion and surrounding parenchyma, were computed to quantify lesion washout. Coefficient of variation (COV) of RT , DW , and rDW was calculated for each patient between injections for both the lesion and surrounding parenchyma to gauge reproducibility of these metrics. Spearman rank correlation tests were performed among size, RT , DW , and rDW values to evaluate statistical dependence between the variables.

RESULTS

The mean ± SD lesion diameter was 23 ± 8 mm. The RT for all lesions, capturing arterial phase hyperenhancement, was shorter than that of surrounding liver parenchyma ( P < 0.05). All lesions also demonstrated significant ( P < 0.05) but variable levels of washout at both 2-minute and 5-minute time points, quantified in rDW . The COV of RT for the lesion and surrounding parenchyma were both 11%, and the COV of DW and rDW at 2 and 5 minutes ranged from 22% to 31%. Statistically significant relationships between lesion and parenchyma RT and between lesion RT and lesion DW at the 2- and 5-minute time points were found ( P < 0.05).

CONCLUSIONS

The imaging protocol and analysis method presented provide robust, quantitative metrics that describe the dynamic vascular patterns of LI-RADS 5 lesions classified as hepatocellular carcinomas. The RT of the bolus transit quantifies the arterial phase hyperenhancement, and the DW and rDW parameters quantify the washout from linearized CEUS intensity data. This unique methodology is able to implement the CEUS-LIRADS scheme in a quantifiable manner for the first time and remove its existing issues of currently being qualitative and suffering from subjective evaluations.

EFSUMB Technical Review - Update 2023: Dynamic Contrast-Enhanced Ultrasound (DCE-CEUS) for the Quantification of Tumor Perfusion

Dynamic contrast-enhanced ultrasound (DCE-US) is a technique to quantify tissue perfusion based on phase-specific enhancement after the injection of microbubble contrast agents for diagnostic ultrasound. The guidelines of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) published in 2004 and updated in 2008, 2011, and 2020 focused on the use of contrast-enhanced ultrasound (CEUS), including essential technical requirements, training, investigational procedures and steps, guidance regarding image interpretation, established and recommended clinical indications, and safety considerations. However, the quantification of phase-specific enhancement patterns acquired with ultrasound contrast agents (UCAs) is not discussed here. The purpose of this EFSUMB Technical Review is to further establish a basis for the standardization of DCE-US focusing on treatment monitoring in oncology. It provides some recommendations and descriptions as to how to quantify dynamic ultrasound contrast enhancement, and technical explanations for the analysis of time-intensity curves (TICs). This update of the 2012 EFSUMB introduction to DCE-US includes clinical aspects for data collection, analysis, and interpretation that have emerged from recent studies. The current study not only aims to support future work in this research field but also to facilitate a transition to clinical routine use of DCE-US.

Imaging Methods for Ultrasound Contrast Agents

Microbubble contrast agents were introduced more than 25 years ago with the objective of enhancing blood echoes and enabling diagnostic ultrasound to image the microcirculation. Cardiology and oncology waited anxiously for the fulfillment of that objective with one clinical application each: myocardial perfusion, tumor perfusion and angiogenesis imaging. What was necessary though at first was the scientific understanding of microbubble behavior in vivo and the development of imaging technology to deliver the original objective. And indeed, for more than 25 years bubble science and imaging technology have evolved methodically to deliver contrast-enhanced ultrasound. Realization of the basic bubbles properties, non-linear response and ultrasound-induced destruction, has led to a plethora of methods; algorithms and techniques for contrast-enhanced ultrasound (CEUS) and imaging modes such as harmonic imaging, harmonic power Doppler, pulse inversion, amplitude modulation, maximum intensity projection and many others were invented, developed and validated. Today, CEUS is used everywhere in the world with clinical indications both in cardiology and in radiology, and it continues to mature and evolve and has become a basic clinical tool that transforms diagnostic ultrasound into a functional imaging modality. In this review article, we present and explain in detail bubble imaging methods and associated artifacts, perfusion quantification approaches, and implementation considerations and regulatory aspects.

A fast scheme for renal microvascular perfusion functional imaging: Assessed by an imaging quality evaluation model

PURPOSE

This study aimed to develop a fast scheme of multiparametric perfusion functional imaging (PFI) based on dynamic contrast-enhanced ultrasound (DCEUS) for assessing renal microvascular hemodynamics.

METHOD

The flow process in the DCEUS-based PFI was modified step-by-step to improve its operational efficiency, which was validated through in vivo renal perfusion experiments. A multiparametric model with a comprehensive coefficient of imaging quality (CIQ) was then built on four terms of the average information entropy, contrast, gray, and noise coefficient of PFIs to evaluate the sacrifice of imaging quality during modifications of DCEUS-based PFI.

RESULTS

The multiparametric model successfully evaluated modifications of DCEUS-based PFI from multiple perspectives (R²  = 0.73, P < 0.01). Compared with the raw scheme in the renal sagittal and coronal planes, the fast PFI scheme significantly improved its operational efficiency by 62.82 ± 1.07% (P < 0.01) and the nine PFIs simultaneously maintained a similar CIQ of 0.26 ± 0.06.

CONCLUSIONS

The inhomogeneous hemodynamic distributions with a ring-like feature in the renal microvasculature were accurately and efficiently characterized by the fast PFI scheme. The fast PFI scheme can be applied for early diagnosis, follow-up evaluation and monitoring treatment of chronic kidney disease.

In-vitro evaluation of accuracy of dynamic contrast-enhanced ultrasound (DCEUS)-based parametric perfusion imaging with respiratory motion-compensation

PURPOSE

The accuracy of multi-parametric perfusion imaging (PPI) based on dynamic contrast-enhanced ultrasound is disturbed by the respiratory motion in some cases, especially during characterizing hemodynamic features of abdominal tumor angiogenesis. This study aimed to effectively remove those disturbances on PPI and evaluate its accuracy.

METHOD

The respiratory motion-compensation (rMoCo) strategy in PPI was modified by employing non-negative matrix factorization combined with phase-by-phase compensation. According to the known and controllable ground truths in in-vitro perfusion experiments, the accuracy of the modified rMoCo strategy was further evaluated from multiple perspectives in a simulated dual-vessel flow phantom.

RESULTS

Compared with that of PPIs without rMoCo, the mean correlation coefficient between six PPIs with rMoCo and the corresponding static PPIs was up to 0.98 ± 0.01 and improved by 0.17 ± 0.04 (P < 0.05). The estimated error of vascular diameter decreased from 87.85% (P < 0.05) to 7.25% (P < 0.05) after rMoCo. PPIs with rMoCo were significantly consistent with static PPIs without respiratory motion disturbances.

CONCLUSIONS

These quantitative results illustrated the disturbances induced by respiratory motion were effectively removed and the accuracy of PPIs was significantly improved. The partial parabolic and bimodal hemodynamic characteristics and the anatomical structures and sizes were accurately quantified and depicted by PPIs with rMoCo. The modified method can benefit physicians in providing accurate diagnoses and in developing appropriate therapeutic strategies for abdominal diseases.