Chronic liver disease: Quantitative MRI vs CEUS-based microperfusion

A Review of Clinical Applications for Super-resolution Ultrasound Localization Microscopy

Microvascular structure and hemodynamics are important indicators for the diagnosis and assessment of many diseases and pathologies. The structural and functional imaging of tissue microvasculature in vivo is a clinically significant objective for the development of many imaging modalities. Contrast-enhanced ultrasound (CEUS) is a popular clinical tool for characterizing tissue microvasculature, due to the moderate cost, wide accessibility, and absence of ionizing radiation of ultrasound. However, in practice, it remains challenging to demonstrate microvasculature using CEUS, due to the resolution limit of conventional ultrasound imaging. In addition, the quantification of tissue perfusion by CEUS remains hindered by high operator-dependency and poor reproducibility. Inspired by super-resolution optical microscopy, super-resolution ultrasound localization microscopy (ULM) was recently developed. ULM uses the same ultrasound contrast agent (i.e. microbubbles) in CEUS. However, different from CEUS, ULM uses the location of the microbubbles to construct images, instead of using the backscattering intensity of microbubbles. Hence, ULM overcomes the classic compromise between imaging resolution and penetration, allowing for the visualization of capillary-scale microvasculature deep within tissues. To date, many in vivo ULM results have been reported, including both animal (kidney, brain, spinal cord, xenografted tumor, and ear) and human studies (prostate, tibialis anterior muscle, and breast cancer tumors). Furthermore, a variety of useful biomarkers have been derived from using ULM for different preclinical and clinical applications. Due to the high spatial resolution and accurate blood flow speed estimation (approximately 1 mm/s to several cm/s), ULM presents as an enticing alternative to CEUS for characterizing tissue microvasculature in vivo. This review summarizes the principles and present applications of CEUS and ULM, and discusses areas where ULM can potentially provide a better alternative to CEUS in clinical practice and areas where ULM may not be a better alternative. The objective of the study is to provide clinicians with an up-to-date review of ULM technology, and a practical guide for implementing ULM in clinical research and practice.

Preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma based on kupffer phase radiomic features of sonazoid contrast-enhanced ultrasound (SCEUS): A prospective study

OBJECTIVES

To establish and evaluate a machine learning radiomics model based on grayscale and Sonazoid contrast enhanced ultrasound images for the preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.

METHODS

100 cases of histopathological confirmed HCC lesions were prospectively included. Regions of interest were segmented on both grayscale and Kupffer phase of Sonazoid contrast enhanced (CEUS) images. Radiomic features were extracted from tumor region and region containing 5 mm of peritumoral liver tissues. Maximum relevance minimum redundancy (MRMR) and Least Absolute Shrinkage and Selection Operator (LASSO) were used for feature selection and Support Vector Machine (SVM) classifier was trained for radiomic signature calculation. Radiomic signatures were incorporated with clinical variables using univariate-multivariate logistic regression for the final prediction of MVI. Receiver operating characteristic curves, calibration curves and decision curve analysis were used to evaluate model's predictive performance of MVI.

RESULTS

Age were the only clinical variable significantly associated with MVI. Radiomic signature derived from Kupffer phase images of peritumoral liver tissues (kupfferPT) displayed a significantly better performance with an area under the receiver operating characteristic curve (AUROC) of 0.800 (95% confidence interval: 0.667, 0.834), the final prediction model using Age and kupfferPT achieved an AUROC of 0.804 (95% CI: 0.723, 0.878), accuracy of 75.0%, sensitivity of 87.5% and specificity of 69.1%.

CONCLUSIONS

Radiomic model based on Kupffer phase ultrasound images of tissue adjacent to HCC lesions showed an observable better predictive value compared to grayscale images and has potential value to facilitate preoperative identification of HCC patients at higher risk of MVI.

Doppler ultrasonography and contrast-enhanced ultrasonography to evaluate liver allograft discard: A pilot prospective study

BACKGROUND

Broad hemodynamic changes, is believed to have a profoundly damaging effect on donor livers after brain death (DBD) or cardiac death (DCD). It remains unclear whether Doppler ultrasonography (DUS) and contrast-enhanced ultrasonography (CEUS), the imaging modalities to evaluate perfusion, could provide more information of liver discarded.

OBJECTIVE

To evaluate the ability of DUS and CEUS to predict the risk of DBD or DCD liver discarded.

METHODS

The consecutive DBD or DCD donors with DUS/CEUS examinations before surgical procurement from February 2016 to June 2018 at our institution were included. The US and CEUS images of each donor liver were analyzed and the parameters were recorded.

RESULTS

Among the 67 eligible donor livers, 15 (22.4%) were discarded and 52 (77.6%) were used. The discarded livers showed prolonged SAT of hepatic artery (0.08s vs 0.06s, OR = 2.169, P = 0.008) on DUS, less cases with homogeneous enhancement (40.0% vs 73.1%, OR = 0.243, P = 0.028) on CEUS, more cases with decreased enhancement (53.3% vs 19.2%, OR = 4.800, P = 0.009), and less difference of the peak time between portal vein and liver parenchymal (0.5s vs 6.7s, OR = 0.917, P = 0.034). The multivariable analysis showed that donor liver with prolonged SAT of hepatic artery (OR = 7.304, 95% CI: 1.195-44.655, P = 0.031) and decreased enhancement (OR = 2.588, 95% CI: 1.234-5.426, P = 0.012) were independent factors of liver discarded.

CONCLUSIONS

DUS/CEUS could be applied as a promising predictive tool to screen high-risk liver donors. The prolonged SAT of hepatic artery on DUS and the decrease of liver donor in enhancement on CEUS, indicating hemodynamic changes in DBD and DCD donor livers, were risk factors of liver discarded.

Contrast-enhanced ultrasonography to evaluate risk factors for short-term and long-term outcomes after liver transplantation: A pilot prospective study

PURPOSE

To evaluate whether Doppler ultrasonography (DUS) and contrast-enhanced ultrasonography (CEUS) can identify liver donation after brain death (DBD) and cardiac death (DCD) with the risk of developing short-term primary graft dysfunction (PGD) or arterial and biliary complications within 1 year.

MATERIALS AND METHODS

Consecutive DBD and DCD donors who underwent DUS/CEUS examinations before surgical procurement from February 2016 to June 2018 at our institution were included. The US and CEUS images of each donor liver were analysed, and the parameters were recorded.

RESULTS

The mean time for US examination was 32 min (range, 20-59 min), and all donors tolerated the examination well. In terms of short-term outcomes, among the 52 eligible donor livers, 20 (38.5 %) of their recipients developed PGD. The multivariable analysis showed that decreased enhancement of donor livers on CEUS (OR = 15.976, 95 % CI: 1.652-154.628, P = 0.017) and high recipient model for end-stage liver disease (MELD) scores (OR = 1.050, 95 % CI: 1.004-1.099, P = 0.034) before liver transplantation (LT) were independent factors of PGD. In contrast, for long-term complications, among the 48 eligible donor livers, 16 (33.3 %) developed arterial or biliary complications within 1 year. The multivariable analysis did not show any independent factors of arterial or biliary complications within 1 year.

CONCLUSIONS

A decrease in enhancement on CEUS is an independent risk factor for poor short-term outcomes of LT. CEUS may be promising for predicting post-LT outcomes of critically ill donors effectively and safely by evaluating the haemodynamic changes in DBD and DCD donor livers.

Evaluation of two-point Dixon water-fat separation for liver specific contrast-enhanced assessment of liver maximum capacity

Gadoxetic acid-enhanced magnetic resonance imaging has become a useful tool for quantitative evaluation of liver capacity. We report on the importance of intrahepatic fat on gadoxetic acid-supported T1 mapping for estimation of liver maximum capacity, assessed by the realtime ¹³C-methacetin breathing test (¹³C-MBT). For T1 relaxometry, we used a respective T1-weighted sequence with two-point Dixon water-fat separation and various flip angles. Both T1 maps of the in-phase component without fat separation (T1_in) and T1 maps merely based on the water component (T1_W) were generated, and respective reduction rates of the T1 relaxation time (rrT1) were evaluated. A steady considerable decline in rrT1 with progressive reduction of liver function could be observed for both T1_in and T1_W (p < 0.001). When patients were subdivided into 3 different categories of ¹³C-MBT readouts, the groups could be significantly differentiated by their rrT1_in and rrT1_W values (p < 0.005). In a simple correlation model of ¹³C-MBT values with T1_inpost (r = 0.556; p < 0.001), T1_Wpost (r = 0.557; p < 0.001), rrT1_in (r = 0.711; p < 0.001) and rrT1_W (r = 0.751; p < 0.001), a log-linear correlation has been shown. Liver maximum capacity measured with ¹³C-MBT can be determined more precisely from gadoxetic acid-supported T1 mapping when intrahepatic fat is taken into account. Here, T1_W maps are shown to be significantly superior to T1_in maps without separation of fat.

A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with contrast enhanced ultrasound images

OBJECTIVE

With the fast development of artificial intelligence techniques, we proposed a novel two-stage multi-view learning framework for the contrast-enhanced ultrasound (CEUS) based computer-aided diagnosis for liver tumors, which adopted only three typical CEUS images selected from the arterial phase, portal venous phase and late phase.

MATERIALS AND METHODS

In the first stage, the deep canonical correlation analysis (DCCA) was performed on three image pairs between the arterial and portal venous phases, arterial and delayed phases, and portal venous and delayed phases respectively, which then generated total six-view features. While in the second stage, these multi-view features were then fed to a multiple kernel learning (MKL) based classifier to further promote the diagnosis result. Two MKL classification algorithms were evaluated in this MKL-based classification framework. We evaluated proposed DCCA-MKL framework on 93 lesions (47 malignant cancers vs. 46 benign tumors).

RESULTS

The proposed DCCA-MKL framework achieved the mean classification accuracy, sensitivity, specificity, Youden index, false positive rate, and false negative rate of 90.41 ± 5.80%, 93.56 ± 5.90%, 86.89 ± 9.38%, 79.44 ± 11.83%, 13.11 ± 9.38% and 6.44 ± 5.90%, respectively, by soft margin MKL classifier.

CONCLUSION

The experimental results indicate that the proposed DCCA-MKL framework achieves best performance for discriminating benign liver tumors from malignant liver cancers. Moreover, it is also proved that the three-phase CEUS image based CAD is feasible for liver tumors with the proposed DCCA-MKL framework.

Prognostic analysis of hepatocellular carcinoma on the background of liver cirrhosis via contrast-enhanced ultrasound and pathology

The aim of this study was to analyze the correlation between the quantitative parameters of contrast-enhancement ultrasound for primary hepatocellular carcinoma (HCC) and biological manifestations of tumor (Ki-67), and to explore the related risk factors of primary hepatocellular carcinoma, so as to provide the theoretical basis for the further study on contrast-enhancement ultrasound manifestations, clinical features and prognosis of HCC. The patients with HCC confirmed by operation or puncture were collected, and those with the background of liver cirrhosis and immunohistochemical staining for tumor sample sections were selected. H&E staining sections of pathological tissues of tumor samples were observed, whether there was any microvessel invasion (MVI) was recorded, the microvessel density (MVD) was counted and the recurrence situations after liver cancer operation was followed up. The change in size of tumor at arterial phase in contrast-enhancement ultrasound, enhancement mode and form at arterial phase, and whether there were tortuous vessels inside or not, and the enhancement intensity, extinction time and extinction intensity at portal phase were observed. The relationship between the parameters of contrast-enhancement ultrasound and Ki-67, AFP, MVD, MVI, tissue differentiation degree of tumor samples and recurrence was analyzed. Under the background of liver cirrhosis, there were significant differences in different enhancement modes and quantification parameters of contrast-enhancement ultrasound for HCC with different expression of Ki-67. Those with obvious tumor enlargement, inhomogeneous enhancement at arterial phase and irregular enhancement form at arterial phase after contrast-enhancement ultrasound had a high incidence of positive Ki-67 and a high early recurrence rate. The inhomogeneous enhancement at arterial phase might predict the proliferative activity and recurrence time of tumor cells; irregular enhancement form at arterial phase might indicate tumor MVI; and the low enhancement of tumor at portal phase may predict a lower degree of tissue differentiation, a higher tumor malignancy and poor prognosis. The incidence of positive Ki-67 under the background of liver cirrhosis is high, indicating poor prognosis. The enhancement mode and parameters of contrast-enhancement ultrasound for HCC may help evaluate the clinical biological manifestations of HCC and predict the postoperative recurrence of HCC.

Effect of iodinated contrast media on renal perfusion: A randomized comparison study in pigs using quantitative contrast-enhanced ultrasound (CEUS)

The administration of iodinated contrast media (CM) can cause microcirculatory disorder leading to acute renal dysfunction. In a prospective, randomized investigation two CM (Iodixanol vs Iopromide) were compared in 16 pigs. Each animal received 10 intra-aortal injections (5 ml Iodixanol or 4.32 ml Iopromide). Microcirculation was assessed using contrast-enhanced ultrasound (CEUS) directly on the kidney surface using time-to-peak (TTP) and blood-volume-analysis. Macroscopic observations were documented. Post mortem residual CM distribution in the kidneys was detected using X-ray. TTP was significantly prolonged over the descending vasa recta of the Iopromide group. This coincided with a visible marble-like pattern on the kidney surface occurring in 30 out of 80 Iopromide-injections but in 4 out of 80 Iodixanol-injections (p = 0.007). The blood volume over the entire kidney did not change after Iodixanol-application, but decreased by about 6.1% after Iopromide-application. The regional blood volume in the renal cortex showed a tendency to decrease by about 13.5% (p = 0.094) after Iodixanol-application, and clearly decreased by about 31.7% (p = 0.022) after Iopromide-application. The study revealed a consistent influence of repeated injections of two different CM on the kidney perfusion using three different imaging methods (CEUS analysis, macroscopic observation and X-ray analysis).