Detection and differentiation of early hepatocellular carcinoma from cirrhosis using CT perfusion in a rat liver model

Current Imaging Diagnosis of Hepatocellular Carcinoma

Simple Summary

The role of imaging in the management of hepatocellular carcinoma (HCC) has significantly evolved and expanded beyond the plain radiological confirmation of the tumor based on the typical appearance in a multiphase contrast-enhanced CT or MRI examination. The introduction of hepatobiliary contrast agents has enabled the diagnosis of hepatocarcinogenesis at earlier stages, while the application of ultrasound contrast agents has drastically upgraded the role of ultrasound in the diagnostic algorithms. Newer quantitative techniques assessing blood perfusion on CT and MRI not only allow earlier diagnosis and confident differentiation from other lesions, but they also provide biomarkers for the evaluation of treatment response. As distinct HCC subtypes are identified, their correlation with specific imaging features holds great promise for estimating tumor aggressiveness and prognosis. This review presents the current role of imaging and underlines its critical role in the successful management of patients with HCC.

Abstract

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer related death worldwide. Radiology has traditionally played a central role in HCC management, ranging from screening of high-risk patients to non-invasive diagnosis, as well as the evaluation of treatment response and post-treatment follow-up. From liver ultrasonography with or without contrast to dynamic multiple phased CT and dynamic MRI with diffusion protocols, great progress has been achieved in the last decade. Throughout the last few years, pathological, biological, genetic, and immune-chemical analyses have revealed several tumoral subtypes with diverse biological behavior, highlighting the need for the re-evaluation of established radiological methods. Considering these changes, novel methods that provide functional and quantitative parameters in addition to morphological information are increasingly incorporated into modern diagnostic protocols for HCC. In this way, differential diagnosis became even more challenging throughout the last few years. Use of liver specific contrast agents, as well as CT/MRI perfusion techniques, seem to not only allow earlier detection and more accurate characterization of HCC lesions, but also make it possible to predict response to treatment and survival. Nevertheless, several limitations and technical considerations still exist. This review will describe and discuss all these imaging modalities and their advances in the imaging of HCC lesions in cirrhotic and non-cirrhotic livers. Sensitivity and specificity rates, method limitations, and technical considerations will be discussed.

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

Computed tomography vs liver stiffness measurement and magnetic resonance imaging in evaluating esophageal varices in cirrhotic patients: A systematic review and meta-analysis

BACKGROUND

Computed tomography (CT), liver stiffness measurement (LSM), and magnetic resonance imaging (MRI) are non-invasive diagnostic methods for esophageal varices (EV) and for the prediction of high-bleeding-risk EV (HREV) in cirrhotic patients. However, the clinical use of these methods is controversial.

AIM

To evaluate the accuracy of LSM, CT, and MRI in diagnosing EV and predicting HREV in cirrhotic patients.

METHODS

We performed literature searches in multiple databases, including PubMed, Embase, Cochrane, CNKI, and Wanfang databases, for articles that evaluated the accuracy of LSM, CT, and MRI as candidates for the diagnosis of EV and prediction of HREV in cirrhotic patients. Summary sensitivity and specificity, positive likelihood ratio and negative likelihood ratio, diagnostic odds ratio, and the areas under the summary receiver operating characteristic curves were analyzed. The quality of the articles was assessed using the quality assessment of diagnostic accuracy studies-2 tool. Heterogeneity was examined by Q-statistic test and I² index, and sources of heterogeneity were explored using meta-regression and subgroup analysis. Publication bias was evaluated using Deek’s funnel plot. All statistical analyses were conducted using Stata12.0, MetaDisc1.4, and RevMan5.3.

RESULTS

Overall, 18, 17, and 7 relevant articles on the accuracy of LSM, CT, and MRI in evaluating EV and HREV were retrieved. A significant heterogeneity was observed in all analyses (P < 0.05). The areas under the summary receiver operating characteristic curves of LSM, CT, and MRI in diagnosing EV and predicting HREV were 0.86 (95% confidence interval [CI]: 0.83-0.89), 0.91 (95%CI: 0.88-0.93), and 0.86 (95%CI: 0.83-0.89), and 0.85 (95%CI: 0.81-0.88), 0.94 (95%CI: 0.91-0.96), and 0.83 (95%CI: 0.79-0.86), respectively, with sensitivities of 0.84 (95%CI: 0.78-0.89), 0.91 (95%CI: 0.87-0.94), and 0.81 (95%CI: 0.76-0.86), and 0.81 (95%CI: 0.75-0.86), 0.88 (95%CI: 0.82-0.92), and 0.80 (95%CI: 0.72-0.86), and specificities of 0.71 (95%CI: 0.60-0.80), 0.75 (95%CI: 0.68-0.82), and 0.82 (95%CI: 0.70-0.89), and 0.73 (95%CI: 0.66-0.80), 0.87 (95%CI: 0.81-0.92), and 0.72 (95%CI: 0.62-0.80), respectively. The corresponding positive likelihood ratios were 2.91, 3.67, and 4.44, and 3.04, 6.90, and2.83; the negative likelihood ratios were 0.22, 0.12, and 0.23, and 0.26, 0.14, and 0.28; the diagnostic odds ratios were 13.01, 30.98, and 19.58, and 11.93, 49.99, and 10.00. CT scanner is the source of heterogeneity. There was no significant difference in diagnostic threshold effects (P > 0.05) or publication bias (P > 0.05).

CONCLUSION

Based on the meta-analysis of observational studies, it is suggested that CT imaging, a non-invasive diagnostic method, is the best choice for the diagnosis of EV and prediction of HREV in cirrhotic patients compared with LSM and MRI.

Differentiation of regenerative nodule, dysplastic nodule, and small hepatocellular carcinoma in cirrhotic patients: a contrast-enhanced ultrasound-based multivariable model analysis

OBJECTIVE

To develop a contrast-enhanced ultrasound (CEUS)-based model for differentiating cirrhotic liver lesions and for active surveillance of hepatocellular carcinoma (HCC).

METHODS

Patients with focal liver lesions (FLLs) with biopsy/resection-proven pathology and pre-procedure CEUS were enrolled from our institution between January 2011 and November 2014. Univariable and multivariable regression models were constructed using qualitative CEUS features and/or contrast arrival time ratio (CAT_R). The optimism-adjusted Harrell's generalized concordance index (C_H) was used to quantify the discriminatory ability of each CEUS feature and model.

RESULTS

A total of 149 patients (113 men and 36 women) with 162 FLLs were enrolled with mean age 53.4 ± 12.7 years. A 0.1-unit reduction in CAT_R was associated with a 68% increase in the odds of having a higher nodule ranking (RN < DN < small HCC) (OR, 0.32; 95% CI, 0.20-0.50, p < .001). Arterial phase hypoenhancement and isoenhancement were inversely associated with a higher nodule ranking compared to hyperenhancement. Late-phase isoenhancement was associated with lower odds of a higher nodule ranking. The CEUS + CAT_R model (C_H 0.92, 0.89-0.95) provided greater discriminatory ability when compared to the CAT_R model (ΔC_H 0.09, 0.04-0.13, p < .001) and the CEUS model (ΔC_H 0.03, 0.01-0.05, p = .02).

CONCLUSIONS

Our results provide preliminary evidence that multivariable regression model constructed using both qualitative CEUS features and CAT_R provides the greatest discriminatory ability to differentiate RN, DN, and small HCC in patients with cirrhosis, and might allow for active surveillance of the progression of cirrhotic liver lesions.

KEY POINTS

• Proportional odds logistic regression models based on qualitative CEUS features and/or CAT_R can be used for differentiating cirrhotic liver lesions and for active surveillance of HCC. • The reduction of CAT_R (RN < DN < small HCC) was strongly associated with high-risk cirrhotic liver nodules. • Inclusion of CAT_R in the CEUS prediction model significantly improved its performance for cirrhotic liver lesions risk-stratification.

RAF1 Expression is Correlated with HAF, a Parameter of Liver Computed Tomographic Perfusion, and may Predict the Early Therapeutic Response to Sorafenib in Advanced Hepatocellular Carcinoma Patients

Objectives

Monitoring the early treatment effect of sorafenib in advanced hepatocellular carcinoma (HCC) patients is a diagnostic challenge. In a previous study, we reported the potential role of liver computed tomography perfusion (CTP) in the assessment of the response to sorafenib therapy in HCC. The present study aims to investigate whether sorafenib-targeted genes is correlated with CTP parameter, and investigate the potential of sorafenib-targeted genes in early prediction of therapeutic response to sorafenib in advanced HCC.

Methods

A total of 21 HCC patients were enrolled. Sorafenib was administered orally at a dose of 400 mg twice daily continuously. Treatment response was assessed using modified response evaluation criteria in solid tumors (mRECIST) criteria. CTP scanning was performed before and after two weeks of sorafenib treatment using a 320-detector row CT scanner. The perfusion parameters of portal vein flow (PVF), hepatic artery flow (HAF), and perfusion index (PI) were acquired by CTP. The expression levels of several sorafenib-targeted genes were assayed using real-time quantitative PCR and western blot analysis. Logistic regression was performed to analyze the relationship between HAF values and RAF1 expression levels.

Results

According to mRECIST, the disease control rate (CR+PR+SD) of treatment group was 70.5% after two months of treatment. Compared to background controls, tumor tissues exhibited higher HAF. A sorafenib-targeted gene, RAF1 expression, was increased in tumor tissues especially in the sorafenib-resistant group. The sorafenib-resistant group exhibited a significantly higher RAF1 expression and HAF than the sensitive group. Moreover, the RAF1 expression is positively correlated with the HAF value.

Conclusion

RAF1 expression might predict therapeutic effects of sorafenib in advanced HCC, where RAF1 could potentially serve as a molecular marker for monitoring early therapeutic effects after sorafenib treatment.

Dynamic Computed Tomography Perfusion Imaging: Complementary Diagnostic Tool in Hepatocellular Carcinoma Assessment From Diagnosis to Treatment Follow-up

Early diagnosis of HCC is of paramount importance in order to enable the application of curative treatments. Among these, radiofrequency ablation (RFA) is actually considered the most effective ablative therapy for early stage hepatocellular carcinoma (HCC) not suitable for surgery. On the other hand, transarterial chemoembolization (TACE) represents the standard of care for intermediate stage HCC and compensated liver function. Finally, sorafenib, an oral antiangiogenic targeted drug, is the only approved systemic therapy for advanced HCC with vascular invasion, extrahepatic spread, and well-preserved liver function. Beside traditional radiological techniques, new functional imaging tools have been introduced in order to provide not only morphological information but also quantitative functional data. In this review, we analyze perfusion-CT (pCT) from a technical point of view, describing the main different mathematical analytical models for the quantification of tissue perfusion from acquired CT raw data, the most commonly acquired perfusion parameters, and the technical parameters required to perform a standard pCT examination. Moreover, a systematic review of the literature was performed to assess the role of pCT as an emerging imaging biomarker for HCC diagnosis, response evaluation to RFA, TACE, and sorafenib, and we examine its challenges in HCC management.

Diagnostic value of hepatic artery perfusion fraction combined with TGF-β in patients with hepatocellular carcinoma

Diagnostic value of hepatic artery perfusion fraction (HAF) combined with transforming growth factor-β (TGF-β) in the diagnosis of primary liver carcinoma (PLC) was evaluated. The clinical data of 128 PLC patients undergoing radical hepatectomy in Affiliated Hospital of Jining Medical University were regarded as the study group. Seventy-four healthy volunteers examined in Affiliated Hospital of Jining Medical University were collected as the control group. Double-antibody sandwich enzyme-linked immunosorbent assay was used to detect the expression level of serum TGF-β. The upper abdomen of the subjects was scanned by a 64-slice spiral CT, and the perfusion parameters were analyzed and calculated. According to the HAF and the expression level of TGF-β in the two groups, single and combined detection of TGF-β and HAF parameters were detected, respectively, by ROC curve. The expression of TGF-β in serum of the study group was higher than that of the control group (P<0.05). The expression level of serum TGF-β was closely related to total bilirubin, ascites, TNM stage, prothrombin time and tumor diameter. Blood flow (BF), blood volume (BV), permeability surface (PS), HAF and other perfusion parameters in the study group were higher than those in the control group (P<0.05). The specificity and sensitivity of TGF-β expression level in diagnosing PLC were 73 and 93%, respectively; the specificity and sensitivity of HAF parameter in diagnosing PLC were 73 and 100%, respectively; the specificity and sensitivity of HAF parameter combined with TGF-β expression level were 84 and 100%, respectively. TGF-β is highly expressed in serum of PLC patients; HAF parameter combined with TGF-β expression level can improve the specificity and has an important value in the diagnosis of PLC, which is worthy of clinical promotion.