Differentiation of focal liver lesions: usefulness of parametric imaging with contrast-enhanced US

Application of Quantitative Parameters of Contrast-Enhanced Ultrasound in Common Benign and Malignant Lesions in Pediatric Livers: A Preliminary Study

We aimed to investigate the diagnostic utility of quantitative parameters of contrast-enhanced ultrasound (CEUS) for benign and malignant liver lesions in pediatric patients. This was a single-center retrospective analysis of children with liver lesions who underwent CEUS at our hospital between July 2019 and February 2023. The CEUS perfusion patterns for all lesions were qualitatively analyzed using histopathology, contrast-enhanced magnetic resonance imaging, contrast-enhanced computed tomography, or long-term clinical follow-up as reference standards. The CEUS images were quantitatively analyzed using SonoLiver® software (TomTec Imaging Systems, Munich, Germany) to obtain data regarding quantitative parameters and dynamic vascular pattern (DVP) parametric images, including rise time (RT), time to peak (TTP), mean transit time (mTT), and maximum intensity (IMAX). Statistical analysis was carried out using Student's t-test and receiver operating characteristic (ROC) curve analysis to evaluate the diagnostic value of quantitative parameters. A total of 53 pediatric cases were included in this study, and 88.57% (31/35) of malignant lesions exhibited hyper-enhancement with rapid washout patterns; the same proportion of DVP parametric images exhibited washout patterns. Conversely, 94.44% (17/18) of benign lesions showed hyper-enhancement with slow washout patterns, and the same proportion of DVP parametric images showed no-washout patterns. RT, TTP, and mTT were significantly shorter in the malignant group than in the benign group (p < 0.05), while IMAX showed no significant difference (p > 0.05). ROC analysis indicated that mTT < 113.34 had the highest diagnostic value, with an area under the curve of 0.82. CEUS quantitative analysis had an accuracy of 98.11%, while qualitative analysis had an accuracy of 92.45%, with no statistically significant difference (p > 0.05). Quantitative analysis of CEUS provides valuable assistance in differentiating benign and malignant liver lesions in children. Among all quantitative parameters, mTT holds promise as a potentially valuable tool for identifying liver tumors.

Multiparametric Dynamic Ultrasound Approach for Differential Diagnosis of Primary Liver Tumors

A correct differentiation between hepatocellular carcinoma (HCC) and intracellular cholangiocarcinoma (ICC) is essential for clinical management and prognostic prediction. However, non-invasive differential diagnosis between HCC and ICC remains highly challenging. Dynamic contrast-enhanced ultrasound (D-CEUS) with standardized software is a valuable tool in the diagnostic approach to focal liver lesions and could improve accuracy in the evaluation of tumor perfusion. Moreover, the measurement of tissue stiffness could add more information concerning tumoral environment. To explore the diagnostic performance of multiparametric ultrasound (MP-US) in differentiating ICC from HCC. Our secondary aim was to develop an US score for distinguishing ICC and HCC. Between January 2021 and September 2022 consecutive patients with histologically confirmed HCC and ICC were enrolled in this prospective monocentric study. A complete US evaluation including B mode, D-CEUS and shear wave elastography (SWE) was performed in all patients and the corresponding features were compared between the tumor entities. For better inter-individual comparability, the blood volume-related D-CEUS parameters were analyzed as a ratio between lesions and surrounding liver parenchyma. Univariate and multivariate regression analysis was performed to select the most useful independent variables for the differential diagnosis between HCC and ICC and to establish an US score for non-invasive diagnosis. Finally, the diagnostic performance of the score was evaluated by receiver operating characteristic (ROC) curve analysis. A total of 82 patients (mean age ± SD, 68 ± 11 years, 55 men) were enrolled, including 44 ICC and 38 HCC. No statistically significant differences in basal US features were found between HCC and ICC. Concerning D-CEUS, blood volume parameters (peak intensity, PE; area under the curve, AUC; and wash-in rate, WiR) showed significantly higher values in the HCC group, but PE was the only independent feature associated with HCC diagnosis at multivariate analysis (p = 0.02). The other two independent predictors of histological diagnosis were liver cirrhosis (p < 0.01) and SWE (p = 0.01). A score based on those variables was highly accurate for the differential diagnosis of primary liver tumors, with an area under the ROC curve of 0.836 and the optimal cut-off values of 0.81 and 0.20 to rule in or rule out ICC respectively. MP-US seems to be a useful tool for non-invasive discrimination between ICC and HCC and could prevent the need for liver biopsy at least in a subgroup of patients.

A Comprehensive Motion Compensation Method for In-Plane and Out-of-Plane Motion in Dynamic Contrast-Enhanced Ultrasound of Focal Liver Lesions

Contrast-enhanced ultrasound (CEUS) acquisitions of focal liver lesions are affected by motion, which has an impact on contrast signal quantification. We therefore developed and tested, in a large patient cohort, a motion compensation algorithm called the Iterative Local Search Algorithm (ILSA), which can correct for both periodic and non-periodic in-plane motion and can reject frames with out-of-plane motion. CEUS cines of 183 focal liver lesions in 155 patients from three hospitals were used to develop and test ILSA. Performance was evaluated through quantitative metrics, including the root mean square error and R2 in fitting time-intensity curves and standard deviation value of B-mode intensities, computed across cine frames), and qualitative evaluation, including B-mode mean intensity projection images and parametric perfusion imaging. The median root mean square error significantly decreased from 0.032 to 0.024 (p < 0.001). Median R2 significantly increased from 0.88 to 0.93 (p < 0.001). The median standard deviation value of B-mode intensities significantly decreased from 6.2 to 5.0 (p < 0.001). B-Mode mean intensity projection images revealed improved spatial resolution. Parametric perfusion imaging also exhibited improved spatial detail and better differentiation between lesion and background liver parenchyma. ILSA can compensate for all types of motion encountered during liver CEUS, potentially improving contrast signal quantification of focal liver lesions.

Interpretable Machine Learning for Characterization of Focal Liver Lesions by Contrast-Enhanced Ultrasound

This work proposes an interpretable radiomics approach to differentiate between malignant and benign focal liver lesions (FLLs) on contrast-enhanced ultrasound (CEUS). Although CEUS has shown promise for differential FLLs diagnosis, current clinical assessment is performed only by qualitative analysis of the contrast enhancement patterns. Quantitative analysis is often hampered by the unavoidable presence of motion artifacts and by the complex, spatiotemporal nature of liver contrast enhancement, consisting of multiple, overlapping vascular phases. To fully exploit the wealth of information in CEUS, while coping with these challenges, here we propose combining features extracted by the temporal and spatiotemporal analysis in the arterial phase enhancement with spatial features extracted by texture analysis at different time points. Using the extracted features as input, several machine learning classifiers are optimized to achieve semiautomatic FLLs characterization, for which there is no need for motion compensation and the only manual input required is the location of a suspicious lesion. Clinical validation on 87 FLLs from 72 patients at risk for hepatocellular carcinoma (HCC) showed promising performance, achieving a balanced accuracy of 0.84 in the distinction between benign and malignant lesions. Analysis of feature relevance demonstrates that a combination of spatiotemporal and texture features is needed to achieve the best performance. Interpretation of the most relevant features suggests that aspects related to microvascular perfusion and the microvascular architecture, together with the spatial enhancement characteristics at wash-in and peak enhancement, are important to aid the accurate characterization of FLLs.

High Frame Rate Contrast-enhanced Ultrasound Helps Differentiate Malignant and Benign Focal Liver Lesions

BACKGROUND AND AIMS

This study aimed to evaluate the diagnostic performance of high frame rate contrast-enhanced ultrasound (H-CEUS) of focal liver lesions (FLLs).

METHODS

From July 2017 to June 2019, conventional contrast-enhanced ultrasound (C-CEUS) and H-CEUS were performed in 78 patients with 78 nodules. The characteristics of C-CEUS and H-CEUS in malignant and benign groups and the differences between different lesion sizes (1-3 cm, 3-5 cm, or >5 cm) of C-CEUS and H-CEUS were examined. The diagnostic performance of C-CEUS and H-CEUS was analyzed. The chi-square test or Fisher's exact test was used to assess inter-group differences. The receiver operating characteristic curve was plotted to determine the diagnostic performance of C-CEUS and H-CEUS.

RESULTS

There were significant differences in the enhancement area, fill-in direction and vascular architecture between C-CEUS and H-CEUS for both benign and malignant lesions (all p=0.000-0.008), but there were no significant differences in washout results (p=0.566 and p=0.684, respectively). For lesions 1-3 cm in size, the enhancement area, fill-in direction, and vascular architecture on C-CEUS and H-CEUS were significantly different (all p=0.000), unlike for lesions 3-5 cm or >5 cm in size. For differentiation of malignant from benign FLLs in the 1-3 cm group, H-CEUS showed sensitivity, specificity, accuracy, and positive and negative predictive values of 92.86%, 95.0%, 96.3%, 90.48% and 93.75%, respectively, which were higher than those for C-CEUS (75.0%, 70.0%, 77.78%, 66.67% and 72.91%, respectively).

CONCLUSIONS

H-CEUS provided more vascular information which could help differentiate malignant from benign FLLs, especially for lesions 1-3 cm in size.

VueBox® for quantitative analysis of contrast-enhanced ultrasound in liver tumors1

Dynamic contrast-enhanced ultrasound (DCE-US) enables quantification of tumor perfusion. VueBox is a platform independent external software using DICOM cine loops which objectively provides various DCE-US parameters of tumor vascularity. This review summaries its use for diagnosis and treatment monitoring of liver tumors. The existing literature provides evidence on the successful application of Vuebox based DCE-US for characterization and differential diagnosis of focal liver lesions, as well as on its use for monitoring of local ablative therapies and of modern systemic treatment in oncology.

Application of Contrast-Enhanced Ultrasound in the Differential Diagnosis of Different Molecular Subtypes of Breast Cancer

To explore the value of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of molecular subtypes of breast cancer. Sixty-two cases of breast cancer were divided into luminal epithelium A or B subtype (luminal A/B), Her-2 over-expression subtype and triple negative subtype (TN). CEUS and routine ultrasonography were performed for all patients before surgery. (1) The luminal epithelium subtype contrast enhancement pattern was more likely to present with radial edge (76.92%, p < 0.05) and low perfusion (69.23%, p < 0.05). The maximum intensity (IMAX) was lower in the luminal epithelium subtype (p < 0.05). (2) The Her-2 over-expression subtype contrast enhancement pattern was more likely to present with centripetal enhancement (93.75%, p < 0.05) and perfusion defect (75.0%, p < 0.05), and the time to peak (TTP) was shorter (80.0%, p < 0.05). (3) The contrast enhancement pattern of the triple negative subtype was shown to have a clear boundary. Compared to the other two subtypes, the triple negative subtype did not have significantly different perfusion parameters (p > 0.05). (4) Our study showed that the areas under the ROC curve for radial edge, low perfusion and IMAX for the luminal epithelium subtype breast lesions were 76.5%, 75.6%, and 82.1%, respectively. Additionally, the areas under the ROC curve for centripetal enhancement, perfusion defect and TTP for the Her-2 over-expression subtype breast lesions were 68.6%, 92.4%, and 97.8%, respectively. The sensitivity, specificity, and diagnostic accuracy of clear boundaries in detecting triple negative subtype breast lesions were 90.5%, 80.0%, and 91.9%, respectively.

Imaging Accuracy in Diagnosis of Different Focal Liver Lesions: A Retrospective Study in North of Iran

INTRODUCTION

Focal liver lesions (FLLs) are incidentally detected masses found in daily abdominal imaging which are necessary to be characterized, because of the potential of being malignant. There are several imaging methods, such as ultrasonography (US), computed tomography (CT scan), and contrast enhanced magnetic resonance imaging (MRI). Here, we evaluate and compare the diagnostic accuracy (i.e., sensitivity and specificity) of these imaging methods for the diagnosis of FLLs.

MATERIAL AND METHODS

In this retrospective study, patients with focal liver lesions included and based on the gastroenterologist decision, in 79 patients different imaging methods were used to determine the nature of FLLs: the US, CT scan, and MRI. At the next step, fine-needle aspiration biopsy (FNA) was performed in all cases, and the results about the true nature of FLLs compared with different imaging results. The chi-square test and McNemar test were used.

RESULTS

Ultrasound diagnosis of benign and malignant was obtained with 82% diagnosis accuracy, 100% sensitivity, 71.4% specificity, 100% negative predictive value, and 69.2% positive predictive value (PPV) compared with the biopsy. Also, the results of benign and malignant masses in CT scan were obtained with diagnostic accuracy of 95%, 100% sensitivity, 80% specificity, 93.9% positive predictive value, and 100% negative predictive value. MRI performed only in 2 cases with similar results to pathology.

CONCLUSION

It seems that CT scan is more appropriate and useful in the diagnosis of hepatic masses due to its higher diagnostic accuracy than the ultrasound.

Respiratory motion correction for liver contrast-enhanced ultrasound by automatic selection of a reference image

PURPOSE

Respiratory motion correction is necessary for the quantitative analysis of liver contrast-enhanced ultrasound (CEUS) image sequences. Most respiratory motion correction methods are based on the dual mode of CEUS image sequences, including contrast and grayscale image sequences. Due to free-breathing motion, the acquired two-dimensional (2D) ultrasound cine might show the in-plane and out-of-plane motion of tumors. The registration of an entire 2D ultrasound contrast image sequence based on out-of-plane images is ineffective. For the respiratory motion correction of CEUS sequences, the reference image is usually considered the standard for the deletion of any out-of-plane images. Most methods used for the selection of the reference image are subjective in nature. Here, a quantitative selection method for an optimal reference image from CEUS image sequences in the B mode and contrast mode was explored.

METHODS

The original high-dimensional ultrasound grayscale image data were mapped into a two-dimensional space using Laplacian Eigenmaps (LE), and K-means clustering was adopted. The center image of the larger cluster with a near-peak contrast intensity was considered the optimal ultrasound reference image. In the ultrasound grayscale image sequence, the images with the maximum correlations to the reference image in the same time interval were selected as the corrected image sequence. The effectiveness of this proposed method was then validated on 18 CEUS cases of VX2 tumors in rabbit livers.

RESULTS

Correction smoothed the time-intensity curves (TICs) extracted from the region of interest of the CEUS image sequences. Before correction, the average of the total mean structural similarity (TMSSIM) and the average of the mean correlation coefficient (MCC) from the image sequences were 0.45 ± 0.11 and 0.67 ± 0.16, respectively, and after correction, the average TMSSIM and MCC increased (P < 0.001) by 31% to 0.59 ± 0.11 and by 21% to 0.81 ± 0.11, respectively. The average deviation value (DV) index of the TICs from the image sequences prior to correction was 92.16 ± 18.12, and correction reduced the average to 31.71 ± 7.31. The average TMSSIM and MCC values after correction using the mean frame of the reference image (MBMFRI) were clearly lower than those after correction using the proposed method (P < 0.001). Moreover, the average DV after correction using the MBMFRI was obviously higher than that after correction using the proposed method (P < 0.001).

CONCLUSIONS

The breathing frequency of rabbits is notably faster than that of human beings, but the proposed correction method could reduce the effect of the respiratory motion in the CEUS image sequences. The reference image was selected quantitatively, which could improve the accuracy of the quantitative analysis of rabbit liver CEUS sequences using the reference image method based on the current standard of manual selection and the MBMFRI. This easy-to-operate method can potentially be used in both animal studies and clinical applications.

Clinical Applications of Superb Microvascular Imaging in the Liver, Breast, Thyroid, Skeletal Muscle, and Carotid Plaques

This article reviews the clinical applications of Superb Microvascular Imaging (SMI; Canon Medical Systems, Otawara, Japan) in the liver, breast, thyroid, skeletal muscle, and carotid plaques. Diseases that are closely associated with angiogenesis can be diagnosed by SMI in a relatively early phase, and using SMI can prevent adverse reactions associated with the contrast agents used in contrast-enhanced ultrasound. Super Microvascular Imaging also shows particular value in grading disease activities and monitoring therapeutic responses. Although SMI has some limitations, such as a lack of clinical standards, it can add information to conventional ultrasound examinations and may become a noninvasive alternative to invasive diagnostic procedures for many clinical conditions.

Evaluation of Indirect Methods for Motion Compensation in 2-D Focal Liver Lesion Contrast-Enhanced Ultrasound (CEUS) Imaging

This study investigates the application and evaluation of existing indirect methods, namely point-based registration techniques, for the estimation and compensation of observed motion included in the 2-D image plane of contrast-enhanced ultrasound (CEUS) cine-loops recorded for the characterization and diagnosis of focal liver lesions (FLLs). The value of applying motion compensation in the challenging modality of CEUS is to assist in the quantification of the perfusion dynamics of an FLL in relation to its parenchyma, allowing for a potentially accurate diagnostic suggestion. Towards this end, this study also proposes a novel quantitative multi-level framework for evaluating the quantification of FLLs, which to the best of our knowledge remains undefined, notwithstanding many relevant studies. Following quantitative evaluation of 19 indirect algorithms and configurations, while also considering the requirement for computational efficiency, our results suggest that the "compact and real-time descriptor" (CARD) is the optimal indirect motion compensation method in CEUS.

Contrast enhanced ultrasound for focal liver lesions: how accurate is it?

With the recent FDA approval for characterization of focal liver lesions (FLL) in both pediatric and adult patients using Lumason (sulfur hexafluoride microbubbles), increased use of ultrasound contrast for routine clinical use is expected. This agent has been available for many years in Europe and Asia, and a large body of literature is available regarding the sensitivity and specificity of this agent. In addition, a few studies have directly compared CEUS to CECT and CEMRI for the characterization of focal liver lesions. This paper reviews the literature to provide a background to investigators in the United States as to the accuracy of CEUS in the characterization of FLL. This paper reviews the literature regarding sulfur hexafluoride microbubbles (Lumason in the USA and Sonovue in the rest of the world) since it is the only FDA approved agent in the USA for characterization of FLL. The results of other ultrasound contrast agents which are not FDA approved for abdominal indications (approval for cardiac indications) most likely will have similar results.

Contrast-enhanced US for characterization of focal liver lesions: a comprehensive meta-analysis

OBJECTIVES

This meta-analysis was performed to evaluate the accuracy of contrast-enhanced ultrasound (CEUS) in differentiating malignant from benign focal liver lesions (FLLs).

METHODS

Cochrane Library, PubMed and Web of Science databases were systematically searched and checked for studies using CEUS in characterization of FLLs. Data necessary to construct 2×2 contingency tables were extracted from included studies. The QUADAS tool was utilized to assess the methodologic quality of the studies. Meta-analysis included data pooling, subgroup analyses, meta-regression and investigation of publication bias was comprehensively performed.

RESULTS

Fifty-seven studies were included in this meta-analysis and the overall diagnostic accuracy in characterization of FLLs was as follows: pooled sensitivity, 0.92 (95%CI: 0.91-0.93); pooled specificity, 0.87 (95%CI: 0.86-0.88); diagnostic odds ratio, 104.20 (95%CI: 70.42-154.16). Subgroup analysis indicated higher diagnostic accuracy of the second-generation contrast agents (CAs) than the first-generation CA (Levovist; DOR: 118.27 vs. 62.78). Furthermore, Sonazoid demonstrated the highest diagnostic accuracy among three major CAs (SonoVue, Levovist and Sonazoid; DOR: 118.82 vs. 62.78 vs. 227.39). No potential publication bias was observed of the included studies.

CONCLUSION

CEUS is an accurate tool to stratify the risk of malignancy in FLLs. The second-generation CAs, especially Sonazoid may greatly improve diagnostic performance.

KEY POINTS

• CEUS shows excellent diagnostic accuracy in differentiating malignant from benign FLLs. • The second-generation CAs have higher diagnostic accuracy than first-generation CAs. • Sonazoid demonstrates the highest diagnostic accuracy among three major CAs.

Automatic Identification of the Optimal Reference Frame for Segmentation and Quantification of Focal Liver Lesions in Contrast-Enhanced Ultrasound

Post-examination interpretation of contrast-enhanced ultrasound (CEUS) cineloops of focal liver lesions (FLLs) requires offline manual assessment by experienced radiologists, which is time-consuming and generates subjective results. Such assessment usually starts by manually identifying a reference frame, where FLL and healthy parenchyma are well-distinguished. This study proposes an automatic computational method to objectively identify the optimal reference frame for distinguishing and hence delineating an FLL, by statistically analyzing the temporal intensity variation across the spatially discretized ultrasonographic image. Level of confidence and clinical value of the proposed method were quantitatively evaluated on retrospective multi-institutional data (n = 64) and compared with expert interpretations. Results support the proposed method for facilitating easier, quicker and reproducible assessment of FLLs, further increasing the radiologists' confidence in diagnostic decisions. Finally, our method yields a useful training tool for radiologists, widening CEUS use in non-specialist centers, potentially leading to reduced turnaround times and lower patient anxiety and healthcare costs.

Computer-Aided Diagnosis of Focal Liver Lesions Using Contrast-Enhanced Ultrasonography With Perflubutane Microbubbles

This paper proposes an automatic classification method based on machine learning in contrast-enhanced ultrasonography (CEUS) of focal liver lesions using the contrast agent Sonazoid. This method yields spatial and temporal features in the arterial phase, portal phase, and post-vascular phase, as well as max-hold images. The lesions are classified as benign or malignant and again as benign, hepatocellular carcinoma (HCC), or metastatic liver tumor using support vector machines (SVM) with a combination of selected optimal features. Experimental results using 98 subjects indicated that the benign and malignant classification has 94.0% sensitivity, 87.1% specificity, and 91.8% accuracy, and the accuracy of the benign, HCC, and metastatic liver tumor classifications are 84.4%, 87.7%, and 85.7%, respectively. The selected features in the SVM indicate that combining features from the three phases are important for classifying FLLs, especially, for the benign and malignant classifications. The experimental results are consistent with CEUS guidelines for diagnosing FLLs. This research can be considered to be a validation study, that confirms the importance of using features from these phases of the examination in a quantitative manner. In addition, the experimental results indicate that for the benign and malignant classifications, the specificity without the post-vascular phase features is significantly lower than the specificity with the post-vascular phase features. We also conducted an experiment on the operator dependency of setting regions of interest and observed that the intra-operator and inter-operator kappa coefficients were 0.45 and 0.77, respectively.

How to Develop a Contrast-Enhanced Ultrasound Program

With the recent Food and Drug Administration approval of Lumason (sulfur hexafluoride lipid-type A microsphere, Bracco Diagnostics Inc, Monroe Township, NJ) for contrast-enhanced ultrasound (CEUS) to characterize focal liver lesions in both adult and pediatric patients, widespread use of CEUS is expected in the United States. This paper provides guidance in setting up a CEUS program, and reviews the practical details that will need to be instituted in a standard ultrasound department to provide both safe and efficient use of CEUS. A review of the indications, contraindications, adverse events, instructions for performing the exam, and image interpretation are discussed.

Characterization of Focal Liver Lesions Indistinctive on B Mode Ultrasound: Benefits of Contrast-Enhanced Ultrasound

Aim. The aim of this prospective study was to evaluate the additional value of contrast-enhanced ultrasound (CEUS) in identifying and characterizing of focal liver lesions (FLLs) that are indistinctive on B mode ultrasound (BMUS). Methods. The study focused on 70 consecutive patients (male 46, female 24; mean age, 53.1 years ± 10). All lesions were detected by MRI but could not be clearly visualized by BMUS. CEUS was performed by injected SonoVue® (Bracco Imaging Spa, Milan, Italy) as a quick bolus into the antecubital vein. All lesions were proved by pathologic and MRI findings as primary or metastatic hepatic malignancies. Results. On CEUS, 45 (64.2%) FLLs displayed arterial hyperenhancement and 55 (78.5%) lesions showed hypoenhancement in portal venous and late phase (PVLP). Homogeneous and complete hyperenhancement pattern during the arterial phase is highly suspicious for HCC in liver cirrhosis (96.8%). Arterial isoenhancement and early washout during PVLP are characteristic for metastasis (73.3%). For recurrence lesions, arterial hyperenhancement and isoenhancement during PVLP are more common (60%). Conclusion. CEUS may provide added diagnostic values in FLLs appearing indistinctive on BMUS. Presence of early arterial enhancement and washout during PVLP may be helpful for detection of those lesions.

Recognizing Focal Liver Lesions in CEUS With Dynamically Trained Latent Structured Models

This work investigates how to automatically classify Focal Liver Lesions (FLLs) into three specific benign or malignant types in Contrast-Enhanced Ultrasound (CEUS) videos, and aims at providing a computational framework to assist clinicians in FLL diagnosis. The main challenge for this task is that FLLs in CEUS videos often show diverse enhancement patterns at different temporal phases. To handle these diverse patterns, we propose a novel structured model, which detects a number of discriminative Regions of Interest (ROIs) for the FLL and recognize the FLL based on these ROIs. Our model incorporates an ensemble of local classifiers in the attempt to identify different enhancement patterns of ROIs, and in particular, we make the model reconfigurable by introducing switch variables to adaptively select appropriate classifiers during inference. We formulate the model learning as a non-convex optimization problem, and present a principled optimization method to solve it in a dynamic manner: the latent structures (e.g. the selections of local classifiers, and the sizes and locations of ROIs) are iteratively determined along with the parameter learning. Given the updated model parameters in each step, the data-driven inference is also proposed to efficiently determine the latent structures by using the sequential pruning and dynamic programming method. In the experiments, we demonstrate superior performances over the state-of-the-art approaches. We also release hundreds of CEUS FLLs videos used to quantitatively evaluate this work, which to the best of our knowledge forms the largest dataset in the literature. Please find more information at "http://vision.sysu.edu.cn/projects/fllrecog/".

Parametric mapping of contrasted ovarian transvaginal sonography

The purpose of this study was to assess the accuracy of parametric analysis of transvaginal contrast-enhanced ultrasound (TV-CEUS) for distinguishing benign versus malignant ovarian masses. A total of 48 ovarian masses (37 benign and 11 borderline/malignant) were examined with TV-CEUS (Definity; Lantheus, North Billerica, MA; Philips iU22; Philips Medical Systems, Bothell, WA). Parametric images were created offline with a quantification software (Bracco Suisse SA, Geneva, Switzerland) with map color scales adjusted such that abnormal hemodynamics were represented by the color red and the presence of any red color could be used to differentiate benign and malignant tumors. Using these map color scales, low values of the perfusion parameter were coded in blue, and intermediate values of the perfusion parameter were coded in yellow. Additionally, for each individual color (red, blue, or yellow), a darker shade of that color indicated a higher intensity value. Our study found that the parametric mapping method was considerably more sensitive than standard region of interest (ROI) analysis for the detection of malignant tumors but was also less specific than standard ROI analysis. Parametric mapping allows for stricter cutoff criteria, as hemodynamics are visualized on a finer scale than ROI analyses, and as such, parametric maps are a useful addition to TV-CEUS analysis by allowing ROIs to be limited to areas of the highest malignant potential.

Focal Lesions in Fatty Liver: If Quantitative Analysis Facilitates the Differentiation of Atypical Benign from Malignant Lesions

To evaluate the diagnostic performance of quantitative analysis as an adjunctive diagnostic tool to contrast-enhanced ultrasound (US) for the differentiation of atypical benign focal liver lesions (FLLs) from malignancies in fatty liver. Twenty-seven benign FLLs and fifty-six malignant FLLs that appeared hyper-enhanced during the arterial phase with washout in the portal or late phase in fatty liver were analyzed. Chi-square tests and logistic regression were applied to identify the specific features. Three sets of criteria were assigned: 1) all FLLs subjected to routine contrast-enhanced US; 2) all FLLs subjected to quantification analysis and contrast-enhanced US; and 3) parts of FLLs that could not be diagnosed using contrast-enhanced US (n = 66, 75.9%) but instead were diagnosed using parametric features. The sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC) of the three sets of criteria were analyzed. The AUCs of the criterion set 2 were significantly higher than those of criterion set 1 (0.904 versus 0.792, P = 0.008). Criterion set 3 showed a relatively high sensitivity (90.2%) with a relatively high AUC (0.845). The quantification analysis offers improved diagnostic performance for the differential identification of atypical benign FLLs from malignancies in fatty liver.

Improved Patch-Based Automated Liver Lesion Classification by Separate Analysis of the Interior and Boundary Regions

The bag-of-visual-words (BoVW) method with construction of a single dictionary of visual words has been used previously for a variety of classification tasks in medical imaging, including the diagnosis of liver lesions. In this paper, we describe a novel method for automated diagnosis of liver lesions in portal-phase computed tomography (CT) images that improves over single-dictionary BoVW methods by using an image patch representation of the interior and boundary regions of the lesions. Our approach captures characteristics of the lesion margin and of the lesion interior by creating two separate dictionaries for the margin and the interior regions of lesions ("dual dictionaries" of visual words). Based on these dictionaries, visual word histograms are generated for each region of interest within the lesion and its margin. For validation of our approach, we used two datasets from two different institutions, containing CT images of 194 liver lesions (61 cysts, 80 metastasis, and 53 hemangiomas). The final diagnosis of each lesion was established by radiologists. The classification accuracy for the images from the two institutions was 99% and 88%, respectively, and 93% for a combined dataset. Our new BoVW approach that uses dual dictionaries shows promising results. We believe the benefits of our approach may generalize to other application domains within radiology.

A new automated quantification algorithm for the detection and evaluation of focal liver lesions with contrast-enhanced ultrasound

PURPOSE

Detect and classify focal liver lesions (FLLs) from contrast-enhanced ultrasound (CEUS) imaging by means of an automated quantification algorithm.

METHODS

The proposed algorithm employs a sophisticated segmentation method to detect and contour focal lesions from 52 CEUS video sequences (30 benign and 22 malignant). Lesion detection involves wavelet transform zero crossings utilization as an initialization step to the Markov random field model toward the lesion contour extraction. After FLL detection across frames, time intensity curve (TIC) is computed which provides the contrast agents' behavior at all vascular phases with respect to adjacent parenchyma for each patient. From each TIC, eight features were automatically calculated and employed into the support vector machines (SVMs) classification algorithm in the design of the image analysis model.

RESULTS

With regard to FLLs detection accuracy, all lesions detected had an average overlap value of 0.89 ± 0.16 with manual segmentations for all CEUS frame-subsets included in the study. Highest classification accuracy from the SVM model was 90.3%, misdiagnosing three benign and two malignant FLLs with sensitivity and specificity values of 93.1% and 86.9%, respectively.

CONCLUSIONS

The proposed quantification system that employs FLLs detection and classification algorithms may be of value to physicians as a second opinion tool for avoiding unnecessary invasive procedures.

Role of portal vein tumor thrombosis in quantitative perfusion analysis of contrast-enhanced ultrasound of hepatocellular carcinoma

The goal of our study was to evaluate the differences between quantitative parameters of hepatocellular carcinoma (HCC) with or without portal vein tumor thrombosis (PVTT) on contrast-enhanced ultrasound (CEUS). Twenty-four patients with HCC with PVTT and 48 without PVTT underwent CEUS using sulfur hexafluoride microbubbles. Dynamic images were analyzed with quantification software. Time-intensity curves were obtained for HCC and surrounding liver parenchyma, and parameters including the intensity maximum (IMAX), rising time (RT), mean transit time and time to peak (TTP) were compared within and between the PVTT and control groups, respectively. RT and TTP of HCC were significantly faster than those of surrounding liver parenchyma in both the PVTT and control groups. IMAX of HCC was significantly stronger than that of surrounding liver in the control group, but not significantly different from that of liver parenchyma in the PVTT group. RT and TTP of HCC and surrounding liver were significantly faster in the PVTT group compared with the control group, whereas IMAX values of HCC in the PVTT group were lower than those in the control group. HCC with PVTT presents different hemodynamic parameters, with faster RT and TTP and lower IMAX than those for HCC without PVTT. Quantitative perfusion analysis of CEUS may be a potential method for predicting PVTT.

Acoustic characterization and pharmacokinetic analyses of new nanobubble ultrasound contrast agents

In contrast to the clinically used microbubble ultrasound contrast agents, nanoscale bubbles (or nanobubbles) may potentially extravasate into tumors that exhibit more permeable vasculature, facilitating targeted molecular imaging and drug delivery. Our group recently presented a simple strategy using the non-ionic surfactant Pluronic as a size control excipient to produce nanobubbles with a mean diameter of 200 nm that exhibited stability and echogenicity on par with microbubbles. The objective of this study was to carry out an in-depth characterization of nanobubble properties as compared with Definity microbubbles, both in vitro and in vivo. Through use of a tissue-mimicking phantom, in vitro experiments measured the echogenicity of the contrast agent solutions and the contrast agent dissolution rate over time. Nanobubbles were found to be more echogenic than Definity microbubbles at three different harmonic frequencies (8, 6.2 and 3.5 MHz). Definity microbubbles also dissolved 1.67 times faster than nanobubbles. Pharmacokinetic studies were then performed in vivo in a subcutaneous human colorectal adenocarcinoma (LS174T) in mice. The peak enhancement and decay rates of contrast agents after bolus injection in the liver, kidney and tumor were analyzed. No significant differences were observed in peak enhancement between the nanobubble and Definity groups in the three tested regions (tumor, liver and kidney). However, the decay rates of nanobubbles in tumor and kidney were significantly slower than those of Definity in the first 200-s fast initial phase. There were no significant differences in the decay rates in the liver in the initial phase or in three regions of interest in the terminal phase. Our results suggest that the stability and acoustic properties of the new nanobubble contrast agents are superior to those of the clinically used Definity microbubbles. The slower washout of nanobubbles in tumors suggests potential entrapment of the bubbles within the tumor parenchyma.

Diagnostic value of contrast-enhanced ultrasound parametric imaging in breast tumors

PURPOSE

This study aimed to evaluate the diagnostic value of SonoLiver software for parametric imaging in breast tumors.

METHODS

Contrast-enhanced ultrasound (CEUS) was performed in 216 breast lesions (113 malignant, 103 benign). The CEUS parameters were compared between benign and malignant lesions. The rise time, the time to peak, the mean transit time and dynamic vessel pattern (DVP) were analyzed using SonoLiver software.

RESULTS

Quantitative analysis showed that the rise time was 16.52±4.15 seconds in the benign group vs. 13.86±3.36 seconds in the malignant group (p=0.007), and the time to peak was 19.86±4.87 seconds in the benign group vs. 16.52±4.85 seconds in the malignant group (p=0.009). The mean transit time was 80.55±18.65 seconds in the benign group vs. 65.16±20.28 seconds in the malignant group (p=0.006). The difference between the distribution of DVP in benign and malignant tumors was statistically significant. One hundred one malignant tumors (89.4%) performed an irregular red/yellow fill in the region of interest (ROI) and 85 benign tumors (82.5%) performed a single blue/green fill in the ROI. The sensitivity, specificity, and accuracy of parametric imaging in breast tumors were 84.1%, 85.4%, 84.7%, respectively.

CONCLUSION

The CEUS parametric imaging can distinguish differences between malignant and benign breast tumors as well as provide diagnostic information on breast lesions.

Hepatocellular carcinoma treated with sorafenib: early detection of treatment response and major adverse events by contrast-enhanced US

BACKGROUND & AIMS

Early prediction of tumour response and major adverse events (AEs), especially liver failure, in patients with hepatocellular carcinoma (HCC) is essential for maximizing the clinical benefits of sorafenib. To evaluate the usefulness of dynamic contrast-enhanced ultrasound (DCE-US) for the early prediction of tumour response and major AEs in HCC patients.

METHODS

Thirty-seven HCC patients were started on a reduced dosage of sorafenib, subsequently increased to the standard dosage. Tumour response at 1 month was assessed by CT using the Response Evaluation Criteria in Solid Tumors (RECIST). Major AEs were defined as grade 3 or higher. DCE-US was performed before treatment (day 0) and on days 7, 14 and 28. Changes in perfusion parameters in the tumour and liver parenchyma between day 0 and later time points were compared between treatment responders and nonresponders based on RECIST and between patients who experienced major AEs and those who did not. Tumour results were also compared with progression-free survival (PFS) and overall survival (OS).

RESULTS

Tumour perfusion parameters based on the area under the time-intensity curve (AUC) were statistically significant, with AUC during washin on day 14, the most relevant for tumour response (P = 0.0016) and AUC during washin on day 7, the most relevant for both PFS (P = 0.009) and OS (P = 0.037). A decrease in total AUC between days 0 and 7 in the liver parenchyma was strongly correlated with major AEs (P = 0.0002).

CONCLUSION

DCE-US may be useful for the early prediction of tumour response and major AEs in patients with HCC.

Liver dysplasia: US molecular imaging with targeted contrast agent enables early assessment

PURPOSE

To investigate the ability of vascular endothelial growth factor receptor type 2 (VEGFR2)-targeted ultrasonographic (US) microbubbles for the assessment of liver dysplasia in transgenic mice.

MATERIALS AND METHODS

Animal experiments were approved by the governmental review committee. Nuclear factor-κB essential modulator knock-out mice with liver dysplasia and wild-type mice underwent liver imaging by using a clinical US system. Two types of contrast agents were investigated: nontargeted, commercially available, second-generation microbubbles (SonoVue) and clinically translatable PEGylated VEGFR2-targeted microbubbles (BR55). Microbubble kinetics was investigated over the course of 4 minutes. Targeted contrast material-enhanced US signal was quantified 5 minutes after injection. Competitive in vivo binding experiments with BR55 were performed in knock-out mice. Immunohistochemical and hematoxylin-eosin staining of liver sections was performed to validate the in vivo US results. Groups were compared by using the Mann-Whitney test.

RESULTS

Peak enhancement after injection of SonoVue and BR55 did not differ in healthy and dysplastic livers (SonoVue, P = .46; BR55, P = .43). Accordingly, immunohistochemical findings revealed comparable vessel densities in both groups. The specificity of BR55 to VEGFR2 was proved by in vivo competition (P = .0262). While the SonoVue signal decreased similarly in healthy and dysplastic livers during the 4 minutes, there was an accumulation of BR55 in dysplastic livers compared with healthy ones. Furthermore, targeted contrast-enhanced US signal indicated a significantly higher site-specific binding of BR55 in dysplastic than healthy livers (P = .005). Quantitative immunohistologic findings confirmed significantly higher VEGFR2 levels in dysplastic livers (P = .02).

CONCLUSION

BR55 enables the distinction of early stages of liver dysplasia from normal liver.

Early detection of ovarian cancer with conventional and contrast-enhanced transvaginal sonography: recent advances and potential improvements

Recently, there have been several major technical advances in the sonographic diagnosis of ovarian cancer in its early stages. These include improved assessment of tumor morphology with transvaginal sonography (TVS), and detection and characterization of tumor neovascularity with transvaginal color Doppler sonography (TV-CDS) and contrast-enhanced transvaginal sonography (CE-TVS). This paper will discuss and illustrate these improvements and describe how they enhance detection of early-stage ovarian cancer. Our initial experience with parametric mapping of CE-TVS will also be mentioned.