A Nomogram Based on Contrast-Enhanced Ultrasound to Predict the Microvascular Invasion in Hepatocellular Carcinoma

ObjectiveThe aim of this study was to establish and validate a contrast-enhanced ultrasound (CEUS) nomogram for pre-operative microvascular invasion (MVI) prediction in hepatocellular carcinoma (HCC), and compare it with the nomogram based on gadopentetate dimeglumine–enhanced magnetic resonance imaging (Gd-MRI).MethodsA total of 251 patients with a single HCC were enrolled in this prospective study, including 176 patients in the training cohort and 75 patients in the validation cohort. Contrast-enhanced ultrasound (CEUS) with Sonazoid and Gd-MRI was performed pre-operatively. Post-operative histopathology was the gold standard for MVI. Univariate and multivariate logistic regression was performed to determine independent risk factors for MVI. Nomograms based on CEUS and Gd-MRI were established, and their discrimination, calibration and decision curve analysis were evaluated and compared.ResultsMultivariate logistic regression revealed that arterial circular enhancement, non-enhancing area and thick ring-like enhancement in the post-vascular phase were independent risk factors for MVI. The areas under the receiver operating characteristic curve of the nomogram were 0.841 (0.779–0.892) and 0.914 (0.827–0.966) in the training and validation cohorts, with no significant difference compared with the Gd-MRI nomogram (p = 0.294, 0.321). The C-indexes were 0.821 and 0.870 in the training and validation cohorts. Decision curve analysis revealed that the CEUS nomogram had better clinical applicability than the Gd-MRI nomogram when the threshold probability was between 0.35 and 0.95.Conclusion: The CEUS-based nomogram was available for predicting MVI in HCC, and its predictive performance was not inferior to that of Gd-MRI.     

Determination of Skeletal Muscle Microvascular Flowmotion with Contrast-Enhanced Ultrasound

Most methods of assessing flowmotion (rhythmic oscillation of blood flow through tissue) are limited to small sections of tissue and are invasive in tissues other than skin. To overcome these limitations, we adapted the contrast-enhanced ultrasound (CEUS) technique to assess microvascular flowmotion throughout a large region of tissue, in a non-invasive manner and in real time. Skeletal muscle flowmotion was assessed in anaesthetised Sprague Dawley rats, using CEUS and laser Doppler flowmetry (LDF) for comparison. Wavelet transformation of CEUS and LDF data was used to quantify flowmotion. The α-adrenoceptor antagonist phentolamine was infused to predictably blunt the neurogenic component of flowmotion. Both techniques identified similar flowmotion patterns, validating the use of CEUS to assess flowmotion. This study demonstrates for the first time that the novel technique of CEUS can be adapted for determination of skeletal muscle flowmotion in large regions of skeletal muscle.     

Dynamic Contrast-Enhanced Ultrasonography with Sonazoid for Diagnosis of Microvascular Invasion in Hepatocellular Carcinoma

The aim of the present study was to investigate the imaging features observed in pre-operative Sonazoid contrast-enhanced ultrasound (SZ-CEUS) and the correlations with the presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. In this single-center retrospective study, 31 patients with surgically and histopathologically confirmed HCC lesions were included. Patients were classified according to the presence of MVI into the MVI-positive group (n = 15) and MVI-negative group (n = 16). The CEUS examinations were performed within 2 or 3 d before surgery. Features, including tumor necrosis and ultrasound contrast agent (UCA) distribution characteristics in the arterial phase (AP), tumor types (single nodular [SN] or non-single nodular [non-SN]) in the post-vascular phase (PVP), wash-in time, wash-in slope, time to peak (TTP) and peak intensity (PI), were assessed. Univariate analysis revealed statistically significant differences between the two groups with respect to tumor necrosis (p = 0.002), inhomogeneous distribution of contrast agent in the AP (p = 0.001) and non-SN type in the PVP (p < 0.001). There was no significant difference in the quantitative parameters. Multivariate analysis revealed that non-SN type in the PVP was a significant independent risk factor for MVI of HCC (odds ratio = 30.51, 95% confidence interval [CI]: 2.335–398.731, p = 0.009). The area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 0.873, 93.3%, 81.3%, 82.4% and 92.9%, respectively. Thus, SZ-CEUS can provide useful information for the diagnosis of MVI in HCC.     

Prospective Comparison of Oral Contrast-Enhanced Transabdominal Ultrasound Imaging With Contrast-Enhanced Computed Tomography in Pre-operative Tumor Staging of Gastric Cancer

The aim of this prospective study was to compare the diagnostic accuracy of oral contrast-enhanced transabdominal ultrasound imaging (OCTU) with that of contrast-enhanced computed tomography (CT) for the pre-operative tumor staging of gastric cancer, with post-operative pathology as the standard. We included 108 cases of gastric cancer with simultaneous OCTU and enhanced CT pre-operative tumor staging diagnoses. Results were compared with post-operative pathology based on the eighth edition of the American Joint Committee on Cancer tumor–node–metastasis staging guidelines for gastric cancer. The accuracy of each tumor stage was obtained by comparing OCTU and enhanced CT diagnoses with post-operative pathology. The McNemar test was used to compare the overall accuracy of the two methods. There was no statistical difference in accuracy between OCTU (72.2%) and enhanced CT (75.9%, p = 0.644) for overall pre-operative tumor staging diagnosis. For stages T1 to T4, the accuracy rates of OCTU were 84.2%, 81.8%, 69.4% and 65.5%, respectively, and those for enhanced CT were 52.6%, 72.7%, 87.8% and 72.4%, respectively. OCTU is comparable to enhanced CT in the preoperative overall T-stage diagnosis of gastric cancer.     

Differentiation of Vascular Characteristics Using Contrast-Enhanced Ultrasound Imaging

Ultrasound contrast imaging has been used to assess tumour growth and regression by assessing the flow through the macro- and micro-vasculature. Our aim was to differentiate the blood kinetics of vessels such as veins, arteries and microvasculature within the limits of the spatial resolution of contrast-enhanced ultrasound imaging. The highly vascularised ovine ovary was used as a biological model. Perfusion of the ovary with SonoVue was recorded with a Philips iU22 scanner in contrast imaging mode. One ewe was treated with prostaglandin to induce vascular regression. Time-intensity curves (TIC) for different regions of interest were obtained, a lognormal model was fitted and flow parameters calculated. Parametric maps of the whole imaging plane were generated for 2 × 2 pixel regions of interest. Further analysis of TICs from selected locations helped specify parameters associated with differentiation into four categories of vessels (arteries, veins, medium-sized vessels and micro-vessels). Time-dependent parameters were associated with large veins, whereas intensity-dependent parameters were associated with large arteries. Further development may enable automation of the technique as an efficient way of monitoring vessel distributions in a clinical setting using currently available scanners.     

Fully Automated Carotid Plaque Segmentation in Combined Contrast-Enhanced and B-Mode Ultrasound

Carotid plaque segmentation in B-mode ultrasound (BMUS) and contrast-enhanced ultrasound (CEUS) is crucial to the assessment of plaque morphology and composition, which are linked to plaque vulnerability. Segmentation in BMUS is challenging because of noise, artifacts and echo-lucent plaques. CEUS allows better delineation of the lumen but contains artifacts and lacks tissue information. We describe a method that exploits the combined information from simultaneously acquired BMUS and CEUS images. Our method consists of non-rigid motion estimation, vessel detection, lumen–intima segmentation and media–adventitia segmentation. The evaluation was performed in training (n = 20 carotids) and test (n = 28) data sets by comparison with manually obtained ground truth. The average root-mean-square errors in the training and test data sets were comparable for media–adventitia (411 ± 224 and 393 ± 239 μm) and for lumen–intima (362 ± 192 and 388 ± 200 μm), and were comparable to inter-observer variability. To the best of our knowledge, this is the first method to perform fully automatic carotid plaque segmentation using combined BMUS and CEUS.     

Semi-Automated Segmentation of the Tumor Vasculature in Contrast-Enhanced Ultrasound Data

The vascular architecture in tumors contains relevant information for tumor classification and evaluation of therapy responses. To develop a reliable and user-independent analysis tool, a foreground detection algorithm was combined with a maximum-intensity projection to obtain a high signal-to-noise image from contrast-enhanced B-mode data sets, enabling vessel segmentation by thresholding. Parameters describing the density of the vascular network, the number of vessels and the number of branches were extracted. The highly angiogenic A431 tumors had a relative blood volume of 49%, a mean pixel distance to the next vessel of 1.8?±?0.3 px, 51?±?29 individual vessels and 478?±?184 branching points, whereas the more mature and heterogeneous vascularized human epithelial ovarian carcinoma (MLS) and A549 tumors had values of 30%, 3.7?±?2.7 px, 65?±?12 and 220?±?159, and 13%, 7.4?±?2 px, 31?±?9 and 59?±?40, respectively. Thus, our semi-automated analysis method enables the extraction of quantitative vascular features that may help to simplify and standardize tumor characterization.     

基于临床实验室指标的HBV相关性原发性肝癌微血管侵犯预测模型的建立

目的通过分析临床检验数据,探寻HBV相关性原发性肝细胞癌(HCC)微血管侵犯(MVI)的独立危险因素,建立回归模型并分析其预测价值。方法回顾性分析2015年1月至12月东方肝胆外科医院收治的1 628例HBV相关性HCC患者的临床资料,采用单因素及多因素Logistic回归分析HCC发生MVI的独立危险因素,建立预测模型,并分析该模型的预测价值。结果多因素Logistic回归结果表明,HBeAg(P0.01)、AFP(P0.01)、AFP-L3(P0.01)、PT(P0.01)和PLT(P0.01)是HCC发生MVI的独立危险因素。基于此建立回归预测模型,Logistic(P)鉴别M0与高危MVI(M2)(M0 vs M2)时,其敏感性为73.7%,特异性为61.6%,准确性为66.6%,AUC~(ROC)(95%CI)为0.722(0.692,0.751)。结论 HBeAg、AFP、AFP-L3、PT、PLT是HBV相关性HCC发生MVI的独立危险因素,基于临床检验数据建立的回归模型对于预测HBV相关性HCC患者是否发生高危MVI(M2)具有一定的临床价值。     

Logistic Regression Analysis of Contrast-Enhanced Ultrasound and Conventional Ultrasound Characteristics of Sub-centimeter Thyroid Nodules

The purpose of the study described here was to determine specific characteristics of thyroid microcarcinoma (TMC) and explore the value of contrast-enhanced ultrasound (CEUS) combined with conventional ultrasound (US) in the diagnosis of TMC. Characteristics of 63 patients with TMC and 39 with benign sub-centimeter thyroid nodules were retrospectively analyzed. Multivariate logistic regression analysis was performed to determine independent risk factors. Four variables were included in the logistic regression models: age, shape, blood flow distribution and enhancement pattern. The area under the receiver operating characteristic curve was 0.919. With 0.113 selected as the cutoff value, sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 90.5%, 82.1%, 89.1%, 84.2% and 87.3%, respectively. Independent risk factors for TMC determined with the combination of CEUS and conventional US were age, shape, blood flow distribution and enhancement pattern. Age was negatively correlated with malignancy, whereas shape, blood flow distribution and enhancement pattern were positively correlated. The logistic regression model involving CEUS and conventional US was found to be effective in the diagnosis of sub-centimeter thyroid nodules.     

3-D Multi-parametric Contrast-Enhanced Ultrasound for the Prediction of Prostate Cancer

Trans-rectal ultrasound-guided 12-core systematic biopsy (SBx) is the standard diagnostic pathway for prostate cancer (PCa) because of a lack of sufficiently accurate imaging. Quantification of 3-D dynamic contrast-enhanced ultrasound (US) might open the way for a targeted procedure in which biopsies are directed at lesions suspicious on imaging. This work describes the expansion of contrast US dispersion imaging algorithms to 3-D and compares its performance against malignant and benign disease. Furthermore, we examined the feasibility of a multi-parametric approach to predict SBx-core outcomes using machine learning. An area under the receiver operating characteristic (ROC) curve of 0.76 and 0.81 was obtained for all PCa and significant PCa, respectively, an improvement over previous US methods. We found that prostatitis, in particular, was a source of false-positive readings.     

Presentation of Chloromas in B-Mode Ultrasound and Contrast-Enhanced Ultrasound

Chloromas, also referred to as myeloid sarcomas, describe rare extramedullary tumor aggregates of malignant myeloid progenitor cells. The aim of this study was investigate the diagnostic features and characteristics of chloromas using contrast-enhanced ultrasound (CEUS). Between July 2007 and April 2021, 15 patients with 20 myeloid neoplasms and suspected chloroma manifestations were examined using B-mode US (B-US) and CEUS. Clinical data and B-US (echogenicity, border, size) and CEUS (hyper-, iso-, hypo- or complex enhancement) characteristics were retrospectively analyzed. Absolute and relative frequencies were determined. In B-US, the chloromas were most frequently hypo-echoic (n = 15, 75%). In addition, a hyperechoic (n = 2, 10%) or echocomplex (n = 3, 15%) presentation was observed. On CEUS, 7 chloromas (35%) had an arterial hyperenhancement, 8 (40%) an iso-enhancement and 3 (15%) a complex enhancement. Two chloromas (10%) did not exhibit any enhancement. We describe for the first time CEUS and B-US patterns of chloromas. They are typically hypo-echoic on B-US and have a strong iso- or hyperenhancement on CEUS, which may help in the differential diagnosis of some unclear masses (e.g., hematoma, abscess) in patients with myeloid neoplasias. Nevertheless, histology is necessary for a reliable diagnosis.     

Echo-Power Estimation from Log-Compressed Video Data in Dynamic Contrast-Enhanced Ultrasound Imaging

Ultrasound (US) scanners typically apply lossy, non-linear modifications to the US data for visualization purposes. The resulting images are then stored as compressed video data. Some system manufacturers provide dedicated software for quantification purposes to eliminate such processing distortions, at least partially. This is currently the recommended approach for quantitatively assessing changes in contrast-agent concentration from clinical data. However, the machine-specific access to US data and the limited set of analysis functionalities offered by each dedicated-software package make it difficult to perform comparable analyses with different US systems. The objective of this work was to establish if linearization of compressed video images obtained with an arbitrary US system can provide an alternative to dedicated-software analysis of machine-specific files for the estimation of echo-power. For this purpose, an Aplio 50 system (Toshiba Medical Systems, Tochigi, Japan), coupled with dedicated CHI-Q (Contrast Harmonic Imaging Quantification) software by Toshiba Medical Systems, was used. Results were compared with two approaches that apply algorithms to estimate relative echo-power from compressed video images: commercially available VueBox software by Bracco Suisse SA (Geneva, Switzerland) and in-laboratory software called PixPower. The echo-power estimated by CHI-Q analysis indicated a strong linear relationship versus agent concentration in vitro (R² ≥ 0.9996) for dynamic range (DR) settings of DR60 and DR80, with slopes between 9.22 and 9.57 dB/decade (p = 0.05). These values approach the theoretically predicted dependence of 10.0 dB/decade (equivalent to 3 dB for each concentration doubling). Echo-power estimations obtained from compressed video images with VueBox and PixPower also exhibited strong linear proportionality with concentration (R² ≥ 0.9996), with slopes between 9.30 and 9.68 dB/decade (p = 0.05). On an independent in vivo data set (N = 24), the difference in echo-power estimation between CHI-Q and each of the other two approaches was calculated after excluding regions that contain pixels affected by saturated or thresholded pixel values. The mean difference in estimates (expressed in decibels) was −0.25 dB between VueBox and CHI-Q (95% confidence interval: −0.75 to 0.26 dB) and −0.17 dB between PixPower and CHI-Q (95% confidence interval: −0.67 to 0.13 dB). To achieve linearization of data, one of the approaches (VueBox) requires calibration files provided by the software manufacturer for each machine type and setting. The other (PixPower) requires empirical correction of the imaging dynamic range based on ground truth data. These requirements could potentially be removed if US system manufacturers were willing to make relevant information on the applied processing publically available. Reliable echo-power estimation from linearized data would facilitate inclusion of different US systems in multicentric studies and more widespread implementation of emerging techniques for quantitative analysis of contrast ultrasound.     

Role of Contrast-Enhanced Ultrasound in the Pre-operative Diagnosis of Cervical Lymph Node Metastasis in Patients with Papillary Thyroid Carcinoma

The objective of this study was to prospectively evaluate the diagnostic accuracy of contrast-enhanced ultrasonography (CEUS) in differentiating between benign and metastatic cervical lymph nodes in patients with papillary thyroid cancer (PTC). Three hundred nineteen cervical lymph nodes (162 metastatic from PTC and 157 benign) were evaluated using conventional ultrasonography (US) and CEUS before biopsy or surgery. Metastatic lymph nodes more often manifested centripetal or asynchronous perfusion, hyper-enhancement, heterogeneous enhancement, perfusion defects and ring-enhancing margins than benign lymph nodes at pre-operative CEUS (all p values < 0.001). The area under the receiver operating characteristic curve (AUC) for the combination of conventional US and CEUS (0.983, 95% confidence interval [CI]: 0.971–0.994) was higher than that of conventional US alone (0.929, 95% CI: 0.899–0.958) and CEUS (0.911, 95% CI: 0.876–0.947). In conclusion, CEUS is a promising tool in conjunction with conventional US for the pre-operative prediction of metastatic cervical lymph nodes in patients with PTC.     

Qualitative and Quantitative Contrast-Enhanced Ultrasound Combined with Conventional Ultrasound for Predicting the Malignancy of Soft Tissue Tumors

This study was aimed at evaluating the performance of perfusion patterns and the quantitative parameters of contrast-enhanced ultrasound (CEUS) in the detection of soft tissue tumors (STTs) and establishing a US workflow for STTs to improve patient management. Conventional ultrasound (US) and CEUS data were retrospectively collected from 156 soft tissue masses. Six perfusion patterns (P1–P6) were applied for CEUS qualitative analysis. Multivariate logistic regression was used to evaluate the performance of conventional US and qualitative and quantitative CEUS in distinguishing benign and malignant STTs. The malignancy rates of P1–P6 in STTs were 0%, 50.0%, 9.1%, 33.3%, 73.4% and 61.0%, respectively. For "non-P1" STTs, the predictive model combining quantitative CEUS parameters with conventional US features, including margin (odds ratio [OR] = 4.490, p = 0.000), vascular density (OR = 2.307, p = 0.013), 50% wash-out intensity (OR = 1.904, p = 0.032) and 50% wash-out time (OR = 1.031, p = 0.019), performed favorably in predicting malignancy, with an accuracy of 81.0% and an area under the receiver operating characteristic curve of 0.868. Furthermore, a US workflow for the detection of STTs based on conventional US and CEUS was established. CEUS with qualitative and quantitative analyses could be an effective tool for STT diagnosis. The US workflow in this study may improve the management of STT patients.     

How Pre-operative Sentinel Lymph Node Contrast-Enhanced Ultrasound Helps Intra-operative Sentinel Lymph Node Biopsy in Breast Cancer: Initial Experience

We aimed to evaluate the value of sentinel lymph node contrast-enhanced ultrasound (SLN-CEUS) and surface tracing for the biopsy of intra-operative sentinel lymph nodes (SLNs). Between June 2015 and December 2017, a total of 453 patients with early invasive breast cancer were recruited. Patients received an intradermal injection of microbubble contrast agent around the areola on the day before surgery. The locations and sizes of lymphatic channels (LCs) and SLNs were marked on the body surface using gentian violet. Then, injection of double blue dye was performed half an hour before surgery. We compared the pathway of LCs and the location of SLNs obtained from SLN-CEUS and blue dye during surgery. Among the 453 patients, the mean numbers of LCs and SLNs detected by SLN-CEUS were 1.42 and 1.72, respectively, and the coincidence rate was 98.2% compared with blue dye during surgery. The median distance from the SLN to skin measured by pre-operative CEUS and blue dye was 1.95 ± 0.69 and 2.03 ± 0.87 cm (p = 0.35). There were three SLN enhancement in our research, including homogeneous enhancement, inhomogeneous enhancement and no enhancement, with the sensitivity, specificity, positive predictive value and negative predictive value of SLN-CEUS for the diagnosis of SLNs being 96.82%, 91.91%, 87.54% and 98.01%, respectively. SLN-CEUS with skin marking can identify the pathway of LCs and the location of the SLN before surgery, measure the distance from the SLN to skin and determine if the SLN is metastatic. SLN-CEUS can be used as an effective complement to the blue dye method.     

Contrast-Enhanced Ultrasound Characteristics of Breast Cancer: Correlation with Prognostic Factors

The purpose of the work described here was to investigate the correlation of contrast-enhanced ultrasound (CEUS) characteristics with prognostic factors in breast cancer. Forty-five consecutive breast cancer patients were studied with CEUS. All patients were diagnosed with invasive ductal carcinoma on the basis of biopsy or surgery results. Lack of blood perfusion of the tumor was identified in 2 cases; blood perfusion was observed in 43 cases. Enhancement was heterogeneous in 25 cases, and centripetal in 25 cases. A blood perfusion defect was present in 27 cases. Enhancement shape was irregular in 37 cases, margins were poorly defined in 34 cases, and penetrating vessels were present in 32 cases. Compared with the surrounding normal tissue, tumor tissue had faster rising times and times to peak and higher peak intensities and wash-in slopes; the differences between the two groups were statistically significant (p < 0.05). Compared with the interior of the tumor, the periphery had faster times to peak and higher peak intensities and wash-in slopes (p < 0.05). Heterogeneous enhancement, perfusion defect, centripetal enhancement and penetrating vessels were correlated with prognosis (p < 0.05). Overall, some CEUS characteristics of breast cancer were associated with prognostic factors that can predict breast cancer prognosis in vivo.