Efficacy of sonazoid (perflubutane) for contrast-enhanced ultrasound in the differentiation of focal breast lesions: phase 3 multicenter clinical trial.

OBJECTIVE: The objective of our study was to compare the efficacy of contrast-enhanced ultrasound (CEUS) using the ultrasound contrast agent Sonazoid (perflubutane) with unenhanced ultrasound and supplementary contrast-enhanced MRI in the differential diagnosis (benign vs malignant) of focal breast lesions. The safety of Sonazoid was also assessed in this study. SUBJECTS AND METHODS: A total of 127 patients with focal breast lesions were enrolled in this study at five centers in Japan. Three reviewers who were blinded to the patient characteristics independently assessed the ultrasound images and MR images in a randomized sequence. The accuracy, sensitivity, and specificity of CEUS, unenhanced ultrasound, and supplementary contrast-enhanced MRI for the differential diagnosis were compared using generalized estimating equation analyses. Diagnostic confidence was also assessed. RESULTS: The accuracy of CEUS was significantly higher than that of unenhanced ultrasound (87.2% vs 65.5%, respectively; p < 0.001). In addition, CEUS showed significantly higher specificity, although the improvement in sensitivity was not statistically significant. The accuracy and specificity were significantly higher with CEUS than with contrast-enhanced MRI, but the improvement in sensitivity was not statistically significant. The area under the curve in a receiver operating characteristic analysis was significantly greater with CEUS than with unenhanced ultrasound. The incidence of adverse events was 11.4% and the incidence of adverse drug reactions was 3.3%. All adverse drug reactions were mild. CONCLUSION: CEUS using Sonazoid was confirmed to be superior to unenhanced ultrasound for the differential diagnosis (benign vs malignant) of focal breast lesions in terms of diagnostic accuracy with no serious adverse reactions.

Acceleration time ratio for the assessment of extracranial internal carotid artery stenosis.

PURPOSE: To apply the acceleration time (AcT) ratio as an additional marker for diagnosing internal carotid artery (ICA) stenosis. METHODS: Carotid artery sonography was performed in 140 patients, and the AcT ratio was calculated as the AcT of the ICA divided by the AcT of the ipsilateral common carotid artery, and compared with diameter stenosis. RESULTS: There was a significant correlation between diameter stenosis and the AcT ratio. The receiver operating characteristic curve revealed a cutoff level of 1.5, with 90.0 % sensitivity and 93.5 % specificity for stenosis >65 %. CONCLUSION: Our results indicate that applying the AcT ratio can help in the diagnosis of ICA stenosis.

Principle of contrast-enhanced ultrasonography.

Sonazoid, an ultrasound contrast agent, has been covered by insurance in Japan since January 2007 for the diagnosis of hepatic mass lesions and is widely used for diagnosing not only primary liver cancer but also liver metastases such as those from breast cancer and colorectal cancer. Contrast-enhanced ultrasound for breast mass lesions has been covered by insurance since August 2012 after phase II and phase III clinical trials showed that the diagnostic performance was significantly superior to that of B-mode and contrast-enhanced magnetic resonance imaging. This paper describes the principles of imaging techniques in contrast-enhanced ultrasonography including the filter, pulse inversion, amplitude modulation, and amplitude-modulated pulse inversion methods. The pulse inversion method, which visualizes the second-harmonic component using the nonlinear scattering characteristics of the contrast agent, is widely used regardless of the contrast agent and target organ because of its high resolution. Sonazoid has a stiffer shell and requires a higher acoustic amplitude than Sonovue to generate nonlinear vibrations. The higher transmitted sound pressure generates more tissue harmonic components. Since pulse inversion allows visualization of the tissue harmonic components, amplitude modulation and amplitude-modulated pulse inversion, which include few tissue harmonic components, are primarily used. Amplitude modulation methods detect nonlinear signals from the contrast agent in the fundamental band. The mechanism of the amplitude modulation is considered to be changes in the echo signal's phase depending on the sound pressure. Since the tissue-derived component is minor in amplitude modulation methods, good contrast sensitivity can be obtained.

JSUM ultrasound elastography practice guidelines: breast.

Ten years have passed since the first elastography application: Real-time Tissue Elastography™. Now there are several elastography applications in existence. The Quality Control Research Team of The Japan Association of Breast and Thyroid Sonology (JABTS) and the Breast Elasticity Imaging Terminology and Diagnostic Criteria Subcommittee, Terminology and Diagnostic Criteria Committee of the Japan Society of Ultrasonics in Medicine (JSUM) have advocated breast elastography classifications for exact knowledge and good clinical use. We suggest two types of classifications: the technical classification and the classification for interpretation. The technical classification has been created to use vibration energy and to make images, and also shows how to obtain a good elastic image. The classification for interpretation has been prepared on the basis of interpretation of evidence in this decade. Finally, we describe the character and specificity of each vender equipment. We expect the present guidelines to be useful for many physicians and examiners throughout the world.

Transmission electron microscopy study on the effects of the ultrasound contrast agent Levovist on hepatic cells.

PURPOSE: The Ultrasound Equipment and Safety Committee of The Japan Society of Ultrasonics in Medicine performed experiments to confirm whether contrast-enhanced ultrasonography damages liver cells. METHODS: Rats were injected with 0.1 ml of 300 mg/ml ultrasound contrast agent (UCA). Diagnostic ultrasound pulses with a center frequency of 6 MHz and a mechanical index of 1.9 were applied to rat livers with a water bag as a coupler to maintain a distance of 2-6 cm between the ultrasound probe surface and the liver. Contrast-enhanced ultrasonography was carried out for 10 s to visualize the entire liver. Then, specimens of liver tissue were fixed using two types of fixation: immersion and perfusion fixation. RESULTS: Although some variations were found in electron micrographs of liver tissue fixed using immersion fixation, none of three blinded readers found any significant differences between micrographs of liver tissue from rats receiving UCA with sonication and those from sham-treated control rats. Changes observed were not thought to be group-specific but instead due to differences between individual rats. When the livers were fixed using perfusion fixation and the hepatic vein was cut after injection of physiological saline for perfusion, a large number of vacuoles ≥2 µm in diameter were observed. This finding suggested that hepatic cell damage observed in this study was caused by high perfusion pressure during the liver fixation process rather than by sonication with UCA. CONCLUSION: Blinded readings of electron micrographs showed no clear evidence that the use of Levovist in ADI mode ultrasonography causes significant damage to liver tissue.

Phase II clinical study of DD-723 (perflubutane): dose-response study in patients with breast tumors.

PURPOSE: We compared the contrast effect of three doses of DD-723 in subjects with breast tumors to determine the recommended dose. We then evaluated differential diagnosis results using plain ultrasonography, contrast-enhanced ultrasonography (plain + enhanced), and contrast-enhanced magnetic resonance imaging (MRI) compared to the pathological diagnosis. METHODS: To evaluate the contrast effect, contrast-enhanced ultrasonic images were independently evaluated in a randomized sequence by three blinded reviewers trained in the evaluation method beforehand. Multiple evaluation results from the three reviewers were used to assess the overall contrast effect. The differential diagnosis was evaluated independently by three blinded reviewers using contrast-enhanced ultrasonic images and contrast-enhanced magnetic resonance images in a randomized sequence; reviewers were also blinded to subject characteristics. Multiple evaluation results from the three reviewers were used to assess the overall differential diagnosis. RESULTS: The recommended dose of DD-723 is an intermediate dose of 0.12 µL MB/kg. Accuracy, sensitivity, and specificity were improved more in the differential diagnosis by contrast-enhanced ultrasonography than in plain ultrasonography. Accuracy and specificity were better and sensitivity similar compared to contrast-enhanced MRI. CONCLUSIONS: An intermediate dose showed the highest efficacy in terms of overall contrast effect. Contrast-enhanced ultrasonography is safe and useful when used in differential diagnosis.

Rapid image stitching and computer-aided detection for multipass automated breast ultrasound.

PURPOSE: Breast ultrasound (US) is recently becoming more and more popular for detecting breast lesions. However, screening results in hundreds of US images for each subject. This magnitude of images can lead to fatigue in radiologist, causing failure in the detection of lesions of a subtle nature. In this study, an image stitching technique is proposed for combining multipass images of the whole breast into a series of full-view images, and a fully automatic screening system that works off these images is also presented. METHODS: Using the registration technique based on the simple sum of absolute block-mean difference (SBMD) measure, three-pass images were merged into full-view US images. An automatic screening system was then developed for detecting tumors from these full-view images. The preprocessing step was used to reduce the tumor detection time of the system and to improve image quality. The gray-level slicing method was then used to divide images into numerous regions. Finally, seven computerized features--darkness, uniformity, width-height ratio, area size, nonpersistence, coronal area size, and region continuity--were defined and used to determine whether or not each region was a part of a tumor. RESULTS: In the experiment, there was a total of 25 experimental cases with 26 lesions, and each case was composed of 252 images (three passes, 84 images/pass). The processing time of the proposed stitching procedure for each case was within 30 s with a Pentium IV 2.0 processor, and the detection sensitivity of the proposed CAD system was 92.3% with 1.76 false positives per case. CONCLUSIONS: The proposed automatic screening system can be applied to the whole breast images stitched together via SBMD-based registration in order to detect tumors.

Breast density analysis for whole breast ultrasound images.

Breast density has been established as an independent risk factor associated with the development of breast cancer. The terms mammographic density and breast density are often used interchangeably, since most breast density studies are performed with projection mammography. It is known that increase in mammographic density is associated with an increased cancer risk. A sensitive method that allows for the measurement of small changes in breast density may provide useful information for risk management. Despite the efforts to develop quantitative breast density measurements from projection mammograms, the measurements show large variability as a result of projection imaging, differing body position, differing levels of compression, and variation of the x-ray beam characteristics. This study used two separate computer-aided methods, threshold-based and proportion-based evaluations, to analyze breast density on whole breast ultrasound (US) imaging and to compare with the grading results of three radiologists using projection mammography. Thirty-two female subjects with 252 images per case were included in this study. Whole breast US images were obtained from an Aloka SSD-5500 ultrasound machine with an ASU-1004 transducer (Aloka, Japan). Before analyzing breast density, an adaptive speckle reduction filter was used for removing speckle noise, and a robust thresholding algorithm was used to divide breast tissue into fatty or fibroglandular classifications. Then, the proposed approaches were applied for analysis. In the threshold-based method, a statistical model was employed to determine whether each pixel in the breast region belonged to fibroglandular or fatty tissue. The proportion-based method was based on three-dimensional information to calculate the volumetric proportion of fibroglandular tissue to the total breast tissue. The experimental cases were graded by the proposed analysis methods and compared with the ground standard density classification assigned by a majority voting of three experienced breast radiologists. For the threshold-based method, 28 of 32 US test cases and for the proportion-based density classifier, 27 of 32 US test cases were found to be in agreement with the radiologist "ground standard" mammographic interpretations, resulting in overall accuracies of 87.5% and 84.4%, respectively. Moreover, the concordance values of the proposed methods were between 0.0938 and 0.1563, which were less than the average interobserver concordance of 0.3958. The experiment result showed that the proposed methods could be a reference opinion and offer concordant and reliable quantification of breast density for the radiologist.

Computer-Aided tumor diagnosis in 3-D breast elastography.

BACKGROUND AND OBJECTIVE: Breast cancer is the major cause of cancer-related mortality in women. However, the death rate can be effectively decreased if the breast cancer can be detected early and treated appropriately. In recent years, many studies have indicated that the elastography has the better diagnosis performance than conventional ultrasound (US). METHOD: In this study, the 3-D tumor contour is obtained by using the proposed segmentation methods and then the features containing texture information, shape information, ellipsoid fitting information are extracted respectively by using the segmented 3-D tumor contour and B-mode images, and the features containing elasticity information are calculated using the same contour and elastographic images. RESULTS: In this experiment, totally 40 biopsy-proved lesions containing 20 benign tumors and 20 malignant tumors are used to evaluate the proposed computer-aided diagnosis (CAD) system. From the experimental results, the combination of shape, ellipsoid fitting and elastographic features has the best performance with accuracy 90.50% (36/40), sensitivity 85.00% (17/20), specificity 95.00% (19/20), and the area under the ROC curve Az 0.987. CONCLUSION: The result shows that tumors can be diagnosed more precisely by using the elastography images.

Development of a fully automatic scheme for detection of masses in whole breast ultrasound images.

Ultrasonography has been used for breast cancer screening in Japan. Screening using a conventional hand-held probe is operator dependent and thus it is possible that some areas of the breast may not be scanned. To overcome such problems, a mechanical whole breast ultrasound (US) scanner has been proposed and developed for screening purposes. However, another issue is that radiologists might tire while interpreting all images in a large-volume screening; this increases the likelihood that masses may remain undetected. Therefore, the aim of this study is to develop a fully automatic scheme for the detection of masses in whole breast US images in order to assist the interpretations of radiologists and potentially improve the screening accuracy. The authors database comprised 109 whole breast US imagoes, which include 36 masses (16 malignant masses, 5 fibroadenomas, and 15 cysts). A whole breast US image with 84 slice images (interval between two slice images: 2 mm) was obtained by the ASU-1004 US scanner (ALOKA Co., Ltd., Japan). The feature based on the edge directions in each slice and a method for subtracting between the slice images were used for the detection of masses in the authors proposed scheme. The Canny edge detector was applied to detect edges in US images; these edges were classified as near-vertical edges or near-horizontal edges using a morphological method. The positions of mass candidates were located using the near-vertical edges as a cue. Then, the located positions were segmented by the watershed algorithm and mass candidate regions were detected using the segmented regions and the low-density regions extracted by the slice subtraction method. For the removal of false positives (FPs), rule-based schemes and a quadratic discriminant analysis were applied for the distribution between masses and FPs. As a result, the sensitivity of the authors scheme for the detection of masses was 80.6% (29/36) with 3.8 FPs per whole breast image. The authors scheme for a computer-aided detection may be useful in improving the screening performance and efficiency.

Establishment of seminars to improve the diagnostic accuracy and effectiveness of breast ultrasound.

PURPOSE: To improve the ability of technicians and physicians to find and diagnose breast lesions in breast ultrasound screening. METHODS: Seminars were organized for technicians and physicians engaged in breast ultrasound screening, and tests were carried out to evaluate the usefulness of the seminars. Each seminar lasted 2 days and comprised lectures and group activities. Pretests and post-tests conducted before and after each seminar, respectively, consisted of 100 questions: 50 about animated images, and 50 about static images. The tests required the participant to find lesions in animated images and estimate the probability of malignancy from static images. RESULTS: In the animated image tests, sensitivity was greater after the seminar, although specificity did not change significantly. In the static image tests, sensitivity increased, and a significant increase was also observed in the receiver operating curve analysis for degree of certainty in diagnosing cancer. CONCLUSION: The seminars improved the participants' ability to find and diagnose breast lesions during ultrasound screening.

Stereoscopic images of breast tumors using 3D real-time tissue elastography.

PURPOSE: This study aimed at evaluating the usefulness of 3D real-time tissue elastography (RTE) images for diagnosing breast tumors. METHODS: A total of 166 breast tumor patients who underwent conventional ultrasound and 2D and 3D RTE examinations were retrospectively analyzed. The 3D RTE images were divided into three types according to the occupancy of blue contrast images. Elastic scores (ES) were obtained by 2D RTE examination. The diagnostic accuracy of 3D and 2D RTE images in differentiating malignant from benign breast tumors was evaluated. RESULTS: Of all cases, 89.4 % of the malignant cases were Type 3 and 86.6 % of the benign cases were Type 1 or 2 according to 3D RTE images. 3D RTE Type 3 and ES ≥ 4 on 2D RTE examination diagnosed malignant tumors with an accuracy of 87.4 and 88.6 %, respectively. In addition, among 34 patients with an ES of 3, the presence of 3D RTE Type 3 diagnosed malignant tumors with an accuracy of 82.4 %. CONCLUSION: In this study, the utility of 3D RTE images was comparable to that of ES on 2D RTE examination in differentiating malignant from benign breast tumors. In addition, utilizing 3D RTE images in cases with an ES of 3 on 2D RTE may increase the diagnostic accuracy for breast tumors.

Relevance of substantia nigra hyperechogenicity and reduced odor identification in idiopathic REM sleep behavior disorder.

BACKGROUND: Substantia nigra (SN) hyperechogenicity determined by transcranial sonography (TCS) and olfactory dysfunction are common findings in Parkinson disease (PD), which may reveal a prodromal synucleinopathy in idiopathic REM sleep behavior disorder (iRBD). METHODS: TCS and the Odor Stick Identification Test for Japanese (OSIT-J) were performed in 34 consecutive patients with iRBD (67.9+/-6.1years), 17 consecutive patients with PD (66.4+/-6.7years), and 21 control group subjects (64.4+/-5.8years). RESULTS: There was a significantly increased area of echogenicity in the SN in the iRBD group (0.20+/-0.13cm2) and PD group (0.22+/-0.11cm2) compared with the control group (0.06+/-0.06cm(2)). We found pathological SN hyperechogenicity (0.20cm2) in 41.2% of the iRBD group, 52.6% of the PD group, and 9.5% of the control group. Further, there were abnormal findings of both pathological SN hyperechogenicity (0.20cm2) and functional anosmia or hyposmia in 4 (11.8%) or 9 (26.5%) of the iRBD group subjects, respectively, and 7 (57.9%) or 2 (11.8%) of the PD group subjects, respectively. CONCLUSION: Pathological SN hyperechogenic abnormality and functional anosmia in iRBD may be a disease state in the transition to a neurodegenerative disease.

Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience.

PURPOSE: A computerized classification scheme to recognize breast parenchymal patterns in whole breast ultrasound (US) images was developed. A preliminary evaluation of the system performance was performed. METHODS: Breast parenchymal patterns were classified into three categories: mottled pattern (MP), intermediate pattern (IP), and atrophic pattern (AP). Each classification was defined as proposed by an experienced physician. A total of 281 image features were extracted from a volume of interest which was automatically segmented. Canonical discriminant analysis with stepwise feature selection was employed for the classification of the parenchymal patterns. RESULTS: The classification scheme accuracy was computed to be 83.3% (10/12 cases) in MP cases, 91.7% (22/24 cases) in IP cases, 92.9% (13/14 cases) in AP cases, and 90.0% (45/50 cases) in all the cases. CONCLUSIONS: The feasibility of an automated ultrasonography classifier for parenchymal patterns was demonstrated with promising results in whole breast US images.

Analysis of elastographic and B-mode features at sonoelastography for breast tumor classification.

The purpose of this study was to evaluate the accuracy of neural network analysis of elastographic features at sonoelastography for the classification of biopsy-proved benign and malignant breast tumors. Sonoelastography of 181 solid breast masses (113 benign and 68 malignant tumors) was performed for 181 patients (mean age, 47 years; range, 24-75 years). After the manual segmentation of the tumors, five elastographic features (strain difference, strain ratio, mean, median and mode) and six B-mode features (orientation, undulation, angularity, average gradient, gradient variance and intensity variance) were computed. A neural network was used to classify tumors by the use of these features. The Student's t test and receiver operating characteristic (ROC) curve analysis were used for statistical analysis. Area under ROC curve (Az) values of the three elastographic features- mean (0.87), median (0.86) and mode (0.83)-were significantly higher than the Az values for the six B-mode features (0.54-0.69) (p < 0.01). Accuracy, sensitivity, specificity and Az of the neural network for the classification of solid breast tumors were 86.2% (156/181), 83.8% (57/68), 87.6% (99/113) and 0.84 for the elastographic features, respectively, and 82.3% (149/181), 70.6% (48/68), 89.4% (101/113) and 0.78 for the B-mode features, respectively, and 90.6% (164/181), 95.6% (65/68), 87.6% (99/113) and 0.92 for the combination of the elastographic and B-mode features, respectively. We conclude that sonoelastographic images and neural network analysis of features has the potential to increase the accuracy of the use of ultrasound for the classification of benign and malignant breast tumors.

Breast density analysis in 3-D whole breast ultrasound images.

The breast density information is one of important factors for estimating the risk in breast cancer detection and early prevention. In this paper, we present two methods, including threshold-based and proportion-based, to automatically analyze the breast density using whole breast ultrasound. The two algorithms are experimented with 32 cases which are scanned from 32 patients using the US machine SSD-5500 with a recent developed scanner ASU-1004 (Aloka, Japan). The experimental results are graded from 4 (extremely dense tissue) to 1 (almost entirely fat), and respectively compared with the majority grades of three radiologists. The accuracy of the threshold-based and proportion-based strategies is 88% and 84% respectively.

Three comparative approaches for breast density estimation in digital and screen film mammograms.

In general, several factors are used for risk estimation in breast cancer detection and early prevention, and one of the important factors in risk of breast cancer is breast density. The mammography is important and effective adjunct in diagnosing the breast cancer. The radiologists would analyze visually the breast density with the BI-RADS lexicon on mammograms. However, this usually causes a large inter-observer variability among the different experienced radiologists. In this paper, we individually adopt three methods, including pixel-based, region-based, and physics-based, to analyze the breast density on mammograms, and the results can offer radiologists a second quantification reading for predicting the risk of breast cancer. The three methods are tested on 208 digital and conventional film mammograms which are scanned from both breasts of 104 patients respectively. The experimental results show that the accuracy of the proposed region-based method, which is more consistent with the radiologists' viewpoint, is 88% more than other two conventional methods.