Can Doppler or contrast-enhanced ultrasound analysis add diagnostically important information about the nature of breast lesions?

OBJECTIVES:

Despite evidence suggesting that Doppler ultrasonography can help to differentiate between benign and malignant breast lesions, it is rarely applied in clinical practice. The aim of this study was to determine whether certain vascular features of breast masses observed by duplex Doppler and color Doppler ultrasonography (before and/or after microbubble contrast injection) add information to the gray-scale analysis and support the Breast Imaging-Reporting and Data System (BI-RADS) classification.

METHODS:

Seventy solid lesions were prospectively evaluated with gray-scale ultrasonography, color Doppler ultrasonography, and contrast-enhanced ultrasonography. The morphological analysis and lesion vascularity were correlated with the histological results.

RESULTS:

Percutaneous core biopsies revealed that 25/70 (17.5%) lesions were malignant, while 45 were benign. Hypervascular lesions with tortuous and central vessels, a resistive index (RI)≥0.73 before contrast injection, and an RI≥0.75 after contrast injection were significantly predictive of malignancy (p<0.001).

CONCLUSION:

The combination of gray-scale ultrasonography data with unenhanced or enhanced duplex Doppler and color Doppler US data can provide diagnostically useful information. These techniques can be easily implemented because Doppler devices are already present in most health centers.     

An Artificial Immune System-Based Support Vector Machine Approach for Classifying Ultrasound Breast Tumor Images

A rapid and highly accurate diagnostic tool for distinguishing benign tumors from malignant ones is required owing to the high incidence of breast cancer. Although various computer-aided diagnosis (CAD) systems have been developed to interpret ultrasound images of breast tumors, feature selection and the setting of parameters are still essential to classification accuracy and the minimization of computational complexity. This work develops a highly accurate CAD system that is based on a support vector machine (SVM) and the artificial immune system (AIS) algorithm for evaluating breast tumors. Experiments demonstrate that the accuracy of the proposed CAD system for classifying breast tumors is 96.67 %. The sensitivity, specificity, PPV, and NPV of the proposed CAD system are 96.67, 96.67, 95.60, and 97.48 %, respectively. The receiver operator characteristic (ROC) area index A_z is 0.9827. Hence, the proposed CAD system can reduce the number of biopsies and yield useful results that assist physicians in diagnosing breast tumors.     

乳腺肿瘤超声图像特征参数量化研究进展

乳腺肿瘤超声图像的特征量化分析对判别肿瘤的良、恶性具有重要价值。本文总结了良性和恶性乳腺肿瘤在超声图像上的特点，将乳腺良性肿瘤和恶性肿瘤鉴别特征在形状、边缘、边界、朝向、回声特点几个方面的量化方法和量化参数进行了较为全面的梳理，并对量化特征与肿瘤良、恶性之间的关系进行了分析。     

Comparing Performance of the CADstream and the DynaCAD Breast MRI CAD Systems

Computer-aided diagnosis (CAD) systems are software programs that use algorithms to find patterns associated with breast cancer on breast magnetic resonance imaging (MRI). The most commonly used CAD systems in the USA are CADstream (CS) (Merge Healthcare Inc., Chicago, IL) and DynaCAD for Breast (DC) (Invivo, Gainesville, FL). Our primary objective in this study was to compare the CS and DC breast MRI CAD systems for diagnostic accuracy and postprocessed image quality. Our secondary objective was to compare the evaluation times of radiologists using each system. Three radiologists evaluated 30 biopsy-proven malignant lesions and 29 benign lesions on CS and DC and rated the lesions’ malignancy status using the Breast Imaging Reporting and Data System. Image quality was ranked on a 0–5 scale, and mean reading times were also recorded. CS detected 70 % of the malignant and 32 % of the benign lesions while DC detected 81 % of the malignant lesions and 34 % of the benign lesions. Analysis of the area under the receiver operating characteristic curve revealed that the difference in diagnostic performance was not statistically significant. On image quality scores, CS had significantly higher volume rendering (VR) (p < 0.0001) and motion correction (MC) scores (p < 0.0001). There were no statistically significant differences in the remaining image quality scores. Differences in evaluation times between DC and CS were also not statistically significant. We conclude that both CS and DC perform similarly in aiding detection of breast cancer on MRI. MRI CAD selection will likely be based on other factors, such as user interface and image quality preferences, including MC and VR.     

超声造影增强模式在乳腺良恶性肿块鉴别诊断中的价值

目的探讨超声造影增强模式对乳腺良恶性肿块鉴别诊断的价值。方法选择40例经病理组织检查证实的乳腺肿瘤患者,均为女性,年龄25～54岁,平均年龄35岁。其中良性肿块25例,恶性肿块15例。使用Siemens Sequoia 512彩色多普勒超声诊断仪,造影剂采用SonoVue,行超声造影增强方式检查。结果乳腺良恶性肿块超声增强方式不同,良性肿块以整体不同程度地均匀型增强改变为主(80%,20/25),恶性肿块主要表现为不均匀增强或周边增强(86.7%,13/15)。结论乳腺良恶性肿块超声造影增强模式不同,可为鉴别诊断提供帮助。     

Expression of MAGE-A and NY-ESO-1 cancer/testis antigens in medullary breast cancer: retrospective immunohistochemical study

Aim

To immunohistochemically evaluate the expression of MAGE-A1, MAGE-A, and NY-ESO-1 cancer/testis (C/T) tumor antigens in medullary breast cancer (MBC) tumor samples and to analyze it in relation to the clinicopathological features.

Methods

This retrospective study included samples from 49 patients: 40 with typical MBC and 9 with atypical MBC. Tumor specimens were obtained from patients operated on in the University Hospital for Tumors and the Sisters of Mercy University Hospital, Zagreb, Croatia, from 1999 to 2005. Standard immunohistochemistry was used on archival paraffin-embedded MBC tissues.

Results

MAGE-A1, MAGE-A, and NY-ESO-1 antigens were expressed in 33% (16/49), 33% (16/49), and 22% (11/49) of patients, respectively. No difference between the groups with and without C/T tumor antigen expression in age at diagnosis, tumor size, axillary lymph node metastasis, adjuvant therapy, and HER-2 expression was identified. Significantly more patients died in the MAGE-A-positive group than in the MAGE-A-negative group (P = 0.010), whereas a borderline significance was found between MAGE-A1-positive and the MAGE-A1-negative group (P = 0.079) and between NY-ESO-1-positive and NY-ESO-1-negative group (P = 0.117). Overall survival, as evaluated by the Kaplan-Meier curves, was lower in MAGE-A1- (P = 0.031), MAGE-A- (P = 0.004), NY-ESO-1-positive groups (P = 0.077).

Conclusion

Expression of C/T antigens may represent a marker of potential prognostic relevance in MBC.Breast cancers are a very heterogeneous group of diseases in terms of natural history, histopathological features, genetic alterations, gene-expression profiles, and response to treatment (1-5). Medullary breast cancers (MBC), both typical and atypical, account for <2% of breast invasive carcinomas. Despite histopathologically highly malignant characteristics, operable and non-metastatic MBCs have a more favorable prognosis than the more common infiltrating ductal breast carcinoma of the same stage (1,6-13). Recent updating of breast cancer classification, based on gene expression profile analyses, has indicated that MBCs can be considered as part of the basal-like carcinoma spectrum made up of the estrogen receptor (ER) negative-, progesterone receptor (PR) negative-, and human epidermal growth factor receptor 2 (HER-2)-negative tumors (‘triple-negative phenotype’) (14-17).Cancer/testis (C/T) antigens are a subgroup of tumor-associated antigens expressed in normal testis germ line cells and trophoblast, and in various malignancies of different histological types. They were discovered in the last two decades by a combination of immunological and molecular biology techniques. Most genes that encode these antigens are localized on the X-chromosome, frequently as multigene families and are referred to as CT-X genes or CT-X antigens (18-23). Biological functions of C/T genes and C/T antigens in both germ lines and tumors remain poorly understood. Due to their tumor-associated expression pattern and limited presence in normal tissues, C/T antigens appear to be valuable targets for immunotherapy of cancer. The best-studied C/T antigens are those of the MAGE-A family and the NY-ESO-1 antigen (18-23). Our initial reports on C/T antigens expression detected by immunohistochemistry in breast invasive ductal carcinomas of no special type (24,25) has been confirmed by other studies (26,27). However, these studies have not been performed on special or relatively rare histological types of breast cancers, such as the MBC.We have recently reported clinicopathological features of MBCs in 48 patients who were operated on in our two hospitals between 1999 and 2005 (28). The present study includes immunohistochemical analysis of the expression of C/T antigens MAGE-A, MAGE-A1, and NY-ESO 1 in these MBC samples.     

Transvaginal color Doppler and CA125 as tools in the differential diagnosis of postmenopausal ovarian masses

Objective: To evaluate whether transvaginal color Doppler and CA125 are valid in differentiating malignant from benign postmenopausal ovarian masses. Methods: Sixty-two women with ovarian masses were studied with transvaginal color Doppler ultrasound before surgery. Serum CA125 levels were also measured. Resistance index (RI) and pulsatility index (PI) were calculated from the waveforms generated from blood flow within the ovary. Results: Benign tumors had a significantly higher pulsatility index (mean 1.23 ± 1.02; range 0.65–2.99) and resistive index (mean 0.78 ± 0.22; range 0.5–1.1) than did malignant tumors. However some overlap in individual values for benign and malignant lesions was found. RI and PI sensitivity were significantly higher than those with CA125 (P < 0.05). Blood flow was detectable by color Doppler imaging in 95% of cases with malignant masses. Conclusion: Doppler sonographic evaluation of resistance and pulsatility indexes in the vessels of ovarian masses together with CA125 increased the sensitivity of prediction of malignancy for pelvic masses, but further work is needed before the validity of these factors is proved.     

Breast Ultrasound Image Classification Based on Multiple-Instance Learning

Breast ultrasound (BUS) image segmentation is a very difficult task due to poor image quality and speckle noise. In this paper, local features extracted from roughly segmented regions of interest (ROIs) are used to describe breast tumors. The roughly segmented ROI is viewed as a bag. And subregions of the ROI are considered as the instances of the bag. Multiple-instance learning (MIL) method is more suitable for classifying breast tumors using BUS images. However, due to the complexity of BUS images, traditional MIL method is not applicable. In this paper, a novel MIL method is proposed for solving such task. First, a self-organizing map is used to map the instance space to the concept space. Then, we use the distribution of the instances of each bag in the concept space to construct the bag feature vector. Finally, a support vector machine is employed for classifying the tumors. The experimental results show that the proposed method can achieve better performance: the accuracy is 0.9107 and the area under receiver operator characteristic curve is 0.96 (p < 0.005).     

Immunohistochemical expression of manganese-superoxide dismutase (Mn-SOD) and triose-phosphate isomerase (TPI) in canine mammary gland tumor

Canine tumors, especially canine breast cancer, share common properties, including metastatic pattern, histopathological characteristics, and biological features with human cancers. Therefore, canine mammary gland tumor is deemed as an appropriate model for human breast cancer. We investigated expression of two important tumor antigens, including manganese superoxide dismutase (Mn-SOD) and triose-phosphate isomerase (TPI) in canine mammary gland tumors using immunohistochemistry analysis. Expression of these proteins were evaluated in tumor (29 malignant and 16 benign samples) and normal (n?=?9) tissues. Protein expression was scored according to a standard method and correlation of protein expression was analyzed with clinicopathological features, including animal age, tumor size, histological type, histological grade, and lymph node metastasis. Overexpressions of Mn-SOD and TPI were detected in 9 (31 %) and 14 (48.3 %) malignant and 3 (18.7 %) and 5 (31.3 %) benign samples, respectively, where overexpressed samples were more frequent in malignant cases than in benign cases (Mn-SOD: P?=?0.049, TPI: P?=?039). Moreover, expression level of Mn-SOD significantly correlated with tumor grade (P?=?0.030). No significant correlation was detected between Mn-SOD or TPI immunoreactivity and other clinicopathological parameters.     

Pilot Study: Evaluation of Dual-Energy Computed Tomography Measurement Strategies for Positron Emission Tomography Correlation in Pancreatic Adenocarcinoma

We sought to determine whether dual-energy computed tomography (DECT) measurements correlate with positron emission tomography (PET) standardized uptake values (SUVs) in pancreatic adenocarcinoma, and to determine the optimal DECT imaging variables and modeling strategy to produce the highest correlation with maximum SUV (SUV_max). We reviewed 25 patients with unresectable pancreatic adenocarcinoma seen at Mayo Clinic, Scottsdale, Arizona, who had PET–computed tomography (PET/CT) and enhanced DECT performed the same week between March 25, 2010 and December 9, 2011. For each examination, DECT measurements were taken using one of three methods: (1) average values of three tumor regions of interest (ROIs) (method 1); (2) one ROI in the area of highest subjective DECT enhancement (method 2); and (3) one ROI in the area corresponding to PET SUV_max (method 3). There were 133 DECT variables using method 1, and 89 using the other methods. Univariate and multivariate analysis regression models were used to identify important correlations between DECT variables and PET SUV_max. Both R² and adjusted R² were calculated for the multivariate model to compensate for the increased number of predictors. The average SUV_max was 5 (range, 1.8–12.0). Multivariate analysis of DECT imaging variables outperformed univariate analysis (r = 0.91; R² = 0.82; adjusted R² = 0.75 vs r < 0.58; adjusted R² < 0.34). Method 3 had the highest correlation with PET SUV_max (R² = 0.82), followed by method 1 (R² = 0.79) and method 2 (R² = 0.57). DECT thus has clinical potential as a surrogate for, or as a complement to, PET in patients with pancreatic adenocarcinoma.     

Cystic breast lesions by conventional ultrasonography: sonographic subtype-pathologic correlation and BI-RADS Assessment

Introduction

Appropriate categorization is very important because the clinical management of each subtype of cystic breast lesions (CBLs) differs. The purpose was to evaluate the sonographic subtype-pathologic correlation, and to identify the effectiveness of the Breast Imaging Reporting and Data System (BI-RADS)-ultrasound (US) for differentiation of benign and malignant CBLs.

Material and methods

A database from December 1, 2007 and November 30, 2009 was identified in the Department of Diagnostic Ultrasound, Rui Jin Hospital, School of Medicine, Shanghai Jiao Tong University, China. Those patients with palpable or clinical symptomatic breast masses were associated with a cystic component in lesions on breast US. All patients underwent a subsequent fine-needle/core-needle biopsy or surgical excision. The sonographic findings were analyzed according to the BI-RADS-US, and were categorized by two different methods of subtype categorization compared with the pathologic results.

Results

Ninety-nine breast cystic lesions in 83 women were included, among whom 16 patients were identified with bilateral cystic lesions. The total malignancy rate of CBLs was 14.1% (95% confidence interval 7.3–21.0%). Among 99 CBLs, 14 malignant lesions were associated with sonographic appearances of complex cystic lesions, while the remaining subtypes were benign. Shape, margin, echo pattern, orientation, calcification, and vascularity were statistically significantly different between the benign and malignant lesions (p = 0.010, p = 0.004, p < 0.001, p < 0.001, p = 0.036, and p < 0.001, respectively) (degrees of freedom = 1).

Conclusions

By comparison of the two different methods of subtype categorization of CBLs, the appropriate 5-variety classification should be suggested. The BI-RADS-US was useful for differentiating benign from malignant cystic lesions.     

Computer-Aided Diagnosis of Breast DCE-MRI Images Using Bilateral Asymmetry of Contrast Enhancement Between Two Breasts

Dynamic contrast material-enhanced magnetic resonance imaging (DCE-MRI) of breasts is an important imaging modality in breast cancer diagnosis with higher sensitivity but relatively lower specificity. The objective of this study is to investigate a new approach to help improve diagnostic performance of DCE-MRI examinations based on the automated detection and analysis of bilateral asymmetry of characteristic kinetic features between the left and right breast. An image dataset involving 130 DCE-MRI examinations was assembled and used in which 80 were biopsy-proved malignant and 50 were benign. A computer-aided diagnosis (CAD) scheme was developed to segment breast areas depicted on each MR image, register images acquired from the sequential MR image scan series, compute average contrast enhancement of all pixels in one breast, and a set of kinetic features related to the difference of contrast enhancement between the left and right breast, and then use a multi-feature based Bayesian belief network to classify between malignant and benign cases. A leave-one-case-out validation method was applied to test CAD performance. The computed area under a receiver operating characteristic (ROC) curve is 0.78 ± 0.04. The positive and negative predictive values are 0.77 and 0.64, respectively. The study indicates that bilateral asymmetry of kinetic features between the left and right breasts is a potentially useful image biomarker to enhance the detection of angiogenesis associated with malignancy. It also demonstrates the feasibility of applying a simple CAD approach to classify between malignant and benign DCE-MRI examinations based on this new image biomarker.     

Observer Performance Using Virtual Pathology Slides: Impact of LCD Color Reproduction Accuracy

The use of color LCDs in medical imaging is growing as more clinical specialties use digital images as a resource in diagnosis and treatment decisions. Telemedicine applications such as telepathology, teledermatology, and teleophthalmology rely heavily on color images. However, standard methods for calibrating, characterizing, and profiling color displays do not exist, resulting in inconsistent presentation. To address this, we developed a calibration, characterization, and profiling protocol for color-critical medical imaging applications. Physical characterization of displays calibrated with and without the protocol revealed high color reproduction accuracy with the protocol. The present study assessed the impact of this protocol on observer performance. A set of 250 breast biopsy virtual slide regions of interest (half malignant, half benign) were shown to six pathologists, once using the calibration protocol and once using the same display in its “native” off-the-shelf uncalibrated state. Diagnostic accuracy and time to render a decision were measured. In terms of ROC performance, Az (area under the curve) calibrated = 0.8570 and Az uncalibrated = 0.8488. No statistically significant difference (p = 0.4112) was observed. In terms of interpretation speed, mean calibrated = 4.895 s; mean uncalibrated = 6.304 s which is statistically significant (p = 0.0460). Early results suggest a slight advantage diagnostically for a properly calibrated and color-managed display and a significant potential advantage in terms of improved workflow. Future work should be conducted using different types of color images that may be more dependent on accurate color rendering and a wider range of LCDs with varying characteristics.     

Mixed echoic thyroid nodules on ultrasound: approach to management

Purpose

To evaluate malignancy risk according to ultrasound (US) features and size change on follow-up US in mixed echoic thyroid nodules and to suggest management guidelines thereof.

Materials and Methods

Among patients who underwent US-guided fine needle aspiration biopsy, 316 mixed echoic nodules in 303 patients were included after excluding the patients with pure solid or cystic nodules or without further cytopathologic evaluation. We evaluated malignancy risk according to US features and changes in size and shape on follow-up US.

Results

The malignancy rate was 31.6% (6 of 19) for nodules with suspicious US features and 2.7% (8 of 297) for nodules without suspicious US features (p<0.001). Among 265 nodules with no suspicious US features and initial benign cytology, 15 nodules with suspicious US change and decreased size, 25 nodules with no suspicious US change and increased size, and 225 nodules with no suspicious US change and no change in size were observed on follow-up USs. The malignancy risk thereof was 0%, 0% and 0.4%, respectively (p=1.000).

Conclusion

Mixed echoic nodules with no suspicious US features and benign cytology can be followed up using US, as they revealed very low malignancy rates, even if they showed growth on follow-up US.     

Shape symmetry analysis of breast tumors on ultrasound images

Shape characteristics of malignant and benign breast tumors are significantly different. In this paper, the reflective symmetry of breast tumor shapes on ultrasound images was investigated. A new reflective symmetry measure (RSML) derived from multiscale local area integral invariant was proposed to quantify the shape symmetry of breast tumor, which could be computed directly from the binary mask image without the shape parameterization in terms of arc length. The performance of several symmetry measures for differentiating malignant and benign breast tumors at varying scales was evaluated and compared by receiver operating characteristic (ROC) analysis. RSML with Gaussian kernel at scale 0.04 (related to the maximal diameter) achieved the highest area under the ROC curve (0.85) on the image data of 168 tumors (104 benign and 64 malignant). The experimental results showed that the reflective symmetry of breast tumor shape was capable of providing potential diagnostic information, which could be characterized quantitatively by RSML with the appropriate scale parameter.     

彩色多普勒超声诊断鉴别甲状腺良恶性肿瘤的效果评价

目的 评价彩色多普勒超声诊断鉴别甲状腺良恶性肿瘤的效果。方法 随机选取2016年5月~2017年5月本院收治的甲状腺肿瘤患者60例,所有患者均经手术病理诊断确诊,在此之前均实施彩色多普勒超声诊断鉴别诊断,并与病理结果对比,分析彩色多普勒超声诊断符合率、甲状腺良恶性肿瘤血流分布情况、彩色多普勒超声诊断敏感性度。结果 彩色多普勒超声诊断发现,良性肿瘤37例（61.67%）、恶性肿瘤17例（28.33%）、结节性甲状腺肿3例（5.00%）,其与病理诊断结果相比,差异不具有统计学意义（P＞0.05）;恶性肿瘤血流分布高于良性肿瘤血流分布,差异具有统计学意义（P＜0.05）;彩色多普勒超声诊断敏感度96.67%。结论 彩色多普勒超声在鉴别诊断甲状腺良恶性肿瘤中,诊断效果显著,可为临床诊治提供有效显著,临床应用价值较高,值得推广应用。     

计算机辅助系统在诊断乳腺良恶性肿瘤中的应用

目的:探讨计算机辅助诊断系统在良恶性肿瘤检测与特征提取基础上的分类对于乳腺肿瘤的诊断价值。方法:回顾性分析乳腺超声检查发现肿瘤且经过病理学证实的617例患者影像资料,采用手工提取的方式得到乳腺超声图像的感兴趣区域及病灶轮廓,再利用方向梯度直方图（HOG）、局部二值模式（LBP）和灰度共生矩阵（GLCM）3个特征进行乳腺肿瘤的良恶性病变真假阳性检测;最后用受试者操作特征曲线（ROC）分别分析每个特征对于两类病变判别的诊断性能和应用所有特征集合的分类诊断性能。结果:多特征融合方法的各项诊断效能及ROC曲线下面积（AUC）值均优于单特征LBP、HOG、GLCM（P值均<0.05）。与人工诊断相比,多特征融合的敏感性无显著差异,但特异度显著升高达98.57%（Z值=2.25, P<0.05）,同时AUC值为0.985,显著优于人工诊断的0.910（Z值=1.99, P<0.05）。结论:计算机辅助系统乳腺超声肿瘤良恶性检测的算法是有效的,能够对乳腺癌鉴别诊断提供有益的参考。     

超声造影在肝实质性肿块诊断及鉴别中的临床价值

目的 探讨超声造影在肝实质性肿块诊断及鉴别中的临床价值。方法 选取2016年7月~2017年8月我院检查的疑似肝实质性肿块患者90例,所有患者均给予超声造影及彩色多普勒超声检查,对比两种方法在肝实质性肿块中的检出率,诊断肝实质性肿块中恶性肿瘤、良性肿瘤及良性病变的灵敏度及特异度。结果 90例患者中,共检出110个肝实质性肿块,恶性肿瘤71个,其中为肝转移癌16个、原发性肝癌55个;良性肿瘤为肝血管瘤25个;良性病变14个,其中为肝孤立性坏死结节4个、肝局灶性结节增生10个。超声造影在恶性肿瘤、良性肿瘤及良性病变检出率高于彩色多普勒超声检查,差异有统计学意义（P＜0.05）。超声造影在诊断肝实质性肿块中灵敏度及特异度均高于彩色多普勒超声检查,但差异无统计学意义（P＞0.05）。结论 超声造影与彩色多普勒超声检查均可诊断及鉴别肝实质性肿块,但超声造影在诊断及鉴别中优势更加明显,肿块检出率及临床应用价值较高,可为临床诊断提供影像学参考。