Whole-Breast Ultrasound for Breast Screening and Archiving

The incidence of breast cancer is increasing worldwide, reinforcing the importance of breast screening. Conventional hand-held ultrasound (HHUS) for breast screening is efficient and relatively easy to perform; however, it lacks systematic recording and localization. This study investigated an electromagnetic tracking-based whole-breast ultrasound (WBUS) system to facilitate the use of HHUS for breast screening. One-hundred nine breast masses were collected, and the detection of suspicious breast lesions was compared between the WBUS system, HHUS and a commercial automated breast ultrasound (ABUS) system. The positioning error between WBUS and ABUS (1.39 ± 0.68 cm) was significantly smaller than that between HHUS and ABUS (1.62 ± 0.91 cm, p = 0.014) and HHUS and WBUS (1.63 ± 0.9 cm, p = 0.024). WBUS is a practical clinical tool for breast screening that can be used instead of the often unavailable and costly ABUS.     

Automatic Breast Volume Scanner versus Handheld Ultrasound in Differentiation of Benign and Malignant Breast Lesions: A Systematic Review and Meta-analysis

The goal of the study described here was to compare the automatic breast volume scanner (ABVS) and handheld ultrasound (HHUS) with respect to diagnostic performance in the differential diagnosis of benign and malignant breast lesions. A literature search of the PubMed, EMBASE and Cochrane Library databases through 30 June 2018 was conducted. Pooled sensitivity, specificity, positive and negative likelihood ratios and diagnostic odds ratios of the ABVS and HHUS were calculated, and summary receiver operating characteristic (SROC) curves were drawn. A total of nine studies, including 1985 lesions (628 malignant and 1357 benign) from 1774 patients, were analyzed. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio for ABVS were 90.8% (95% confidence interval: 88.3%–93.0%), 82.2% (80.0%–84.2%), 5.39 (4.26–6.80), 0.10 (0.06–0.15) and 61.68 (32.31–117.76); those for HHUS were 90.6% (88.1%–92.8%), 81.0% (78.8%–83.0%), 5.22 (3.14–8.67), 0.11 (0.08–0.17) and 52.60 (32.06–86.35), respectively. The areas under the SROC curves in the differentiation of benign and malignant breast lesions were 0.93 and 0.94 for ABVS and HHUS, respectively, which were not significantly different (p = 0.853). In conclusion, based on available evidence in the literature, ABVS the diagnostic performance of the ABVS is similar to that of HHUS in the differentiation of benign and malignant breast lesions.     

Comparative Study of Automated Breast 3-D Ultrasound and Handheld B-Mode Ultrasound for Differentiation of Benign and Malignant Breast Masses

The automated breast volume scanner (ABVS) represents a new technology for diagnosing breast masses. In this study, a total of 219 breast masses in 175 patients underwent both conventional handheld B-mode ultrasound (HHUS) and ABVS examinations, and the differences in the diagnostic values of the two modalities for benign and malignant breast masses were compared with the final pathologic findings. In addition, the diagnostic accuracy for breast masses with features including retraction phenomenon and hyperechoic rim in the coronal plane of the ABVS was evaluated. There were no differences between the ABVS and HHUS in terms of sensitivity (92.5% vs. 88.0%), specificity (86.2% vs. 87.5%), accuracy (88.1% vs. 87.2%), false-positive rate (13.8% vs. 12.5%), false-negative rate (11.8% vs. 7.5%), positive predictive value (74.7% vs. 75.6%) and negative predictive value (96.3% vs. 94.3%) (p > 0.05 for all). However, there were significant differences between the malignant and benign masses with respect to retraction phenomenon and hyperechoic rim in the coronal plane of the ABVS. For retraction phenomenon, both the specificity and positive predictive value of a malignant diagnosis reached 100%, and the accuracy and false-positive rate were 96.8% and 0, respectively; for the hyperechoic rim, the specificity, negative predictive value and accuracy of a benign diagnosis were 92.8%, 95.3% and 95.9%, respectively. Overall, ABVS is a promising modality for the clinical diagnosis of breast masses with retraction phenomenon and hyperechoic rim in the coronal plane, although the ABVS and HHUS do not differ in diagnostic accuracy for the differentiation of malignant or benign breast masses.     

Breast Cancer Classification in Automated Breast Ultrasound Using Multiview Convolutional Neural Network with Transfer Learning

To assist radiologists in breast cancer classification in automated breast ultrasound (ABUS) imaging, we propose a computer-aided diagnosis based on a convolutional neural network (CNN) that classifies breast lesions as benign and malignant. The proposed CNN adopts a modified Inception-v3 architecture to provide efficient feature extraction in ABUS imaging. Because the ABUS images can be visualized in transverse and coronal views, the proposed CNN provides an efficient way to extract multiview features from both views. The proposed CNN was trained and evaluated on 316 breast lesions (135 malignant and 181 benign). An observer performance test was conducted to compare five human reviewers' diagnostic performance before and after referring to the predicting outcomes of the proposed CNN. Our method achieved an area under the curve (AUC) value of 0.9468 with five-folder cross-validation, for which the sensitivity and specificity were 0.886 and 0.876, respectively. Compared with conventional machine learning-based feature extraction schemes, particularly principal component analysis (PCA) and histogram of oriented gradients (HOG), our method achieved a significant improvement in classification performance. The proposed CNN achieved a >10% increased AUC value compared with PCA and HOG. During the observer performance test, the diagnostic results of all human reviewers had increased AUC values and sensitivities after referring to the classification results of the proposed CNN, and four of the five human reviewers’ AUCs were significantly improved. The proposed CNN employing a multiview strategy showed promise for the diagnosis of breast cancer, and could be used as a second reviewer for increasing diagnostic reliability.     

Diagnostic Performance of Automated Breast Ultrasound as a Replacement for a Hand-Held Second-Look Ultrasound for Breast Lesions Detected Initially on Magnetic Resonance Imaging

To evaluate the diagnostic performance of automated breast ultrasound (ABUS) after breast magnetic resonance imaging (MRI) as a replacement for hand-held second-look ultrasound (HH-SLUS), we evaluated 58 consecutive patients with breast cancer who had additional suspicious lesions on breast MRI. All patients underwent HH-SLUS and ABUS. Three breast radiologists evaluated the detectability, location, characteristics and conspicuity of lesions on ABUS. We also evaluated inter-observer variability and compared the results with HH-SLUS results. Eighty additional suspicious lesions were identified on breast MRI. Fifteen of the 80 lesions (19%) were not detected on HH-SLUS. Eight of the 15 lesions (53%) were detected on ABUS, whereas the remaining 7 were not detected on ABUS. Among the 65 lesions detected on HH-SLUS, only 3 lesions were not detected on ABUS. The intra-class correlation coefficients for lesion location and size all exceeded 0.70, indicating high reliability. Moderate to fair agreement was found for mass shape, orientation, margin and Breast Imaging Reporting and Data System (BI-RADS) final assessment. Therefore, ABUS can reliably detect additional suspicious lesions identified on breast MRI and may help in the decision on biopsy guidance method (US vs. MRI) as a replacement tool for HH-SLUS.     

自动乳腺全容积扫查与手持超声诊断乳腺病灶价值的对比研究

目的 探讨自动乳腺全容积扫查系统（automated breast volume scanner,ABVS）与手持超声（handheld ultrasound,HHUS）诊断乳腺病灶的价值.方法 回顾性分析191例接受ABVS及HHUS 2种检查方法患者的临床资料,比较2种方法的病灶检出率.然后筛选出2种检查方法对患者病灶数检查结果一致的83例患者（104个病灶）,以病理诊断为标准,对2种方法检查乳腺病灶的结果进行比较.结果 191例患者中ABVS的乳腺病灶阳性检出率为70.2％（134/191）,HHUS的乳腺病灶阳性检出率为59.2％（113/191）,ABVS的阳性检出率明显高于HHUS的阳性检出率（P＜0.05）.ABVS诊断乳腺恶性病灶的敏感度为82.1％,特异度为80.0％,准确性为80.8％;HHUS诊断乳腺恶性病灶的敏感度为74.4％,特异度为72.3％,准确性为73.1％,ABVS的敏感度、特异度及准确度均高于HHUS（均P＜0.05）.结论 ABVS在乳腺病灶阳性检出率方面及对乳腺恶性病灶诊断的敏感性、特异性以及准确性方面均要高于HHUS,适合在临床上广泛应用.     

Computer-aided diagnosis for the classification of breast masses in automated whole breast ultrasound images

New automated whole breast ultrasound (ABUS) machines have recently been developed and the ultrasound (US) volume dataset of the whole breast can be acquired in a standard manner. The purpose of this study was to develop a novel computer-aided diagnosis system for classification of breast masses in ABUS images. One hundred forty-seven cases (76 benign and 71 malignant breast masses) were obtained by a commercially available ABUS system. Because the distance of neighboring slices in ABUS images is fixed and small, these continuous slices were used for reconstruction as three-dimensional (3-D) US images. The 3-D tumor contour was segmented using the level-set segmentation method. Then, the 3-D features, including the texture, shape and ellipsoid fitting were extracted based on the segmented 3-D tumor contour to classify benign and malignant tumors based on the logistic regression model. The Student’s t test, Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis were used for statistical analysis. From the Az values of ROC curves, the shape features (0.9138) are better than the texture features (0.8603) and the ellipsoid fitting features (0.8496) for classification. The difference was significant between shape and ellipsoid fitting features (p = 0.0382). However, combination of ellipsoid fitting features and shape features can achieve a best performance with accuracy of 85.0% (125/147), sensitivity of 84.5% (60/71), specificity of 85.5% (65/76) and the area under the ROC curve Az of 0.9466. The results showed that ABUS images could be used for computer-aided feature extraction and classification of breast tumors. (E-mail: rfchang@csie.ntu.edu.tw)     

Meta-Analysis: Contrast-Enhanced Ultrasound Versus Conventional Ultrasound for Differentiation of Benign and Malignant Breast Lesions

This meta-analysis aimed to compare the diagnostic performance of contrast-enhanced ultrasound (CEUS), conventional ultrasound (US) combined with CEUS (US?+?CEUS) and US for distinguishing breast lesions. From thorough literature research, studies that compared the diagnostic performance of CEUS versus US or US?+?CEUS versus US, using pathology results as the gold standard, were included. A total of 10 studies were included, of which 9 compared the diagnostic performance of CEUS and US, and 5 studies compared US?+?CEUS and US. In those comparing CEUS versus US, the pooled sensitivity was 0.93 (95% CI: 0.91–0.95) versus 0.87 (95% CI: 0.85–0.90) and pooled specificity was 0.86 (95% CI: 0.84–0.88) versus 0.72 (95% CI: 0.69–0.75). In studies comparing US?+?CEUS versus US, the pooled sensitivity was 0.94 (95% CI: 0.92–0.96) versus 0.87 (95% CI: 0.84–0.90) and pooled specificity was 0.86 (95% CI: 0.82–0.89) versus 0.80 (95% CI: 0.76–0.84). In terms of diagnosing breast malignancy, areas under the curve of the summary receiver operating characteristic (of both CEUS (p?=?0.003) and US?+?CEUS (p?=?0.000) were statistically higher than that of US. Both CEUS alone and US?+?CEUS had better diagnostic performance than US in differentiation of breast lesions, and US?+?CEUS also had low negative likelihood ratio.     

Accuracy of an Automated Breast Volume Ultrasound System for Assessment of the Pre-operative Extent of Pure Ductal Carcinoma In Situ: Comparison with a Conventional Handheld Ultrasound Examination

The goal of the study described here was to compare the accuracy of an automated breast volume scanner (ABVS) with that of hand-held ultrasound (HHUS) in assessing the pre-operative extent of pure ductal carcinoma in situ (DCIS). This prospective study consisted of 33 patients with histopathologically proven pure DCIS who received conventional HHUS and ABVS examinations. The discrepancy and correlation coefficients were calculated to assess differences in sizes determined by imaging and histopathologic examination. Mean age was 51.8 y. Mean lesion size as assessed with the ABVS did not differ significantly from that determined by histopathology. Lesion size was adequately estimated, under-estimated or over-estimated with the ABVS in 64%, 15% and 21% of patients, and with HHUS in 42%, 15% and 42%, respectively (p < 0.05). The coefficient of correlation between histopathologic and ABVS measurements was higher than that between histopathologic and HHUS measurements. The ABVS appears to assess the extent of the lesion better than HHUS and can provide more accurate information pre-operatively.     

Diagnostic Value of Automated 3D Ultrasound for Incisional Hernia

The automated volume scanning system (AVSS) has been applied in breast diseases, but its use in incisional hernias has not been reported. In this study, conventional handheld B-mode ultrasound (HHUS) and AVSS examined a total of 122 hernia defects in 78 patients. The results from two modalities were then compared with surgical findings for the purpose of assessing the diagnostic value of AVSS. Statistics showed that surgeries identified 38 small, 23 medium and 17 large incisional hernias. The results of AVSS completely agreed with surgical findings; however, HHUS misidentified nine large hernias as medium and seven medium hernias as large. AVSS proved to be more accurate than HHUS in measuring the length and width of the hernia. It also outperformed HHUS in both detecting the incisional hernias (91.8% vs. 78.7%, p = 0.00) and determining hernia contents (89.3% vs. 68.0%, p = 0.00). Moreover, the coronal images AVSS obtained clearly displayed the shapes of the hernias, with 46 being regular and 32 irregular. Overall, AVSS can be used as a promising diagnostic modality for incisional hernias.     

Implementation of Elastography Score and Strain Ratio in Combination with B-Mode Ultrasound Avoids Unnecessary Biopsies of Breast Lesions

The aim of this study was to evaluate whether the combination of B-mode ultrasound, elastography score (ES) and strain ratio (SR) improves diagnostic performance with respect to breast lesions. One hundred thirty lesions were prospectively evaluated by B-mode ultrasound and strain elastography, followed by fine-needle aspiration cytology/biopsy in 117 woman who were scheduled for regular breast BUS. The median ES (4.5 vs. 2.9, p < 0.001) and SR (4.9 vs. 2.3, p < 0.001) were significantly higher for malignant than for benign lesions. A sensitivity of 90.5% and specificity of 93.2% for the ES (cutoff point = 3.8) and a sensitivity of 87.5% and specificity of 87.6% for the SR (cutoff point = 3.5) were obtained. Elastography combined with B-mode ultrasound improved the specificity, accuracy and positive predictive value. Receiver operating characteristic curves yielded a higher value for the combined technique for diagnosis of breast lesions. Routine use of such a diagnostic algorithm could reduce the number of unnecessary biopsies.     

Multimodal Ultrasound Imaging in Breast Imaging-Reporting and Data System 4 Breast Lesions: A Prediction Model for Malignancy

The purpose of this study was to develop, validate and test a prediction model for discriminating malignant from benign breast lesions using conventional ultrasound (US), US elastography of strain elastography and contrast-enhanced ultrasound (CEUS). The study included 454 patients with breast imaging-reporting and data system (BI-RADS) category 4 breast lesions identified on histologic examinations. Firstly, 228 breast lesions (cohort 1) were analyzed by logistic regression analysis to identify the risk factors, and a breast malignancy prediction model was created. Secondly, the prediction model was validated in cohort 2 (84 patients) and tested in cohort 3 (142 patients) by using analysis of the area under the receiver operating characteristic curve (AUC). Univariate regression indicated that age ≥40 y, taller than wide shape on US, early hyperenhancement on CEUS and enlargement of enhancement area on CEUS were independent risk factors for breast malignancy (all p < 0.05). The logistic regression equation was established as follows: p = 1/1+Exp∑[–5.066 + 3.125 x (if age ≥40 y) + 1.943 x (if taller than wide shape) + 1.479 x (if early hyperenhancement) + 4.167 x (if enlargement of enhancement area). The prediction model showed good discrimination performance with an AUC of 0.967 in cohort 1, 0.948 in cohort 2 and 0.920 in cohort 3. By using the prediction model to selectively downgrade category 4a lesions, the re-rated BI-RADS yield an AUC of 0.880 (95% confidence interval [CI], 0.794–0.965) in cohort 2 and 0.870 (95% CI, 0.801–0.939) in cohort 3. The specificity increased from 0.0% (0/35) to 80.0% (28/35) without loss of sensitivity (from 100.0% to 95.9%, p = 0.153) in cohort 2. Similarly, the specificity increased from 0.0% (0/58) to 77.6% (45/58) without loss of sensitivity (from 100.0% to 96.4%, p = 0.081) in cohort 3. Multimodal US showed good diagnostic performance in predicting breast malignancy of BI-RADS category 4 lesions. Although the loss of sensitivity was existing, the addition of multimodal US to US BI-RADS could improve the specificity in BI-RADS category 4 lesions, which reduced unnecessary biopsies.     

Utility of B-Mode,Color Doppler and Elastography in the Diagnosis of Breast Cancer: Results of the CD-CONFIRM Multicenter Study of 1351 Breast Solid Masses

The usefulness of color Doppler ultrasound (CD) in distinguishing between benign and malignant breast lesions remains controversial. Our prior study, the Japan Association of Breast and Thyroid Sonology (JABTS) BC-04 study (malignant: 839, benign: 569), found CD was useful in breast cancer diagnosis, and we developed CD diagnostic criteria. The first aim of the current study (the CD-CONFIRM study) was to evaluate the usefulness of the CD diagnostic criteria. The second aim was to evaluate the relationship between CD and elastography. We evaluated ultrasound images of breast masses from 13 institutions (malignant: 639, benign: 712). While the sensitivity of B-mode alone was very high and was not significantly improved with CD, the specificity was significantly improved with CD (61.2%–69.2%, p < 0.0001). Furthermore, the specificity of the combination of B-mode and CD improved significantly with the addition of elastography (72.8%–79.0%, p < 0.0001). This study found that the CD criteria are useful, and CD and elastography are independent.     

Deformable Mapping Method to Relate Lesions in Dedicated Breast CT Images to Those in Automated Breast Ultrasound and Digital Breast Tomosynthesis Images

This work demonstrates the potential for using a deformable mapping method to register lesions between dedicated breast computed tomography (bCT) and both automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT) images (craniocaudal [CC] and mediolateral oblique [MLO] views). Two multi-modality breast phantoms with external fiducial markers attached were imaged by the three modalities. The DBT MLO view was excluded for the second phantom. The automated deformable mapping algorithm uses biomechanical modeling to determine corresponding lesions based on distances between their centers of mass (d_COM) in the deformed bCT model and the reference model (DBT or ABUS). For bCT to ABUS, the mean d_COM was 5.2 ± 2.6 mm. For bCT to DBT (CC), the mean d_COM was 5.1 ± 2.4 mm. For bCT to DBT (MLO), the mean d_COM was 4.7 ± 2.5 mm. This application could help improve a radiologist's efficiency and accuracy in breast lesion characterization, using multiple imaging modalities.     

Shear-Wave Elastography: Could it be Helpful for the Diagnosis of Non-Mass-Like Breast Lesions?

The goal of this study was to analyze the diagnostic performance of shear wave elastography (SWE) in differentiation of benign and malignant non-mass-like (NML) breast lesions. Three hundred sixteen consecutive breast lesions in 305 patients who have been scheduled for ultrasound (US)-guided core needle biopsy or vacuum-assisted biopsy or surgical excision between January 2013 and August 2013 were initially included in this study. Finally, 63 patients with 67 lesions classified as NML lesions comprised our study population. The features of SWE and its diagnostic performance in NML lesions were analyzed. Among the 67 NML lesions, 33 were malignant and 34 were benign. The maximum elastic modulus, mean elastic modulus, minimum elastic modulus, elastic modulus ratio and stiff rim sign of the malignant lesions were all significantly higher than those of benign lesions (p < 0.05). The combination of conventional US with maximum elastic modulus and stiff rim sign got significantly higher diagnostic specificity and positive predictive value (PPV) than conventional US (p < 0.05 for both). In the benign lesions, 23 (67.6%) unnecessary biopsies could have been eliminated after the combination of conventional US and SWE. SWE could increase diagnostic specificity and positive predictive values of NML breast lesions. The combination of conventional US and SWE could reduce unnecessary benign biopsies of NML lesions.     

常规超声阴性乳腺癌的腋窝淋巴结超声影像分析

目的总结并分析常规超声在阴性乳腺癌腋窝淋巴结评估中的作用。方法对在我院常规超声阴性的73例乳腺癌患者的术前腋窝磁共振、钼靶、超声检查结果进行分析,并与病理结果进行对照。结果73例病例中,导管原位癌20例,浸润性导管癌43例,浸润性小叶癌2例,其他8例。腋窝淋巴结有转移病例15例,无转移58例。磁共振诊断腋窝转移性淋巴结灵敏度60.0%、特异度63.8%、准确率63.0%。钼靶分别为46.7%、94.8%、84.9%。常规超声分别为60.0%、98.3%、90.4%。结论常规超声阴性乳腺癌中,腋窝淋巴结具有一定的转移比例,在灵敏度上常规超声与磁共振相当,优于钼靶;在特异度和准确率上常规超声均优于磁共振和钼靶。     

Clinical Application Value of Automated Breast Volume Scanner in the Diagnosis of Abdominal External Hernia

This study investigated the clinical application value of the automated breast volume scanner (ABVS) in patients with abdominal external hernias. A total of 121 abdominal external hernias from 103 inpatients were examined with both conventional handheld ultrasound (HHUS) and the ABVS before surgery. The rate of detection of abdominal external hernias and the diagnostic accuracy of classifying inguinal hernias using the two modalities were compared between junior and senior sonographers. Additionally, the sonographic appearance of abdominal external hernias with the ABVS system was evaluated. The results revealed that junior sonographers had a higher detection rate with the ABVS (92.6%) than with HHUS (83.5%). For the classification of inguinal hernias, the accuracy of junior sonographers using the ABVS was 89.2%, which was higher than that for the HHUS system (77.6%), but there was no significant difference between HHUS (92.7%) and the ABVS (93.1%) for senior sonographers. Measurement of the hernia orifice size with the ABVS was accurate. In addition, the ABVS could provide coronal images and visually revealed the contents of the hernia, the shape of the hernia orifice and the pathway of herniation, as well as the relationship with adjacent tissues. Therefore, the clinical application value of the ABVS for abdominal external hernias is excellent.     

Characterization of Benign and Malignant Solid Breast Masses: Harmonic Versus Nonharmonic 3D Power Doppler Imaging

The aim of this study was to compare the diagnostic performance of nonharmonic ultrasound (US) and tissue harmonic imaging (THI) using three-dimensional (3D) power Doppler sonographic technique to classify benign and malignant breast tumors by vascularization. From January 2003 to February 2004, we evaluated 200 patients and one of lobular carcinoma in situ was excluded from the malignant category. One hundred and ninety-nine subjects were enrolled. All subjects with one or more breast masses were studied with 3D power Doppler US nonharmonic and harmonic technologies. Sixteen of 199 subjects were excluded because masses exceeded 3 cm limit of our US probe's footprint (n = 5) or no harmonic Doppler information (n = 11). A total of 97 benign and 86 pathologically proven malignant breast tumor images were analyzed. 3D power Doppler US imaging was performed using a Voluson730 US system. Three histogram indices, the vascularization index (VI), flow index (FI) and vascularization-flow index (VFI), on both nonharmonic and harmonic images were calculated for the intratumor and for shells with an outside thickness of 3 mm surrounding the breast lesion. A multilayer perception (MLP) neural network classifier used the vascularity indices to determine whether the breast tumors are benign or malignant. The receiver operating characteristic (ROC) curves are performed to estimate the diagnostic performances for nonharmonic and harmonic methods. ROC curve analysis used overall age, volume, VI, FI and VFI for both intratumor and shells with an outside thickness of 3 mm surrounding the breast lesions in nonharmonic US and THI. The area under the ROC curve (A_Z) was 0.9086 and 0.9009 (p = 0.3770). The sensitivity was 90.7% and 83.7% (p = 0.72), respectively, and the specificity was 92.8% and 92.8% (p = 1.00), respectively. In conclusion, the performance of 3D power Doppler US with respect to the characterization of solid breast masses as benign or malignant was not significantly improved with tissue harmonic imaging. (E-mail: darren_chen@cch.org.tw)     

对比观察超声自动乳腺全容积扫描与乳腺X线摄影对乳腺癌的诊断价值

目的 对比分析超声自动乳腺全容积(ABVS)与乳腺X线摄片(MG)对乳腺癌的诊断价值.方法 回顾性分析经病理证实的65例乳腺癌的术前影像学资料,比较ABVS与MG对乳腺癌的诊断效果.结果 对65例均进行ABVS检查,冠状面上乳腺癌病灶呈不同程度的强回声“汇聚”征,术前ABVS初步诊断55例(55/65,84.62％)为乳腺癌;对42例同期进行MG检查,术前MG初步诊断27例(27/42,64.29％)为乳腺癌.术前ABVS与MG对乳腺癌的总体检出率差异有统计学意义(P＜0.05),且ABVS(26/65,40.00％)对小病灶的检出率高于MG(9/42,21.43％,P＜0.05).结论 ABVS冠状切面显示“汇聚”征对诊断乳腺癌具有高度价值.ABVS对乳腺癌的检出率高于MG,且对小病灶的检出率亦高于MG.