Accuracy of CESM versus conventional mammography and ultrasound in evaluation of BI-RADS 3 and 4 breast lesions with pathological correlation

Aim

Assess accuracy of contrast enhanced spectral mammography (CESM) versus conventional mammography and ultrasound in evaluation of BI-RADS 3 and 4 breast lesions with pathological correlation.

Breast ultrasound computer-aided diagnosis using BI-RADS features

RATIONALE AND OBJECTIVES: Based on the definitions in mass category of Breast Imaging Reporting and Data System developed by American College of Radiology, eight computerized features including shape, orientation, margin, lesion boundary, echo pattern, and posterior acoustic feature classes are proposed. MATERIALS AND METHODS: Our experimental database consists of 265 pathology-proven cases including 180 benign and 85 malignant masses. The capacity of each proposed feature in differentiating malignant from benign masses was validated by Student's t test and the correlation between each proposed feature and the pathological result was evaluated by point biserial coefficient. Binary logistic regression model was used to relate all proposed features and pathological result as a computer-aided diagnosis (CAD) system. The diagnostic value of each proposed feature in the CAD system was further evaluated by the feature selection methods. Additionally, the likelihood of malignancy for each individual feature was also estimated by binary logistic regression. RESULTS: On each proposed feature, the malignant cases were significantly different from the benign ones. The correlation between the angular characteristic and pathological result was indicated as very high. Three substantial correlations appear in features irregular shape, undulation characteristic, and degree of abrupt interface, but the relationship for orientation feature is low. For the constructed CAD system, the performance indices accuracy, sensitivity, specificity, PPV, and NPV were 91.70% (243 of 265), 90.59% (77 of 85), 92.22% (166 of 180), 84.62% (77 of 91), and 95.40% (166 of 174), respectively, and the area index in the ROC analysis was 0.97. Compared with the significant contribution of angular characteristic, the diagnostic values of posterior acoustic feature and orientation feature were relatively low for the CAD system. When three or more angular characteristics are discovered or the degree of abrupt interface is lower than 18, the likelihood of malignancy could be predicted as greater than 40%. CONCLUSION: The computerized BI-RADS sonographic features conform to the sign of malignancy in the clinical experience and efficiently help the CAD system to diagnose the mass.     

Assessment of breast lesions using BI-RADS US lexicon in mammographically dense breasts (ACR categories 3 and 4) with histopathological correlation

Purpose

To assess the role of ultrasonography in detection, and categorization of breast lesions in patients with mammographically dense breasts with the use of the BI-RADS US lexicon.

Patients and methods

This study included 60 female patients (age range from 20 to 80 years, mean 38.3 ± 11.9) complaining of mastalgia, breast lump or nipple discharge with mammographically dense breast tissue. Breast ultrasound was performed to all patients with a 12-MHz linear-array transducer. Sonographic findings of the breast lesions were described and categorized according to the BI-RADS US assessment categories. Biopsy procedures were performed for the sonographically detected breast lesions with histopathological examination of the biopsied tissue.

Results

The main complaint was palpable breast mass encountered in 25 patients, 12 of mastalgia, 4 of nipple discharge, 12 patients were on screening and 7 on follow up. 36 patients were categorized as ACR 3 and 24 ACR 4 regarding the density of their breasts in mammography. Mammography revealed no abnormalities in 31 patients and abnormal in 29 patients, the commonest mammographic finding was breast mass, detected in 19 patients. Ultrasound detected breast lesions in 56 (93.3%) out of 60 patients. BI-RADS US category 2 was the most common category representing 36.7%. Ultrasonography had a diagnostic reliability for differentiating between benign and malignant breast lesions (p = 0.869) in mammographically dense breasts while mammography was diagnostically unreliable (p = 0.045).

Conclusion

Ultrasound is a mandatory adjunct to mammography in detection and characterization of breast lesions in mammographically dense breasts.     

Accuracy of assigned BI-RADS breast density category definitions

RATIONALE AND OBJECTIVES: Quantitative criteria for the Breast Imaging Reporting and Data System (BI-RADS) mammographic density categories have recently been defined as <25% dense for almost entirely fatty, 25%-50% dense for scattered fibroglandular densities, 51%-75% for heterogeneously dense, and >75% dense for the extremely dense category. The purpose of this study is to compare the range of percent mammographic densities with radiologist-assigned BI-RADS mammographic density categories and compare with the recently issued definitions. MATERIALS AND METHODS: In this study, 200 consecutive negative analog screening mammograms were assigned BI-RADS mammographic density categories independently by three radiologists blinded to the other readers' density assignment. Quantitative assessment of percent mammographic density was performed using previously validated software. RESULTS: All three readers agreed on BI-RADS mammographic density categories in 98 cases (49%), and two of three readers agreed in all 200 cases. Using two reader's consensus, median mammographic density (range) was 6.0% (0.5%-19.2%) for fatty, 14.8% (1.2%-52.7%) for scattered densities, 51.2% (15.9%-82.2%) for heterogeneously dense, and 78.4% (60.1%-87.9%) for extremely dense breasts. The percent mammographic density ranges for fatty and extremely dense breasts correlated well with BI-RADS definitions, whereas the ranges of densities in the scattered and heterogeneously dense categories were considerably broader. CONCLUSION: Fatty and extremely dense BI-RADS categories compare relatively well to defined criteria, and therefore may be helpful in breast cancer risk models. Scattered fibroglandular densities and heterogeneously dense categories have broad percent mammographic density ranges and may not function well in breast cancer risk models.     

乳腺影像报告与数据系统在鉴别诊断乳腺良恶性肿瘤中的应用价值

目的评价乳腺影像报告与数据系统(BI-RADS)在乳腺良恶性肿瘤鉴别诊断中的应用价值.资料与方法根据 BI-RADS 规范,分析202例患者共234个肿瘤的形态、方向、边缘、边界、内部回声、后方回声及钙化情况,并将病灶定义为3级(可能良性)、4级(可能恶性)和5级(高度可疑恶性).计算每个病灶特征的阳性预测值与阴性预测值,分析影响诊断的因素.结果?49个(20.9%)为 BI-RADS 3级,47个(20.1%)为 BI-RADS 4级,138个(59.0%)为 BI-RADS 5级,BI-RADS 3级对乳腺肿瘤的阴性预测值为98.0%(48/49),BI-RADS 4级与5级对乳腺肿瘤的阳性预测值分别为34.0%(16/47)和92.8%(128/138).BI-RADS 对乳腺恶性肿瘤的诊断敏感性为99.3%,特异性为53.9%,阳性预测值为77.8%,阴性预测值为98.0%.对恶性肿瘤的诊断有较高阳性预测值的超声特征包括不完整的边缘(100.0%)、微钙化(100.0%)、不清晰的边界(97.3%)、后方回声衰减(97.0%);对良性肿瘤的诊断有较高阳性预测值的超声特征包括后方回声增强(100.0%)、形态规则(98.0%)、病灶方向平行于皮肤长轴(98.0%)、边缘完整(98.0%)、边界清晰(98.0%)与无钙化(98.0%).结论 BI-RADS 可帮助分析影响诊断的因素,有助于乳腺良恶性肿瘤的鉴别诊断.     

Applications and literature review of the BI-RADS classification

The Breast Imaging Reporting and Data System (BI-RADS) of the American College of Radiology (ACR) is a tool created to reduce variability in the terminology used in mammographic reports. An illustration of mammographic examples from our institution interpreted according to the BI-RADS lexicon of the American College of Radiology (ACR) is presented. A literature review concerning the usefulness and limitations of the BI-RADS lexicon is given.     

Interobserver reliability of automated breast volume scanner (ABVS) interpretation and agreement of ABVS findings with hand held breast ultrasound (HHUS), mammography and pathology results

Objectives

Handheld breast ultrasound (HHUS) lacks standardization and reproducibility. The automated breast volume scanner (ABVS) could overcome this limitation. To analyze the interobserver reliability of ABVS and the agreement with HHUS, mammography and pathology is the aim of this study.

Methods

All 42 study participants (=84 breasts) received an ABVS examination in addition to the conventional breast diagnostic work-up. 25 breasts (30%) showed at least one lesion. The scans were interpreted by six breast diagnostic specialists blinded to results of breast imaging and medical history. 32 lesions received histological work-up: 20 cancers were detected. We used kappa statistics to interpret agreement between examiners and diagnostic instruments.

Results

On the basis of the Breast Imaging Reporting and Data System (BI-RADS) classification of the 84 breasts an agreement (defined as ≥4 of 6 examiners) was achieved in 63 cases (75%) (mk = 0.35) and even improved when dichotomizing the interpretation in benign (BI-RADS 1, 2) and suspicious (BI-RADS 4, 5) to 98% (mk = 0.52). Agreement of ABVS examination to HHUS, mammography and pathology was fair to substantial depending on the specific analysis.

Conclusions

The development of an ABVS seems to be a promising diagnostic method with a good interobserver reliability, as well as a comparable good test criteria as HHUS.     

The Breast Imaging Reporting and Data System (BI-RADS) in the Dutch breast cancer screening programme: its role as an assessment and stratification tool

Objectives

To assess the suitability of the Breast Imaging Reporting and Data System (BI-RADS) as a quality assessment tool in the Dutch breast cancer screening programme.

Methods

The data of 93,793 screened women in the Amsterdam screening region (November 2005–July 2006) were reviewed. BI-RADS categories, work-up, age, final diagnosis and final TNM classification were available from the screening registry. Interval cancers were obtained through linkage with the cancer registry. BI-RADS was introduced as a pilot in the Amsterdam region before the nationwide introduction of digital mammography (2009–2010).

Results

A total of 1,559 women were referred to hospital (referral rate 1.7?%). Breast cancer was diagnosed in 485 women (detection rate 0.52?%); 253 interval cancers were reported, yielding a programme sensitivity of 66?% and specificity of 99?%. BI-RADS 0 had a lower positive predictive value (PPV, 14.1?%) than BI-RADS 4 (39.1?%) and BI-RADS 5 (92.9?%; P?P?Conclusion The significant differences in PPV, invasive procedures and tumour size match with stratification into BI-RADS categories. It revealed inter-observer variability between screening radiologists and can thus be used as a quality assessment tool in screening and as a stratification tool in diagnostic work-up.

Key Points

? The BI-RADS atlas is widely used in breast cancer screening programmes. ? There were significant differences in results amongst different BI-RADS categories. ? Those differences represented the radiologists’ degree of suspicion for malignancy, thus enabling stratification of referrals. ? BI-RADS can be used as a quality assessment tool in screening. ? Training should create more uniformity in applying the BI-RADS lexicon.     

Breast ultrasound elastography—Results of 193 breast lesions in a prospective study with histopathologic correlation

Purpose

To evaluate the diagnostic performance of ultrasound elastography in breast masses.

Material and methods

193 lesions (129 benign, 64 malignant) were analyzed with the EUB 8500 Logos-ultrasonic-unit (Hitachi Medical, Japan) and a linear-array-transducer of 7.5-13-MHz. Standard of reference was cytology (FNAfine needle aspiration) or histology (core biopsy). The elastic-score was classified according to a 6-point colour-scale (Ueno classification; 1-3 = benign, 4-5 = malignant). Conventional B-mode ultrasound (US) findings were classified according to the BI-RADS classification. Statistical analysis included sensitivity, specificity, ROC-analysis and kappa-values for intra-/interobserver reliability.

Results

The mean score for elasticity was 4.1 ± 0.9 for malignant lesions, and 2.1 ± 1.0 for benign lesions (p < 0.001). With a best cut-off point between elasticity scores 3 and 4, sensitivity was 96.9%, and specificity 76%. Setting a best cut-off point for conventional US between BI-RADS 4 and 5, sensitivity was 57.8%, and specificity 96.1%. Elastography provided higher sensitivity and lower specificity than conventional US, but two lesions with elasticity score 1 were false negative, whereas no lesion scored BI-RADS 1-3 were false negative. ROC-curve was 0.884 for elastography, and 0.820 for conventional US (p < 0.001). Weighted kappa-values for intra-/interobserver reliability were 0.784/0.634 for BI-RADS classification, and 0.720/0.561 for elasticity scores.

Conclusion

In our study setting, elastography does not have the potential to replace conventional B-mode US for the detection of breast cancer, but may complement conventional US to improve the diagnostic performance.     

The Thyroid Imaging Reporting and Data System (TIRADS) for ultrasound of the thyroid

PurposeTo develop a standardized system for analyzing and reporting thyroid ultrasound, or Thyroid Imaging Reporting and Data System (TIRADS), in order to improve the management of patients with thyroid nodules.Materials and methodsAn atlas of imaging features, a standardized vocabulary, a report template and TIRADS categories 0 to 6 were defined, based on the BI-RADS^® system used for mammography. The diagnostic efficacy of the system was tested by a retrospective review of 500 nodules (159 cancers and 341 benign nodules) and comparing US imaging features to histological findings.ResultsFive signs allow accurate detection of 90% of thyroid cancers. The score of a nodule can be easily defined by using an organigram. Sensitivity, specificity and odds-ratio of the score were respectively 95%, 68% and 40.ConclusionTIRADS is a quality assurance tool for thyroid ultrasound. It contains an image atlas, a standardized report and categories to evaluate thyroid nodules to easily assess the risk of individual nodules being cancers and facilitate patient management.     

多模态X线影像组学模型对乳腺BI-RADS4类肿块良恶性的辅助诊断价值

目的 探讨多模态X线影像组学模型在鉴别乳腺BI-RADS 4类肿块型病变良恶性方面的价值.方法 回顾性分析山东省千佛山医院2017年8月至2020年4月,经全屏数字化乳腺X线摄影(FFDM)和数字乳腺断层合成摄影(DBT)检查诊断为BI-RADS 4类乳腺病变并经病理证实的120例女性患者(4A 41例,良性34例、恶...     

Clinical application of qualitative assessment for breast masses in shear-wave elastography

Purpose

To evaluate the interobserver agreement and the diagnostic performance of various qualitative features in shear-wave elastography (SWE) for breast masses.

Materials and methods

A total of 153 breast lesions in 152 women who underwent B-mode ultrasound and SWE before biopsy were included. Qualitative analysis in SWE was performed using two different classifications: E values (Ecol; 6-point color score, Ehomo; homogeneity score and Esha; shape score) and a four-color pattern classification. Two radiologists reviewed five data sets: B-mode ultrasound, SWE, and combination of both for E values and four-color pattern. The BI-RADS categories were assessed B-mode and combined sets. Interobserver agreement was assessed using weighted κ statistics. Areas under the receiver operating characteristic curve (AUC), sensitivity, and specificity were analyzed.

Results

Interobserver agreement was substantial for Ecol (κ = 0.79), Ehomo (κ = 0.77) and four-color pattern (κ = 0.64), and moderate for Esha (κ = 0.56). Better-performing qualitative features were Ecol and four-color pattern (AUCs, 0.932 and 0.925) compared with Ehomo and Esha (AUCs, 0.857 and 0.864; P < 0.05). The diagnostic performance of B-mode ultrasound (AUC, 0.950) was not significantly different from combined sets with E value and with four color pattern (AUCs, 0.962 and 0.954). When all qualitative values were negative, leading to downgrade the BI-RADS category, the specificity increased significantly from 16.5% to 56.1% (E value) and 57.0% (four-color pattern) (P < 0.001) without improvement in sensitivity.

Conclusion

The qualitative SWE features were highly reproducible and showed good diagnostic performance in suspicious breast masses. Adding qualitative SWE to B-mode ultrasound increased specificity in decision making for biopsy recommendation.     

超声乳腺影像报告和数据系统与18F-FDG PET/CT在乳腺疾病诊断中的相关性及联合应用价值

目的：分析超声乳腺影像报告和数据系统（BI-RADS）分级与18F-脱氧葡萄糖（18F-FDG）PET/CT之间的相关性,并评价其在乳腺疾病诊断中的联合应用价值。资料与方法对103例疑似乳腺癌患者的18F-FDG PET/CT图像及超声BI-RADS分级进行回顾性研究,分析最大SUV（SUVmax）与超声BI-RADS分级的相关性,并以病理或长期随访结果为“金标准”,分别分析其灵敏度、特异度、阳性及阴性预测值。结果在103例疑似乳腺癌患者中,良性46例,恶性57例;SUVmax与超声BI-RADS分级的Pearson相关系数r=0.464（P<0.01）;所有患者中PET/CT诊断的灵敏度、特异度、阳性及阴性预测值分别为89.47%、73.91%、80.95%、84.99%;BI-RADS分级诊断的灵敏度、特异度、阳性及阴性预测值分别为94.70%、69.60%、79.42%、91.38%;在BI-RADS 3~4级的患者中PET/CT诊断的灵敏度、特异度、阳性及阴性预测值分别为88.90%、71.40%、66.65%、90.91%;BI-RADS分级诊断的灵敏度、特异度、阳性及阴性预测值分别为88.90%、46.40%、51.60%、86.67%。结论 SUVmax与超声BI-RADS分级不具有明显相关性,对于BI-RADS 3~4级病例, BI-RADS分级诊断的特异度明显降低,PET/CT可以很好地弥补这一缺点,两者联合诊断乳腺疾病具有一定的临床推广潜力。     

Breast Imaging Reporting and Data System: inter- and intraobserver variability in feature analysis and final assessment

OBJECTIVE: We sought to evaluate the use of the Breast Imaging Reporting and Data System (BI-RADS) standardized mammography lexicon among and within observers and to distinguish variability in feature analysis from variability in lesion management. MATERIALS AND METHODS: Five experienced mammographers, not specifically trained in BI-RADS, used the lexicon to describe and assess 103 screening mammograms, including 30 (29%) showing cancer, and a subset of 86 mammograms with diagnostic evaluation, including 23 (27%) showing cancer. A subset of 13 screening mammograms (two with malignant findings, 11 with diagnostic evaluation) were rereviewed by each observer 2 months later. Kappa statistics were calculated as measures of agreement beyond chance. RESULTS: After diagnostic evaluation, the interobserver kappa values for describing features were as follows: breast density, 0.43; lesion type, 0.75; mass borders, 0.40; special cases, 0.56; mass density, 0.40; mass shape, 0.28; microcalcification morphology, 0.36; and microcalcification distribution, 0.47. Lesion management was highly variable, with a kappa value for final assessment of 0.37. When we grouped assessments recommending immediate additional evaluation and biopsy (BI-RADS categories 0, 4, and 5 combined) versus follow-up (categories 1, 2, and 3 combined), five observers agreed on management for only 47 (55%) of 86 lesions. Intraobserver agreement on management (additional evaluation or biopsy versus follow-up) was seen in 47 (85%) of 55 interpretations, with a kappa value of 0.35-1.0 (mean, 0.60) for final assessment. CONCLUSION: Inter- and intraobserver variability in mammographic interpretation is substantial for both feature analysis and management. Continued development of methods to improve standardization in mammographic interpretation is needed.     

The positive predictive value of the breast imaging reporting and data system (BI-RADS) as a method of quality assessment in breast imaging in a hospital population

Evaluation of the diagnostic performance of mammography and US in our hospital, based upon the positive predictive value (PPV) for breast cancer of the breast imaging reporting and data system (BI-RADS) final assessment categories, has been performed. A follow-up study of 2,762 mammograms was performed, along with 955 diagnostic exams and 1,807 screening exams. Additional US was performed in 655 patients (23.7%). The combined reports were assigned a BI-RADS category. Follow-up was obtained by pathologic examination, mammography at 12 months or from PALGA, a nationwide network and registry of histo- and cytopathology. Overall sensitivity was 85% (specificity 98.7%); sensitivity of the diagnostic examinations was 92.9% (specificity 97.7%) and of the screening examinations 69.2% (specificity 99.2%). The PPV of BI-RADS 1 was 5 of 1,542 (0.3%), and of BI-RADS 2, it was 6 of 935 (0.6%). BI-RADS 3 was 6 of 154 (3.9%), BI-RADS 4 was 39 of 74 (52.7%) and BI-RADS 5 was 57 of 57 (100%). The difference between BI-RADS 1 and 2 vs. BI-RADS 3 was statistically significant (P<0.01). Analysis of BI-RADS 3 cases revealed inconsistencies in its assignment. Evaluation of the BI-RADS final assessment categories enables a valid analysis of the diagnostic performance of mammography and US and reveals tools to improve future outcomes.