The biology of malignant breast tumors has an impact on the presentation in ultrasound: an analysis of 315 cases

An Effective Ultrasound Features-Based Diagnostic Model via Principal Component Analysis Facilitated Differentiating Subtypes of Mucinous Breast Cancer From Fibroadenomas

BACKGROUND

Mucinous breast carcinoma (MBC) is often misdiagnosed as fibroadenoma (FA),which can lead to inappropriate or delayed treatments. This study aimed to establish an efficient ultrasound (US)-based diagnostic model to distinguish MBC subtypes from FAs.

METHODS

Between January 2017 and February 2024, 240 lesions were enrolled, comprising 65 cases of pure mucinous breast carcinoma (PMBC), 47 cases of mixed mucinous breast carcinoma (MMBC), and 128 cases of FAs. Ten US feature variables underwent principal component analysis (PCA). Models were constructed based on components explaining over 75% of the total variation, with varimax rotation applied for interpretability. Comprehensive models were developed to distinguish PMBCs and MMBCs from FAs.

RESULTS

Six principal components were selected, achieving a cumulative contribution rate of 77.46% for PMBCs vs. FAs and 78.62% for MMBCs vs. FAs. The principal component of cystic-solid composition and posterior acoustic enhancement demonstrated the highest diagnostic value for distinguishing PMBCs from FAs (AUC: 0.86, ACC: 80.31%). Features including vascularization, irregular shape, ill-defined border, and larger size exhibited the highest diagnostic value for distinguishing MMBCs from FAs (AUC: 0.90, ACC: 87.43%). The comprehensive models showed excellent clinical value in distinguishing PMBCs (AUC = 0.86, SEN = 86.15%, SPE = 73.44%, ACC = 77.72%) and MMBCs (AUC = 0.92, SEN = 80.85%, SPE = 95.31%, ACC = 91.43%) from FAs.

CONCLUSION

This diagnostic model holds promise for effectively distinguishing PMBCs and MMBCs from FAs, assisting radiologists in mitigating diagnostic biases and enhancing diagnostic efficiency.

Correlation of shear-wave elastography stiffness and apparent diffusion coefficient values with tumor characteristics in breast cancer

We aimed to investigate the correlation between shear-wave elastography (SWE) and apparent diffusion coefficient (ADC) values in breast cancer and to identify the associated characteristics. We included 91 breast cancer patients who underwent SWE and breast MRI prior to surgery between January 2016 and November 2017. We measured the lesion's mean (Emean) and maximum (Emax) elasticities of SWE and ADC values. We evaluated the correlation between SWE, ADC values and tumor size. The mean SWE and ADC values were compared for categorical variable of the pathological/imaging characteristics. ADC values showed negative correlation with Emean (r =  - 0.315, p = 0.002) and Emax (r =  - 0.326, p = 0.002). SWE was positively correlated with tumor size (r = 0.343-0.366, p < 0.001). A higher SWE value indicated a tendency towards a higher T stage (p < 0.001). Triple-negative breast cancer showed the highest SWE values (p = 0.02). SWE were significantly higher in breast cancers with posterior enhancement, vascularity, and washout kinetics (p < 0.02). SWE stiffness and ADC values were negatively correlated in breast cancer. SWE values correlated significantly with tumor size, and were higher in triple-negative subtype and aggressive imaging characteristics.

Ultrasound radiomics-based nomogram to predict lymphovascular invasion in invasive breast cancer: a multicenter, retrospective study

OBJECTIVES

To develop and validate an ultrasound (US) radiomics-based nomogram for the preoperative prediction of the lymphovascular invasion (LVI) status in patients with invasive breast cancer (IBC).

MATERIALS AND METHODS

In this multicentre, retrospective study, 456 consecutive women were enrolled from three institutions. Institutions 1 and 2 were used to train (n = 320) and test (n = 136), and 130 patients from institution 3 were used for external validation. Radiomics features that reflected tumour information were derived from grey-scale US images. The least absolute shrinkage and selection operator and the maximum relevance minimum redundancy (mRMR) algorithm were used for feature selection and radiomics signature (RS) building. US radiomics-based nomogram was constructed by using multivariable logistic regression analysis. Predictive performance was assessed with the receiving operating characteristic curve, discrimination, and calibration.

RESULTS

The nomogram based on clinico-ultrasonic features (menopausal status, US-reported lymph node status, posterior echo features) and RS yielded an optimal AUC of 0.88 (95% confidence interval [CI], 0.84-0.91), 0.89 (95% CI, 0.84-0.94) and 0.95 (95% CI, 0.92-0.99) in the training, internal and external validation cohort. The nomogram outperformed the clinico-ultrasonic and RS model (p < 0.05). The nomogram performed favourable discrimination (C-index, 0.88; 95% CI: 0.84-0.91) and was confirmed in the validation (0.88 for internal, 0.95 for external) cohorts. The calibration and decision curve demonstrated the nomogram showed good calibration and was clinically useful.

CONCLUSIONS

The radiomics nomogram incorporated in the RS and US and the clinical findings exhibited favourable preoperative individualised prediction of LVI.

CLINICAL RELEVANCE STATEMENT

The US radiomics-based nomogram incorporating menopausal status, posterior echo features, US reported-ALN status, and radiomics signature has the potential to predict lymphovascular invasion in patients with invasive breast cancer.

KEY POINTS

• The clinico-ultrsonic model of menopausal status, posterior echo features, and US-reported ALN status achieved a better predictive efficacy for LVI than either of them alone. • The radiomics nomogram showed optimal prediction in predicting LVI from patients with IBC (ROC, 0.88 and 0.89 in the training and validation sets). • A nomogram demonstrated favourable performance (area under the receiver operating characteristic curve, 0.95) and well calibration (C-index, 0.95) in an independent validation cohort (n = 130).

Comparison of the diagnostic efficacy of mathematical models in distinguishing ultrasound imaging of breast nodules

This study compared the diagnostic efficiency of benign and malignant breast nodules using ultrasonographic characteristics coupled with several machine-learning models, including logistic regression (Logistics), partial least squares discriminant analysis (PLS-DA), linear support vector machine (Linear SVM), linear discriminant analysis (LDA), K-nearest neighbor (KNN), artificial neural network (ANN) and random forest (RF). The clinical information and ultrasonographic characteristics of 926 female patients undergoing breast nodule surgery were collected and their relationships were analyzed using Pearson's correlation. The stepwise regression method was used for variable selection and the Monte Carlo cross-validation method was used to randomly divide these nodule cases into training and prediction sets. Our results showed that six independent variables could be used for building models, including age, background echotexture, shape, calcification, resistance index, and axillary lymph node. In the prediction set, Linear SVM had the highest diagnosis rate of benign nodules (0.881), and Logistics, ANN and LDA had the highest diagnosis rate of malignant nodules (0.910~0.912). The area under the ROC curve (AUC) of Linear SVM was the highest (0.890), followed by ANN (0.883), LDA (0.880), Logistics (0.878), RF (0.874), PLS-DA (0.866), and KNN (0.855), all of which were better than that of individual variances. On the whole, the diagnostic efficacy of Linear SVM was better than other methods.

Prediction for pathological and immunohistochemical characteristics of triple-negative invasive breast carcinomas: the performance comparison between quantitative and qualitative sonographic feature analysis

OBJECTIVE

Sonographic features are associated with pathological and immunohistochemical characteristics of triple-negative breast cancer (TNBC). To predict the biological property of TNBC, the performance using quantitative high-throughput sonographic feature analysis was compared with that using qualitative feature assessment.

METHODS

We retrospectively reviewed ultrasound images, clinical, pathological, and immunohistochemical (IHC) data of 252 female TNBC patients. All patients were subgrouped according to the histological grade, Ki67 expression level, and human epidermal growth factor receptor 2 (HER2) score. Qualitative sonographic feature assessment included shape, margin, posterior acoustic pattern, and calcification referring to the Breast Imaging Reporting and Data System (BI-RADS). Quantitative sonographic features were acquired based on the computer-aided radiomics analysis. Breast cancer masses were manually segmented from the surrounding breast tissues. For each ultrasound image, 1688 radiomics features of 7 feature classes were extracted. The principal component analysis (PCA), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM) were used to determine the high-throughput radiomics features that were highly correlated to biological properties. The performance using both quantitative and qualitative sonographic features to predict biological properties of TNBC was represented by the area under the receiver operating characteristic curve (AUC).

RESULTS

In the qualitative assessment, regular tumor shape, no angular or spiculated margin, posterior acoustic enhancement, and no calcification were used as the independent sonographic features for TNBC. Using the combination of these four features to predict the histological grade, Ki67, HER2, axillary lymph node metastasis (ALNM), and lymphovascular invasion (LVI), the AUC was 0.673, 0.680, 0.651, 0.587, and 0.566, respectively. The number of high-throughput features that closely correlated with biological properties was 34 for histological grade (AUC 0.942), 27 for Ki67 (AUC 0.732), 25 for HER2 (AUC 0.730), 34 for ALNM (AUC 0.804), and 34 for LVI (AUC 0.795).

CONCLUSION

High-throughput quantitative sonographic features are superior to traditional qualitative ultrasound features in predicting the biological behavior of TNBC.

KEY POINTS

• Sonographic appearances of TNBCs showed a great variety in accordance with its biological and clinical characteristics. • Both qualitative and quantitative sonographic features of TNBCs are associated with tumor biological characteristics. • The quantitative high-throughput feature analysis is superior to two-dimensional sonographic feature assessment in predicting tumor biological property.

Comparing breast cancer imaging characteristics of CHEK2 with BRCA1 and BRCA2 gene mutation carriers

PURPOSE

Breast cancer gene (BRCA) 1 and 2 mutations are frequently studied gene mutations (GM); the incidence of checkpoint kinase 2 (CHEK2) is increasing. We describe the imaging features of breast cancer (BC) in CHEK2 mutations, compared to BRCA 1 and 2 using mammography, ultrasound (US) and magnetic resonance imaging (MRI).

METHOD

Inclusion criteria were primary BC in GM carriers, treated in the same hospital. Age at diagnosis, histology, hormone receptor and human epidermal growth factor receptor 2 (HER2) status were retrieved. Mammography descriptors were mass, asymmetry and suspicious microcalcifications. The enhancement pattern (MRI), shape and border, architectural distortion, the presence of a hyperechoic rim and cystic complex structure (US) were documented. Analyses were performed using SAS software (version 9.4). Fishers' exact test was used to test associations between two categorical variables.

RESULTS

In 191 women, 233 malignant lesions were diagnosed (78 in BRCA1, 109 in BRCA2, 46 in CHEK2). In CHEK2 carriers, mammographically, suspicious microcalcifications (54%) were more prevalent (BRCA2 (48%) and BRCA1 carriers (33%)) (p-value = 0.057) compared to mass lesions (35%). On US, lesions were most frequently ill-defined (86%) (p = 0.579) and irregular (94.5%) (p = 0.098) compared to BRCA2 (77% and 80% resp.) and BRCA1 carriers (71% and 72% resp.). On MRI, mass lesions showed a type 3 curve in CHEK2 (67%) compared to BRCA1 (36%) and BRCA2 (50%) (p = 0.056).

CONCLUSIONS

Malignant radiological characteristics of breast cancer, more specifically suspicious microcalcifications, were more frequently seen in CHEK2 and BRCA2 compared to BRCA1 mutation carriers (without a significant difference) indicating the importance of mammography in follow-up of CHEK2 carriers.

Breast involvement of hematological malignancies: imaging and clinical findings

Background

Breast involvement of hematological malignancies is a very rare entity. Accurate diagnosis is essential for appropriate treatment. The aim of this study was to clarify the clinical and radiological findings of hematological malignancy breast involvement and to describe possible pitfalls in diagnosis.

Results

The images of 20 patients with breast involvement of hematological malignancies were retrospectively evaluated on ultrasonography, mammography, and magnetic resonance imaging (MRI) and the findings were reported. Bilaterality was seen only in cases with secondary involvement, and there was no marked difference between primary and secondary breast involvement of hematological malignancies. All patients underwent ultrasonography examination. According to ultrasonography, breast masses were most frequently irregular in shape (11/20, 55%) with non-circumscribed margins (11/20, 55%). Posterior acoustic enhancement was noted in 14 cases (70%). Posterior shadowing was not observed in any of the patients. Mammography was available in 10 patients. Microcalcification was not observed in any patient on mammography. MRI was available in four patients. Hyperintensity in T2-weighted images, type 2 or type 3 dynamic curve, and diffusion restriction were observed in all cases.

Conclusions

Hematological malignancies may mimic both benign breast lesions and breast carcinoma. Familiarity with the radiological features of hematological malignancies can help accurate diagnosis.

Characteristics of Breast Masses of Female Patients Referred for Diagnostic Breast Ultrasound from a Saudi Primary Health Care Setting

Background

Breast masses are common among females presenting to primary health care (PHC) facilities. The family physician’s role is crucial in detecting breast disease. Utilization of breast ultrasonography has been increasing recently as a diagnostic tool.

Objective

This study aims to determine the characteristics of masses detected on breast ultrasound, their associations with characteristics of females attending the PHC setting and explore the management of these cases by family physicians.

Methods

This registered based, cross-sectional study included 321 females who were referred for diagnostic breast ultrasound in the PHC center of the University hospital, Eastern province, Saudi Arabia (2017–2019). t-test, Chi-squared and Fisher’s Exact tests were performed to assess associations between the presence of breast masses in the ultrasound and patients’ characteristics. Moreover, to compare the breast masses in two groups of patients (< 40 years and ≥ 40 years) regarding their characteristics, ultrasound findings, and further management performed. P < 0.05 was considered statistically significant.

Results

Approximately 24% patients had a breast mass and 70.92% of cases were detected among females ≥ 40 years old. The odds of having a breast mass were highest among overweight, females complaining from a breast lump, and who had early menarche. Grand multiparous had lower odds of a breast mass. Females < 40 years old had higher rates of breastfeeding, increasing parity, and obesity than older females. Sonographic examined masses were larger in young females, and posterior enhancement of the mass was more reported in older. BI-RADs of the masses were not associated with the patient’s age.

Conclusion

Breast masses were prevalent among females who underwent breast ultrasound. The results support referral for investigation when a female complains of a breast lump. Family physicians have a vital role in encouraging protective behaviors from developing breast masses such as maintaining normal weight and breastfeeding.

Tumor Proliferation and Invasiveness Derived From Ultrasound Appearances of Invasive Breast Cancers: Moving Beyond the Routine Differential Diagnosis

OBJECTIVES

To investigate the correlation between ultrasound (US) appearances of invasive breast cancers and tumor proliferation and invasiveness measured according to the histologic grade, Ki-67 expression, axillary lymph node metastasis (ALNM), and lymphovascular invasion (LVI).

METHODS

This study evaluated 676 patients who underwent primary surgical treatment of invasive breast cancers. The preoperative US reports and postoperative pathologic and immunohistochemical results of the patients were retrospectively reviewed. Ultrasound characteristics were evaluated according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) lexicon. Logistic regression analyses were used to identify independent predictive US features that were correlated with tumor proliferation and invasiveness of breast cancers. Odds ratios (ORs) were calculated.

RESULTS

Posterior acoustic enhancement and calcifications on US images were independent predictive factors of a higher histologic grade and a higher Ki-67 level (OR, 1.69-6.54; P < .05). Meanwhile, a noncircumscribed margin (OR, 2.61; P < .05) and posterior acoustic shadow (OR, 1.62; P < .05) were independent predictors of ALNM. An irregular shape (OR, 2.13; P < .05) and calcifications (OR, 1.69; P < .05) were independent risk factors for LVI. Infiltrative breast cancers scored as BI-RADS category 5 had higher probability to be associated with ALNM (OR, 3.33; P < .0005) and LVI (OR, 2.87; P < .0005).

CONCLUSIONS

Ultrasound features of invasieve breast cancers might have a predictive value for tumor proliferation and invasiveness. The US features correlated with a high cellular proliferation rate were different from those associated with ALNM. The tumor shape, margin, posterior acoustic pattern, and calcifications at US are suggested to be considered by clinicians when making clinical decisions.

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

OBJECTIVES

To investigate the value of ultrasound (US) feature-based models in predicting the proliferation and invasiveness of invasive breast cancer (IBC) and to compare the performance of models based solely on US features with models that combined US features, patient age, tumor size, and axilla status from US.

METHODS

With ethical approval, 746 patients with a pathologic diagnosis of IBC were reviewed for preoperative clinical, US, and postoperative pathologic data. The proliferation and invasiveness properties of the IBC included the histologic grade and Ki-67 status and lymphovascular invasion (LVI) and axillary lymph node metastasis (ALNM), respectively. Logistic regression analyses were used to identify independent risk factors for tumor proliferation and invasiveness.

RESULTS

Posterior echo enhancement, calcification, a tumor size larger than 2 cm, and suspicion of ALNM from axillary US were independent risk factors for a high histologic grade and high Ki-67 expression of IBC (P < .05). A posterior echo shadow, patient age younger than 45 years, and suspicious findings on axillary US imaging were independent variables for predicting the presence of LVI and ALNM in IBC (P < .05). Calcification was the independent factor for predicting LVI (P = .013). The predictive performance of the combined models was improved compared with the US feature-based models, with a higher accuracy rate and negative predictive value. The area under curve of the combined models was also significantly higher than that of the single models (P < .05).

CONCLUSIONS

Compared with the US feature-based models, the combined models yielded better predictive performance. This may provide a more robust model to predict the tumor biological properties of IBC before surgery.

Ultrasonographic appearance of triple-negative invasive breast carcinoma is associated with novel molecular subtypes based on transcriptomic analysis

Background

Various sonographic features of triple-negative invasive breast carcinomas (TNBC) expected to be associated with the molecular subtypes based on transcriptomic analysis were examined. The effects of clinical, sonographic, pathological, and molecular features on survival outcome was also studied.

Methods

One hundred and fourteen patients with breast cancer with negative expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal receptor 2 (HER2) were included in our retrospective study. Based on the transcriptomic profiles, four stable clusters named immunomodulatory (IM), luminal androgen receptor (LAR), mesenchymal-like (MES), and basal-like and immune-suppressed (BLIS) were identified. Ultrasound (US) images were reviewed by two US physicians according to Breast Imaging Reporting and Data System (BI-RADS). Multivariate Cox regression was used to determine the variables associated with recurrence-free survival (RFS) and overall survival (OS).

Results

There were 21 IM, 18 LAR, 36 MES, and 39 BLIS cases. The four molecular subtypes showed significant differences in terms of tumor shape (P=0.008) and posterior acoustic pattern (P=0.028). Compared with the subtypes LAR and MES, the IM and BLIS subtypes had higher probability of presenting benign-like sonographic features, such as regular shape, no angular/spiculated margin, and posterior acoustic enhancement (P<0.05). The independent risk factors for RFS events and death were axillary lymph node metastasis (P<0.05) and BLIS subtype (P<0.05). BLIS subtype showed worse OS than other subtypes (log rank P=0.05). TNBCs with benign sonographic features tended to have less death events (3.3% vs. 15.2%, P=0.088).

Conclusions

Sonographic appearance of TNBCs is associated with transcriptome-based molecular subtypes, and tends to correlate with the survival outcome.

Clinicopathologic and Ultrasound Variables Associated With a Heavy Axillary Nodal Tumor Burden in Invasive Breast Carcinoma

OBJECTIVES

To identify clinicopathologic and ultrasound (US) variables that were associated with a heavy nodal tumor burden, which was defined as 3 or more lymph nodes involved with metastasis to the axilla after invasive breast carcinoma.

METHODS

With ethical approval, 621 patients with a pathologic diagnosis of invasive breast carcinoma were retrospectively analyzed for clinical, pathologic, and US data. Pathologic findings were ascertained by the final paraffin pathologic analysis. Ultrasound characteristics were evaluated on the basis of the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS). Univariate and multivariate logistic regression analyses were used to assess the clinicopathologic and US variables that were associated with a heavy nodal tumor burden at the axilla.

RESULTS

There were 107 cases (17.2%) of invasive breast carcinoma with a heavy tumor burden at the axilla. The independent clinicopathologic variables for a heavy tumor burden at the axilla included a tumor size of 2 to 5 cm (odds ratio [OR], 1.86; P = .036), the presence of lymphovascular invasion (OR, 23.52; P < .001), the presence of papillary invasion (OR, 2.93; P = .043), and a non-triple-negative subtype (OR, 2.34; P = .04). The independent US features of breast tumors that were associated with a heavy tumor burden at the axilla included BI-RADS category 5 (OR, 5.50; P = .024) and a posterior acoustic shadow (OR, 1.94; P = .024).

CONCLUSIONS

A large tumor size, lymphovascular invasion, papillary invasion, and a non-triple-negative subtype on the pathologic analysis as well as BI-RADS category 5 and a posterior acoustic shadow on a US assessment were associated with a heavy nodal tumor burden at the axilla. These US characteristics of the primary breast carcinoma might provide additional information to axillary US for the prediction of axillary nodal tumor loads.

Triple-negative invasive breast carcinoma: the association between the sonographic appearances with clinicopathological feature

In this study, we aimed to evaluate the clinical and pathological factors that associated with sonographic appearances of triple-negative (TN) invasive breast carcinoma. With the ethical approval, 560 patients who were pathologically confirmed as invasive breast carcinoma were reviewed for ultrasound, clinical, and pathological data. Logistic regression analysis was used to identify the typical sonographic features for TN invasive breast carcinomas. The effect of clinical and pathological factors on the sonographic features of TN invasive breast carcinoma was studied. There were 104 cases of TN invasive breast carcinoma. The independent sonographic features for the TN subgroup included regular shape (odds ratio, OR = 2.14, p = 0.007), no spiculated/angular margin (OR = 1.93, p = 0.035), posterior acoustic enhancement (OR = 2.14, p = 0.004), and no calcifications (OR = 2.10, p = 0.008). Higher pathological grade was significantly associated with regular tumor shape of TN breast cancer (p = 0.012). Higher Ki67 level was significantly associated with regular tumor shape (p = 0.023) and absence of angular/spiculated margin (p = 0.005). Higher human epidermal growth factor receptor 2 (HER2) score was significantly associated with the presence of calcifications (p = 0.033). We conclude that four sonographic features are associated with TN invasive breast carcinoma. Heterogeneity of sonographic features was associated with the pathological grade, Ki67 proliferation level and HER2 score of TN breast cancers.

Ultrasonography methods for predicting malignancy in canine mammary tumors

The aim of this study was to evaluate and compare the efficacy of B-mode, Doppler, contrast-enhanced ultrasonography (CEUS), and Acoustic Radiation Force Impulse (ARFI) elastography in predicting malignancy in canine mammary masses. This was a prospective cohort study from 2014 to 2016, which included 153 bitches with one or more mammary masses. A total of 300 masses were evaluated by ultrasonography (B-mode, Doppler, CEUS, and ARFI) and subsequently classified as benign or malignant by histopathology. Each ultrasound parameters studied were compared between benign and malignant masses by Chi-square or Student tests and differences were considered significant when P < 0.01. For the variables that proved significant differences were estimated the cut-off point, sensitivity, specificity, accuracy, and area under curve (AUC) by receiver-operating characteristic curve (ROC) analysis in a logistic regression model using histopathological classification as reference, to assess and compare diagnostic performance of each technique. Out of 300 mammary masses evaluated 246 were classified as malignant and 54 as benign. B-mode measurements showed sensitivity 67.9%, and specificity 67.6% as malignancy predictors on canine mammary masses; Doppler indexes systolic (>21.2 m/s) and diastolic velocity (>4.8 m/s) sensitivity 79.2% and specificity 70.8%; CEUS wash-out time (<80.5 s) sensitivity 80.2% and specificity 16.7%; and ARFI elastography shear velocity (SWV > 2.57 m/s) sensitivity 94.7% and specificity 97.2% In conclusion B-mode and Doppler ultrasound evaluations may assist in malignancy prediction of canine mammary masses with moderate sensitivity and specificity, already the SWV was an great accurate predictor. Therefore, ARFI elastography exam inclusion in veterinary clinic oncology and research is highly recommended, since it allows fast, non-invasive, and complication-free malignancy prediction of canine mammary masses.

Modulation of mammary tumor vascularization by mast cells: Ultrasonographic and histopathological approaches

AIMS

The inhibition of mast cells' degranulation may be an approach to prevent the formation of new vessels during the mammary carcinogenesis.

MATERIALS AND METHODS

Female Sprague-Dawley rats were randomly divided into five experimental groups. Mammary tumors were induced by intraperitoneal injection of N-methyl-N-nitrosourea (MNU). Animals from group II were treated with ketotifen for 18weeks immediately after the MNU administration, while animals from group III only received the ketotifen after the development of the first mammary tumor. Mammary tumors vascularization was assessed by ultrasonography (Doppler, B Flow and contrast-enhanced ultrasound) and immunohistochemistry (vascular endothelial growth factor-A).

KEY FINDINGS AND SIGNIFICANCE

Similar to what occurs in women with breast cancer, the majority of MNU-induced mammary tumors exhibited a centripetal enhancement order of the contrast agent, clear margin and heterogeneous enhancement. Ultrasonographic and immunohistochemical data suggest that the inhibition of mast cells' degranulation did not change the mammary tumors vascularization.

Computer-aided assessment of tumor grade for breast cancer in ultrasound images

This study involved developing a computer-aided diagnosis (CAD) system for discriminating the grades of breast cancer tumors in ultrasound (US) images. Histological tumor grades of breast cancer lesions are standard prognostic indicators. Tumor grade information enables physicians to determine appropriate treatments for their patients. US imaging is a noninvasive approach to breast cancer examination. In this study, 148 3-dimensional US images of malignant breast tumors were obtained. Textural, morphological, ellipsoid fitting, and posterior acoustic features were quantified to characterize the tumor masses. A support vector machine was developed to classify breast tumor grades as either low or high. The proposed CAD system achieved an accuracy of 85.14% (126/148), a sensitivity of 79.31% (23/29), a specificity of 86.55% (103/119), and an A_Z of 0.7940.

Pregnancy-associated breast cancer: optimal treatment options

Cancer is diagnosed approximately once per 1,000 pregnancies; most commonly due to the reproductive age of the women, these include breast, cervical, melanoma, thyroid, and Hodgkin’s lymphoma diagnoses. As a single diagnosis, breast cancer is the most common cancer diagnosed during pregnancy. Cancer is expected to complicate pregnancy more often due to the trend for women to delay child bearing to later maternal ages. Delayed first birth is itself a risk factor for breast cancer. Termination of pregnancy has not been shown to afford a survival benefit. While protecting the interests of mother and unborn fetus, breast cancer can be safely diagnosed, staged, and treated during pregnancy with good outcomes for both. Some modification of the protocols used for nonpregnant women with suspicious palpable breast masses is required. This article reviews the challenges for physicians in making the diagnosis of breast cancer during pregnancy and upon diagnosis, counseling patients about treatment options. The consequences of diagnostic investigations and cancer treatment for the exposed fetus are also addressed.

Specific challenges in treating breast cancer in pregnant women

SUMMARY 

A cancer diagnosis during pregnancy presents a challenge to practitioners and patients. Often diagnosis is delayed. There are limited prospective case series and scant long-term neonatal and maternal data on which to base treatment plans. Also, the majority of pregnancy-associated case series include women diagnosed with breast cancer up to 1 year postpartum. The later-diagnosed group has a poorer prognosis and should be evaluated separately. To avoid attributing breast masses to pregnancy-related changes, masses should be evaluated as if the patient were not pregnant. Mammography, MRI, ultrasound, mastectomy and lumpectomy, axillary dissection, sentinel lymph node biopsy and even chemotherapy during the second and third trimesters can be considered for the pregnant patient with breast cancer.

Heterogeneity of triple-negative breast cancer: mammographic, US, and MR imaging features according to androgen receptor expression

OBJECTIVE

Our aim was to determine whether triple-negative breast cancers (TNBCs) with and without androgen receptor (AR) expression have distinguishing imaging features on mammography, breast ultrasound (US), and magnetic resonance (MR) imaging.

METHODS

AR expression was assessed immunohistochemically in 125 patients with TNBC from a consecutive series of 1,086 operable invasive breast cancers. Two experienced radiologists blinded to clinicopathological findings reviewed all imaging studies in consensus using the BI-RADS lexicon. The imaging and pathological features of 33 AR-positive TNBCs were compared with those of 92 AR-negative TNBCs.

RESULTS

The presence of mammographic calcifications with or without a mass (p < 0.001), non-mass enhancement on MR imaging (p < 0.001), and masses with irregular shape or spiculated margins on US (p < 0.001 and p = 0.002) and MR imaging (p = 0.001 and p < 0.001) were significantly associated with AR-positive TNBC. Compared with AR-negative TNBC, AR-positive TNBC was more likely to have a ductal carcinoma in situ component (59.8% vs. 90.9%, p = 0.001) and low Ki-67 expression (30.4% vs. 51.5%, p = 0.030).

CONCLUSION

AR-positive and AR-negative TNBCs have different imaging features, and certain imaging findings can be useful to predict AR status in TNBC.

KEY POINTS

• Triple-negative breast cancers have distinguishing imaging features according to AR expression. • AR-positive TNBC is associated with calcifications, spiculated masses, and non-mass enhancement. • Multimodality imaging can help predict androgen receptor status in TNBC.