Preoperative Role of Superb Microvascular Imaging and Shear-Wave Elastography for Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer

ABSTRACT

This study aims to evaluate the role of shearwave elastography (SWE) and superb microvascular imaging (SMI) for preoperative prediction of axillary lymph node metastasis (ALNM) in patients with breast cancer. In a cohort of 214 women with breast cancer, B-Mode ultrasonography (US), SMIvascular-index (SMIvi), and SWE (E-mean, E-ratio) values were recorded before tru-cut biopsy. Axillary fine-needle aspiration biopsy (FNAB) and sentinel lymph node sampling results were collected. Imaging findings and histopathological data were statistically compared. Receiver operating characteristic curve analysis was used to evaluate diagnostic performance. Reverse stepwise logistical regression analysis was conducted. Although ALNM was negative in 111 cases, it was positive in 103 patients. Axillary lymph node metastasis (+) group had larger size ( P < 0.001), higher vascularization (SMIvi: 8.0 ± 6.0 versus 5.0 ± 4.3, P < 0.001), and higher elasticity value (E-mean: 129 ± 31 kPa versus 117.3 ± 40 kPa, P = 0.014). Axillary lymph node metastasis was observed statistically more frequently in Her-2 positive cases ( P = 0.005). There was no significant difference between other B-mode US findings ( P > 0.05), SMI Adler ( P = 0.878), and E-ratio ( P = 0.212). The most appropriate cutoff value for the prediction of ALNM was 23.5 mm for size, 3.8 for SMIvi, and 138.5 kPa for E-mean. The most sensitive (77%) method was the SMIvi measurement, while the most specific (86%) finding was Her-2 positivity. The combined model (being Her-2 positive, >23.5 cm, and >3.8 SMIvi) increased the specificity (78%), PPV (71%), and accuracy (68%). Although the increased size is a previously studied parameter in predicting the risk of ALNM, Her-2 and data obtained by SWE, and SMI can be used to assist conventional US.

A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection

BACKGROUND

To develop a clinical model for predicting high axillary nodal burden in patients with early breast cancer by integrating ultrasound (US) and clinicopathological features.

METHODS AND MATERIALS

Patients with breast cancer who underwent preoperative US examination and breast surgery at the Affiliated Hospital of Nantong University (centre 1, n = 250) and at the Affiliated Hospital of Jiangsu University (centre 2, n = 97) between January 2012 and December 2016 and between January 2020 and March 2022, respectively, were deemed eligible for this study (n = 347). According to the number of lymph node (LN) metastasis based on pathology, patients were divided into two groups: limited nodal burden (0-2 metastatic LNs) and heavy nodal burden (≥ 3 metastatic LNs). In addition, US features combined with clinicopathological variables were compared between these two groups. Univariate and multivariate logistic regression analysis were conducted to identify the most valuable variables for predicting ≥ 3 LNs in breast cancer. A nomogram was then developed based on these independent factors.

RESULTS

Univariate logistic regression analysis revealed that the cortical thickness (p < 0.001), longitudinal to transverse ratio (p = 0.001), absence of hilum (p < 0.001), T stage (p = 0.002) and Ki-67 (p = 0.039) were significantly associated with heavy nodal burden. In the multivariate logistic regression analysis, cortical thickness (p = 0.001), absence of hilum (p = 0.042) and T stage (p = 0.012) were considered independent predictors of high-burden node. The area under curve (AUC) of the nomogram was 0.749.

CONCLUSION

Our model based on US variables and clinicopathological characteristics demonstrates that can help select patients with ≥ 3 LNs, which can in turn be helpful to predict high axillary nodal burden in early breast cancer patients and prevent unnecessary axillary lymph node dissection.

Nipple Lesions of the Breast: An Update on Morphologic Features, Immunohistochemical Findings and Differential Diagnosis

Because of the unique anatomic structure of the nipple, a few specific breast lesions occur only at this site. Large lactiferous sinuses may be involved by inflammatory conditions such as squamous metaplasia of lactiferous ducts and ductal ectasia or be the site of uncommon superficial epithelial neoplasms such as nipple adenoma or syringomatous tumor of the nipple. Paget disease of the nipple may be secondary to intraepidermal extension of ductal carcinoma in situ in the underlying lactiferous ducts or develop from malignant transformation of Toker cells. Invasive breast cancer may also arise primarily in the nipple. Most of these conditions present as a palpable mass and/or skin changes with or without nipple discharge. Due to the delicate location and often relatively small size of nipple lesions, biopsy specimens are often superficial and fragmented, and the interpretation is challenging. Knowledge of the morphologic and immunophenotypic features of nipple lesions is essential in making the correct diagnosis. Information on the molecular alterations underpinning nipple neoplasms is currently very limited.

The effect of the tumor-to-skin distance on axillary lymph node metastasis in breast cancer

OBJECTIVE

Tumor-to-skin distance is known to have an effect on axillary lymph node metastasis but has no clinical use with nomograms. This study aimed to investigate the effect of tumor-to-skin distance on axillary lymph node metastasis alone and in combination with nomogram for clinical use.

METHODS

A total of 145 patients who underwent surgery for breast cancer (T1-T2 stage) and whose axillary lymph nodes were evaluated (axillary dissection or sentinel lymph node biopsy) between January 2010 and December 2020 were included in the study. Tumor-to-skin distance and other pathological data of the patients were evaluated.

RESULTS

Of the 145 patients, 83 (57.2%) had metastatic lymph nodes in the axilla. Tumor-to-skin distance was different in terms of lymph node metastasis (p=0.045). In the receiver operating characteristic curve for tumor-to-skin distance, area under curve was 0.597 (95%CI 0.513-0.678, p=0.046), area under curve of the nomogram was 0.740 (95%CI 0.660-0.809), p<0.001) and nomogram+tumor-to-skin distance was 0.753 (95%CI 0.674-0.820), p<0.001). No statistical difference was found for axillary lymph node metastasis between the nomogram+tumor-to-skin distance and the nomogram alone (p=0.433).

CONCLUSION

Although tumor-to-skin distance demonstrated a significant difference in axillary lymph node metastasis, it had a poor association with an area under curve value of 0.597 and did not produce a significant improvement in predicting lymph node metastasis when combined with the nomogram. The tumor-to-skin distance may be unlikely to enter clinical practice.

Preoperative predictive factors affecting sentinel lymph node positivity in breast cancer and comparison of their effectiveness with existing nomograms

This study aimed to establish a strong regression model by revealing the preoperative predictive factors for sentinel lymph node (SLN) positivity in patients with early stage breast cancer (ESBC). In total, 445 patients who underwent SLN dissection for ESBC were included. All data that may be potential predictors of SLN positivity were retrospectively analyzed. Tumor size >2 cm, human epidermal growth factor receptor 2 (HER2) + status, lymphovascular invasion (LVI), palpable tumor, microcalcifications, multifocality or multicentricity, and axillary ultrasonographic findings were defined as independent predictors of SLN involvement. The area under the receiver operating characteristic (ROC) curve (AUC) values were 0.797, 0.808, and 0.870 for the Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram, MD Anderson Cancer Center (MDACC) nomogram, and our regression model, respectively (P < .001). The recent model for predicting SLN status in ESBC was found to be stronger than existing nomograms. Parameters not included in current nomograms, such as palpable tumors, microcalcifications, and axillary ultrasonographic findings, are likely to make this model more meaningful.

Deep Learning Mechanism for Predicting the Axillary Lymph Node Metastasis in Patients with Primary Breast Cancer

The second largest cause of mortality worldwide is breast cancer, and it mostly occurs in women. Early diagnosis has improved further treatments and reduced the level of mortality. A unique deep learning algorithm is presented for predicting breast cancer in its early stages. This method utilizes numerous layers to retrieve significantly greater amounts of information from the source inputs. It could perform automatic quantitative evaluation of complicated image properties in the medical field and give greater precision and reliability during the diagnosis. The dataset of axillary lymph nodes from the breast cancer patients was collected from Erasmus Medical Center. A total of 1050 images were studied from the 850 patients during the years 2018 to 2021. For the independent test, data samples were collected for 100 images from 95 patients at national cancer institute. The existence of axillary lymph nodes was confirmed by pathologic examination. The feed forward, radial basis function, and Kohonen self-organizing are the artificial neural networks (ANNs) which are used to train 84% of the Erasmus Medical Center dataset and test the remaining 16% of the independent dataset. The proposed model performance was determined in terms of accuracy (Ac), sensitivity (Sn), specificity (Sf), and the outcome of the receiver operating curve (Roc), which was compared to the other four radiologists' mechanism. The result of the study shows that the proposed mechanism achieves 95% sensitivity, 96% specificity, and 98% accuracy, which is higher than the radiologists' models (90% sensitivity, 92% specificity, and 94% accuracy). Deep learning algorithms could accurately predict the clinical negativity of axillary lymph node metastases by utilizing images of initial breast cancer patients. This method provides an earlier diagnostic technique for axillary lymph node metastases in patients with medically negative changes in axillary lymph nodes.

The value of prognostic ultrasound features of breast cancer in different molecular subtypes with a focus on triple negative disease

The ultrasound (US) features of breast cancer have recently been shown to have prognostic significance. We aim to assess these features according to molecular subtype. 1140 consecutive US visible invasive breast cancers had US size and mean stiffness by shearwave elastography (SWE) recorded prospectively. Skin thickening (> 2.5 mm) overlying the cancer on US and the presence of posterior echo enhancement were assessed retrospectively while blinded to outcomes. Cancers were classified as luminal, triple negative (TN) or HER2 + ve based on immunohistochemistry and florescent in-situ hybridization. The relationship between US parameters and breast cancer specific survival (BCSS) was ascertained using Kaplan–Meier survival curves and ROC analysis. At median follow-up 6.3 year, there were 117 breast cancer (10%) and 132 non-breast deaths (12%). US size was significantly associated with BCSS all groups (area under the curve (AUC) 0.74 in luminal cancers, 0.64 for TN and 0.65 for HER2 + ve cancers). US skin thickening was associated most strongly with poor prognosis in TN cancers (53% vs. 80% 6 year survival, p = 0.0004). Posterior echo enhancement was associated with a poor BCSS in TN cancers (63% vs. 82% 6 year survival, p = 0.02). Mean stiffness at SWE was prognostic in the luminal and HER2 positive groups (AUC 0.69 and 0.63, respectively). In the subgroup of patients with TN cancers receiving neo-adjuvant chemotherapy posterior enhancement and skin thickening were not associated with response. US skin thickening is a poor prognostic indicator is all 3 subtypes studied, while posterior enhancement was associated with poor outcome in TN cancers

Distance Between the Tumour and Nipple as a Predictor of Axillary Lymph Node Involvement in Breast Cancer

Purpose

The possibility of axillary node metastasis via the lymphatics might be related to a cancer’s location within the breast. Previous studies of this topic had small sample sizes, inaccuracies because of subjective differences, and the inability to depict the entire three-dimensional structure of the breast. Here, we aimed to improve upon these existing drawbacks by retrospectively analysing whether tumour location (quadrants) and tumour–nipple distance can predict axillary node positivity.

Patients and Methods

We identified 961 patients with invasive breast cancer between January 2000 and April 2016. The tumour–nipple distance was objectively measured intraoperatively and clinicopathological information was extracted from hospital database. The distance was measured radially from the nipple to the epicentre rather than the edge of tumour to obviate confounders resulting from tumour size variations.

Results

A total of 847 breast cancers (839 patients) met the eligibility criteria and were included in the statistical analysis. The tumour–nipple distance was smaller in node-positive patients (n = 307; 2.76 ± 2.07 cm) than in node-negative patients (n = 297; 3.41 ± 2.18 cm) (p < 0.001). Tumour–nipple distance was an independent predictor of axillary involvement on logistic regression analysis. However, no statistically significant relationship was detected between node positivity and breast quadrant tumour location.

Conclusion

Tumour–nipple distance can be used to predict axillary lymph node metastasis and assist in surgical decision-making and therapy planning. However, exploratory studies are required to increase our understanding of the mechanism.

Associations between the ultrasound features of invasive breast cancer and breast cancer specific survival

AIM

To assess whether ultrasound features of breast cancer are associated with breast cancer specific survival (BCSS).

MATERIALS AND METHODS

Within a single breast service, data was collected prospectively (April 2010-April 2012) from 319 consecutive women (mean age 63 years) with 335 ultrasound-visible invasive breast cancers. Ultrasound features were evaluated retrospectively from the recorded images according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon by a radiologist blinded to outcomes. Survival and cause of death were ascertained from local and national sources. Kaplan-Meier survival curves were generated, and statistical significance tested using the log-rank test.

RESULTS

Mean follow-up in those alive was 80.9 months. Thirty breast cancer deaths and 45 non-breast cancer deaths occurred. Five-year BCSS in the presence of distal acoustic enhancement was 76% compared to 88%, 96%, and 100% for those with distal shadowing, no distal effect or combined effect respectively (p<0.0002). Patients with sonographic skin involvement had 73% 5-year BCSS compared to 92% for no skin involvement (p<0.0001). Focal oedema was associated with 56% 5-year BCSS compared to 89% for those without (p=0.0002). A significant association was demonstrated between ultrasound tumour size and BCSS (p<0.0001). At multivariate analysis, skin changes, distal enhancement, and focal oedema maintained prognostic significance.

CONCLUSION

Distal enhancement, focal oedema, and skin involvement have strong associations with breast cancer death. These factors could be taken into account, along with lesion size and other commonly used preoperative prognostic features, when considering management of women with breast cancer.

Distance between tumor and nipple as a prognostic factor in breast cancers: Opposite effects in young and old patients

The present study aimed to investigate the prognostic implication of distance from tumor to nipple according to clinicopathological factors with known prognostic value.We retrospectively identified 961 patients of invasive breast cancer from January 2000 to April 2016. Clinicopathological information was extracted from hospital database and distance from tumor to nipple was objectively measured during surgeries. Overall survival (OS) and disease-free survival (DFS) were compared among patients with tumor-nipple distance ≤2, 2 to 5, and >5 cm. Subgroup analyses were performed according to age at diagnosis (≤35 vs >35), tumor size, histological features, treatment, axillary nodal metastasis and lymphovascular invasion.A total of 627 cases were included in statistical analysis. There was no difference detected in OS or DFS among patients with different tumor-nipple distance. Better OS was associated with greater tumor-nipple distance in old patients (HR = 0.582, 95%CI: 0.345-0.982, P = 0.042), while the association between OS and tumor-nipple distance was not observed in young patients. DFS was influenced by tumor-nipple distance in both young (HR = 5.321, 95%CI: 1.151-24.595, P = 0.032) and old (HR = 0.593, 95%CI: 0.385-0.913, P = 0.018) patients with opposite effects.Tumor-nipple distance can be adopted as a prognostic factor of breast cancer and it functions oppositely in young and old patients. Multicenter prospective studies with larger sample size are needed to validate the result.

Combining the Ultrasound Features of Primary Tumor and Axillary Lymph Nodes Can Reduce False-Negative Rate during the Prediction of High Axillary Node Burden in BI-RADS Category 4 or 5 Breast Cancer Lesions

The purpose of this study was to determine whether incorporation of the ultrasound (US) features of the primary tumor and axillary lymph node (ALN) could improve the prediction of high axillary nodal burden (HNB) and, thus, avoid unnecessary sentinel lymph node biopsy (SLNB). A total of 347 patients with Breast Imaging Reporting and Data System US category 4 or 5 breast cancer lesions were included. Their pre-operative US features and post-operative pathologic results were collected. The patients were then divided into the following groups based on surgical histology: limited nodal burden (LNB: 0-2 LNs involved) and heavy nodal burden (HNB: ≥3 metastatic LNs). Univariate and multivariate logistic regression analyses were conducted to determine the most valuable variables for HNB prediction. Receiver operating characteristic curves were obtained to assess their values. We found that a non-circumscribed margin, cortical thickness (≥3 mm) and number (≥3) of suspicious ALNs are indicators for HNB prediction. The false-negative rate (FNR) in model 1 (cortical thickness + number of suspicious ALNs) was 15.5% versus 3.4% in model 2 (non-circumscribed margin + cortical thickness + number of suspicious ALNs). Our results indicate that combining the US features of the primary tumor and ALNs can reduce the FNR during HNB prediction.

Mode of presentation and skin thickening on ultrasound may predict nodal burden in breast cancer patients with a positive axillary core biopsy

OBJECTIVE

A number of pre-operative factors predicting nodal burden in females with breast cancer have recently been identified. The aim of this study is to assess if these factors independently influence nodal burden in females with a positive axillary core biopsy.

METHODS

All node positive patients detected on axillary core biopsy were identified in our cancer audit database. Mode of presentation, age, core tumour grade, core tumour type, ER and HER2 status were evaluated. Tumours were assessed for ultrasound size, distance of tumour-to-skin, presence of invasion of skin and diffuse skin thickening. Axillary lymph nodes were assessed for cortical thickness and presence of ultrasound replaced nodes. Statistical significance was ascertained using univariate logistic regression. A predictive model was produced following a multiple logistic regression model incorporating cross-validation and assessed using receiving operating characteristic curve.

RESULTS

115 patients' data were analysed. Patients referred because of symptoms (70% vs 38%, p = 0.005), and those with ultrasound skin thickening (87% vs 59%, p = 0.055) have higher nodal burden than those referred from screening or without skin thickening. These factors were significant after multivariate analysis. The final predictive model included mode of presentation, ultrasound tumour size, cortical thickness and presence of ultrasound skin thickening. The area under curve is 0.77.

CONCLUSION

We have shown that mode of presentation and ultrasound skin thickening are independent predictors of high nodal burden at surgery. A model has been developed to predict nodal burden pre-operatively, which may lead to avoidance of axillary node clearance in patients with lower nodal burden.

ADVANCES IN KNOWLEDGE

Method of presentation and skin involvement/proximity to skin by the primary tumour are known to influence outcome and nodal involvement respectively but have not been studied with regard to nodal burden. We have shown that mode of presentation and skin thickening at ultrasound are independent predictors of high nodal burden at surgery.

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning

Background Deep learning (DL) algorithms are gaining extensive attention for their excellent performance in image recognition tasks. DL models can automatically make a quantitative assessment of complex medical image characteristics and achieve increased accuracy in diagnosis with higher efficiency. Purpose To determine the feasibility of using a DL approach to predict clinically negative axillary lymph node metastasis from US images in patients with primary breast cancer. Materials and Methods A data set of US images in patients with primary breast cancer with clinically negative axillary lymph nodes from Tongji Hospital (974 imaging studies from 2016 to 2018, 756 patients) and an independent test set from Hubei Cancer Hospital (81 imaging studies from 2018 to 2019, 78 patients) were collected. Axillary lymph node status was confirmed with pathologic examination. Three different convolutional neural networks (CNNs) of Inception V3, Inception-ResNet V2, and ResNet-101 architectures were trained on 90% of the Tongji Hospital data set and tested on the remaining 10%, as well as on the independent test set. The performance of the models was compared with that of five radiologists. The models' performance was analyzed in terms of accuracy, sensitivity, specificity, receiver operating characteristic curves, areas under the receiver operating characteristic curve (AUCs), and heat maps. Results The best-performing CNN model, Inception V3, achieved an AUC of 0.89 (95% confidence interval [CI]: 0.83, 0.95) in the prediction of the final clinical diagnosis of axillary lymph node metastasis in the independent test set. The model achieved 85% sensitivity (35 of 41 images; 95% CI: 70%, 94%) and 73% specificity (29 of 40 images; 95% CI: 56%, 85%), and the radiologists achieved 73% sensitivity (30 of 41 images; 95% CI: 57%, 85%; P = .17) and 63% specificity (25 of 40 images; 95% CI: 46%, 77%; P = .34). Conclusion Using US images from patients with primary breast cancer, deep learning models can effectively predict clinically negative axillary lymph node metastasis. Artificial intelligence may provide an early diagnostic strategy for lymph node metastasis in patients with breast cancer with clinically negative lymph nodes. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Bae in this issue.

Correlation of Conventional Ultrasound Characteristics of Breast Tumors With Axillary Lymph Node Metastasis and Ki-67 Expression in Patients With Breast Cancer

OBJECTIVES

To explore the association between the ultrasound (US) characteristics of breast tumors with axillary lymph node metastasis (ALNM) and Ki-67 expression in patients with breast cancer.

METHODS

In total, 527 consecutive patients with breast cancer who had undergone US examinations and curative surgery with axillary lymph node evaluations were included. The size, shape, aspect ratio, margin, internal echo, internal calcification, posterior echo attenuation, lymphatic hilar structure, cortical thickness, and blood flow of the axillary lymph nodes or primary breast lesions were observed with conventional US. Pathologic prognostic factors, including the histologic type of the tumor, histologic grade, estrogen and progesterone receptor status, lymph node status, and Ki-67 expression were determined. A logistic regression model was used to evaluate whether the US characteristics of primary breast lesions were associated with ALNM and Ki-67 expression.

RESULTS

The maximum tumor diameter (odds ratio [OR], 1.54; 95% confidence interval [CI], 1.05-2.27; P = .028), tumor margin (OR, 2.89; 95% CI, 1.69-4.94; P < .001), internal echo (OR, 2.17; 95% CI, 1.47-3.20; P < .001), and Ki-67 status (OR, 3.57; 95% CI, 2.29-5.58; P < .001) had significant value as independent predictors of ALNM. Only the internal echo (OR, 1.95; 95% CI, 1.28-2.95; P = .002) of breast cancer was an independent predictor of the Ki-67 status. The heterogeneity in the internal echo indicated faster cancer cell proliferation and was associated with a worse prognosis in patients with breast carcinoma.

CONCLUSIONS

Certain conventional US characteristics may be useful predictors of ALNM and the Ki-67 status in patients with breast cancer.

Effect of Primary Breast Tumor Location on Axillary Nodal Positivity

BACKGROUND

Variables such as tumor size, histology, and grade, tumor biology, presence of lymphovascular invasion, and patient age have been shown to impact likelihood of nodal positivity. The aim of this study is to determine whether primary location of invasive disease within the breast is associated with nodal positivity.

PATIENTS AND METHODS

Patients with invasive breast cancer undergoing axillary staging from 2010 to 2014 were identified from the National Cancer Data Base. Rates of axillary nodal positivity by primary tumor locations were compared, and multivariable analysis performed using logistic regression to control for factors known to impact nodal positivity.

RESULTS

A total of 599,722 patients met inclusion criteria. Likelihood of nodal positivity was greatest with primary tumors located in the nipple (43.8%), followed by multicentric disease (40.8%), central breast lesions (39.4%), and axillary tail lesions (38.4%). Tumor location remained independently associated with nodal positivity on multivariable analysis adjusting for variables known to affect nodal positivity with odds ratio 2.8 for tumors in the nipple [95% confidence interval (CI) 2.5-3.1], 2.2 for central breast (95% CI: 2.2-2.3), and 2.7 for axillary tail (95% CI: 2.4-2.9). When restricted to patients with clinically negative nodes (n = 430,949), a similar association was seen.

CONCLUSION

Patients with invasive breast cancer located in the nipple, central breast, and axillary tail have the highest risk of positive axillary lymph nodes independent of patient age, tumor grade, biologic subtype, histology, and size. This should be considered along with other factors in preoperative counseling and decision-making regarding plans for axillary lymph node staging.

Association between US features of primary tumor and axillary lymph node metastasis in patients with clinical T1-T2N0 breast cancer

Background Most patients with early-stage breast cancer have clinically negative lymph nodes (LNs). However, 15-20% of patients have axillary nodal metastasis based on the sentinel LN biopsy. Purpose To assess whether ultrasound (US) features of a primary tumor are associated with axillary LN metastasis in patients with clinical T1-T2N0 breast cancer. Material and Methods This retrospective study included 138 consecutive patients (median age = 51 years; age range = 27-78 years) who underwent breast surgery with axillary LN evaluation for clinically node-negative T1-T2 breast cancer. Three radiologists blinded to the axillary surgery results independently reviewed the US images. Tumor distance from the skin and distance from the nipple were determined based on the US report. Association between US features of a breast tumor and axillary LN metastasis was assessed using a multivariate logistic regression model after controlling for clinicopathologic variables. Results Of the 138 patients, 28 (20.3%) had nodal metastasis. At univariate analysis, tumor distance from the skin ( P = 0.019), tumor size on US ( P = 0.023), calcifications ( P = 0.036), architectural distortion ( P = 0.001), and lymphovascular invasion ( P = 0.049) were associated with axillary LN metastasis. At multivariate analysis, shorter skin-to-tumor distance (odds ratio [OR] = 4.15; 95% confidence interval [CI] = 1.01-16.19; P = 0.040) and masses with associated architectural distortion (OR = 3.80; 95% CI = 1.57-9.19; P = 0.003) were independent predictors of axillary LN metastasis. Conclusion US features of breast cancer can be promising factors associated with axillary LN metastasis in patients with clinically node-negative early-stage breast cancer.

Nipple-Invasive Primary Carcinomas: Clinical, Imaging, and Pathologic Features of Breast Carcinomas Originating in the Nipple

Context Patients choosing to retain the nipple when undergoing therapeutic or prophylactic mastectomy are at risk for cancers arising at that site. Objective To identify cases of invasive carcinoma arising within the nipple and to investigate their clinical, imaging, biologic, and staging features. Design Carcinomas were identified by prospective review of surgical and consult cases at 4 hospitals. Results The 24 patients identified presented with symptoms related to the nipple. Mammography did not detect the cancer in most cases. Ten patients (42%) had skin changes from ductal carcinoma in situ involving nipple skin (Paget disease), with small foci of invasion into the dermis, and 6 of those 10 carcinomas (60%) stained positive for human epidermal growth factor receptor 2 (HER2). The remaining 14 patients (58%) presented with a nipple mass or with skin changes. These were larger invasive carcinomas of both ductal and lobular types. Only 2 of those 14 carcinomas (14%) were HER2⁺. Three of 15 patients (20%) undergoing lymph node biopsy had a single metastasis. No patients have had recurrent disease. Conclusions Rare, invasive, primary nipple carcinomas typically present as subtle nipple thickening or an exudative crust on the skin. Imaging studies are often nonrevealing. A variety of histologic and biologic types of carcinomas occur, similar to cancers arising deeper in the breast. Although the carcinomas invaded into the dermis, some with skin ulceration, the likelihood of lymph node metastasis was no higher than carcinomas of similar sizes. Patients who choose to preserve their nipple(s) should be aware of the possibility of breast cancer arising at that site and to bring any observed changes to the attention of their health care providers.

Eligibility of patients for minimally invasive breast cancer therapy based on MRI analysis of tumor proximity to skin and pectoral muscle

There is growing interest in minimally invasive breast cancer therapy. Eligibility of patients is, however, dependent on several factors related to the tumor and treatment technology. The aim of this study is to assess the proportion of patients eligible for minimally invasive breast cancer therapy for different safety and treatment margins based on breast tumor location. Patients with invasive ductal cancer were selected from the MARGINS cohort. Semiautomatic segmentation of tumor, skin, and pectoral muscle was performed in Magnetic Resonance images. Shortest distances of tumors to critical organs (ie, skin and pectoral muscle) were calculated. Proportions of eligible patients were determined for different safety and treatment margins. Three-hundred-forty-eight patients with 351 tumors were included. If a 10 mm safety margin to skin and pectoral muscle is required without treatment margin, 72.3% of patients would be eligible for minimally invasive treatment. This proportion decreases to 45.9% for an additional treatment margin of 5 mm. Shortest distances between tumors and critical organs are larger in older patients and in patients with less aggressive tumor subtypes. If a 10 mm safety margin to skin and pectoral muscle is required, more than two-thirds of patients would be eligible for minimally invasive breast cancer therapy.