Factors Associated With Node-Positive Disease in Estrogen Receptor-Positive Breast Cancer Patients

INTRODUCTION

Larger tumor size and shorter tumor-to-nipple distance at diagnosis are associated with greater risk of lymph node involvement in breast cancer. However, the relationship between receptor subtype status and lymph node metastasis remains unclear. Our objective was to examine the association between primary tumor size, location, and nodal metastasis across estrogen receptor (ER)+/ progesterone receptor (PR)+/ human epidermal growth factor receptor 2 (HER2)-, ER+/PR-/HER2-, ER+/PR+/HER2+, and ER+/PR-/HER2+ tumors.

METHODS

A single-institution retrospective chart review was conducted of breast cancer patients diagnosed between 1998 and 2019 who underwent nodal evaluation during primary surgery. Neoadjuvant chemotherapy, pure ductal carcinoma in situ, inflammatory, recurrent, metastatic, bilateral, multicentric, and multifocal disease were excluded. Descriptive statistics (proportions and frequencies for categorical variables and medians [Q1-Q3] for continuous variables) were used to summarize patient characteristics. Kruskal-Wallis test was applied to test the association of outcome variables and continuous variables. Chi-square test or Fisher exact test was applied to test the association of outcome variables and categorical variables.

RESULTS

Six hundred eighteen ER + patients had a median tumor size of 1.7 cm (1.1-2.5 cm). Two hundred ninety six out of 618 (47.9%) were node-positive and 188/618 (30.4%) had axillary dissection. Eighty four point three percent of patients were ER+/PR+/HER2-, 6.31% were ER+/PR-/HER2-, 6.96% were ER+/PR+/HER2+, and 1.13% were ER+/PR-/HER2+. Median tumor size was significantly larger in node-positive cases compared to node-negative cases in ER+/PR+/HER2-, ER+/PR+/HER2+, and ER+/PR-/HER2- subgroups. In ER+/PR+/HER2-patients, median tumor-nipple distance was significantly shorter in node-positive patients compared to node-negative patients. Upper outer quadrant location was significantly associated with nodal positivity in ER+/PR-/HER2- patients.

CONCLUSIONS

Across ER + patients, the significance between tumor size, location, and lymph node positivity varied significantly when differentiating by PR and HER2 status.

Whole-tumor histogram models based on quantitative maps from synthetic MRI for predicting axillary lymph node status in invasive ductal breast cancer

PURPOSE

To investigate the potential of using histogram analysis of synthetic MRI (SyMRI) images before and after contrast enhancement to predict axillary lymph node (ALN) status in patients with invasive ductal carcinoma (IDC).

METHODS

From January 2022 to October 2022, a total of 212 patients with IDC underwent breast MRI examination including SyMRI. Standard T2 weight images, DCE-MRI and quantitative maps of SyMRI were obtained. 13 features of the entire tumor were extracted from these quantitative maps, standard T2 weight images and DCE-MRI. Statistical analyses, including Student's t-test, Mann-Whiney U test, logistic regression, and receiver operating characteristic (ROC) curves, were used to evaluate the data. The mean values of SyMRI quantitative parameters derived from the conventional 2D region of interest (ROI) were also evaluated.

RESULTS

The combined model based on T1-Gd quantitative map (energy, minimum, and variance) and clinical features (age and multifocality) achieved the best diagnostic performance in the prediction of ALN between N0 (with non-metastatic ALN) and N+ group (metastatic ALN ≥ 1) with the AUC of 0.879. Among individual quantitative maps and standard sequence-derived models, the synthetic T1-Gd model showed the best performance for the prediction of ALN between N0 and N+ groups (AUC = 0.823). Synthetic T2_entropy and PD-Gd_energy were useful for distinguishing N1 group (metastatic ALN ≥ 1 and ≤ 3) from the N2-3 group (metastatic ALN > 3) with an AUC of 0.722.

CONCLUSIONS

Whole-tumor histogram features derived from quantitative parameters of SyMRI can serve as a complementary noninvasive method for preoperatively predicting ALN metastases.

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.

Ultrasound-based radiomics combined with immune status to predict sentinel lymph node metastasis in primary breast cancer

In the past few years, the axillary lymph node dissection technique has been steadily replaced by sentinel lymph node biopsy for treating and diagnosing breast cancer, thereby minimizing the complications and sequelae of the patients. Nevertheless, sentinel lymph node biopsy still presents limitations, such as high operation requirements, prolonged surgical duration, and adverse reactions to tracer agents. This study developed a novel non-invasive method to predict sentinel lymph node metastasis in breast cancer by analyzing the ultrasound imaging characteristics of the primary tumor, combined with the analysis of peripheral blood T-cell subsets that reflect the immune status of the body. The radiomic features analyzed in this study were extracted from preoperative ultrasound images of 199 solitary breast cancer patients, who were undergoing surgery and were pathologically diagnosed at the Yancheng First People's Hospital. All cases were randomly categorized in a 4:1 ratio to the training (n = 159) and validation (n = 40) cohorts. The extracted radiomics features were subjected to dimensional reduction with the help of the least absolute shrinkage and selection operator technique, resulting in the inclusion of 19 radiomics features. Four classifiers, including naïve Bayesian, logistic regression, classification decision tree, and support vector machine, were utilized to model the radiomics features, conventional ultrasound features, and peripheral blood T cell subsets in the training dataset, and validated using the validation dataset. The best-performing model was chosen for constructing the combined model. The radiomics model constructed using the logistic regression showed the best performance, with the training and validation cohorts showing areas under the curve (AUCs) of 0.77 and 0.68, respectively. The conventional ultrasound and peripheral blood T cell models constructed using the classification decision tree showed the best performance, wherein the training cohort presented AUCs of 0.71 and 0.81, respectively, while the validation cohort presented AUCs of 0.68 and 0.69, respectively. The combined model constructed by logistic regression showed AUCs of 0.91 and 0.79 in the training and validation datasets, respectively. The resulting combined model can be considered a simple, non-invasive method with strong reproducibility and clinical significance. Thus, it can be utilized to predict sentinel lymph node metastasis in breast cancer. Furthermore, the combined model can be effectively used to guide clinical decisions related to the selection of surgical procedures in breast surgery.

Tumor Characteristics Associated with Axillary Nodal Positivity in Triple Negative Breast Cancer

Larger-size primary tumors are correlated with axillary metastases and worse outcomes. We evaluated the relationships among tumor size, location, and distance to nipple relative to axillary node metastases in triple-negative breast cancer (TNBC) patients, as well as the predictive capacity of imaging. We conducted a single-institution, retrospective chart review of stage I-III TNBC patients diagnosed from 1998 to 2019 who underwent upfront surgery. Seventy-three patients had a mean tumor size of 20 mm (range 1-53 mm). All patients were clinically node negative. Thirty-two patients were sentinel lymph node positive, of whom 25 underwent axillary lymph node dissection. Larger tumor size was associated with positive nodes (p < 0.001): the mean tumor size was 14.30 mm in node negative patients and 27.31 mm in node positive patients. Tumor to nipple distance was shorter in node positive patients (51.0 mm) vs. node negative patients (73.3 mm) (p = 0.005). The presence of LVI was associated with nodal positivity (p < 0.001). Tumor quadrant was not associated with nodal metastasis. Ultrasound yielded the largest number of suspicious findings (21/49), with sensitivity of 0.25 and specificity of 0.40. On univariate analysis, age younger than 60 at diagnosis was also associated with nodal positivity (p < 0.002). Comparative analyses with other subtypes may identify biologic determinants.

Domain knowledge-guided adversarial adaptive fusion of hybrid breast ultrasound data

Contrast-enhanced ultrasound (CEUS), which provides more detailed microvascular information about the tumor, is always taken by radiologists in clinic diagnosis along with B-mode ultrasound (B-mode US). However, automatically analyzing breast CEUS is challenging due to the difference between the CEUS video and the natural video, e.g., sports or action videos, where the CEUS video has no positional displacements. Additionally, most existing methods rarely use the Time Intensity Curve (TIC) information of CEUS and non-imaging clinical (NIC) data. To address these issues, we propose a novel breast cancer diagnosis framework that learns the complementarity and correlation across hybrid modal data, including CEUS, B-mode US, and NIC data, by an adversarial adaptive fusion method. Furthermore, to fully exploit the CEUS information, the proposed method, inspired by the clinical processing of radiologists, first extracts the TIC parameters of CEUS. Then, we select a clip from CEUS using a frame screening strategy and finally get spatio-temporal features from these clips through a critical frame attention network. To our knowledge, this is the first AI system to use TIC parameters, NIC data, and ultrasound imaging in diagnoses. We have validated our method on a dataset collected from 554 patients. The experimental results demonstrate the excellent performance of the proposed method. The result shows that our method can achieve an accuracy of 87.73%, which is higher than that of uni-modal approaches by nearly 5%.

Basosquamous Cell Carcinoma of the Nipple-Areola Complex-Report of a Case

Basosquamous cell carcinoma (BSCC) is a rare malignancy usually arising on sun-exposed areas of the skin. BSCC is described as a rare variant of Basal cell carcinoma (BCC) which shows clinical and microscopic features of both BCC and of Squamous cell carcinoma (SCC). We report the case of a 70-year-old male with a cutaneous lesion of the nipple-areola complex (NAC); to the best of our knowledge, this is the first ever reported patient with BSCC in this area. The lesion had a fast growth, but, due to the COVID19 crisis, the patient only came to our observation one year after onset of this condition. Physical examination showed a bleeding red ulcerated lesion that involved the NAC, measuring 27 mm × 20 mm. Biopsy showed a BSCC. Pre-operative breast ultrasound scan, mammogram and MRI were all performed before surgery, which consisted of simple mastectomy and sentinel lymph-node biopsy. The patient was discharged home on the 4th post-operative day, and at 18-month follow-up there are no signs or clinical evidence of local recurrence or metastases. Diagnosis of BSCC of the nipple-areola complex requires high index of suspicion and a thorough differential diagnosis, management, and suitable radical treatment due to well described high rates of recurrence and of metastases. Differential diagnosis with similar lesions (e.g., Paget's disease, Bowen's disease, BCC, and SCC) should also be taken into account.

The Advantage of Using an Optical See-Through Head-Mounted Display in Ultrasonography-Guided Needle Biopsy Procedures: A Prospective Randomized Study

An optical see-through head-mounted display (OST-HMD) can potentially improve the safety and accuracy of ultrasonography (US)-guided fine-needle aspiration. We aimed to evaluate the usefulness of an OST-HMD in US-guided needle-puncture procedures. We conducted a prospective randomized controlled study in which we compared the accuracy and safety of the US-guided needle puncture procedure and the stress on the practitioner when using OST-HMD versus standard US display (SUD). Inexperienced medical students were enrolled and randomly divided into two groups. A breast phantom was used to evaluate the required time and accuracy of the US-guided needle puncture. Practitioner stress was quantified using a visual analog scale (VAS). When the procedure was performed for the first time, the time required to reach the target lesion at a shallow depth was significantly shorter in the OST-HMD group (39.8 ± 39.9 s) than in the SUD group (71.0 ± 81.0 s) (p = 0.01). Using the OST-HMD significantly reduced the unintentional puncture of a non-target lesion (p = 0.01). Furthermore, the stress felt by the practitioners when capturing the image of the target lesion (p < 0.001), inserting and advancing the needle more deeply (p < 0.001), and puncturing the target lesion (p < 0.001) was significantly reduced in the OST-HMD group compared with that in the SUD group. Use of OST-HMD may improve the accuracy and safety of US-guided needle puncture procedures and may reduce practitioner stress during the procedure.

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.

Real-world outcomes for Chinese breast cancer patients with tumor location of central and nipple portion

Background

The association between tumor location and breast cancer prognosis has been controversial. We sought to explore the relationship between tumors located in central and nipple portion (TCNP) and Chinese breast cancer.

Patients and methods

A total of 1,427 breast cancer patients were recruited. There were 328 cases of TCNP and 1,099 cases of tumors in the breast peripheral quadrant (TBPQ). The chi-square test was used to compare different variables between TCNP and TBPQ groups. A one-to-one propensity score matching (PSM) was applied to construct a matched sample consisting of pairs of TCNP and TBPQ groups. Kaplan–Meier curves were used for survival analysis of disease-free survival (DFS), breast cancer-specific survival (BCSS) and overall survival (OS). The Cox proportional hazards regression model was applied to identify prognostic risk factors.

Results

The median follow-up time was 58 months. Compared to TBPQ, TCNP patients had significantly larger tumor size, more frequent metastasis to lymph nodes (LN) and more proportions of TNM stage II–III. DFS, OS and BCSS rates were markedly lower in the TCNP group as compared to the TBPQ group before and after PSM (all p < 0.05). Multivariate Cox analysis showed that TCNP was an independent prognostic factor for breast cancer. Subgroup analysis indicated that for breast molecular subtypes and TNM stage II-III breast cancer, TCNP were related to worse prognosis. Multivariate logistic regression revealed that TCNP was an independent contributing factor for LN metastasis.

Conclusion

In Chinese breast cancer, compared to TBPQ, TCNP is associated with more LN metastasis and poorer prognosis.

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.

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.

Predictive Factors Among Clinicopathological Characteristics for Sentinel Lymph Node Metastasis in T1-T2 Breast Cancer

Background

The axillary lymph node status is an important prognostic factor of breast cancer. This study explores the predictive factors for sentinel lymph node (SLN) metastasis among the preoperative clinicopathological features, including impaired glucose tolerance (IGT).

Methods

This study comprised patients diagnosed with breast cancer who underwent surgery at Nagasaki Harbor Medical Center between April 2014 and December 2019. The factors assessed using univariate and multivariate analyses were the clinicopathological data of these cancers, including the patient age, gender, menstrual status, breast or ovarian cancer family history, body mass index, glycosylated hemoglobin, clinical tumor size, nipple-tumor distance (NTD), tumor histology, histological grade, node status, estrogen receptor, progesterone receptor, human epidermal growth factor receptor type 2 status, and Ki67 labeling index.

Results

In the cohort of 313 cases, the ratio of SLN metastasis was 17.3%. A univariate analysis found that the tumor size, NTD, IGT, and clinical tumor stage were associated with SLN metastasis. In a multivariable analysis, the tumor size, NTD, and IGT were associated with SLN metastasis. The receiver operating characteristic curve showed a sensitivity and specificity of 61.1% and 65.6%, respectively, at a cut-off of 1.7 cm for the tumor size (area under the curve [AUC]: 0.664; 95% confidence interval: 0.592–0.736), and a sensitivity and specificity of 60.4% and 62.9%, respectively, at a cut-off of 2.0 cm for NTD (AUC: 0.651; 95% confidence interval: 0.571–0.731) to predict the risk of SLN metastasis.

Conclusion

T1 and T2 breast cancer patients with a larger tumor size, tumor located closer to the nipple, and IGT have a higher risk of SLN metastases than others.

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.

Predictive performance of ultrasonography-based radiomics for axillary lymph node metastasis in the preoperative evaluation of breast cancer

PURPOSE

The purpose of this study was to evaluate the predictive performance of ultrasonography (US)-based radiomics for axillary lymph node metastasis and to compare it with that of a clinicopathologic model.

METHODS

A total of 496 patients (mean age, 52.5±10.9 years) who underwent breast cancer surgery between January 2014 and December 2014 were included in this study. Among them, 306 patients who underwent surgery between January 2014 and August 2014 were enrolled as a training cohort, and 190 patients who underwent surgery between September 2014 and December 2014 were enrolled as a validation cohort. To predict axillary lymph node metastasis in breast cancer, we developed a preoperative clinicopathologic model using multivariable logistic regression and constructed a radiomics model using 23 radiomic features selected via least absolute shrinkage and selection operator regression.

RESULTS

In the training cohort, the areas under the curve (AUC) were 0.760, 0.812, and 0.858 for the clinicopathologic, radiomics, and combined models, respectively. In the validation cohort, the AUCs were 0.708, 0.831, and 0.810, respectively. The combined model showed significantly better diagnostic performance than the clinicopathologic model.

CONCLUSION

A radiomics model based on the US features of primary breast cancers showed additional value when combined with a clinicopathologic model to predict axillary lymph node metastasis.

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.

Tumor location of the central and nipple portion is associated with impaired survival for women with breast cancer

Background

Tumor location in the breast varies, with the highest frequency in the upper outer quadrant and lowest frequency in the lower inner quadrant. Nevertheless, tumors in the central and nipple portion (TCNP) are poorly studied types of breast cancer; therefore, we aimed to clarify the clinicopathological characteristics and prognostic features of TCNP.

Methods

Using the Surveillance, Epidemiology, and End Results database, we identifed 105,037 patients diagnosed with tumor in the breast peripheral quadrant (TBPQ) (n=97,046) or TCNP (n=7,991). The chi-squared test was used to compare categorical variables across TCNP and TBPQ. Cox proportional hazard models with hazard ratios were applied to estimate the factors associated with prognosis.

Results

The median follow-up was over 43 months. Compared with TBPQ, TCNP patients were signifcantly older (age ≥66 years: 40.4% vs 34.1%, P<0.001), with larger tumor sizes (>20 mm size: 46.9% vs 37.3%, P<0.001), higher proportions of TNM stage II–III (18.6% vs 9.9%, P<0.001), and more mastectomies (58.1% vs 37.8%, P<0.001). The breast cancer-specifc survival (BCSS)/overall survival (OS) rate was signifcantly worse for TCNP than for TBPQ. Multivariate Cox analysis showed a higher hazard ratios for TCNP over TBPQ (BCSS: hazard ratios =1.160, P=0.005, 95% CI: 1.046–1.287; OS: hazard ratios =1.301, P<0.001, 95% CI: 1.211–1.398). A subgroup analysis revealed inferior outcomes for TCNP in TNM stage II–III and breast subtype subgroup. Multivariate logistic regression indicated that TCNP was an independent contributing factor to LN metastasis.

Conclusions

TCNP was associated with older age, larger tumor size, higher TNM stage, and lymph node metastasis. Compared with TBPQ, TCNP had adverse impacts on BCSS and OS.

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.

Distance of Tumor to Skin as a Predictive Marker for Axillary Lymph Node Metastasis in Cases of Breast Carcinoma - A Retrospective Study

Background: Breast cancer is arising as the most common cancer among women. Axillary lymph node status is considered as one of the most important predictors of survival in breast cancer and a very important component to the staging system. The tumors under the skin have abundant access to the dermal lymphatic and have an increased chance of metastasizing to draining lymph nodes. Aim of the Study: To evaluate whether distance of tumor to skin can be considered as a predictor for lymph node metastasis. Materials and Methods: This was a retrospective study on all operated cases of infiltrating mammary carcinoma from January 2013 to December 2016. Both lumpectomy and mastectomy specimens with invasive carcinoma component were included in the study. The distance of the tumor was measured from the base of the epidermis of the skin to the anterior margin of the tumor on gross examination or microscopically the closest invasive carcinoma component. The distance was measured, tabulated, and correlated with the nodal status on axillary node dissection. Also, compared are the other parameters such as size, site, and grade of the tumor. Results:: Out of 200 patients enrolled, positive nodes were seen in 67.5% (135) of cases, of which tumor with distance from skin <0.3 cm show maximum nodal positivity (64.4%) and maximum cases with N2 and N3 disease (48.8%). Most important and significant finding was that 100% cases with tumor size corresponding in T2 size with skin invasion either grossly or microscopically and T3 size tumor with microscopically involving epidermis was positive for metastatic deposits in axillary nodes and 10/11 cases (90%) in T4 stage were positive. Conclusion: The distance of tumor from skin is an important predictor for Axillary lymph nodal metastasis in invasive breast cancers. Closer the tumor, the incidence of axillary nodal metastasis increases. Hence, distance of tumor from skin should be considered while evaluating a breast cancer patient.

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.

Feasibility of spatial frequency-domain imaging for monitoring palpable breast lesions

In breast cancer diagnosis and therapy monitoring, there is a need for frequent, noninvasive disease progression evaluation. Breast tumors differ from healthy tissue in mechanical stiffness as well as optical properties, which allows optical methods to detect and monitor breast lesions noninvasively. Spatial frequency-domain imaging (SFDI) is a reflectance-based diffuse optical method that can yield two-dimensional images of absolute optical properties of tissue with an inexpensive and portable system, although depth penetration is limited. Since the absorption coefficient of breast tissue is relatively low and the tissue is quite flexible, there is an opportunity for compression of tissue to bring stiff, palpable breast lesions within the detection range of SFDI. Sixteen breast tissue-mimicking phantoms were fabricated containing stiffer, more highly absorbing tumor-mimicking inclusions of varying absorption contrast and depth. These phantoms were imaged with an SFDI system at five levels of compression. An increase in absorption contrast was observed with compression, and reliable detection of each inclusion was achieved when compression was sufficient to bring the inclusion center within ∼12  mm of the phantom surface. At highest compression level, contrasts achieved with this system were comparable to those measured with single source-detector near-infrared spectroscopy.

Primary tumor location predicts the site of local relapse after nipple-areola complex (NAC) sparing mastectomy

PURPOSE

To assess the oncological safety of nipple-areola complex (NAC) sparing mastectomy in breast cancer patients.

METHODS

From 2010 to 2015, 518 breast cancer patients were submitted to NAC sparing mastectomy. Breast MRI and intraoperative assessment of the subareolar (SD) and proximal (ND) nipple ducts were performed to predict NAC involvement. Significant associations between pre- and postoperative variables with SD/ND involvement and with the risk of local recurrence were retrospectively investigated.

RESULTS

SD/ND were involved in 26.1% of the cases. Final pathology of SD/ND was predicted by tumor-NAC distance at MRI and intraoperative pathology with 75 and 93% accuracy, respectively. NAC involvement was more frequent in case of positive ND than positive SD (68.3 vs. 38.3%; p = 0.003). Fourteen (2.7%) local relapses developed over a mean follow-up of 33 months. Ki-67 ≥25% (p = 0.002) and high tumor grade (p = 0.027) correlated with local recurrence. Most relapses developed in the subcutaneous tissue of the quadrant where the primary tumor was located (12/14; 85.7%). No local relapses occurred in patients who received post-mastectomy radiotherapy as compared to patients who did not, although they had a higher rate of positive surgical margins (40.5 vs. 16.2%; p = 0.000).

CONCLUSIONS

NAC involvement can be predicted by MRI and intraoperative pathology of ND/SD. Local recurrences after NAC sparing mastectomy almost invariably develop in the same quadrant where the primary tumor was located and in highly proliferative tumors.

Breast Cancer Detected at Screening US: Survival Rates and Clinical-Pathologic and Imaging Factors Associated with Recurrence

Purpose To determine the survival rates and clinical-pathologic and imaging factors associated with recurrence in women with breast cancer detected at screening ultrasonography (US). Materials and Methods This study was approved by the institutional review board, and the requirement to obtain informed consent was waived. A retrospective review of the databases of four institutions identified 501 women (median age, 47 years; range, 27-74 years) with breast cancer (425 invasive cancers and 76 ductal carcinoma in situ) detected at screening US between January 2004 and March 2011. Five-year overall survival (OS) and recurrence-free survival (RFS) rates were estimated, and the clinical-pathologic and imaging data were collected. Multivariate analysis was performed by using Cox proportional hazard regression to determine factors associated with recurrence. Results At a median follow-up of 7.0 years (range, 5.0-12.1 years), 15 (3.0%) recurrences were detected: five in ipsilateral breast and 10 in contralateral breast. The 5-year OS and RFS rates were 100% and 98.0% (95% confidence interval [CI]: 96.8%, 99.2%), respectively. In patients with invasive cancers, age younger than 40 years (hazard ratio: 3.632 [95% CI: 1.099, 11.998]; P = .032), the triple-negative subtype (hazard ratio: 7.498 [95% CI: 2.266, 24.816]; P = .001), and Breast Imaging Reporting and Data System (BI-RADS) category 4A lesions (hazard ratio: 5.113 [95% CI: 1.532, 17.195]; P = .008) were associated with recurrence. Conclusion Women with breast cancers detected at screening US have excellent outcomes, with a 5-year RFS rate of 98.0%. However, in patients with invasive breast cancer, age younger than 40 years, the triple-negative subtype, and BI-RADS category 4A lesions were associated with recurrence. ^© RSNA, 2017 Online supplemental material is available for this article.

[The role of nipple-sparing mastectomy in breast cancer: a comprehensive review of the literature]

BACKGROUND

The role of nipple-sparing mastectomy (NSM) for breast cancer is controversial as there is concern regarding its oncological safety and complication rate. We carried out a review of the literature to quantify the incidence of occult nipple malignancy in breast cancer, identify the factors influencing occult nipple malignancy, quantify locoregional recurrence rates and quantify NSM complication rates.

METHODS

A search of the literature was performed using PubMed. Keywords used were "mastectomy", "nipple involvement", "nipple-sparing mastectomy", "skin-sparing mastectomy" "occult nipple malignancy" "occult nipple disease" "breast cancer recurrence". Articles were analyzed regarding incidence of occult nipple malignancy, potential factors influencing the incidence of occult malignancy and recurrence/complications following NSM. The incidence of occult nipple disease was compared between groups using Chi(2) or Fisher's exact tests for categorical variables and Student's t-tests for continuous variables. P values were considered significant<0.05. We identified nearly 30 studies compiling nearly 10 000 cases examining the rate of occult nipple malignancy and 23 studies compiling 2300 cases providing information on the rate of local recurrence after NSM.

RESULTS

The overall rate of occult nipple malignancy was 11.5 %. Primary tumour characteristics influencing occult nipple malignancy were tumour-nipple distance<2cm, grade, lymph node metastasis, lymphovascular invasion, HER2 positive, ER/PR negative, tumour size>5cm, retro-areolar/central location and multicentric tumours. The overall nipple recurrence rate following NSM was 0.9 %, skin flap recurrence rate was 4.2 %. Full and partial thickness nipple necrosis rates were 2.9 % and 6.3 % respectively.

CONCLUSION

NSM for primary breast cancer is appropriate in carefully selected patients. All patients should have retro-areolar sampling. There is strong evidence to suggest that suitable cases are well circumscribed single or multifocal lesions that have a TND>2cm. Tumours should be graded 1-2 and not have LVI, axillary node metastasis or HER2 positivity.

Monte Carlo simulations shed light on Bathsheba's suspect breast

In 1654, Rembrandt van Rijn painted his famous painting Bathsheba at her Bath. Over the years, the depiction of Bathsheba's left breast and especially the presence of local discoloration, has generated debate on whether Rembrandt's Bathsheba suffered from breast cancer. Historical, medical and artistic arguments appeared to be not sufficient to prove if Bathsheba's model truly suffered from breast cancer. However, the bluish discoloration of the breast is an intriguing aspect from a biomedical optics point of view that might help us ending the old debate. By using Monte Carlo simulations in combination with the retinex theory of color vision, we showed that is highly unlikely that breast cancer results in a local bluish discoloration of the skin as is present on Bathsheba's breast.