Preoperative Axillary Ultrasound versus Sentinel Lymph Node Biopsy in Patients with Early Breast Cancer

Factors Predictive of Positive Lymph Nodes for Breast Cancer

BACKGROUND

Axillary node status is an important prognostic factor in breast cancer. The primary aim was to evaluate tumor size and other characteristics relative to axillary disease.

MATERIALS AND METHODS

Single institution retrospective chart review of stage I-III breast cancer patients collected demographic and clinical/pathologic data from 1998-2019. Student's t-test, Chi-squared test (or Fisher exact test if applicable), and logistic regression models were used for testing the association of pN+ to predictive variables.

RESULTS

Of 728 patients (mean age 59 yrs) with mean follow up of 50 months, 86% were estrogen receptor +, 10% Her2+, 78% ER+HER2-negative, and 10% triple-negative. In total, 351/728 (48.2%) were pN+ and mean tumor size was larger in pN+ cases compared to pN- cases (mean = 27.7 mm versus 15.5 mm) (p < 0.001). By univariate analysis, pN+ was associated with lymphovascular invasion (LVI), higher grade, Her2, and histology (p < 0.005). Tumor-to-nipple distance was shorter in pN+ compared to pN- (45 mm v. 62 mm; p< 0.001). Age < 60, LVI, recurrence, mastectomy, larger tumor size, and shorter tumor-nipple distance were associated with 3+ positive nodes (p < 0.05).

CONCLUSIONS

Larger tumor size and shorter tumor-nipple distance were associated with higher lymph node positivity. Age less than 60, LVI, recurrence, mastectomy, larger tumor size, and shorter tumor-nipple distance were all associated with 3+ positive lymph nodes.

Ultrasonography and clinicopathological features of breast cancer in predicting axillary lymph node metastases

Background

Early identification of axillary lymph node metastasis (ALNM) in breast cancer (BC) is still a clinical difficulty. There is still no good method to replace sentinel lymph node biopsy (SLNB). The purpose of our study was to develop and validate a nomogram to predict the probability of ALNM preoperatively based on ultrasonography (US) and clinicopathological features of primary tumors.

Methods

From September 2019 to April 2022, the preoperative US) and clinicopathological data of 1076 T1-T2 BC patients underwent surgical treatment were collected. Patients were divided into a training set (875 patients from September 2019 to October 2021) and a validation set (201 patients from November 2021 to April 2022). Patients were divided into positive and negative axillary lymph node (ALN) group according pathology of axillary surgery. Compared the US and clinicopathological features between the two groups. The risk factors for ALNM were determined using multivariate logistic regression analysis, and a nomogram was constructed. AUC and calibration were used to assess its performance.

Results

By univariate and multivariate logistic regression analysis, age (p = 0.009), histologic grades (p = 0.000), molecular subtypes (p = 0.000), tumor location (p = 0.000), maximum diameter (p = 0.000), spiculated margin (p = 0.000) and distance from the skin (p = 0.000) were independent risk factors of ALNM. Then a nomogram was developed. The model was good discriminating with an AUC of 0.705 and 0.745 for the training and validation set, respectively. And the calibration curves demonstrated high agreement. However, in further predicting a heavy nodal disease burden (> 2 nodes), none of the variables were significant.

Conclusion

This nomogram based on the US and clinicopathological data can predict the presence of ALNM good in T1-T2 BC patients. But it cannot effectively predict a heavy nodal disease burden (> 2 nodes).

A Convolutional Neural Network Based on Ultrasound Images of Primary Breast Masses: Prediction of Lymph-Node Metastasis in Collaboration With Classification of Benign and Malignant Tumors

Purpose: A convolutional neural network (CNN) can perform well in either of two independent tasks [classification and axillary lymph-node metastasis (ALNM) prediction] based on breast ultrasound (US) images. This study is aimed to investigate the feasibility of performing the two tasks simultaneously.

Methods: We developed a multi-task CNN model based on a self-built dataset containing 5911 breast US images from 2131 patients. A hierarchical loss (HL) function was designed to relate the two tasks. Sensitivity, specificity, accuracy, precision, F1-score, and analyses of receiver operating characteristic (ROC) curves and heatmaps were calculated. A radiomics model was built by the PyRadiomics package.

Results: The sensitivity, specificity and area under the ROC curve (AUC) of our CNN model for classification and ALNM tasks were 83.5%, 71.6%, 0.878 and 76.9%, 78.3%, 0.836, respectively. The inconsistency error of ALNM prediction corrected by HL function decreased from 7.5% to 4.2%. Predictive ability of the CNN model for ALNM burden (≥3 or ≥4) was 77.3%, 62.7%, and 0.752, and 66.6%, 76.8%, and 0.768, respectively, for sensitivity, specificity and AUC.

Conclusion: The proposed multi-task CNN model highlights its novelty in simultaneously distinguishing breast lesions and indicating nodal burden through US, which is valuable for “personalized” treatment.

The Role of US in Depicting Axillary Metastasis in High-Risk Breast Cancer Patients

Purpose: The aim of this study is to evaluate the role of US in depicting axillary nodal disease in high-risk patients with and without pathogenic mutations. Methods: The retrospective study included consecutive high-risk breast cancer (BC) patients who underwent a multigene testing panel for hereditary cancers, pre-operative axillary US and breast/axillary surgery. The group was divided into patients with pathogenic mutations (PM group) and patients without PM. Statistical analyses were performed using GraphPad Prism by applying Chi-square and Fisher exact tests, with a reference p-value < 0.05 and a CI of 95%. Results: Out of 190 patients with BC, 96 (51%) were negative and 94 (49%) were positive for PM as follows: 28 (25.5%) BRCA1, 16 (17%) BRCA2, 15 (16%) CHECK2, 14 (14%) RAD Group, 7 (7%) PALB, 6 (6%) NBN, 3 (3%) TP53 and ATM and 2 (2%) BARD1. US was positive in 88 of the patients, 36 with PM and 52 without PM. US and surgery (≥N1 stage) were both positive in 31 (62%) of PM patients and 44 (88%) of patients without genetic changes. There were 19 (61%) false negative US examinations in the PM group and 6 (13%) in the group without genetic changes, respectively. If the US is positive, there is a 2.6 times greater risk of positive nodes in PM patients (p-value < 0.000, 95% CI = 4.2–37.9), and a 6.2 times greater risk of positive nodes in patients without genetic changes (p-value < 0.000, 95%CI = 8.4–37.4). In the PM group, US compared to surgery reached a sensitivity = 62, with PPV = 86 and NPV = 67. In the BRCA1/2 subgroup, there is 2.5 greater times risk of nodal disease if the US is positive (p-value = 0.001, 95%CI = 2.6–76). In patients without PM, US compared to surgery reached a sensitivity = 88, PPV = 84 and NPV = 86. Conclusion: US is more sensitive in depicting axillary nodal disease in high-risk patients without PM compared to PM patients. Furthermore, there are more false negative US examinations in PM patients, compared to surgery patients.

Axillary lymph node status in BIRADS 4-5 female patients: can shear wave and strain ultrasound elastography help?

Background

The status of axillary nodes is a determining factor of management and prognosis for patients having a recent diagnosis of breast cancer. Axillary nodes are usually evaluated by ultrasonography (US) and biopsy, if indicated. Ultrasound-guided sampling and intraoperative or sentinel nodal sampling are available options, however, are invasive and hold risks of potential complications, calling for reliable, non-invasive axillary imaging. In the current prospective study, we assessed the performance of shear wave (SWE) and strain (SE) ultrasound elastography regarding preoperative axillary assessment. Sixty axillary nodes from 60 patients (age 28–65 years, mean 49.88 ± 7.61 SD) were included, all scoring BIRADS 4–5 on sonomammography.

Results

For US, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 100%, 66.67%, 84.78%, 100%, and 88.33%, respectively. Cortical thickness and vascularity were the most sensitive. For qualitative SWE, indices were 76.92%, 80.95%, 88.24%, 65.38% and 78.33%, respectively. Calculated cut-off for Emax was 59.3 and for Eratio was 4.56, giving statistical indices of 76.9%, 90.5%, 93.75%, 67.86%, and 81.67% for Emax and 76.9%, 100%, 100%, 70% and 85% respectively for Eratio. Both Emax and Eratio were greater for malignant (Emax 81.77 ± 1.904, Eratio 8.95 ± 5.69) than for benign nodes (Emax 37.59 ± 33.37, Eratio 2.5 ± 1.37) (P values < 0.001). For qualitative SE, sensitivity and specificity were 92.31% and 57.14%, while PPV, NPV, and accuracy were 80% each (P values < 0.001). The calculated cut-off value for SR was 3.85, giving indices of 87.2%, 76.2%, 76.19%, 87.18% and 83.33% respectively.

Conclusion

Adding elastography evaluation to conventional US positively impacts the specificity and accuracy of the preoperative axillary nodal status assessment in patients having newly diagnosed breast cancer.

Staging of the Axilla in Breast Cancer and the Evolving Role of Axillary Ultrasound

Axillary lymph nodes have long been recognized as a route for breast cancer to spread systemically. As a result, staging of the axilla has always played a central role in the treatment of breast cancer. Anatomic staging was believed to be important for two reasons: 1) it predicts prognosis and guides medical therapy, and 2) it is a potential therapy for removal of disease in the axilla. This paradigm has now been called into question. Prognostic information is driven increasingly by tumor biology, and trials such as the ACOSOG Z0011 demonstrates removal of axillary disease is not therapeutic. Staging of the axilla has undergone a dramatic de-escalation; however, sentinel lymph node biopsy (SLNB) is still an invasive surgery and represents a large economic burden on the healthcare system. In this review, we outline the changing paradigms of axillary staging in breast cancer from emphasis on anatomic staging to tumor biology, and the evolving role of axillary ultrasound, bringing patients less invasive and more personalized therapy.

Dopamine D1 Receptor in Cancer

Simple Summary

Circulating hormones and their specific receptors play a significant role in the development and progression of various cancers. This review aimed to summarize current knowledge about the dopamine D1 receptor’s biological role in different cancers, including breast cancer, central nervous system tumors, lymphoproliferative disorders, and other neoplasms. Treatment with dopamine D1 receptor agonists was proven to exert a major anti-cancer effect in many preclinical models. We highlight this receptor’s potential as a target for the adjunct therapy of tumors and discuss possibilities and necessities for further research in this area.

Abstract

Dopamine is a biologically active compound belonging to catecholamines. It plays its roles in the human body, acting both as a circulating hormone and neurotransmitter. It acts through G-protein-coupled receptors divided into two subgroups: D1-like receptors (D1R and D5R) and D2-like receptors (D2R, D3R, D4R). Physiologically, dopamine receptors are involved in central nervous system functions: motivation or cognition, and peripheral actions such as blood pressure and immune response modulation. Increasing evidence indicates that the dopamine D1 receptor may play a significant role in developing different human neoplasms. This receptor’s value was presented in the context of regulating various signaling pathways important in tumor development, including neoplastic cell proliferation, apoptosis, autophagy, migration, invasiveness, or the enrichment of cancer stem cells population. Recent studies proved that its activation by selective or non-selective agonists is associated with significant tumor growth suppression, metastases prevention, and tumor microvasculature maturation. It may also exert a synergistic anti-cancer effect when combined with tyrosine kinase inhibitors or temozolomide. This review provides a comprehensive insight into the heterogeneity of dopamine D1 receptor molecular roles and signaling pathways in human neoplasm development and discusses possible perspectives of its therapeutic targeting as an adjunct anti-cancer strategy of treatment. We highlight the priorities for further directions in this research area.