The efficacy of axillary ultrasound in the detection of nodal metastasis in breast cancer

ACR Appropriateness Criteria® Imaging of Invasive Breast Cancer

As the proportion of women diagnosed with invasive breast cancer increases, the role of imaging for staging and surveillance purposes should be determined based on evidence-based guidelines. It is important to understand the indications for extent of disease evaluation and staging, as unnecessary imaging can delay care and even result in adverse outcomes. In asymptomatic patients that received treatment for curative intent, there is no role for imaging to screen for distant recurrence. Routine surveillance with an annual 2-D mammogram and/or tomosynthesis is recommended to detect an in-breast recurrence or a new primary breast cancer in women with a history of breast cancer, and MRI is increasingly used as an additional screening tool in this population, especially in women with dense breasts. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Assessment of the axilla in women with early-stage breast cancer undergoing primary surgery: a review

Sentinel node biopsy (SNB) is routinely performed in people with node-negative early breast cancer to assess the axilla. SNB has no proven therapeutic benefit. Nodal status information obtained from SNB helps in prognostication and can influence adjuvant systemic and locoregional treatment choices. However, the redundancy of the nodal status information is becoming increasingly apparent. The accuracy of radiological assessment of the axilla, combined with the strong influence of tumour biology on systemic and locoregional therapy requirements, has prompted many to consider alternative options for SNB. SNB contributes significantly to decreased quality of life in early breast cancer patients. Substantial improvements in workflow and cost could accrue by removing SNB from early breast cancer treatment. We review the current viewpoints and ideas for alternative options for assessing and managing a clinically negative axilla in patients with early breast cancer (EBC). Omitting SNB in selected cases or replacing SNB with a non-invasive predictive model appear to be viable options based on current literature.

Axillary ultrasonography for early-stage invasive breast cancer

BACKGROUND

Among women with early invasive breast cancer and 1-2 positive sentinel nodes, sentinel lymph node biopsy (SLNB) is non-inferior to axillary lymph node dissection (ALND).1-3 However, preoperative axillary ultrasonography (AxUS) may not be sensitive enough to discriminate burden of nodal metastasis in these patients, potentially leading to overtreatment.4-6 This study compares axillary operation rates in patients who did and did not receive preoperative AxUS, assessing its utility and risks for overtreatment.

METHODS

This is a retrospective cohort study of patients with clinical T1/T2 breast tumors who were clinically node negative and underwent an axillary operation.

RESULTS

Patients who had preoperative AxUS received more ALND compared to patients who did not (5.6% vs. 1.4%, p ​< ​0.001). There was no significant difference in the number of additional axillary operations following SLNB (2.1% vs. 2.3%, p ​= ​0.77).

CONCLUSION

Eliminating preoperative AxUS is associated with fewer invasive ALND procedures, without increased rate of axillary reoperations.

Multimodal ultrasound imaging: a method to improve the accuracy of sentinel lymph node diagnosis in breast cancer

Aim

This study assessed the utility of multimodal ultrasound in enhancing the accuracy of breast cancer sentinel lymph node (SLN) assessment and compared it with single-modality ultrasound.

Methods

Preoperative examinations, including two-dimensional ultrasound (2D US), intradermal contrast-enhanced ultrasound (CEUS), intravenous CEUS, shear-wave elastography (SWE), and surface localization, were conducted on 86 SLNs from breast cancer patients. The diagnostic performance of single and multimodal approaches for detecting metastatic SLNs was compared to postoperative pathological results.

Results

Among the 86 SLNs, 29 were pathologically diagnosed as metastatic, and 57 as non-metastatic. Single-modality ultrasounds had AUC values of 0.826 (intradermal CEUS), 0.705 (intravenous CEUS), 0.678 (2D US), and 0.677 (SWE), respectively. Intradermal CEUS significantly outperformed the other methods (p<0.05), while the remaining three methods had no statistically significant differences (p>0.05). Multimodal ultrasound, combining intradermal CEUS, intravenous CEUS, 2D US, and SWE, achieved an AUC of 0.893, with 86.21% sensitivity and 84.21% specificity. The DeLong test confirmed that multimodal ultrasound was significantly better than the four single-modal ultrasound methods (p<0.05). Decision curve analysis and clinical impact curves demonstrated the superior performance of multimodal ultrasound in identifying high-risk SLN patients.

Conclusion

Multimodal ultrasound improves breast cancer SLN identification and diagnostic accuracy.

Noninvasive prediction of node-positive breast cancer response to presurgical neoadjuvant chemotherapy therapy based on machine learning of axillary lymph node ultrasound

OBJECTIVES

To explore an optimal model to predict the response of patients with axillary lymph node (ALN) positive breast cancer to neoadjuvant chemotherapy (NAC) with machine learning using clinical and ultrasound-based radiomic features.

METHODS

In this study, 1014 patients with ALN-positive breast cancer confirmed by histological examination and received preoperative NAC in the Affiliated Hospital of Qingdao University (QUH) and Qingdao Municipal Hospital (QMH) were included. Finally, 444 participants from QUH were divided into the training cohort (n = 310) and validation cohort (n = 134) based on the date of ultrasound examination. 81 participants from QMH were used to evaluate the external generalizability of our prediction models. A total of 1032 radiomic features of each ALN ultrasound image were extracted and used to establish the prediction models. The clinical model, radiomics model, and radiomics nomogram with clinical factors (RNWCF) were built. The performance of the models was assessed with respect to discrimination and clinical usefulness.

RESULTS

Although the radiomics model did not show better predictive efficacy than the clinical model, the RNWCF showed favorable predictive efficacy in the training cohort (AUC, 0.855; 95% CI 0.817-0.893), the validation cohort (AUC, 0.882; 95% CI 0.834-0.928), and the external test cohort (AUC, 0.858; 95% CI 0.782-0.921) compared with the clinical factor model and radiomics model.

CONCLUSIONS

The RNWCF, a noninvasive, preoperative prediction tool that incorporates a combination of clinical and radiomics features, showed favorable predictive efficacy for the response of node-positive breast cancer to NAC. Therefore, the RNWCF could serve as a potential noninvasive approach to assist personalized treatment strategies, guide ALN management, avoiding unnecessary ALND.

Predicting axillary nodal metastasis based on the side of asymmetrical cortical thickening in breast cancer: Evaluation with grayscale and microvascular imaging findings

PURPOSE

To investigate the relationship between sonographic findings and the axillary status, especially the side of thickening in the presence of cortical asymmetry.

METHODS

Patients with biopsy-proven axillary lymph node (ALN) metastasis were included in this study. The lymph nodes were divided into three groups depending on the type of cortical thickening as diffuse, closer (eccentric cortical thickening on the side near the tumor and/or breast) and distant (thickening on the further side) asymmetry. Longitudinal to transverse axis (L/T) ratio, the largest cortical thickness, cortex to hilum ratio (C/H), hilar status (normal/displaced/absent), orientation (parallel/vertical), capsular integrity (sharp/indistinct), vascularisation pattern (hilar/peripheral/penetrant/anarchic/avascular) on superb microvascular imaging (SMI) and presence of conglomeration were recorded for each lymph node. Axillary nodal status on ¹⁸F-FDG PET-CT/MRI scans was recorded, if available. Features of the breast lesions like size, laterality, nuclear grade, hormone receptor status and the level of Ki-67 expression have been added.

RESULTS

A total of 219 metastatic ALNs [diffuse (n = 122), closer asymmetry (n = 71), distant asymmetry (n = 26)] were evaluated. By the univariate analysis, ALN metastasis was significantly associated with the presence of closer asymmetrical cortical thickening (p < 0,0001), C/H ratio (p = 0.001), cortical thickness (p = 0.001), hilar status (p < 0.005) and vascular pattern (p < 0.005). L/T ratio was only a statistically significant parameter for lymph nodes with diffuse cortical enlargement in predicting metastasis, and conglomeration was also observed only in this group (p < 0.05). By multivariate analysis, nodal metastasis was significantly associated with asymmetrical cortical thickening (p = 0.001), C/H ratio (p = 0.005) and vascular pattern (p < 0.0001).

CONCLUSION

Asymmetrical cortical enlargement on the side closer to the breast, C/H ratio and abnormal microvascular pattern are the independent predictors of axillary nodal involvement. Closer asymmetry is an eligible, easy-to-detect grayscale US finding to decide sampling that highly predicts ALN metastasis.

Predicting the risk of axillary lymph node metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features and the use of nomograms: a prospective single-center observational study

OBJECTIVES

The purpose of this study was to establish two preoperative nomograms to evaluate the risk for axillary lymph node (ALN) metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features.

METHODS

We prospectively evaluated 593 consecutive female participants who were diagnosed with cT_1-3N_0-1M₀ breast cancer between March 2018 and May 2019 at Sun Yat-Sen Memorial Hospital. The participants were randomly classified into training and validation sets in a 4:1 ratio for the development and validation of the nomograms, respectively. Multivariate logistic regression analysis was performed to identify independent predictors of ALN status. We developed Nomogram A and Nomogram B to predict ALN metastasis (presence vs. absence) and the number of metastatic ALNs (≤ 2 vs. > 2), respectively.

RESULTS

A total of 528 participants were evaluated in the final analyses. Multivariable analysis revealed that the number of suspicious lymph nodes, long axis, short-to-long axis ratio, cortical thickness, tumor location, and histological grade were independent predictors of ALN status. The AUCs of nomogram A in the training and validation groups were 0.83 and 0.78, respectively. The AUCs of nomogram B in the training and validation groups were 0.87 and 0.87, respectively. Both nomograms were well-calibrated.

CONCLUSION

We developed two preoperative nomograms that can be used to predict ALN metastasis (presence vs. absence) and the number of metastatic ALNs (≤ 2 vs. > 2) in early breast cancer patients. Both nomograms are useful tools that will help clinicians predict the risk of ALN metastasis and facilitate therapy decision-making about axillary surgery.

KEY POINTS

• We developed two preoperative nomograms to predict axillary lymph node status based on ultrasonographic-clinicopathologic features. • Nomogram A was used to predict axillary lymph node metastasis (presence vs. absence). The AUCs in the training and validation groups were 0.83 and 0.78, respectively. Nomogram B was used to estimate the number of metastatic lymph nodes ( ≤ 2 vs. > 2). The AUCs in the training and validation group were 0.87 and 0.87, respectively. • Our nomograms may help clinicians weigh the risks and benefits of axillary surgery more appropriately.

ACR Appropriateness Criteria® Imaging of the Axilla

This publication reviews the current evidence supporting the imaging approach of the axilla in various scenarios with broad differential diagnosis ranging from inflammatory to malignant etiologies. Controversies on the management of axillary adenopathy results in disagreement on the appropriate axillary imaging tests. Ultrasound is often the appropriate initial imaging test in several clinical scenarios. Clinical information (such as age, physical examinations, risk factors) and concurrent complete breast evaluation with mammogram, tomosynthesis, or MRI impact the type of initial imaging test for the axilla. Several impactful clinical trials demonstrated that selected patient's population can received sentinel lymph node biopsy instead of axillary lymph node dissection with similar overall survival, and axillary lymph node dissection is a safe alternative as the nodal staging procedure for clinically node negative patients or even for some node positive patients with limited nodal tumor burden. This approach is not universally accepted, which adversely affect the type of imaging tests considered appropriate for axilla. This document is focused on the initial imaging of the axilla in various scenarios, with the understanding that concurrent or subsequent additional tests may also be performed for the breast. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

The NILS Study Protocol: A Retrospective Validation Study of an Artificial Neural Network Based Preoperative Decision-Making Tool for Noninvasive Lymph Node Staging in Women with Primary Breast Cancer (ISRCTN14341750)

Newly diagnosed breast cancer (BC) patients with clinical T1–T2 N0 disease undergo sentinel-lymph-node (SLN) biopsy, although most of them have a benign SLN. The pilot noninvasive lymph node staging (NILS) artificial neural network (ANN) model to predict nodal status was published in 2019, showing the potential to identify patients with a low risk of SLN metastasis. The aim of this study is to assess the performance measures of the model after a web-based implementation for the prediction of a healthy SLN in clinically N0 BC patients. This retrospective study was designed to validate the NILS prediction model for SLN status using preoperatively available clinicopathological and radiological data. The model results in an estimated probability of a healthy SLN for each study participant. Our primary endpoint is to report on the performance of the NILS prediction model to distinguish between healthy and metastatic SLNs (N0 vs. N+) and compare the observed and predicted event rates of benign SLNs. After validation, the prediction model may assist medical professionals and BC patients in shared decision making on omitting SLN biopsies in patients predicted to be node-negative by the NILS model. This study was prospectively registered in the ISRCTN registry (identification number: 14341750).

Development of High-Resolution Dedicated PET-Based Radiomics Machine Learning Model to Predict Axillary Lymph Node Status in Early-Stage Breast Cancer

Simple Summary

Accurate clinical axillary evaluation plays an important role in the diagnosis of and treatment planning for breast cancer (BC). This study aimed to develop a machine learning model integrating dedicated breast PET and clinical characteristics for prediction of axillary lymph node status in cT1-2N0-1M0 BC non-invasively. The performance of this integrating model in identifying pN0 and pN1 with the AUC was 0.94. We achieved an NPV of 96.88% in the cN0 and PPV of 92.73% in the cN1 subgroup. The higher true positive and true negative rate could delineate clinical subtypes and apply more precise treatment for patients with early-stage BC.

Abstract

Purpose of the Report: Accurate clinical axillary evaluation plays an important role in the diagnosis and treatment planning for early-stage breast cancer (BC). This study aimed to develop a scalable, non-invasive and robust machine learning model for predicting of the pathological node status using dedicated-PET integrating the clinical characteristics in early-stage BC. Materials and Methods: A total of 420 BC patients confirmed by postoperative pathology were retrospectively analyzed. 18F-fluorodeoxyglucose (¹⁸F-FDG) Mammi-PET, ultrasound, physical examination, Lymph-PET, and clinical characteristics were analyzed. The least absolute shrinkage and selection operator (LASSO) regression analysis were used in developing prediction models. The characteristic curve (ROC) of the area under receiver-operator (AUC) and DeLong test were used to evaluate and compare the performance of the models. The clinical utility of the models was determined via decision curve analysis (DCA). Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and was validated using the calibration plots. Results: A total of 290 patients were enrolled in this study. The AUC of the integrated model diagnosed performance was 0.94 (95% confidence interval (CI), 0.91–0.97) in the training set (n = 203) and 0.93 (95% CI, 0.88–0.99) in the validation set (n = 87) (both p < 0.05). In clinical N0 subgroup, the negative predictive value reached 96.88%, and in clinical N1 subgroup, the positive predictive value reached 92.73%. Conclusions: The use of a machine learning integrated model can greatly improve the true positive and true negative rate of identifying clinical axillary lymph node status in early-stage BC.

Diagnostic performance of a novel high-resolution dedicated axillary PET system in the assessment of regional nodal spread of disease in early breast cancer

Background

In early breast cancer, a non-invasive method with higher sensitivity and negative predictive value (NPV) is needed to identify and recognize more indolent axillary lymph nodes (ALNs). This study aimed to assess whether a novel high-resolution dedicated ALN positron emission tomography (LymphPET) system could improve sensitivity in detecting early breast cancer (clinical N0-N1 stage).

Methods

A total of 103 patients with clinical stage T1-2N0-1M0 breast cancer were evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) LymphPET. The maximum single-voxel PET uptake value of ALNs (maxLUV) and the tumor-to-background ratio (TBR) for fat (TBR1) and muscle (TBR2) tissue were calculated. Then, 78 patients with cN0 stage breast cancer received sentinel lymph node biopsy alone or combined with axillary lymph node dissection (ALND), and 25 patients with cN1 stage breast cancer underwent fine-needle aspiration.

Results

A total of 99 invasive breast carcinoma cases were included in this study. The diagnostic sensitivity of LymphPET was 88%, specificity was 79%, false-negative rate was 12%, the false-positive rate was 21%, positive predictive value was 75%, NPV was 90%, and accuracy was 83%. The maxLUV was superior to TBR1 and TBR2 in detecting ALNs, with 0.27 being the most optimal cutoff value.

Conclusions

The ¹⁸F-FDG LymphPET system can be used to identify and recognize more indolent ALNs of breast cancer due to greater sensitivity and a much higher NPV.

Comparison of lymphatic contrast-enhanced ultrasound and intravenous contrast-enhanced ultrasound in the preoperative diagnosis of axillary sentinel lymph node metastasis in patients with breast cancer

OBJECTIVES

This study aimed to compare diagnostic efficiency for axillary sentinel lymph node (SLN) metastasis between lymphatic contrast-enhanced ultrasound (LCEUS) and intravenous contrast-enhanced ultrasound (ICEUS) in patients with breast cancer. We also examined whether adding ICEUS to LCEUS could improve the diagnostic accuracy of LCEUS.

METHODS

Sixty-nine patients with breast cancer were recruited preoperatively. All patients underwent LCEUS followed by ICEUS, and the enhancement pattern of one SLN was analysed for each patient. The targeted SLN was marked with wire and excised during surgery. The imaging diagnosis was compared with the histopathological result. Diagnostic efficiency was compared among LCEUS, ICEUS, and the combination of LCEUS and ICEUS.

RESULTS

The sensitivity values for LCEUS, ICEUS, and the combination of LCEUS and ICEUS were 86.2%, 82.6% and 93.1%, respectively. Specificity values for the three methods were 95.0%, 92.5% and 87.5%, respectively. Accuracy values for the three methods were 91.3%, 88.4% and 89.9%, respectively. The area under the receiver operating characteristic (ROC) curve for LCEUS was 0.906, and there was no significant difference among LCEUS, ICEUS, and the combination of LCEUS and ICEUS (p = 0.752).

CONCLUSIONS

LCEUS may represent an accurate method for predicting SLN metastasis preoperatively. Our findings suggest that adding ICEUS to LCEUS for SLN evaluation in patients with breast cancer is unnecessary.

ADVANCES IN KNOWLEDGE

This is the first study in which both LCEUS and ICEUS were performed for the same lymph node and the first to compare the diagnostic efficiency of LCEUS, ICEUS, and the combination of LCEUS + ICEUS.

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.

Prospective comparison of CT and 18F-FDG PET/MRI in N and M staging of primary breast cancer patients: Initial results

Objectives

To compare the diagnostic accuracy of contrast-enhanced thoraco-abdominal computed tomography and whole-body ¹⁸F-FDG PET/MRI in N and M staging in newly diagnosed, histopathological proven breast cancer.

Material and methods

A total of 80 consecutive women with newly diagnosed and histopathologically confirmed breast cancer were enrolled in this prospective study. Following inclusion criteria had to be fulfilled: (1) newly diagnosed, treatment-naive T2-tumor or higher T-stage or (2) newly diagnosed, treatment-naive triple-negative tumor of every size or (3) newly diagnosed, treatment-naive tumor with molecular high risk (T1c, Ki67 >14%, HER2neu over-expression, G3). All patients underwent a thoraco-abdominal ceCT and a whole-body ¹⁸F-FDG PET/MRI. All datasets were evaluated by two experienced radiologists in hybrid imaging regarding suspect lesion count, localization, categorization and diagnostic confidence. Images were interpreted in random order with a reading gap of at least 4 weeks to avoid recognition bias. Histopathological results as well as follow-up imaging served as reference standard. Differences in staging accuracy were assessed using Mc Nemars chi² test.

Results

CT rated the N stage correctly in 64 of 80 (80%, 95% CI:70.0–87.3) patients with a sensitivity of 61.5% (CI:45.9–75.1), a specificity of 97.6% (CI:87.4–99.6), a PPV of 96% (CI:80.5–99.3), and a NPV of 72.7% (CI:59.8–82.7). Compared to this, ¹⁸F-FDG PET/MRI determined the N stage correctly in 71 of 80 (88.75%, CI:80.0–94.0) patients with a sensitivity of 82.1% (CI:67.3–91.0), a specificity of 95.1% (CI:83.9–98.7), a PPV of 94.1% (CI:80.9–98.4) and a NPV of 84.8% (CI:71.8–92.4). Differences in sensitivities were statistically significant (difference 20.6%, CI:-0.02–40.9; p = 0.008). Distant metastases were present in 7/80 patients (8.75%). ¹⁸ F-FDG PET/MRI detected all of the histopathological proven metastases without any false-positive findings, while 3 patients with bone metastases were missed in CT (sensitivity 57.1%, specificity 95.9%). Additionally, CT presented false-positive findings in 3 patients.

Conclusion

¹⁸F-FDG PET/MRI has a high diagnostic potential and outperforms CT in assessing the N and M stage in patients with primary breast cancer.

Factors predicting one or two sentinel lymph nodes to be accepted for sentinel lymph node biopsy alone after neoadjuvant therapy in initially node-positive breast cancer patients

BACKGROUND

Current guidelines recommend harvesting ≥3 sentinel nodes if sentinel lymph node biopsy (SLNB) alone is considered after neoadjuvant therapy (NAT) for initially node-positive (cN+) breast cancer. We attempted to investigate factors predicting one or two sentinel lymph nodes harvested to be accepted for SLNB alone after NAT in initially cN + patients.

METHODS

Overall, 157 patients who received NAT (clinically T1-3/N1-2/M0) and underwent SLNB were identified from a prospectively maintained database. Significant factors were identified using a multiple logistic regression model.

RESULTS

The overall SLN identification rate was 83.4%. Failed SLN identification was associated with a 2-day protocol using a single tracer (odds ratio: 0.331 [95% confidence interval {CI}: 0.132-0.830], p = 0.018), age >52 years (0.345 [0.131-0.913], p = 0.032), and lobular histology (0.156 [0.026-0.944], p = 0.043). The overall false-negative SLNB rate was 14.7%. Its increased risk was associated with radioactivity count >530 for any SLN during SLNB (96.4 [4.00-2320], p = 0.005), age ≥57 years (34.2 [1.92-610], p = 0.016), and taxane use (105 [1.02-10700], p = 0.049); its decreased risk was associated with more harvested SLNs (0.191 [0.054-0.669], p = 0.01) and dual tracers (0.101 [0.012-0.843], p = 0.034). A predictive model using these factors achieved an area under the curve of 0.935 (95% CI: 0.878-0.991).

CONCLUSION

When taxane was administered during NAT, the false-negative rate was predicted at <5% for patients aged <57 years, if 1-2 SLNs were harvested using dual tracers, and when the count of every SLN was lower than 530 after NAT in cN + breast cancer.

Axillary ultrasound and fine-needle aspiration cytology to predict clinically relevant nodal burden in breast cancer patients

Background

Axillary lymph node involvement is one important prognostic factor in breast cancer, but the way to access this information has been modified over the years. This study evaluated if axillary ultrasound (US) coupled with fine-needle aspiration cytology (FNAC) can accurately predict clinically relevant node metastasis in patients with breast cancer, and thus assist clinical decisions

Methods

This is a cross-sectional study with retrospective data collection of 241 individuals (239 women and 2 men) with unilateral operable breast cancer who were submitted to preoperative axillary assessment by physical exam, US and FNAC if suspicious nodes by imaging. We calculated sensitivity, specificity, and accuracy of the methods. We compared the patient's characteristics using chi-square test, parametrics and non-parametrics statistics according to the variable.

Results

The most sensible method was US (0.59; 95% CI, 0.50–0.69), and the most specific was US coupled with FNAC (0.97; 95% CI, 0.92–0.99). Only 2.7% of the patients with normal axillary US had more than 2 metastatic nodes in the axillary lymph node dissection, against 50% of the patients with suspicious lymph nodes in the US and positive FNAC.

Conclusions

Axillary US coupled with FNAC can sort patients who have a few metastatic nodes at most from those with heavy axillary burden and could be one more tool to initially evaluate patients and define treatment strategies.

Is image-guided core needle biopsy of borderline axillary lymph nodes in breast cancer patients clinically helpful?

BACKGROUND

When borderline axillary lymph nodes (bALN) are identified on ultrasound (US) for breast cancer (BC) patients, preoperative management is unclear. We aimed to evaluate if core needle biopsy (CNB) for bALN is clinically helpful or disruptive.

METHODS

Retrospective review of BC patients with bALN from 2014 to 2019 was performed. Clinicopathologic data were compared for those who did and did not have CNB.

RESULTS

CNB (n = 34) and no CNB (n = 31) were similar with respect to clinicopathologic factors. Surgical LN-positive rate was the same between cohorts (p = 0.26). CNB was disruptive in 58.8 %; all had CNB for pN0 disease. CNB was helpful in 34.2 %: 14.7 % proceeded directly to axillary dissection; 17.6 % had positive LN localized after neoadjuvant chemotherapy.

CONCLUSIONS

CNB for bALN is more likely clinically disruptive and did not impact surgical LN positive rate. BC patients with bALN should undergo CNB only if it will change clinical management.

A new nomogram for predicting the malignant diagnosis of Breast Imaging Reporting and Data System (BI-RADS) ultrasonography category 4A lesions in women with dense breast tissue in the diagnostic setting

Background

Biopsy has been recommended for Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions. However, the malignancy rate of category 4A lesions is very low (2-10%). Therefore, most biopsies of category 4A lesions are benign, and the results will generally cause additional health care costs and patient anxiety.

Methods

A prediction model was developed based on an analysis of 418 BI-RADS ultrasonography (US) category 4A patients at Sun Yat-sen Memorial Hospital. Univariate and multivariate logistic regression analyses were applied to identify significant variables for inclusion in the final nomogram. The predictive accuracy and discriminative ability were evaluated using the concordance index (C-index) and calibration curves. An independent cohort of 97 patients from the Second Affiliated Hospital of Guangzhou Medical University was used for external validation.

Results

The independent risk factors from the multivariate analysis for the training cohort were family history of breast cancer (OR =4.588, P=0.004), US features [margin (OR =2.916, P=0.019), shape (irregular vs. oval, OR =2.474, P=0.044; round vs. oval, OR =1.935, P=0.276), parallel orientation vs. not parallel (OR =2.204, P=0.040)], low suspicious lymph nodes (OR =7.664, P=0.019), and suspicious calcifications on mammography (MG) (OR =6.736, P=0.001). The C-index was good in the training [0.813, 95% confidence interval (95% CI), 0.733 to 0.893] and validation cohorts (0.765, 95% CI, 0.584 to 0.946). The calibration curves showed optimal agreement between the nomogram prediction and actual observations for the probability of malignancy. Also, the cutoff score was set to 100 for discriminating high and low risk. The model performed well in discerning different risk groups.

Conclusions

We developed a well-discriminated and calibrated nomogram to predict the malignancy of BI-RADS US category 4A lesions in dense breast tissue, which may help clinicians identify patients at lower or higher risk.

Is pre-operative axillary ultrasound alone sufficient to determine need for axillary dissection in early breast cancer patients?

Pre-operative status of axillary lymph node (ALN) in early breast cancer is usually initially assessed by pre-operative ultrasound, followed by ultrasound-guided needle biopsy (UNB) confirmation. Patients with positive nodal status will undergo axillary lymph node dissection (ALND), while those with negative nodal status will have sentinel lymph node biopsy. ALND is associated with higher morbidity than Sentinel lymph node biopsy. The objective of this study is to determine if axillary ultrasound alone without UNB is predictive enough to assign patients to ALND and to identify ultrasound features that are significantly associated with pathologically positive ALN.383 newly diagnosed primary breast cancer patients between 2012 and 2014, and who had undergone pre-operative axillary ultrasound in University Malaya Medical Centre with a complete histopathology report of the axillary surgery were retrospectively reviewed. ALN was considered positive if it had any of these features: cortical thickening > 3 mm, loss of fatty hilum, hypoechoic solid node, mass-like appearance, round shape and lymph node size > 5 mm. Post-operative histopathological reports were then analyzed for nodal involvement.The overall sensitivity, specificity, and accuracy of pre-operative axillary ultrasound in detecting diseased nodes were 45.5%, 80.7%, and 60.3% respectively. The positive (PPV) and negative predictive values were 76.5% and 51.8%. Round shape, loss of fatty hilum and mass-like appearance had the highest PPVs of 87%, 83% and 81.6% respectively and significant odds ratios (ORs) of 5.22 (95% confidence interval [CI]: 1.52 - 17.86), ORs of 4.77 (95% CI: 2.62 - 8.70) and ORs of 4.26 (95% CI: 2.37 - 7.67) respectively (P-value < .05). Cortical thickness of > 3 mm was identified to have low PPV at 69.1%, ORs of 1.71 (95% CI: 0.86 - 3.41, P = .126).There are features on axillary ultrasound that confer high PPV for axillary involvement i.e. round shape, loss of fatty hilum, and mass-like appearance. In a low resource setting, these features may benefit from ALND without further pre-operative biopsies. However, pre-operative UNB for features with low PPV that is, cortical thickness > 3 mm should be considered to obviate the unnecessary morbidity associated with ALND.

Evaluation of Axillary Lymph Nodes in Breast Cancer Patients with Atopic Dermatitis

This study assessed the diagnostic accuracy of ultrasound in detecting axillary lymph node metastases in women with breast cancer and atopic dermatitis. We retrospectively reviewed the records of 91 breast cancer patients with a history of atopic dermatitis and compared the dimensions of the lymph nodes on ultrasonographic images of women with and without lymph node metastases diagnosed using histology. Using a major-axis length of ≥5 mm, a short-axis length of ≥5 mm and a cortical thickness of ≥2.3 mm as the criteria for diagnosing axillary lymph node metastases, the specificity was 12.7%, 41.3% and 58.7%, respectively. The low specificity of the ultrasound criteria makes ultrasound unsuitable for diagnosing axillary lymph nodes metastases in breast cancer patients with atopic dermatitis.

Sentinel lymph node biopsy with one-step nucleic acid assay relegates the need for preoperative ultrasound-guided biopsy staging of the axilla in patients with early stage breast cancer

Avoiding axillary node clearance in patients with early stage breast cancer and low-burden node-positive axillary disease is an emerging practice. Informing the decision to adopt axillary conservation is examined by comparing routine preoperative axillary staging using ultrasound (AUS) ± AUS biopsy (AUSB) with intraoperative staging using sentinel lymph node biopsy (SLNB) and a one-step nucleic acid cytokeratin-19 amplification assay (OSNA). A single-centre, retrospective cohort study of 1,315 consecutive new diagnoses of breast cancer in 1,306 patients was undertaken in the present study. An AUS ± AUSB was performed on all patients as part of their initial assessment. Patients who had a normal ultrasound (AUS-) or negative biopsy (AUSB-) followed by SLNB with OSNA ± axillary lymph node dissection (ALND), and those with a positive AUSB (AUSB+), were assessed. Tests for association were determined using a χ² and Fisher's Exact test. A total of 266 (20.4%) patients with cT1-3 cN0 staging received 271 AUSBs. Of these, 205 biopsies were positive and 66 were negative. The 684 patients with an AUS-/AUSB-assessment proceeded to SLNB with OSNA. AUS sensitivity and negative predictive value (NPV) were 0.53 [0.44-0.62; 95% confidence interval (CI)] and 0.58 (0.53-0.64, 95% CI), respectively. Using a total tumour load cut-off of 15,000 copies/µl to predict ≥2 macro-metastases, the sensitivity and NPV for OSNA were 0.82 (0.71-0.92, 95% CI) and 0.98 (0.97-0.99, 95% CI) (OSNA vs. AUS P<0.0001). Of the AUSB+ patients, 51% had ≤2 positive nodes following ALND and were potentially over-treated. Where available, SLNB with OSNA should replace AUSB for axillary assessment in cT1-2 cN0 patients with ≤2 indeterminate nodes seen on AUS.

Adding contrast-enhanced ultrasound markers to conventional axillary ultrasound improves specificity for predicting axillary lymph node metastasis in patients with breast cancer

OBJECTIVE

To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) combined with conventional ultrasound of axillary lymph nodes (ALNs) in predicting metastatic ALNs in patients with breast cancer.

METHODS

This retrospective study included 259 patients with breast cancer who underwent conventional ultrasound and CEUS. The parameters and patterns evaluated on conventional ultrasound included short axis diameter (S), long axis/short axis (L/S) ratio, cortical thickness, resistive index (RI), lymph node (LN) morphology of greyscale ultrasound, hilum and vascular pattern. Meanwhile, enhancement pattern, wash-in time, time to peak (TP), maximum signal intensity, and duration of contrast enhancement were evaluated on CEUS. Univariate and multiple logistic regression analyses were performed to identify independent factors of ALN status. Three models (conventional ultrasound, CEUS, and combined parameters) were established. Receiver operating characteristic (ROC) curves were applied to evaluate the accuracy of the three predictive models.

RESULTS

On conventional axillary ultrasound, LN morphology and vascular pattern were independent factors in predicting metastatic ALNs. On CEUS, maximum signal intensity, duration of contrast enhancement, and TP were independent factors in predicting metastatic ALNs. When combining conventional ultrasound and CEUS features, five independent factors obtained from the conventional ultrasound and CEUS were associated with ALN status. ROC curve analysis showed that the use of CEUS markers combined with conventional ultrasound features (AUC = 0.965) was superior to the use of CEUS markers (AUC = 0.936) and conventional ultrasound features alone (AUC = 0.851).

CONCLUSION

Combining conventional ultrasound and CEUS features can enable discrimination of ALN status better than the use of CEUS and conventional ultrasound features alone.

ADVANCES IN KNOWLEDGE

The axillary lymph node status in breast cancer patients impacts the treatment decision. Our ultrasonic data demonstrated that CEUS features of ALNs in breast cancer patients could be image markers for predicting ALN status. Combining conventional ultrasound and CEUS features of ALNs can improve specificity discrimination of ALN status better than the use of CEUS and the conventional ultrasound features alone, which will help the treatment planning optimization.

Diagnostic accuracy of axillary staging by ultrasound in early breast cancer patients

BACKGROUND

Axillary ultrasound (AUS) is a standard procedure in the preoperative clinical identification of axillary metastatic lymph node (LN) involvement. It guides decisions about local and systemic therapy for patients with early breast cancer (EBC). But there is only weak evidence on the diagnostic criteria and standard interpretation. The aim of this study was to assess the performance of AUS in the detection and exclusion of LN metastases.

METHODS

In a retrospective single-center study, 611 consecutive EBC patients with 622 axillae underwent AUS +/- core needle biopsy (CNB) plus axillary surgery, i.e. sentinel lymph node biopsy and/or axillary lymph node dissection. For all patients, AUS image documentation of at least the most suspicious LN was saved during the initial diagnostic work-up. The diagnostic outcome measures were sensitivity, specificity, accuracy, Youden-index (YI), and diagnostic odds ratio (DOR) on the basis of the daily routine interpretation and on the basis of previously recommended diagnostic criteria by two blinded examiners.

RESULTS

On the basis of the daily routine interpretation, AUS had a sensitivity (95 % CI) of 53.3 % (46.4-60.1), a specificity (95 % CI) of 93.6 % (90.8-95.8), an accuracy (95 % CI) of 79.7 % (76.4-82.8), a YI (95 % CI) of 0.47 (0.40 - 0.54), and a DOR (95 % CI) of 16.75 (10.37-27.05). Systematic application of previously recommended diagnostic criteria did not improve the diagnostic accuracy of routinely interpreted AUS.

CONCLUSION

AUS performance alone is not sufficient to accurately identify or exclude axillary metastatic disease in unselected patients with EBC.

Prospective evaluation of whole-body MRI and 18F-FDG PET/MRI in N and M staging of primary breast cancer patients

OBJECTIVES

To evaluate and compare the diagnostic potential of whole-body MRI and whole-body 18F-FDG PET/MRI for N and M staging in newly diagnosed, histopathologically proven breast cancer.

MATERIAL AND METHODS

A total of 104 patients (age 53.4 ± 12.5) with newly diagnosed, histopathologically proven breast cancer were enrolled in this study prospectively. All patients underwent a whole-body 18F-FDG PET/MRI. MRI and 18F-FDG PET/MRI datasets were evaluated separately regarding lesion count, lesion localization, and lesion characterization (malignant/benign) as well as the diagnostic confidence (5-point ordinal scale, 1-5). The N and M stages were assessed according to the eighth edition of the American Joint Committee on Cancer staging manual in MRI datasets alone and in 18F-FDG PET/MRI datasets, respectively. In the majority of lesions histopathology served as the reference standard. The remaining lesions were followed-up by imaging and clinical examination. Separately for nodal-positive and nodal-negative women, a McNemar chi2 test was performed to compare sensitivity and specificity of the N and M stages between 18F-FDG PET/MRI and MRI. Differences in diagnostic confidence scores were assessed by Wilcoxon signed rank test.

RESULTS

MRI determined the N stage correctly in 78 of 104 (75%) patients with a sensitivity of 62.3% (95% CI: 0.48-0.75), a specificity of 88.2% (95% CI: 0.76-0.96), a PPV (positive predictive value) of 84.6% % (95% CI: 69.5-0.94), and a NPV (negative predictive value) of 69.2% (95% CI: 0.57-0.8). Corresponding results for 18F-FDG PET/MRI were 87/104 (83.7%), 75.5% (95% CI: 0.62-0.86), 92.2% (0.81-0.98), 90% (0.78-0.97), and 78.3% (0.66-0.88), showing a significantly better sensitivity of 18F-FDG PET/MRI determining malignant lymph nodes (p = 0.008). The M stage was identified correctly in MRI and 18F-FDG PET/MRI in 100 of 104 patients (96.2%). Both modalities correctly staged all 7 patients with distant metastases, leading to false-positive findings in 4 patients in each modality (3.8%). In a lesion-based analysis, 18F-FDG PET/MRI showed a significantly better performance in correctly determining malignant lesions (85.8% vs. 67.1%, difference 18.7% (95% CI: 0.13-0.26), p < 0.0001) and offered a superior diagnostic confidence compared with MRI alone (4.1 ± 0.7 vs. 3.4 ± 0.7, p < 0.0001).

CONCLUSION

18F-FDG PET/MRI has a better diagnostic accuracy for N staging in primary breast cancer patients and provides a significantly higher diagnostic confidence in lesion characterization than MRI alone. But both modalities bear the risk to overestimate the M stage.

A Nomogram Combined Radiomics and Kinetic Curve Pattern as Imaging Biomarker for Detecting Metastatic Axillary Lymph Node in Invasive Breast Cancer

Objective: To construct and validate a nomogram model integrating the magnetic resonance imaging (MRI) radiomic features and the kinetic curve pattern for detecting metastatic axillary lymph node (ALN) in invasive breast cancer preoperatively. Materials and Methods: A total of 145 ALNs from two institutions were classified into negative and positive groups according to the pathologic or surgical results. One hundred one ALNs from institution I were taken as the training cohort, and the other 44 ALNs from institution II were taken as the external validation cohort. The kinetic curve was computed using dynamic contrast-enhanced MRI software. The preprocessed images were used for radiomic feature extraction. The LASSO regression was applied to identify optimal radiomic features and construct the Radscore. A nomogram model was constructed combining the Radscore and the kinetic curve pattern. The discriminative performance was evaluated by receiver operating characteristic analysis and calibration curve.

Results: Five optimal features were ultimately selected and contributed to the Radscore construction. The kinetic curve pattern was significantly different between negative and positive lymph nodes. The nomogram model showed a better performance in both training cohort [area under the curve (AUC) = 0.91, 95% CI = 0.83–0.96] and external validation cohort (AUC = 0.86, 95% CI = 0.72–0.94); the calibration curve indicated a better accuracy of the nomogram model for detecting metastatic ALN than either Radscore or kinetic curve pattern alone.

Conclusion: A nomogram model integrated the Radscore and the kinetic curve pattern could serve as a biomarker for detecting metastatic ALN in patients with invasive breast cancer.

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.

Establishment of Simple Nomograms for Predicting Axillary Lymph Node Involvement in Early Breast Cancer

Purpose

Axillary lymph node (ALN) involvement is an important prognostic factor of early invasive breast cancer. The objective of this study was to establish simple nomograms for predicting ALN involvement based on ultrasound (US) characteristics and evaluate the predictive value of US in the detection of ALN involvement.

Patients and Methods

A total of 1328 patients with cT1-2N0 breast cancer by physical exam were retrospectively analyzed. Univariate analysis was used for the comparison of variables, and multivariate analysis was performed by binary logistic regression analysis. The R software was used to establish simple nomograms based on the US characteristics alone. The receiver operating characteristic (ROC) curves of the prediction model and the verification group were drawn, and the area under the curve (AUC) was calculated to evaluate the discrimination of the prediction model. A calibration curve was plotted to assess the nomogram predictions vs the actual observations of the ALN metastasis rate and axillary tumor burden rate.

Results

The ALN metastasis rates of the training group and the validation group were 35.1% and 34.1%, respectively. Multivariate analysis showed that molecular subtype, lymphovascular invasion, mass descriptors (size, margin, microcalcification and blood flow signal) and LN descriptors (shape, cortical thickness and long-to-short ratio) were independent impact factors in early breast cancer. The AUC of ALN metastasis rate of prediction model based on US features was 0.802, the AUC of high tumor burden rate was 0.873, and the AUC of external validation group was 0.731 and 0.802, respectively. The calibration curve of the nomogram showed that the nomogram predictions are consistent with the actual metastasis rate and the high tumor burden rate. The results showed that preoperative US had a sensitivity of 59.4% and a specificity of 88.9% for predicting the ALN metastasis rate.

Conclusion

The successfully established nomograms based on US characteristics to predict ALN metastasis rate and high axillary tumor burden rate in early breast cancer can achieve individual prediction. Compared with other nomogram predictions, it is more intuitive, and can help clinical decision-making; thus, it should be promoted. However, at this time US features alone are insufficient to replace sentinel lymph node biopsy.

Can We Identify or Exclude Extensive Axillary Nodal Involvement in Breast Cancer Patients Preoperatively?

Background

Breast cancer treatment has rapidly changed in the last few years. Particularly, treatment of patients with axillary nodal involvement has evolved after publication of several randomized clinical trials. Omitting axillary lymph node dissection in selected early breast cancer patients with one or two positive sentinel nodes did not compromise overall survival nor regional disease control in these trials. Hence, either excluding or identifying extensive axillary nodal involvement becomes increasingly important.

Purpose

To evaluate whether the current diagnostic modalities can accurately identify or exclude extensive axillary nodal involvement. Evaluated modalities were axillary ultrasound, ultrasound-guided needle biopsy, MRI, and PET/CT.

Methods

A literature search was performed in the Cochrane Library, EMBASE, and PubMed databases up to June 2019. The search strategy included terms for breast cancer, lymph nodes, and the different imaging modalities. Only articles that reported pathological N-stage or the total number of positive axillary lymph nodes were considered for inclusion. Studies with patients undergoing neoadjuvant systemic therapy were excluded.

Conclusion

There is no evidence that any of the current preoperative axillary imaging modalities can accurately exclude or identify breast cancer patients with extensive nodal involvement. Both negative PET/CT and negative MRI scans (with gadolinium-based contrast agents) are promising in excluding extensive nodal involvement. Larger studies should be performed to strengthen this conclusion. False-negative rates of axillary ultrasound and ultrasound-guided needle biopsy are too high to rely on negative results of these modalities in excluding extensive nodal involvement.

Axillary Lymph Node Ultrasound Following Neoadjuvant Chemotherapy in Biopsy-Proven Node-Positive Breast Cancer: Results from the SN FNAC Study

BACKGROUND

The sentinel node biopsy following neoadjuvant chemotherapy (SN FNAC) study has shown that in node-positive (N+) breast cancer, sentinel node biopsy (SNB) can be performed following neoadjuvant chemotherapy (NAC), with a low false negative rate (FNR = 8.4%). A secondary endpoint of the SN FNAC study was to determine whether axillary ultrasound (AxUS) could predict axillary pathological complete response (ypN0) and increase the accuracy of SNB.

METHODS

The SN FNAC trial is a study of patients with biopsy-proven N+ breast cancer who underwent SNB followed by completion node dissection. All patients had AxUS following NAC and the axillary nodes were classified as either positive (AxUS+) or negative (AxUS-). AxUS was compared with the final axillary pathology results.

RESULTS

There was no statistical difference in the baseline characteristics of patients with AxUS+ versus those with AxUS-. Overall, 82.5% (47/57) of AxUS+ patients had residual positive lymph nodes (ypN+) at surgery and 53.8% (42/78) of AxUS- patients had ypN+. Post NAC AxUS sensitivity was 52.8%, specificity 78.3%, and negative predictive value 46.2%. AxUS FNR was 47.2%, versus 8.4% for SNB. If post-NAC AxUS- was used to select patients for SNB, FNR would decrease from 8.4 to 2.7%. However, using post-NAC AxUS in addition to SNB as an indication for ALND would have led to unnecessary ALND in 7.8% of all patients.

CONCLUSION

AxUS is not appropriate as a standalone staging procedure, and SNB itself is sufficient to assess the axilla post NAC in patients who present with N+ breast cancer.

Performance of Molecular Lymphosonography for Detection and Quantification of Metastatic Involvement in Sentinel Lymph Nodes

OBJECTIVES

To assess the performance of molecular lymphosonography with dual-targeted microbubbles in detecting and quantifying the metastatic involvement in sentinel lymph nodes (SLNs) using a swine melanoma model.

METHODS

Targeted microbubbles were labeled with P-selectin and αV β3 -integrin antibodies. Control microbubbles were labeled with immunoglobulin G antibodies. First lymphosonography with Sonazoid (GE Healthcare, Oslo, Norway) was used to identify SLNs. Then dual-targeted and control microbubbles were injected intravenously to detect and quantify metastatic disease in the SLNs. Distant non-SLNs were imaged as benign controls. All evaluated lymph nodes (LNs) were surgically removed, and metastatic involvement was characterized by a histopathologic analysis. Two radiologists blinded to histopathologic results assessed the baseline B-mode images of LNs, and the results were compared to the histologic reference standard. The mean intensities of targeted and control microbubbles within the examined LNs were measured and compared to the LN histologic results.

RESULTS

Thirty-five SLNs and 34 non-SLNs from 13 Sinclair swine were included in this study. Twenty-one SLNs (62%) were malignant, whereas 100% of non-SLNs were benign. The sensitivity of B-mode imaging for metastatic LN diagnosis for both readers was relatively high (90% and 71%), but the specificity was very poor (50% and 58%). The sensitivity and specificity of molecular lymphosonography for metastatic LN detection were 91% and 67%, respectively. The mean intensities from dual-targeted microbubbles correlated well with the degree of metastatic LN involvement (r = 0.6; P < 0.001).

CONCLUSIONS

Molecular lymphosonography can increase the specificity of metastatic LN detection and provide a measure to quantify the degree of metastatic involvement.

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.

Correlation of Ultrasound Findings and Fine-Needle Aspiration Cytology for the Diagnosis of Axillary Lymph Node Metastasis in Patients with Breast Carcinoma

OBJECTIVE

Ultrasound-guided fine-needle aspiration cytology (USG-FNAC) is used for the detection of axillary lymph node (ALN) metastasis in patients with breast carcinoma (BC). US findings have a good diagnostic accuracy with high sensitivity and specificity. The aim of this study is to correlate the detection of ALN metastases on US with FNAC in BC patients.

STUDY DESIGN

In 75 BC patients, over a period of 9 months (January to September 2017), the size, cortical thickness (CT), presence or absence of hilar fat, and length/width ratio of ALN on US were reviewed and correlated with FNAC findings.

RESULTS

The age range was 29-78 (mean 52) years. There were 38 patients with a single ALN and 37 with multiple ALNs. ALNs with a maximum length of > 2.5 cm were malignant in 100% of cases while those ≥1.5 cm were malignant in 80.4%. ALNs with a CT of > 3 mm had metastasis in 78.1% cases. ALNs with absent hilar fat showed tumour in 87.5% cases. A length/width ratio of < 2 showed a metastatic tumour in 66.7% of aspirates.

CONCLUSION

An association was seen between metastatic carcinoma on FNAC and axillary US features of a maximum length of ≥1.5 cm, the absence of hilar fat, and a CT of > 3 mm (p < 0.05).

Serum miRNA-based Prediction of Axillary Lymph Node Metastasis in Breast Cancer

PURPOSE

Sentinel lymph node biopsy (SLNB) is the gold-standard procedure for evaluating axillary lymph node (ALN) status in patients with breast cancer. However, the morbidity of SLNB is not negligible, and the procedure is invasive for patients without ALN metastasis. Here, we developed a diagnostic model for evaluating ALN status using a combination of serum miRNAs and clinicopathologic factors as a novel less-invasive biomarker.Experimental Design: Preoperative serum samples were collected from patients who underwent surgery for primary breast cancer or breast benign diseases between 2008 and 2014. A total of 958 serum samples (921 cases of primary breast cancer, including 630 cases in the no ALN metastasis group and 291 cases in the ALN metastasis group, and 37 patients with benign breast diseases) were analyzed by miRNA microarray. Samples were randomly divided into training and test sets. Logistic LASSO regression analysis was used to construct diagnostic models in the training set, which were validated in the test set.

RESULTS

An optimal diagnostic model was identified using a combination of two miRNAs (miR-629-3p and miR-4710) and three clinicopathologic factors (T stage, lymphovascular invasion, and ultrasound findings), which showed a sensitivity of 0.88 (0.84-0.92), a specificity of 0.69 (0.61-0.76), an accuracy of 0.818, and an area under the receiver operating characteristic curve of 0.86 in the test set.

CONCLUSIONS

Serum miRNA profiles may be useful for the diagnosis of ALN metastasis before surgery in a less-invasive manner than SLNB.

Strategy for the accurate preoperative evaluation of the number of metastatic axillary lymph nodes in breast cancer

BACKGROUND

After the ACOSOG Z0011 trial, it became important to evaluate the number of metastatic axillary lymph nodes (LNs) preoperatively. The purpose of this paper is to confirm whether the number of metastases can be accurately diagnosed by preoperative computed tomography (CT), ultrasound sonography (US), and US-guided fine-needle aspiration cytology (FNAC).

METHODS

We retrospectively analyzed the axillary LNs finding of preoperative CT/US of 470 breast cancer patients. Metastasis was suspected based on the following findings: LNs with a long-axis diameter of ≥10 mm or a short-axis diameter of ≥5 mm on CT, and LNs with the absence of a fatty hilum, focal cortical thickness or a cortical thickness ≥2 mm on US. We also examined the results of FNAC making a rapid bedside diagnosis (bedside-FNAC) of 162 LNs that were suspected to metastatic based on the US findings.

RESULTS

On CT, all cases with ≥3 LNs with a long-axis diameter of ≥10 mm and a short-axis diameter of ≥5 mm had metastasis. However, there was no relationship between the number of detected LNs and the number of metastases. On US, 75.7% of LNs with the absence of a fatty hilum and all LNs with cortical thickness ≥6 mm had metastasis. The accuracy of bedside-FNAC for suspicious LNs was 100%.

CONCLUSIONS

Although we can pick up LNs that are likely to have metastasis on CT/US, it was impossible to accurately predict the number of metastases on CT/US. However, bedside-FNAC of suspicious LNs could accurately predict the number of metastases.

Preoperative predictors of high and low axillary nodal burden in Z0011 eligible breast cancer patients with a positive lymph node needle biopsy result

BACKGROUND

Z0011 trial showed that early breast cancer patients with low axillary nodal burden, may be spared an axillary lymph node dissection with no survival compromise. Axillary lymph node dissection can be reserved for patients with a high axillary nodal burden. We aim to determine the preoperative factors that could distinguish between low and high axillary nodal burden in Z0011 eligible patients with a needle biopsy proven metastatic node.

METHOD

Patients who fulfilled Z0011 trial criteria with a positive lymph node needle biopsy and had axillary lymph node dissection (ALND) were recruited. These patients were classified into low and high nodal burden subgroups, defined as having 1-2 and ≥3 metastatic lymph nodes, respectively. The clinical, radiological and pathological features between the 2 subgroups were compared.

RESULTS

70 (40%) and 105 (60%) patients had low and high nodal burden respectively. The high nodal burden subgroup was more likely to have on ultrasound ≥3 abnormal lymph nodes (37.14% versus 4.29%) (P < 0.0001) and maximum cortical thickness >4 mm (31.43% versus 10.0%) (P = 0.0036). Multivariate analysis revealed abnormal lymph nodes ≥3 to have an odds ratio of 20.72 (95% CI 5.91-72.65) P < 0.0001.

CONCLUSION

≥3 abnormal lymph nodes on ultrasound was the most significant predictor of high nodal burden subgroup in Z0011 eligible patients with a positive lymph node needle biopsy. This information could allow this subgroup to proceed to an upfront ALND and avoid the need of a sentinel lymph node biopsy in the post Z0011 trial era.

Role of Elastography in Axillary Examination of Patients With Breast Cancer

OBJECTIVES

This study aimed at exploring the role of ultrasound (US) elastography in the diagnosis of the axillary lymph node status in patients with breast cancer.

METHODS

We analyzed 140 visible axillary lymph nodes on conventional US imaging. All of them underwent elastography. Five conventional US features were adopted to assess axillary lymph nodes: longitudinal diameter, longitudinal-to-transverse diameter ratio, cortical thickness, status of the hilum, and vascular pattern. As for elastography, the proportion of the hard area within each lymph node was estimated visually. The lymph node was defined as positive on elastography when the proportion was 50% or greater. Meanwhile, disjunctive and conjunctive combinations of US and elastography were adopted to evaluate the lymph nodes. The histopathologic diagnosis was regarded as the reference standard.

RESULTS

The sensitivity, specificity, and accuracy were 76.92%, 87.10%, and 81.43%, respectively, for conventional US and 84.62%, 83.87%, and 84.29% for the disjunctive combination. The conjunctive combination had specificity of 100% and a positive predictive value of 100%, whereas the sensitivity was low.

CONCLUSIONS

Elastography can improve the sensitivity when disjunctively combined with conventional US for diagnosis of the axillary lymph node status. Despite the low sensitivity, the conjunctive combination of US and elastography can improve the positive predictive value on a large scale. Elastography is a useful adjuvant tool in addition to conventional US for the preoperative assessment of axillary lymph nodes in patients with breast cancer.

The Relevance of Ultrasound Imaging of Suspicious Axillary Lymph Nodes and Fine-needle Aspiration Biopsy in the Post-ACOSOG Z11 Era in Early Breast Cancer

RATIONALE AND OBJECTIVES

Evaluation of nodal involvement in early-stage breast cancers (T1 or T2) changed following the Z11 trial; however, not all patients meet the Z11 inclusion criteria. Hence, the relevance of ultrasound imaging of the axilla and fine-needle aspiration biopsy (FNA) in early-stage breast cancers was investigated.

MATERIALS AND METHODS

In this single-center, retrospective study, 758 subjects had pathology-verified breast cancer diagnosis over a 3-year period, of which 128 subjects with T1 or T2 breast tumors had abnormal axillary lymph nodes on ultrasound, had FNA, and proceeded to axillary surgery. Ultrasound images were reviewed and analyzed using multivariable logistic regression to identify the features predictive of positive FNA. Accuracy of FNA was quantified as the area under the receiver operating characteristic curve with axillary surgery as reference standard.

RESULTS

Of 128 subjects, 61 were positive on FNA and 65 were positive on axillary surgery. Sensitivity, specificity, positive predictive value, and negative predictive value of FNA were 52 of 65 (80%), 54 of 63 (85.7%), 52 of 61(85.2%), and 54 of 67 (80.5%), respectively. After adjusting for neoadjuvant chemotherapy between FNA and surgery, a positive FNA was associated with higher likelihood for positive axillary surgery (odds ratio: 22.7; 95% confidence interval [CI]: 7.2-71.3, P < .0001), and the accuracy of FNA was 0.801 (95% CI: 0.727-0.876). Among ultrasound imaging features, cortical thickness and abnormal hilum were predictive (P < .017) of positive FNA with accuracy of 0.817 (95% CI: 0.741-0.893).

CONCLUSIONS

Ultrasound imaging and FNA can play an important role in the management of early breast cancers even in the post-Z11 era. Higher weightage can be accorded to cortical thickness and hilum during ultrasound evaluation.

Assessment of Ultrasound Features Predicting Axillary Nodal Metastasis in Breast Cancer: The Impact of Cortical Thickness

PURPOSE

To evaluate the accuracy of axillary ultrasound (AUS) in detecting nodal metastasis in patients with early-stage breast cancer and to identify AUS features with high predictive power.

MATERIALS AND METHODS

Prospective single-center preliminary study in 105 patients with a primary diagnosis of breast cancer and clinically negative axilla. AUS was performed using a 12 MHz linear-array transducer before ultrasound-guided needle biopsy. Nodal characteristics (shape, longitudinal-transverse [LT] axis ratio, margins, cortical thickness, hyperechoic hilum) were correlated with histopathological nodal status after SLNB or axillary lymph node dissection (ALND).

RESULTS

Nodal metastases were present in 42/105 patients (40.0%). Univariate analyses showed that absence of hyperechoic hilum, round shape, LT axis ratio<2, sharp margins and cortical thickness>3 mm were associated with lymph node metastasis. Multivariate logistic regression analysis revealed cortical thickness > 3 mm as an independent predictive parameter for nodal involvement. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 66.7, 74.6, 63.6, 77.0% and 71.4% respectively when cortical thickness > 3 mm was applied as the criterion for AUS positivity. Axillary tumor volume was low in patients with pT1/2 tumors and negative AUS, since only 3.2% of patients had > 2 metastatic lymph nodes.

CONCLUSION

Cortical thickness>3 mm is a reliable predictor of nodal metastatic involvement. Negative AUS does not exclude lymph node metastases, but extensive axillary tumor volume is rare.

Three-Dimensional Sonography of Axillary Lymph Nodes in Patients With Breast Cancer

Sonography is useful in the evaluation of axillary lymph nodes in patients with breast cancer. In this pictorial essay, we review the range of grayscale and Doppler appearances of abnormal axillary lymph nodes on 2-dimensional and 3-dimensional imaging.

Superparamagnetic iron oxide-enhanced MRI at 3 T for accurate axillary staging in breast cancer

BACKGROUND

The aim of this study was to evaluate whether MRI at 3 T with superparamagnetic iron oxide (SPIO) enhancement is an accurate and useful method for detecting metastases in sentinel nodes identified by CT-lymphography (CT-LG) in patients with breast cancer. The results were compared with those obtained using CT-LG alone and diagnosing metastasis according to size criteria.

METHODS

Patients with clinically node-negative breast cancer were included. Sentinel nodes identified by CT-LG were evaluated prospectively using SPIO-enhanced MRI at 3 T. Sentinel node size was measured on CT-LG, and a node larger than 5 mm in short-axis diameter was considered metastatic. Sentinel nodes localized by CT-LG were removed, and imaging results and histopathological findings were compared.

RESULTS

Sentinel nodes were identified successfully by CT-LG in 69 (99 per cent) of 70 patients. All 19 patients with a finding of metastasis in sentinel nodes at pathology were also shown to have metastases on MRI. Forty-eight of 50 patients with non-metastatic sentinel nodes diagnosed at pathology were classified as having non-metastatic nodes on MRI. On a patient-by-patient basis, the sensitivity, specificity and accuracy of MRI for the diagnosis of sentinel node metastases were 100, 96 and 97 per cent; respective values for CT-LG were 79, 56 and 62 per cent. The specificity and accuracy of MRI were superior to those of CT-LG (P < 0·001 and P = 0·002 respectively).

CONCLUSION

SPIO-enhanced MRI at 3 T is useful for accurate diagnosis of metastatic sentinel nodes, indicating that sentinel node biopsy may be avoided in patients with breast cancer who have non-metastatic sentinel nodes on imaging.

The clinical utility of assessment of the axilla in women with suspicious screen detected breast lesions in the post Z0011 era

Axillary ultrasound (AUS) and biopsy are now part of the preoperative assessment of breast cancer based on the assumption that any nodal disease is an indication for axillary clearance (AC). The Z0011 trial erodes this assumption. We applied Z0011 eligibility criteria to patients with screen detected cancers and positive axillary assessment to determine the relevance of AUS to contemporary practice. Women screened between 1/1/2012 and 30/6/2013 and assessed for lesions with highly suspicious imaging features are included. We analysed demographic and assessment data and ascertained the final histopathology with particular reference to axillary nodal status. Among 449 lesions, AUS was recorded in 303 lesions (67.5 %). 290 (96 %) were carcinomas, 30.3 % with nodal disease. AUS was abnormal in 46 (15.9 %). AUS had a sensitivity of 39.8 %, specificity 94.6 %, positive predictive value (PPV) 79.2 % and negative predictive value (NPV) 78.1 %. Axillary FNAB was positive in 27 women, suspicious in two, benign in 16 and not performed in one. In one FNA positive case, the lesion was a nodular breast primary in the axillary tail in a multifocal breast cancer. Combining AUS and FNAB, the sensitivity was 76.5 %, specificity 90.9 %, PPV 96.3 % and NPV 55.6 %. Applying the Z0011 inclusion criteria, 24 of the 27 (88.9 %) women with abnormal AUS and positive FNA were ineligible for Z0011-based management. Of three women eligible for Z0011, one proceeded to AC after SN biopsy, leaving only two women (7.4 %) who might have been considered for SN only management had it not been for the results of the axillary assessment. Among women with negative AUS, nodal metastasis was demonstrated in 21.7 %, 86.8 % of these women having only 1-2 positive nodes. Abnormal AUS and FNA preferentially identify candidates for AC. Negative AUS predicts negative or low nodal burden. Axillary assessment streamlines care.

Preoperative assessment of the axilla by surgeon performed ultrasound and cytology in patients with breast cancer

BACKGROUND

Preoperative evaluation of the axilla, an important prognostic determinant for patients with invasive breast cancer, is achieved by non- or minimally invasive methods to avoid the potential hazards of operative intervention. The aim of this study was to determine statistical power of axillary ultrasound (US) and US-guided fine needle aspiration cytology (FNAC) for evaluating axillary status.

METHODS

Axillary lymph nodes were imaged for malignant involvement by high resolution US in 93 breast cancer patients with clinically negative axilla. Cytological samples were obtained by US-guided FNAC from image-suspicious lymph nodes. Cytology-positive patients directly underwent axillary lymph node dissection (ALND). Patients with US and/or cytology-negative axilla underwent sentinel lymph node biopsy (SLNB). Using statistical analysis, US findings and US combined with FNAC were compared with SLNB and final pathology to measure performance.

RESULTS

US was suspicious for metastasis in 38 patients (41%), of whom 16 (42%) were cytology-positive. Axilla was positive in 36/93 patients (38.7%). Sixteen patients with positive FNAC directly underwent ALND. SLNB and/or final pathology was positive in 13/55 patients (23.7%) with negative US (false negative of US) and in 7/22 patients (31.8%) with positive US but negative cytology (false negative of FNAC). SLNB and/or final pathology was negative in 15/38 patients (39.5%) with positive US (false positive of US). Sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of US alone were 63.8%, 73.6%, 69.8%, 60.5% and 76.3%, respectively, and 69.6%,100%, 81.6%, 100% and 68.1%, respectively, for US combined with FNAC.

CONCLUSION

Statistical measures of the US alone did not achieve a satisfactory value for excluding operative biopsy. US-negative and US-positive but cytology-negative cases still require SLNB for accurate evaluation of axillary status. On the other hand, US-guided positive cytology can obviate SLNB proceeding directly to ALND and avoiding frozen section of sentinel node(s).

Efficiency of a preoperative axillary ultrasound and fine-needle aspiration cytology to detect patients with extensive axillary lymph node involvement

Background

Recent studies have demonstrated that axillary lymph node dissection (ALND) does not affect patient survival, even in those with one or two positive sentinel lymph nodes (SLNs). On the other hand, patients with 3 or more metastatic lymph nodes are eligible for chemotherapy. Therefore, it is crucial to identify a priori patients at risk of having a high number of metastatic axillary lymph nodes for their surgical and/or clinical management. Ultrasound (US) guided Fine-Needle Aspiration (FNA) has been proven to be a useful and highly specific method for detecting metastatic axillary lymph nodes. However, only one recent study has evaluated the efficiency of this method in identifying patients with high metastatic nodal involvement. Our aim was to validate US-guided FNA as a reliable method to discriminate a priori patients with >3 metastatic lymph nodes.

Methods

A retrospective series of 1287 breast cancer patients who underwent a simultaneous preoperative breast and axillary US to stage their axilla was collected. A total of 365 patients, with either positive SLNs (278) or positive axillary lymph nodes detected via US-guided FNA (87), underwent ALND. In these two subgroups, we compared the number of metastatic lymph nodes in the axilla.

Results

The number of metastatic axillary lymph nodes in patients who underwent US-guided FNA was significantly higher (63% had >3 metastatic lymph nodes) than that in patients with SLNs positive for micro- or macrometastases (3% and 27%, respectively) (P<0.001, χ² = 117.897).

Conclusions

Preoperative axillary US-guided FNA could act as a reliable tool in identifying breast cancer patients with extensive nodal involvement.

Real-time ultrasound and freehand-SPECT. Experiences with sentinel lymph node mapping

Aim of this work is to report first experiences of the feasibility and applicability of a hybrid freehandSPECT/ultrasound (fh-SPECT/US) imaging concept, with regard to SLN imaging, in patients with breast cancer and malignant melanoma.

PATIENTS, METHODS

18 patients with breast cancer or malignant melanoma received standard SLN scintigraphy. Following this, fh-SPECT using declipse®SPECT (SurgicEye, Munich, Germany) was performed, a handheld-gamma camera-based method to visualize activity distribution within a region of interest as a cross-sectional data set. These data were transferred to an ultrasound device and sensor-navigated ultrasound was performed combining fh-SPECT data with ultrasound images, displaying superimposed images. Quality of fh-SPECT and co-registration accuracy was assigned to one of four categories and occurrence of artefacts was assessed.

RESULTS

In 4/18 examinations, there was a no deviation regarding co-registration of both data sets. For 9/18 patients, there was a deviation of <1 cm (mean 0.7±0.3 cm, range 0.3-1.0 cm). For 3/18 patients, a deviation >1 cm was present (mean 1.7±0.3 cm, range 1.5-2.0 cm). In 2/18 examinations no lymph node was found in the region of highest activity. Fh-SPECT reconstruction artifacts occurred in 6/18 examinations.

CONCLUSION

The fusion imaging concept combining SLN information with ultrasound images presented here proves to be feasible and technically successful. However, significant technical limitations were shown in fh-SPECT quality and fusion precision. Subject to technical optimisation of SPECT quality and co-registration, a meaningful contribution to the preoperative planning of lymph node therapy is imaginable. Thus, fundamentally a preoperative histological examination by fh-SPECT/US-guided biopsy is possible.