Patients with breast cancer: differences in color Doppler flow and gray-scale US features of benign and malignant axillary lymph nodes

Multiparametric ultrasound assessment of axillary lymph nodes in patients with breast cancer

The presence and extent of metastatic disease in axillary lymph nodes (ALNs) in the setting of breast cancer (BC) are important factors for staging and therapy planning. The purpose of this study was to perform a multiparametric sonographic evaluation of ALNs to better differentiate between benign and metastatic nodes. Ninety-nine patients (mean age 54.1 y) with 103 BCs were included in this study, and 103 ALNs were examined sonographically. B-mode parameters, such as size in two dimensions, shape, cortical thickness and capsule outline, were obtained, followed by vascularity assessment via colour Doppler and microflow imaging and stiffness evaluation via shear wave elastography. Postoperative histopathological evaluation was the reference standard. In the statistical analysis, logistic regression and ROC analyses were conducted to search for feature patterns of both types of ALNs to evaluate the prediction qualities of the analysed variables and their combinations. For a cortex larger than 3 mm, without a circumscribed margin of the LN capsule and SWE (E max > 26 kPa), the AUC was 0.823. Multiparametric assessment, which combined conventional US, quantitative SWE and vascularity analysis, was superior to the single-parameter approach in the evaluation of ALNs.

Ultrasonographic signs as predictors of metastatic involvement in the axillary lymph nodes in breast cancer patients: from minimal changes to the appearance of the pathological lymph node. A retrospective analysis

INTRODUCTION

The aim of this study was to retrospectively analyse the ultrasound findings in the axillary lymph nodes in breast cancer patients with morphological changes that required biopsy. In most cases the morphological changes were minimal.

MATERIALS AND METHODS

Between January 2014 and September 2019 examination of axillary lymph nodes with subsequent core-biopsy was performed in 185 breast cancer patients at the Department of Radiology. Lymph node metastases were detected in 145 cases, while in the remaining 40 cases benign changes or normal lymph node (LN) histology was observed. Ultrasound morphological characteristics and the sensitivity and specificity were evaluated retrospectively. Seven ultrasound characteristics were evaluated - diffuse cortical thickening, focal cortical thickening, absence of the hilum, cortical non-homogeneities, L/T ratio (longitudinal to transverse axis), type of vascularization and perinodal oedema.

RESULTS AND CONCLUSION

It is a diagnostic challenge to recognize metastases in the lymph nodes with minimal morphological changes. The most specific signs are non-homogeneities in the cortex of the lymph node as well as the absence of fat hilum and perinodal oedema. Metastases are significantly more frequent in LNs with a lower L/T ratio, in LNs with perinodal oedema and with a peripheral type of vascularization. Biopsy of these lymph nodes is necessary to confirm or exclude metastases, especially if it affects the type of treatment.

Shear-wave elastography as a supplementary tool for axillary staging in patients undergoing breast cancer diagnosis

BACKGROUND

Preoperative evaluation of axillary lymph node status is crucial for the selection of both systemic and surgical treatment in early breast cancer. This study assessed the particular role of additional shear wave elastography (SWE) in axillary staging in patients undergoing initial breast cancer diagnostics.

METHODS

One hundred patients undergoing axillary lymph node biopsy due to a sonographically suspicious axillary lymph node were prospectively evaluated with SWE using virtual touch tissue imaging quantification (VTIQ). Mean values of tissue stiffness for axillary tissue and lymph node tissue were measured prior to core-cut biopsy of the lymph node. All lymph nodes were clip-marked during the biopsy. Cut-off values to differentiate between malignant and benign lymph nodes were defined using Youden's index.

RESULTS

Lymph nodes with evidence of malignant tumor cells in the final pathological examination showed a significantly higher velocity as measured by SWE, with a mean velocity of 3.48 ± 1.58 m/s compared to 2.33 ± 0.62 m/s of benign lymph nodes (p < 0.0001). The statistically optimal cutoff to differentiate between malignant and benign lymph nodes was 2.66 m/s with a sensitivity of 69.8% and a specificity of 87.5%.

CONCLUSIONS

Lymph node metastases assessed with SWE showed significantly higher elasticity values compared to benign lymph nodes. Thus, SWE provides an additional useful and quantifiable parameter for the sonographic assessment of suspicious axillary lymph nodes in the context of pre-therapeutic axillary staging in order to differentiate between benign and metastatic processes and support the guidance of definitive biopsy work-up.

CRITICAL RELEVANCE STATEMENT

Shear-wave elastography provides an additional useful and quantifiable parameter for the assessment of suspicious axillary lymph nodes in the context of pre-therapeutic axillary staging in order to differentiate between benign and metastatic processes and support guiding the definitive biopsy work-up.

KEY POINTS

SWE is a quantifiable ultrasound parameter in breast cancer diagnosis. SWE shows a significantly higher velocity in malignant lymph nodes. SWE is useful in improving the sensitivity and specificity of axillary staging.

A nomogram model for predicting the risk of axillary lymph node metastasis in patients with early breast cancer and cN0 status

Axillary staging is commonly performed via sentinel lymph node biopsy for patients with early breast cancer (EBC) presenting with clinically negative axillary lymph nodes (cN0). The present study aimed to investigate the association between axillary lymph node metastasis (ALNM), clinicopathological characteristics of tumors and results from axillary ultrasound (US) scanning. Moreover, a nomogram model was developed to predict the risk for ALNM based on relevant factors. Data from 998 patients who met the inclusion criteria were retrospectively reviewed. These patients were then randomly divided into a training and validation group in a 7:3 ratio. In the training group, receiver operating characteristic curve analysis was used to identify the cutoff values for continuous measurement data. R software was used to identify independent ALNM risk variables in the training group using univariate and multivariate logistic regression analysis. The selected independent risk factors were incorporated into a nomogram. The model differentiation was assessed using the area under the curve (AUC), while calibration was evaluated through calibration charts and the Hosmer-Lemeshow test. To assess clinical applicability, a decision curve analysis (DCA) was conducted. Internal verification was performed via 1000 rounds of bootstrap resampling. Among the 998 patients with EBC, 228 (22.84%) developed ALNM. Multivariate logistic analysis identified lymphovascular invasion, axillary US findings, maximum diameter and molecular subtype as independent risk factors for ALNM. The Akaike Information Criterion served as the basis for both nomogram development and model selection. Robust differentiation was shown by the AUC values of 0.855 (95% CI, 0.817-0.892) and 0.793 (95% CI, 0.725-0.857) for the training and validation groups, respectively. The Hosmer-Lemeshow test yielded P-values of 0.869 and 0.847 for the training and validation groups, respectively, and the calibration chart aligned closely with the ideal curve, affirming excellent calibration. DCA showed that the net benefit from the nomogram significantly outweighed both the 'no intervention' and the 'full intervention' approaches, falling within the threshold probability interval of 12-97% for the training group and 17-82% for the validation group. This underscores the robust clinical utility of the model. A nomogram model was successfully constructed and validated to predict the risk of ALNM in patients with EBC and cN0 status. The model demonstrated favorable differentiation, calibration and clinical applicability, offering valuable guidance for assessing axillary lymph node status in this population.

Predicting three or more metastatic nodes using contrast-enhanced lymphatic US findings in early breast cancer

OBJECTIVES

To develop and validate a nomogram for predicting ≥ 3 metastatic axillary lymph nodes (ALNs) in early breast cancer with no palpable axillary adenopathy by clinicopathologic data, contrast-enhanced (CE) lymphatic ultrasound (US), and grayscale findings of sentinel lymph nodes (SLNs).

MATERIALS AND METHODS

Women with T1-2N0 invasive breast cancer were consecutively recruited for the CE lymphatic US. Patients from Center 1 were grouped into development and internal validation cohorts at a ratio of 2:1. The external validation cohort was constructed from Center 2. The clinicopathologic data and US findings of SLNs were analyzed. A nomogram was developed to predict women with ≥ 3 metastatic ALNs. Nomogram performance was assessed with the area under the receiver operating characteristic curve (AUC) and calibration curve analysis.

RESULTS

One hundred seventy-nine from Center 1 were considered the development cohorts. The remaining 90 participants from Center 1 were internal cohorts and 197 participants from Center 2 were external validation cohorts. The US findings of no enhancement (odds ratio (OR), 15.3; p = 0.01), diffuse (OR, 19.1; p = 0.01) or focal eccentric (OR, 27.7; p = 0.003) cortical thickening, and absent hilum (OR, 169.7; p < 0.001) were independently associated with ≥ 3 metastatic ALNs. Compared to grayscale US or CE lymphatic US alone, the nomogram showed the highest AUC of 0.88 (0.85, 0.91). The nomogram showed a calibration slope of 1.0 (p = 0.80-0.81; Brier = 0.066-0.067) in validation cohorts in predicting ≥ 3 metastatic ALNs.

CONCLUSION

Patients likely to have ≥ 3 metastatic ALNs were identified by combining the lymphatic and grayscale US findings of SLNs. Our nomogram could aid in multidisciplinary treatment decision-making.

TRIAL REGISTRATION

This trial is registered on www.chictr.org.cn : ChiCTR2000031231. Registered March 25, 2020.

CRITICAL RELEVANCE STATEMENT

A nomogram combining lymphatic CEUS and grayscale US findings of SLNs could identify early breast cancer patients with low or high axillary tumor burden preoperatively, which is more applicable to the Z0011 era. Our nomogram could be useful in aiding multidisciplinary treatment decision-making for patients with early breast cancer.

KEY POINTS

• CEUS can help identify and diagnose SLN in early breast cancer preoperatively. • Combining lymphatic and grayscale US findings can predict axillary tumor burden. • The nomogram showed a high diagnostic value in validation cohorts.

Distribution of Contractile Structures in a Mouse and Human Lymph Node Associated with Lymph Flow

Lymph nodes have contractile structures, but their distribution in a lymph node has been less considered in terms of facilitation of lymph flow. Axillary, inguinal, and mesenteric lymph nodes were collected from mice and human cadavers, and their sections were immunostained for alpha-smooth muscle actin (αSMA) and high molecular weight caldesmon (H-caldesmon). The αSMA-positive cells were localized in the capsule beneath the ceiling epithelium on the afferent side in both mice and humans. We found an additional layer of the αSMA-positive cells in the human lymph node, surrounding the inner layer perpendicularly. H-caldesmon was expressed only in these cells of the outer layer. In some human lymph nodes highly containing fat tissue in the medulla, the capsule disappeared on the efferent side, resulting in a disrupted sinusoidal lymph pathway. These findings suggest that human lymph nodes have additional smooth muscles in the outer region of the capsule to facilitate lymph flow. The αSMA-positive cells in the outer and inner layers of human lymph nodes probably have different functions in contraction. The presence of lipomatosis in a human lymph node will reduce its contribution to the lymph flow.

Diagnostic Accuracy of Ultrasonography in Axillary Staging in Breast Cancer Patients

Background

Breast cancer is the most common malignancy affecting women all over the world and represents 7% of all cancer-related deaths in the UK. One of the most crucial elements in assessing a patient's prognosis and chance of survival with breast cancer is the condition of their axillary lymph nodes. Ultrasonography (US) is now used as a routine preoperative diagnostic tool for pretherapeutic axillary evaluation. The aim of the current study is to investigate the diagnostic accuracy of US in axillary staging in breast cancer patients.

Methods

We carried out this retrospective study for all invasive breast cancer patients who had surgery in addition to preoperative axillary staging using US during the period from January 2020 to February 2021. The final histology results were compared with the preoperative US findings to ascertain the sensitivity, specificity, positive predictive value, and negative predictive value of AUS in axillary staging.

Results

One hundred and twenty-eight patients were included in our study. The average age of diagnosis was 63.9 ± 12.3 years of age. We calculated sensitivity rate of 59.6%, specificity rate of 95.1%, positive predictive value of 87.5%, and negative predictive value of 80.2% with overall diagnostic accuracy of 82.2%.

Conclusion

Despite the important role of preoperative US in axillary staging in breast cancer patients; it failed to detect metastatic diseases in 14.8% of our patients. These findings necessitate the routine histological evaluation of the axilla for more accurate staging of the disease.

Prediction of axillary lymph node metastasis in early breast cancer patients with ultrasonic videos based deep learning

Objective

To develop a deep learning (DL) model for predicting axillary lymph node (ALN) metastasis using dynamic ultrasound (US) videos in breast cancer patients.

Methods

A total of 271 US videos from 271 early breast cancer patients collected from Xiang'an Hospital of Xiamen University andShantou Central Hospitabetween September 2019 and June 2021 were used as the training, validation, and internal testing set (testing set A). Additionally, an independent dataset of 49 US videos from 49 patients with breast cancer, collected from Shanghai 10th Hospital of Tongji University from July 2021 to May 2022, was used as an external testing set (testing set B). All ALN metastases were confirmed using pathological examination. Three different convolutional neural networks (CNNs) with R2 + 1D, TIN, and ResNet-3D architectures were used to build the models. The performance of the US video DL models was compared with that of US static image DL models and axillary US examination performed by ultra-sonographers. The performances of the DL models and ultra-sonographers were evaluated based on accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Additionally, gradient class activation mapping (Grad-CAM) technology was also used to enhance the interpretability of the models.

Results

Among the three US video DL models, TIN showed the best performance, achieving an AUC of 0.914 (95% CI: 0.843-0.985) in predicting ALN metastasis in testing set A. The model achieved an accuracy of 85.25% (52/61), with a sensitivity of 76.19% (16/21) and a specificity of 90.00% (36/40). The AUC of the US video DL model was superior to that of the US static image DL model (0.856, 95% CI: 0.753-0.959, P<0.05). The Grad-CAM technology confirmed the heatmap of the model, which highlighted important subregions of the keyframe for ultra-sonographers' review.

Conclusion

A feasible and improved DL model to predict ALN metastasis from breast cancer US video images was developed. The DL model in this study with reliable interpretability would provide an early diagnostic strategy for the appropriate management of axillary in the early breast cancer patients.

The Lucerne Toolbox 2 to optimise axillary management for early breast cancer: a multidisciplinary expert consensus

Clinical axillary lymph node management in early breast cancer has evolved from being merely an aspect of surgical management and now includes the entire multidisciplinary team. The second edition of the "Lucerne Toolbox", a multidisciplinary consortium of European cancer societies and patient representatives, addresses the challenges of clinical axillary lymph node management, from diagnosis to local therapy of the axilla. Five working packages were developed, following the patients' journey and addressing specific clinical scenarios. Panellists voted on 72 statements, reaching consensus (agreement of 75% or more) in 52.8%, majority (51%-74% agreement) in 43.1%, and no decision in 4.2%. Based on the votes, targeted imaging and standardized pathology of lymph nodes should be a prerequisite to planning local and systemic therapy, axillary lymph node dissection can be replaced by sentinel lymph node biopsy ( ± targeted approaches) in a majority of scenarios; and positive patient outcomes should be driven by both low recurrence risks and low rates of lymphoedema.

Noninvasive prediction of axillary lymph node breast cancer metastasis using morphometric analysis of nodal tumor microvessels in a contrast-free ultrasound approach

PURPOSE

Changes in microcirculation of axillary lymph nodes (ALNs) may indicate metastasis. Reliable noninvasive imaging technique to quantify such variations is lacking. We aim to develop and investigate a contrast-free ultrasound quantitative microvasculature imaging technique for detection of metastatic ALN in vivo.

EXPERIMENTAL DESIGN

The proposed ultrasound-based technique, high-definition microvasculature imaging (HDMI) provides superb images of tumor microvasculature at sub-millimeter size scales and enables quantitative analysis of microvessels structures. We evaluated the new HDMI technique on 68 breast cancer patients with ultrasound-identified suspicious ipsilateral axillary lymph nodes recommended for fine needle aspiration biopsy (FNAB). HDMI was conducted before the FNAB and vessel morphological features were extracted, analyzed, and the results were correlated with the histopathology.

RESULTS

Out of 15 evaluated quantitative HDMI biomarkers, 11 were significantly different in metastatic and reactive ALNs (10 with P << 0.01 and one with 0.01 < P < 0.05). We further showed that through analysis of these biomarkers, a predictive model trained on HDMI biomarkers combined with clinical information (i.e., age, node size, cortical thickness, and BI-RADS score) could identify metastatic lymph nodes with an area under the curve of 0.9 (95% CI [0.82,0.98]), sensitivity of 90%, and specificity of 88%.

CONCLUSIONS

The promising results of our morphometric analysis of HDMI on ALNs offer a new means of detecting lymph node metastasis when used as a complementary imaging tool to conventional ultrasound. The fact that it does not require injection of contrast agents simplifies its use in routine clinical practice.

Diagnostic Performance of Superb Microvascular Imaging in Differentiating Benign and Malignant Axillary Lymph Nodes

ABSTRACT

The aim was to evaluate the effectiveness of superb microvascular imaging (SMI) in axillary lymph nodes (LNs).Benign and malignant LNs diagnosed via histopathological examination constituted the study subgroups. In addition to grayscale findings for morphological evaluation, vascular patterns and appearance of internal vessels were analyzed by both power Doppler ultrasound (PDUS) and SMI. The number of vascular branches was counted, and a vascularity index (VI) was calculated by SMI.Fifty-two LNs with suspicious findings in terms of metastasis (33 malignant and 19 benign) were evaluated. Diagnostic accuracy according to vascular patterns was 82% for PDUS and 92% for SMI. In the presence of asymmetric cortical thickening, there was a significant difference between benign and malignant LNs in the number of vascular branches of both thin and thick cortical sides ( P < 0.01). Mean VI was significantly higher in the malignant group ( P < 0.05). In differentiating malignancy, when a cutoff VI value was set to 9%, sensitivity was 69.7%, and specificity was 63.2%.Evaluating the vascularity of axillary LNs by SMI is a useful tool in determining the potential of axillary metastasis, especially in the absence of typical sonographic findings. Superb microvascular imaging can beneficially be used to select the most suspicious LN and suspicious area of the LN to sample.

Ultrasound imaging of the axilla

Axilla is a pyramidal-in-shape "virtual cavity" housing multiple anatomical structures and connecting the upper limb with the trunk. To the best of our knowledge, in the pertinent literature, a detailed sonographic protocol to comprehensively assess the axillary region in daily practice is lacking. In this sense, the authors have briefly described the anatomical architecture of the axilla-also using cadaveric specimens-to propose a layer-by-layer sonographic approach to this challenging district. The most common sonographic pathological findings-for each and every anatomical compartment of the axilla-have been accurately reported and compared with the corresponding histopathological features. This ultrasound approach could be considered a ready-to-use educational guidance for the assessment of the axillary region. CRITICAL RELEVANCE STATEMENT: Axilla is a pyramidal-in-shape "virtual cavity" housing multiple anatomical structures and connecting the upper limb with the trunk. The aim of this review article was to describe the anatomical architecture of the axilla, also using cadaveric specimens, in order to propose a layer-by-layer sonographic approach to this challenging district.

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.

Prediction of axillary lymph node pathological complete response to neoadjuvant therapy using nomogram and machine learning methods

Purpose

To determine the feasibility of predicting the rate of an axillary lymph node pathological complete response (apCR) using nomogram and machine learning methods.

Methods

A total of 247 patients with early breast cancer (eBC), who underwent neoadjuvant therapy (NAT) were included retrospectively. We compared pre- and post-NAT ultrasound information and calculated the maximum diameter change of the primary lesion (MDCPL): [(pre-NAT maximum diameter of primary lesion – post-NAT maximum diameter of preoperative primary lesion)/pre-NAT maximum diameter of primary lesion] and described the lymph node score (LNS) (1): unclear border (2), irregular morphology (3), absence of hilum (4), visible vascularity (5), cortical thickness, and (6) aspect ratio <2. Each description counted as 1 point. Logistic regression analyses were used to assess apCR independent predictors to create nomogram. The area under the curve (AUC) of the receiver operating characteristic curve as well as calibration curves were employed to assess the nomogram’s performance. In machine learning, data were trained and validated by random forest (RF) following Pycharm software and five-fold cross-validation analysis.

Results

The mean age of enrolled patients was 50.4 ± 10.2 years. MDCPL (odds ratio [OR], 1.013; 95% confidence interval [CI], 1.002–1.024; p=0.018), LNS changes (pre-NAT LNS – post-NAT LNS; OR, 2.790; 95% CI, 1.190–6.544; p=0.018), N stage (OR, 0.496; 95% CI, 0.269–0.915; p=0.025), and HER2 status (OR, 2.244; 95% CI, 1.147–4.392; p=0.018) were independent predictors of apCR. The AUCs of the nomogram were 0.74 (95% CI, 0.68–0.81) and 0.76 (95% CI, 0.63–0.90) for training and validation sets, respectively. In RF model, the maximum diameter of the primary lesion, axillary lymph node, and LNS in each cycle, estrogen receptor status, progesterone receptor status, HER2, Ki67, and T and N stages were included in the training set. The final validation set had an AUC value of 0.85 (95% CI, 0.74–0.87).

Conclusion

Both nomogram and machine learning methods can predict apCR well. Nomogram is simple and practical, and shows high operability. Machine learning makes better use of a patient’s clinicopathological information. These prediction models can assist surgeons in deciding on a reasonable strategy for axillary surgery.

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.

Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes

Objective

Axillary lymph node management is an important part of breast cancer surgery and the accuracy of preoperative imaging evaluation can provide adequate information to guide operation. Different molecular subtypes of breast cancer have distinct imaging characteristics. This article was aimed to evaluate the predictive ability of imaging methods in accessing the status of axillary lymph node in different molecular subtypes.

Methods

A total of 2,340 patients diagnosed with primary invasive breast cancer after breast surgery from 2013 to 2018 in Jiangsu Breast Disease Center, the First Affiliated Hospital with Nanjing Medical University were included in the study. We collected lymph node assessment results from mammography, ultrasounds, and MRIs, performed receiver operating characteristic (ROC) analysis, and calculated the sensitivity and specificity of each test. The C-statistic among different imaging models were compared in different molecular subtypes to access the predictive abilities of these imaging models in evaluating the lymph node metastasis.

Results

In Her-2 + patients, the C-statistic of ultrasound was better than that of MRI (0.6883 vs. 0.5935, p=0.0003). The combination of ultrasound and MRI did not raise the predictability compared to ultrasound alone (p=0.492). In ER/PR+HER2- patients, the C-statistic of ultrasound was similar with that of MRI (0.7489 vs. 0.7650, p=0.5619). Ultrasound+MRI raised the prediction accuracy compared to ultrasound alone (p=0.0001). In ER/PR-HER2- patients, the C-statistics of ultrasound was similar with MRI (0.7432 vs. 0.7194, p=0.5579). Combining ultrasound and MRI showed no improvement in the prediction accuracy compared to ultrasound alone (p=0.0532).

Conclusion

From a clinical perspective, for Her-2+ patients, ultrasound was the most recommended examination to assess the status of axillary lymph node metastasis. For ER/PR+HER2- patients, we suggested that the lymph node should be evaluated by ultrasound plus MRI. For ER/PR-Her2- patients, ultrasound or MRI were both optional examinations in lymph node assessment. Furthermore, more new technologies should be explored, especially for Her2+ patients, to further raise the prediction accuracy of lymph node assessment.

To assess the feasibility and diagnostic accuracy of preoperative ultrasound and ultrasound-guided fine needle aspiration cytology of axillary lymph nodes in patients of breast carcinoma

Background:

Metastasis of the lymph node is one of the most significant prognostic factors for breast cancer (BC).

Aim:

To predict positivity of the lymph node in BC patients with help of USG and USG-guided FNAC and thus to prevent unnecessary morbidity.

Methods:

50 patients of incisional/true cut biopsy-proven BC patients were included. All were subjected to mammography, USG and FNAC of the lump breast. USG-guided FNAC of the axillary lymph node was done in 25 of these patients. These findings were assessed by histological examination following dissection of the axillary lymph node.

Results:

Axillary lymph node (ALN) metastasis was present in 42 patients on histopathology; 21 patients suspicious of malignancy on preoperative USG were confirmed by HPE. Out of 88 confirmed lymph nodes evaluated on ultrasonography, 4 were benign, 18 were indeterminate and 66 were suspicious. The most promising features were tumour length/depth ratio of <1.5 in 81, absent fatty hilum in 73% and hypoechoic cortex in 74%. Assessment of axilla with USG had a sensitivity of 50%, a specificity of 100%, a PPV of 100%, an NPV of 27.59% and a diagnostic accuracy of 58%. Preoperative USG-guided FNAC had a sensitivity of 91.67%, a specificity of 100%, a PPV of 100%, an NPV of 33.33% and a diagnostic accuracy of 92%.

Conclusion:

USG can detect non-palpable axillary lymph nodes and FNAC can increase the sensitivity and specificity of this technique, which makes this procedure very promising in detecting axillary metastases in BC patients.

Models for Predicting Sentinel and Non-sentinel Lymph Nodes Based on Pre-operative Ultrasonic Breast Imaging to Optimize Axillary Strategies

Axillary strategy decisions have become more complex and controversial in considering minimally traumatic therapy instead of sentinel lymph node biopsy, axillary lymph node dissection or regional nodal irradiation for people with breast cancer. The purpose of this study was to noninvasively predict sentinel lymph node (SLN) and non-sentinel lymph node (NSLN) status based on pre-operative sonographic and clinicopathologic features to determine optimal decisions regarding axillary therapy. In total, 701 patients with breast cancer from two independent centers were retrospectively analyzed. The SLN model (SLNM) for predicting SLN status and the NSLN model (NSLNM) for predicting NSLN status were trained based on a training set using the random-forest algorithm, and their performance was validated using an independent external test set. A receiver operating characteristic curve was drawn to obtain the area under the curve, which was used to assess performance. The area under the curve for the SLNM in the training and test, respectively, was 94.2% and 83.0%, and for the NSLNM, 99.5% and 92.7%. The SLNM and NSLNM accurately predicted that 61.46% (319/519) and 17.53% (91/519), respectively, of our participants were non-metastatic. The overall benefit of the three models was 78.99% in our participants. The two models for predicting SLN and NSLN status showed excellent application potential in optimizing axillary strategies.

Imaging Updates to Breast Cancer Lymph Node Management

Metastatic lymph node involvement in breast cancer is a key determinant of the overall stage of disease and prognosis. Historically, lymph node status was determined by surgery first, with adjuvant treatments determined based on the results of the final surgical pathologic analysis. While this sequence is still applicable in many cases, neoadjuvant systemic treatment (NST) is increasingly being administered as the initial treatment. In cases that demonstrate good therapeutic response to drug therapies, NST may permit the option to perform less radical surgeries subsequently. Current breast cancer treatment has become multidisciplinary, with overlapping roles from the different disciplines. As surgery may be postponed, imaging and image-guided lymph node interventions have gained importance as the primary means of lymph node assessment. Imaging enables evaluation of all regional nodal basins, including locations where surgery is not usually performed. By differentiating limited versus extensive nodal involvement, imaging findings help determine whether initial treatment should be surgical or medical. If medical treatment with NST is indicated, imaging is performed to monitor the in vivo nodal response to drug therapy and ultimately to help determine the surgical technique to perform on the basis of the final imaging findings after NST. The authors discuss the imaging features of nodal metastases and the indications and techniques for the various image-guided procedures. The relative usefulness and shortcomings of the various imaging examinations are reviewed to discuss how they can be applied when biopsy results are not available. The role of imaging in the multidisciplinary team approach is emphasized based on past clinical trials of lymph node management and recent evolving knowledge of breast cancer staging. Online supplemental material is available for this article. ^©RSNA, 2021.

In vivo 3D Power Doppler Imaging Using Continuous Translation and Ultrafast Ultrasound

The introduction of ultrafast ultrasound and spatiotemporal filtering has significantly improved the sensitivity of Doppler ultrasound imaging. This work describes the development of a novel 3D power Doppler imaging technique which uses a 1D-array ultrasound probe that mechanically translates at a constant speed. The continuous translation allows for a fast scan of a large 3D volume without requiring complex hardware. The technique was realized in a prototype and its feasibility illustrated using phantom and in-vivo kidney and breast lesion experiments. Although this 3D Doppler imaging technique is limited in some aspects, it enables power Doppler imaging of a large volume in a short acquisition time with less computational costs.

Nomograms for Predicting Axillary Lymph Node Status Reconciled With Preoperative Breast Ultrasound Images

Introduction

The axillary lymph node (ALN) status of breast cancer patients is an important prognostic indicator. The use of primary breast mass features for the prediction of ALN status is rare. Two nomograms based on preoperative ultrasound (US) images of breast tumors and ALNs were developed for the prediction of ALN status.

Methods

A total of 743 breast cancer cases collected from 2016 to 2019 at the Second Affiliated Hospital of Harbin Medical University were randomly divided into a training set (n = 523) and a test set (n = 220). A primary tumor feature model (PTFM) and ALN feature model (ALNFM) were separately generated based on tumor features alone, and a combination of features was used for the prediction of ALN status. Logistic regression analysis was used to construct the nomograms. A receiver operating characteristic curve was plotted to obtain the area under the curve (AUC) to evaluate accuracy, and bias-corrected AUC values and calibration curves were obtained by bootstrap resampling for internal and external verification. Decision curve analysis was applied to assess the clinical utility of the models.

Results

The AUCs of the PTFM were 0.69 and 0.67 for the training and test sets, respectively, and the bias-corrected AUCs of the PTFM were 0.67 and 0.67, respectively. Moreover, the AUCs of the ALNFM were 0.86 and 0.84, respectively, and the bias-corrected AUCs were 0.85 and 0.81, respectively. Compared with the PTFM, the ALNFM showed significantly improved prediction accuracy (p < 0.001). Both the calibration and decision curves of the ALNFM nomogram indicated greater accuracy and clinical practicality. When the US tumor size was ≤21.5 mm, the Spe was 0.96 and 0.92 in the training and test sets, respectively. When the US tumor size was greater than 21.5 mm, the Sen was 0.85 in the training set and 0.87 in the test set. Our further research showed that when the US tumor size was larger than 35 mm, the Sen was 0.90 in the training set and 0.93 in the test set.

Conclusion

The ALNFM could effectively predict ALN status based on US images especially for different US tumor size.

The role of ultrasound elastography and virtual touch tissue imaging in the personalized prediction of lymph node metastasis of breast cancer

Background

This study examined the effects of different ultrasound imaging technologies in the identification and prediction of axillary lymph node metastasis of breast cancer. It also investigated the relationship between human papilloma virus (HPV) infection and axillary lymph node metastasis.

Methods

Eighty-five female patients diagnosed with breast masses participated in this study. Each patient underwent a conventional ultrasound, ultrasonic elastography, and virtual touch tissue imaging quantification (VTIQ). The differential diagnosis efficiency of a conventional ultrasound, ultrasound elastography, VTIQ, and ultrasound elastography combined with VTIQ technology was compared with a pathological diagnosis, which represents the gold standard. 85 axillary lymph node tissues and 25 normal breast tissues were used to detect HPV positive infection rate differences in different tissues.

Results

The results showed that metastatic lymph nodes and reactive lymph node hyperplasia accounted for 54.12% and 45.88% of the 85 axillary lymph nodes of breast cancer, respectively. The conventional ultrasound, ultrasound elastography, and VTIQ scores of metastatic lymph nodes were significantly higher than those of reactive lymph node hyperplasia (P<0.05). The diagnostic sensitivity (Se) (91.30%), specificity (Sp) (92.31%), accuracy (Ac) (91.76%), positive predictive value (PPV) (93.33%), and negative predictive value (NPV) (90.00%) of ultrasound elastography combined with VTIQ technology were the highest among the diagnostic efficiency test results of different computer ultrasound imaging technologies. The positive infection rate of HPV in metastatic lymph node tissues was significantly higher than that in reactive lymph node hyperplasia and normal breast tissues (P<0.05).

Conclusions

Combining ultrasound elastography with VTIQ technology has high value in the differential diagnosis of axillary lymph nodes of breast cancer. Further, it appears that HPV infection may have an etiological role in lymph node metastasis in breast cancer patients.

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.

A Comparison of the Diagnostic Value of Positron Emission Tomography/Computed Tomography and Ultrasound for the Detection of Metastatic Axillary Nodal Disease in Treatment-Naive Breast Cancer

ABSTRACT

The objective of this study was to describe the diagnostic value of positron emission tomography/computed tomography (PET/CT) and ultrasound (US) for identifying metastatic axillary disease in primary breast cancer. This is a retrospective review of 240 patients with treatment-naive unilateral primary breast cancer of at least stage T2. Eighty-five patients met our inclusion criteria. Initial whole-body PET/CT and axillary US examinations were reviewed and compared with the criterion standard of fine-needle aspiration cytology. Sensitivity, accuracy, and positive predictive value (PPV) for each modality were computed. Because of all positive US cases, specificity and negative predictive value of US were not determined. Sensitivity and accuracy between modalities were compared using McNemar test. The majority of the patients were White women with clinical inflammatory breast cancer and with histologically invasive ductal carcinoma. The most common tumor and nodal stage was T4N3. The tumors were predominantly estrogen receptor positive, progesterone receptor negative, and human epidermal growth factor receptor 2 negative. The sensitivities of PET/CT and US were 96.2% and 100%, respectively. The accuracies for PET/CT and US were 91.8% and 94.1%, respectively. The PPV for PET/CT was 95.1%, and for US, the PPV was 94.1%. No significant difference in sensitivity or accuracy was shown between PET/CT and US for the diagnosis of metastatic axillary nodal disease. Three of 85 cases showed discordance between negative PET/CT and positive US and fine-needle aspiration cytology.

Axillary ultrasound during neoadjuvant systemic therapy in triple-negative breast cancer patients

PURPOSE

To investigate the value of performing mid-treatment axillary ultrasound (AUS) in triple-negative breast cancer (TNBC) patients who are undergoing neoadjuvant systemic therapy (NAST) by determining the optimal cutoff number of abnormal nodes associated with residual nodal disease on surgical pathology.

MATERIALS AND METHODS

This sub-study, an interim analysis of an ongoing single-institution clinical trial enrolling patients with stage I-III TNBC, included 106 patients. Number of abnormal nodes at mid-treatment was assessed and recorded by experienced breast radiologists, who empirically categorized lymph nodes using a binary approach of sonographically-normal versus abnormal. Pathologic lymph node positivity was defined as presence of macrometastasis or micrometastasis in ≥1 axillary node from sentinel lymph node biopsy and/or axillary lymph node dissection.

RESULTS

Of 106 patients, 26 (25 %) had residual nodal disease and 80 (75 %) had no nodal disease at surgery. Median number of abnormal nodes at mid-treatment was 5 (standard deviation [SD], 5) for patients with residual nodal disease and 0 (SD, 2) for patients with no nodal disease at surgery (p < 0.0001). TNBC patients with >4 abnormal nodes at mid-treatment had a significantly higher chance of being node-positive at surgery (AUC = 0.908, p < 0.0001; PPV = 90 %).

CONCLUSION

Our data suggest that a cutoff of >4 abnormal nodes on mid-treatment AUS is associated with residual disease post-NAST. If our findings are substantiated by subsequent analyses, then mid-treatment AUS could be used to identify patients unlikely to achieve nodal pathologic complete response and who should be offered alternative therapy.

Axillary Nodal Evaluation in Breast Cancer: State of the Art

Axillary lymph node (LN) metastasis is the most important predictor of overall recurrence and survival in patients with breast cancer, and accurate assessment of axillary LN involvement is an essential component in staging breast cancer. Axillary management in patients with breast cancer has become much less invasive and individualized with the introduction of sentinel LN biopsy (SLNB). Emerging evidence indicates that axillary LN dissection may be avoided in selected patients with node-positive as well as node-negative cancer. Thus, assessment of nodal disease burden to guide multidisciplinary treatment decision making is now considered to be a critical role of axillary imaging and can be achieved with axillary US, MRI, and US-guided biopsy. For the node-positive patients treated with neoadjuvant chemotherapy, restaging of the axilla with US and MRI and targeted axillary dissection in addition to SLNB is highly recommended to minimize the false-negative rate of SLNB. Efforts continue to develop prediction models that incorporate imaging features to predict nodal disease burden and to select proper candidates for SLNB. As methods of axillary nodal evaluation evolve, breast radiologists and surgeons must work closely to maximize the potential role of imaging and to provide the most optimized treatment for patients.

Diagnostic performance of axillary ultrasound and standard breast MRI for differentiation between limited and advanced axillary nodal disease in clinically node-positive breast cancer patients

Preoperative differentiation between limited (pN1; 1-3 axillary metastases) and advanced (pN2-3; ≥4 axillary metastases) nodal disease can provide relevant information regarding surgical planning and guiding adjuvant radiation therapy. The aim was to evaluate the diagnostic performance of preoperative axillary ultrasound (US) and breast MRI for differentiation between pN1 and pN2-3 in clinically node-positive breast cancer. A total of 49 patients were included with axillary metastasis confirmed by US-guided tissue sampling. All had undergone breast MRI between 2008-2014 and subsequent axillary lymph node dissection. Unenhanced T2-weighted MRI exams were reviewed by two radiologists independently. Each lymph node on the MRI exams was scored using a confidence scale (0-4) and compared with histopathology. Diagnostic performance parameters were calculated for differentiation between pN1 and pN2-3. Interobserver agreement was determined using Cohen's kappa coefficient. At final histopathology, 67.3% (33/49) and 32.7% (16/49) of patients were pN1 and pN2-3, respectively. Breast MRI was comparable to US in terms of accuracy (MRI reader 1 vs US, 71.4% vs 69.4%, p = 0.99; MRI reader 2 vs US, 73.5% vs 69.4%, p = 0.77). In the case of 1-3 suspicious lymph nodes, pN2-3 was observed in 30.4% on US (positive predictive value (PPV) 69.6%) and in 22.2-24.3% on MRI (PPV 75.7-77.8%). In the case of ≥4 suspicious lymph nodes, pN1 was observed in 33.3% on US (negative predictive value (NPV) 66.7%) and in 38.5-41.7% on MRI (NPV 58.3-61.5%). Interobserver agreement was considered good (k = 0.73). In clinically node-positive patients, the diagnostic performance of axillary US and breast MRI is comparable and limited for accurate differentiation between pN1 and pN2-3. Therefore, there seems no added clinical value of preoperative breast MRI regarding nodal staging in patients with positive axillary US.

Lymph Node Imaging in Patients with Primary Breast Cancer: Concurrent Diagnostic Tools

The detection of lymph node metastasis affects the management of patients with primary breast cancer significantly in terms of staging, treatment, and prognosis. The main goal for the radiologist is to determine and detect the presence of metastatic disease in nonpalpable axillary lymph nodes with a positive predictive value that is high enough to initially select patients for upfront axillary lymph node dissection. Features that are suggestive of axillary adenopathy may be seen with different imaging modalities, but ultrasound is the method of choice for evaluating axillary lymph nodes and for performing image-guided lymph node interventions. This review aims to provide a comprehensive overview of the available imaging modalities for lymph node assessment in patients diagnosed with primary breast cancer. IMPLICATIONS FOR PRACTICE: The detection of lymph node metastasis affects the management of patients with primary breast cancer. The main goal for the radiologist is to detect lymph node metastasis in patients to allow for the selection of patients who should undergo upfront axillary lymph node dissection. Features that are suggestive of axillary adenopathy may be seen with mammography, computed tomography, and magnetic resonance imaging, but ultrasonography is the imaging modality of choice for evaluating axillary lymph nodes. A normal axillary lymph node is characterized by a reniform shape, a maximal cortical thickness of 3 mm without focal bulging, smooth margins, and, depending on size, a discernable central fatty hilum.

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.

L’exploration axillaire : un standard du bilan préthérapeutique

L’exploration préthérapeutique axillaire est une étape majeure du bilan initial du cancer du sein. L’échographie associée à un prélèvement est actuellement recommandée en première intention. L’IRM et la TEP/TDM au 18FDG sont utiles dans l’évaluation ganglionnaire axillaire. Les sensibilités et spécificités des examens d’imagerie sont globalement identiques, et leur combinaison permet d’obtenir les meilleures performances. Actuellement, la technique du ganglion sentinelle est indispensable en cas de tumeurs mammaires T1-T2 N0 et en cas d’adénopathie suspecte échographiquement avec cytoponction ou microbiopsie négative.

A Pictorial Review of Sonography of Intramammary Lymph Nodes: When to Care and What to Do About It

This pictorial essay reviews and illustrates benign and malignant features of intramammary lymph nodes on mammography, ultrasound, and magnetic resonance imaging, including a review of the clinical and the prognostic significance in patients with known breast cancer. This pictorial essay discusses management suggestions for intramammary lymph nodes in patients with breast cancer.

Application of Real-time Elastography Ultrasound in the Diagnosis of Axillary Lymph Node Metastasis in Breast Cancer Patients

The pathological status of axillary lymph nodes (ALN) plays a critical role in the staging and treatment of patients with breast cancer. Therefore, differential diagnosis of metastatic ALN is highly desirable in the clinic. We used real-time elastography (RTE) and gray-scale ultrasound to generate a new scoring system for determining ALN status and estimate their performance of this system. Ninety-seven ALNs were examined by both gray-scale ultrasound and RTE. The performance of gray-scale ultrasound was evaluated by the sum of scores according to its features. RTE images were determined by a modulated scoring system based on the percentage and distribution of hypoechoic cortex regions in the ALNs. Strain ratio was also calculated. Diagnostic performance was obtained by receiver operating characteristic curve analysis with pathologic findings used as the reference standard. The sensitivity, specificity and accuracy were 92%, 73% and 83%, respectively, for gray-scale ultrasound; 78%, 93%, 86%, respectively, for RTE; 88%, 96% and 92%, respectively, for the combined evaluation (AUC = 0.963), and 87%, 76% and 81%, respectively, for strain ratio. Gray-scale ultrasonography had a better sensitivity than RTE (92% vs 78%, P = 0.039), while the specificity for RTE was superior to that of gray-scale ultrasonography (93% vs 73%, P = 0.012). In conclusion, RTE showed a high specificity for evaluating the ALN status and may improve the diagnostic accuracy when combined with gray-scale ultrasound.

Value of ultrasound-guided fine needle aspiration in diagnosing axillary lymph node recurrence after breast cancer surgery

BACKGROUND

This article aims to assess the diagnostic performance of ultrasound-guided fine needle aspiration (US-FNA) in diagnosing axillary lymph node (ALN) recurrence in patients with a history of breast cancer.

METHODS

From January 2005 to June 2015, 231 US-FNA examinations performed for suspicious axillary lesions in 218 patients with a history of breast cancer were included. Diagnostic performance of US-FNA for ALN recurrence were evaluated.

RESULTS

Of the 231 US-FNA examinations, 172 (74.5%) obtained negative and 59 (25.5%) obtained positive cytological results. All US-FNA-negative axillary lesions were considered imaging-cytology concordant and underwent follow-up, with one false-negative result (false negative rate, 1.6% [1/60]). The overall sensitivity, specificity, PPV and NPV of US-FNA for diagnosing ALN recurrence/metastasis per examination were 98.3% (59/60), 100% (171/171), 100% (59/59) and 99.4% (171/172). When excluding nine patients with newly developed contralateral breast cancer, the sensitivity, specificity, PPV and NPV of US-FNA for diagnosing ALN recurrence was 98.1% (51/52),100% (170/170),100% (51/51) and 99.4% (170/171).

CONCLUSIONS

US-FNA is a reliable method for diagnosing axillary recurrence in patients with a history of breast cancer.

Correlation between Ultrasound Appearance of Small Breast Cancer and Axillary Lymph Node Metastasis

To study the correlation of ultrasonographic signs of small breast cancer (maximum diameter ≤2.0 cm) with axillary lymph node metastasis, pre-operative ultrasonographic images of 153 small breast malignant neoplasms in 143 breast cancer patients were analyzed according to their pathologic features. Of the small breast tumors included, 47 showed axillary lymph node metastasis. Diagnosis of all patients was obtained with radical axillary surgery or a sentinel lymph node biopsy procedure. Ultrasonographic signs included irregular shape, microlobulated contour, spiculation, microcalcification, posterior echo attenuation, blood-flow grade, perforating vessels, changes in fascia or cooper's ligament and maximum cortical thickness of lymph nodes. The relationship between ultrasonographic features and axillary lymph node metastasis was analyzed using a chi-square test for univariate distributions and logistic regression for multivariate analysis. A logistic regression model was established by taking the pathologic diagnosis of lymph node metastasis as the dependent variable and the ultrasonographic signs of each small breast cancer as independent variables. In small breast cancer, characteristics such as perforating vessels and maximum cortical thickness of lymph nodes >3.0 mm correlated well with axillary lymph node metastasis as determined by univariate analysis (χ² = 13.945, 51.276, respectively, p <0.05) and multivariate analysis (OR = 48.783, 46.754, respectively, p <0.05).

Computed tomography and magnetic resonance imaging evaluation of pelvic lymph node metastasis in bladder cancer

Background

Accurate evaluation of lymph node metastasis in bladder cancer (BCa) is important for disease staging, treatment selection, and prognosis prediction. In this study, we aimed to evaluate the diagnostic accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) for metastatic lymph nodes in BCa and establish criteria of imaging diagnosis.

Methods

We retrospectively assessed the imaging characteristics of 191 BCa patients who underwent radical cystectomy. The data regarding size, shape, density, and diffusion of the lymph nodes on CT and/or MRI were obtained and analyzed using Kruskal–Wallis test and χ² test. The optimal cutoff value for the size of metastatic node was determined using the receiver operating characteristic (ROC) curve analysis.

Results

A total of 184 out of 3317 resected lymph nodes were diagnosed as metastatic lymph nodes. Among 82 imaging-detectable lymph nodes, 51 were confirmed to be positive for metastasis. The detection rate of metastatic nodes increased along with more advanced tumor stage (P < 0.001). Once the ratio of short- to long-axis diameter ≤ 0.4 or fatty hilum was observed in lymph nodes on imaging, it indicated non-metastases. Besides, lymph nodes with spiculate or obscure margin or necrosis indicated metastases. Furthermore, the short diameter of 6.8 mm was the optimal threshold to diagnose metastatic lymph node, with the area under ROC curve of 0.815.

Conclusions

The probability of metastatic nodes significantly increased with more advanced T stages. Once lymph nodes are detected on imaging, the characteristic signs should be paid attention to. The short diameter > 6.8 mm may indicate metastatic lymph nodes in BCa.

Preoperative Axillary Lymph Node Evaluation in Breast Cancer: Current Issues and Literature Review

Axillary lymph node (ALN) status is an important prognostic factor for overall breast cancer survival. In current clinical practice, ALN status is evaluated before surgery via multimodal imaging and physical examination. Mammography is typically suboptimal for complete ALN evaluation. Currently, ultrasonography is widely used to evaluate ALN status; nonetheless, results may vary according to operator. Ultrasonography is the primary imaging modality for evaluating ALN status. Other imaging modalities including contrast-enhanced magnetic resonance imaging, computed tomography, and positron emission tomography/computed tomography can play additional roles in axillary nodal staging.The purpose of this article is (1) to review the strengths and weaknesses of current imaging modalities for nodal staging in breast cancer patients and (2) to discuss updated guidelines for ALN management with regard to preoperative ALN imaging.

Chapter 5 Ultrasound Characteristics of Benign vs Malignant Cervical Lymph Nodes

With approximately 800 lymph nodes in the body, and more than one-third found within the head and neck, lymph nodes are a common site for neck pathology. Differentiation between benign and malignant lymph nodes is critical in accurate prognosis; similarly, treatment hinges on accurate identification of the etiology of the pathologic process. Key gray-scale and color Doppler ultrasound criteria can help accurately distinguish between benign and malignant lymph nodes.

The Diagnostic Role of Ultrasound in the Chest

Although the plain radiograph and computed tomography remain undoubtedly the primary imaging modalities in the investigation of chest pathology, ultrasound can play an important complementary role, both in the diagnostic workup of a patient and in their subsequent management. Its lack of ionizing radiation, bedside availability and dynamic imaging capacity afford ultrasound certain advantages over other techniques; particularly in the critical care setting where conventional radiography is often suboptimal. This article reviews the technique and diagnostic application of ultrasound in the assessment of pathologies of the diaphragm, pleura, lung, mediastinum and chest wall.

The role of ultrasound and lymphoscintigraphy in the assessment of axillary lymph nodes in patients with breast cancer

Breast cancer is the most common malignancy and the leading cause of death due to cancer in European women. Mammography screening programs aimed to increase the detection of early cancer stages were implemented in numerous European countries. Recent data show a decrease in mortality due to breast cancer in many countries, particularly among young women. At the same time, the number of sentinel node biopsy procedures and breast-conserving surgeries has increased. Intraoperative sentinel lymph node biopsy preceded by lymphoscintigraphy is used in breast cancer patients with no clinical signs of lymph node metastasis. Due to the limited sensitivity and specificity of physical examination in detecting metastatic lesions, developing an appropriate diagnostic algorithm for the preoperative assessment of axillary lymph nodes seems to be a challenge. The importance of ultrasound in patient qualification for sentinel lymph-node biopsy has been discussed in a number of works. Furthermore, different lymphoscintigraphy protocols have been compared in the literature. The usefulness of novel radiopharmaceuticals as well as the methods of image acquisition in sentinel lymph node diagnostics have also been assessed. The aim of this article is to present, basing on current guidelines, literature data as well as our own experience, the diagnostic possibilities of axillary lymph node ultrasound in patient qualification for an appropriate treatment as well as the role of lymphoscintigraphy in sentinel lymph node biopsy.