Retrospective preoperative assessment of the axillary lymph nodes in patients with breast cancer and literature review

Saffar, Bann; Bennett, Michelle; Metcalf, Cecily; Burrows, Sally

doi:10.1016/j.crad.2015.04.019

Cited by 26 publications

(20 citation statements)

References 18 publications

(18 reference statements)

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“…Zhu et al [25] observed a cortical thickness of >3.5 mm as the single most important predictor of three or more axillary lymph node involvement. Saffar et al [26] noted a cortical thickness of >3mm increases the likelihood of axillary lymph node metastasis. Amonkar et al [27] in their grading system noted hilar fatty replacement correlated best with positive FNA.…”

Section: Discussionmentioning

confidence: 99%

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

Vijayaraghavan

Vedantham

Kataoka³

et al. 2017

Academic Radiology

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Rationale and Objective 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/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 and 65 were positive on FNA and axillary surgery, respectively. Sensitivity, specificity, positive- and negative-predictive values of FNA were 52/65 (80%), 54/63 (85.7%), 52/61(85.2%) and 54/67 (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% CI: 7.2–71.3, p<0.0001), 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<0.017) of positive FNA with accuracy of 0.817 (95% CI: 0.741–0.893). Conclusion 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.

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Section: Discussionmentioning

confidence: 99%

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

Vijayaraghavan

Vedantham

Kataoka³

et al. 2017

Academic Radiology

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“…If based on morphologic criteria, the sensitivity and specificity are 26%À76% and 88%À98%, respectively. Most of the previous studies testing ultrasound efficacy evaluated the entire axilla, and the diagnostic criteria of lymph node metastasis included shape, size, longitudinal-to-transverse axis ratio (L/T), cortical morphology and hilum and blood flow status (Saffar et al 2015;Van Berckelaer et al 2016;Akissue de Camargo Teixeira et al 2017;Schwentner et al 2017). While not evaluating the association between ultrasound features and pathology of individual single lymph nodes, this design has an obvious drawback: the ultrasound features of a single lymph node are not used to predict its specific pathology, which may result in prediction bias.…”

Section: Introductionmentioning

confidence: 99%

Lymph Node Predictive Model with in Vitro Ultrasound Features for Breast Cancer Lymph Node Metastasis

Han

Yang

Liu

et al. 2020

Ultrasound in Medicine & Biology

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Ultrasound diagnosis of axillary lymph nodes has the advantages of ease, convenience and low cost; however, most previous studies evaluated lymph node metastasis of the entire axilla rather than the association between the ultrasound features of a single lymph node and its pathology. This prospective study was performed to explore the ultrasound features of lymph nodes observed in bionic medium in vitro and to develop a lymph node-specific model for prediction of metastasis based on analysis of the association between the ultrasound features and pathology of each lymph node.

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“…12 The results of this study showed that the cortical thickness and shape of ALNs were associated with a higher risk of ALN metastasis or a higher axillary tumor burden, which was basically consistent with the findings of previous studies. 13,14 In this study, cortical thickness was not specifically graded but was only evaluated at the time of initial diagnosis. The results still showed that with increased cortical thickness, the higher the risk of ALN metastasis and the greater the risk of high tumor burden.…”

Section: Discussionmentioning

confidence: 99%

<p>Establishment of Simple Nomograms for Predicting Axillary Lymph Node Involvement in Early Breast Cancer</p>

Zong¹,

Deng²,

Ge³

et al. 2020

CMAR

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These authors contributed equally to this workPurpose: 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.

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Retrospective preoperative assessment of the axillary lymph nodes in patients with breast cancer and literature review

Cited by 26 publications

References 18 publications

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

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

Lymph Node Predictive Model with in Vitro Ultrasound Features for Breast Cancer Lymph Node Metastasis

<p>Establishment of Simple Nomograms for Predicting Axillary Lymph Node Involvement in Early Breast Cancer</p>

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