Preoperative axillary nodal staging with ultrasound and magnetic resonance imaging: predictive values of quantitative and semantic features

Kim, Won Hwa; Kim, Hye Jung; Lee, So Mi; Cho, Seung-Hyun; Shin, Kyung Min; Lee, Sang Yub; Lim, Jae‐Kwang; Lee, Won Kee

doi:10.1259/bjr.20180507

Cited by 10 publications

(10 citation statements)

References 25 publications

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“…On multivariate analyses, 9 variables emerged as independent predictors for ALN status, including age, vascular invasion, HER2 status, mass margin, ALN features (margin, hilum, and symmetry) on MRI, and AUS evaluation of the LN hilum and cortex. Age (<40 years), vascular invasion, and absence of ALN hilum and cortical thickening on US are reportedly risk factors for ALN metastasis, in accordance with most previous publications 10,25-29. However, the prediction value of HER2 status in previous studies was uncertain, with some studies showing no predictive value 25,30.…”

Section: Discussionsupporting

confidence: 84%

Development and Validation of Nomograms Predictive of Axillary Nodal Status to Guide Surgical Decision-Making in Early-Stage Breast Cancer

Jiang

et al. 2019

J. Cancer

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Purpose : To develop and validate nomogram models using noninvasive imaging parameters with related clinical variables to predict the extent of axillary nodal involvement and stratify treatment options based on the essential cut-offs for axillary surgery according to the ACOSOG Z0011 criteria. Materials and Methods : From May 2007 to December 2017, 1799 patients who underwent preoperative breast and axillary magnetic resonance imaging (MRI) were retrospectively studied. Patients with data on axillary ultrasonography (AUS) were enrolled. The MRI images were interpreted according to Breast Imaging Reporting and Data system (BI-RADS). Using logistic regression analyses, nomograms were developed to visualize the associations between the predictors and each lymph node (LN) status endpoint. Predictive performance was assessed based on the area under the receiver operating characteristic curve (AUC). Bootstrap resampling was performed for internal validation. Goodness-of-fit of the models was evaluated using the Hosmer-Lemeshow test. Results : Of 397 early breast cancer patients, 200 (50.4%) had disease-free axilla, 119 (30.0%) had 1 or 2 positive LNs, and 78 (19.6%) had ≥3 positive LNs. Patient age, MRI features (mass margin, LN margin, presence/absence of LN hilum, and LN symmetry/asymmetry), and AUS descriptors (presence of cortical thickening or hilum) were identified as predictors of nodal disease. Nomograms with these predictors showed good calibration and discrimination; the AUC was 0.809 for negative axillary node (N0) vs. any LN metastasis, 0.749 for 1 or 2 involved nodes vs. N0, and 0.874 for ≥3 nodes vs. ≤2 metastatic nodes. The predictive ability of the 3 nomograms with additional pathological variables was significantly greater. Conclusion : The nomograms could predict the extent of ALN metastasis and facilitate decision-making preoperatively.

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Section: Discussionsupporting

confidence: 84%

Development and Validation of Nomograms Predictive of Axillary Nodal Status to Guide Surgical Decision-Making in Early-Stage Breast Cancer

Jiang

et al. 2019

J. Cancer

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“…Color and power Doppler US examinations were performed as standard procedures to evaluate the intralesional vascularity in the lesions. An axillary US examination was performed to evaluate the axillary nodal status for all patients . As long as there was at least 1 positive lymph node present in the US scan, we considered it suspicious for metastasis.…”

Section: Methodsmentioning

confidence: 99%

Predicting Axillary Lymph Node Metastasis in Patients With Breast Invasive Ductal Carcinoma With Negative Axillary Ultrasound Results Using Conventional Ultrasound and Contrast‐Enhanced Ultrasound

Zhu

et al. 2020

J of Ultrasound Medicine

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Objectives-The purpose of this study was to establish a scoring system for predicting axillary lymph node metastasis (ALNM) in patients with breast invasive ductal carcinoma with negative axillary ultrasound (US) results. Methods-In this retrospective study, 156 breast invasive ductal carcinoma lesions from 156 women were retrospectively enrolled. The features of conventional US and contrast-enhanced ultrasound (CEUS) qualitative enhancement patterns and quantitative enhancement parameters were analyzed. Subsequently, a scoring system was created by a multivariate logistic regression analysis. Results-The results found that 60 patients (38%) showed ALNM. A scoring system was defined as risk score = 1.75 × (if lesion size ≥20 mm) + 1.93 × (if uncircumscribed margin shown on conventional US) + 1.77 × (if coarse or twisting penetrating vessels shown on CEUS). When the risk scores were less than 1.75, 1.75 to 1.93, 1.94 to 3.70, and 3.70 or higher, the risk rates of ALNM were 0% (0 of 9), 10.7% (5 of 46), 29.2% (14 of 48) and 77.4% (41 of 53), respectively. In comparison with conventional US alone, the scoring system using the combination of conventional US and CEUS showed better discrimination ability in terms of the area under the curve (0.830 versus 0.777; P = .037). Conclusions-A scoring system based on conventional US and CEUS may improve the prediction of ALNM. Key Words-axillary lymph node metastasis; breast invasive ductal carcinoma; contrast-enhanced ultrasound; conventional ultrasound B reast cancer ranks as the most prevalent type of cancer among women worldwide, accounting for nearly one-fourth of all cancers. 1 The most frequent histologic type of breast cancer is invasive ductal carcinoma (IDC). 2 In the absence of distant metastasis, axillary lymph node metastasis (ALNM) serves as an important prognostic indicator in patients with primary breast cancer. 3,4 The ALNM status can influence the clinical classification and decisions on treatment. Recent studies 5,6 have

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“…Because malignant cells enter the LN through the subcapsular sinus in the form of afferent lymphoid deposits (local diffusion), where they grow and eventually replace locally normal lymph node structures [ 40 ]. In fact, cortical thickening of metastatic lymph nodes is often found in axillary images [ 39 , 41 ]. Our results showed a significant difference in cortical thickness between the metastatic and non-metastatic groups.…”

Section: Discussionmentioning

confidence: 99%

Imaging features of sentinel lymph node mapped by multidetector-row computed tomography lymphography in predicting axillary lymph node metastasis

Zhu

et al. 2021

BMC Med Imaging

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Introduction Accurately assessing axillary lymph node (ALN) status in breast cancer is vital for clinical decision making and prognosis. The purpose of this study was to evaluate the predictive value of sentinel lymph node (SLN) mapped by multidetector-row computed tomography lymphography (MDCT-LG) for ALN metastasis in breast cancer patients. Methods 112 patients with breast cancer who underwent preoperative MDCT-LG examination were included in the study. Long-axis diameter, short-axis diameter, ratio of long-/short-axis and cortical thickness were measured. Logistic regression analysis was performed to evaluate independent predictors associated with ALN metastasis. The prediction of ALN metastasis was determined with related variables of SLN using receiver operating characteristic (ROC) curve analysis. Results Among the 112 cases, 35 (30.8%) cases had ALN metastasis. The cortical thickness in metastatic ALN group was significantly thicker than that in non-metastatic ALN group (4.0 ± 1.2 mm vs. 2.4 ± 0.7 mm, P < 0.001). Multi-logistic regression analysis indicated that cortical thickness of > 3.3 mm (OR 24.53, 95% CI 6.58–91.48, P < 0.001) had higher risk for ALN metastasis. The best sensitivity, specificity, negative predictive value(NPV) and AUC of MDCT-LG for ALN metastasis prediction based on the single variable of cortical thickness were 76.2%, 88.5%, 90.2% and 0.872 (95% CI 0.773–0.939, P < 0.001), respectively. Conclusion ALN status can be predicted using the imaging features of SLN which was mapped on MDCT-LG in breast cancer patients. Besides, it may be helpful to select true negative lymph nodes in patients with early breast cancer, and SLN biopsy can be avoided in clinically and radiographically negative axilla.

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Preoperative axillary nodal staging with ultrasound and magnetic resonance imaging: predictive values of quantitative and semantic features

Abstract: (1) Imaging features of ultrasound and MRI for preoperative axillary nodal staging can be classified into quantitative and semantic features. (2) Predictive values of each imaging features are heterogeneous for predicting nodal metastases.

Cited by 10 publications

References 25 publications

Development and Validation of Nomograms Predictive of Axillary Nodal Status to Guide Surgical Decision-Making in Early-Stage Breast Cancer

Development and Validation of Nomograms Predictive of Axillary Nodal Status to Guide Surgical Decision-Making in Early-Stage Breast Cancer

Predicting Axillary Lymph Node Metastasis in Patients With Breast Invasive Ductal Carcinoma With Negative Axillary Ultrasound Results Using Conventional Ultrasound and Contrast‐Enhanced Ultrasound

Imaging features of sentinel lymph node mapped by multidetector-row computed tomography lymphography in predicting axillary lymph node metastasis

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