Accuracy of Axillary Lymph Node Staging in Breast Cancer Patients: An Observer-Performance Study Comparison of MRI and Ultrasound

doi:10.1016/j.acra.2013.08.003

Academic Radiology

Volume 20, Issue 11, November 2013, Pages 1399-1404

https://doi.org/10.1016/j.acra.2013.08.003 Get rights and content

Purpose

To compare magnetic resonance imaging (MRI) and ultrasound (US) for axillary lymph node (LN) staging in breast cancer patients in an observer-performance study.

Materials and Methods

An observer-performance study was conducted with five breast radiologists reviewing 50 consecutive patients of newly diagnosed invasive breast cancer with the use of ipsilateral axillary MRI and US. LN status was pathologically proved in all patients. Each observer reviewed the images in two separate sessions: one for MRI and the other for US. Observers were asked to indicate their confidence of the presence of at least one ipsilateral metastatic LN on a quasi-continuous rating scale and whether they recommend percutaneous biopsy preoperatively. Receiver operating characteristic (ROC) analysis and area under the ROC curve were used to characterize diagnostic performance. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated from whether observers recommended biopsy.

Results

There were no statistically significant differences in each observer's performance between MRI and US, or in the performance of all observers as a group, in terms of ROC analysis. There were no statistically significant differences in sensitivity, specificity, PPV, or NPV between MRI and US, but there were statistically significant improvements in specificity and PPV from either MRI or US alone to MRI and US combined.

Conclusions

Observer performance on MRI and US are comparable for axillary LN staging. When US and MRI are concordant for positive findings, higher specificity and PPV can be obtained.

Section snippets

Patients

This study consisted of 50 consecutive cases with invasive breast cancer who underwent breast MRI and US examinations of the ipsilateral axilla between January and August 2009. Patient ages were between 33 and 83 years (mean, 59.9 years; median, 57 years). The histologic types of the primary lesion were infiltrating ductal carcinoma, 44 (88%) cases, and infiltrating lobular carcinoma, 6 (12%) cases. The size of the primary invasive cancers was between 1 and 125 mm (mean, 18.5 mm; median,

Results

Based on radiology reports of the US studies and final pathology results, the sensitivity, specificity, PPV, and NPV in detecting metastatic LN(s) in the 50 cases were 69% (11/16), 94% (32/34), 85% (11/13), and 87% (32/37), respectively. These data are well within the range of published statistics for axillary US (21).

The results of AUC estimates for each of the five individual observers, and for the observers as a group, are shown in Table 2. There was no statistically significant difference

Discussion

US has been used widely for evaluation of axillary LNs of breast cancer patients, and it is considered a useful tool for the detection, diagnosis, and biopsy guidance. Sensitivity and specificity of US for the detection of metastatic axillary LNs have been reported as 49% to 87% and 56% to 97%, respectively; and when combined with US-guided fine needle aspiration (FNA) or core needle biopsy, the values are 31% to 63% and 95% to 100%, respectively (21). Technical and user-experience differences

Conclusions

Observer performance for ipsilateral axillary LN staging in breast cancer patients is comparable between US and MRI. The specificity and PPV improved significantly when both MR and US are positive for metastatic LN(s), compared to either MR or US alone. The results of this study suggest that MR and US are complementary to each other for the detection of metastatic LNs and that in instances where axillary US is not initially performed, MRI could serve as the initial imaging method for staging of

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Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy
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Citation Excerpt :
They found reported the accuracies to be 77.9% and 81.1% respectively. Abe et al.49 performed radiological scoring on MRI and ultrasound and reported ROC AUC of 0.732 and 0.727, respectively. In a retrospective study, He et al.50 performed radiologist scoring on MRI with SLNB and ALND as the reference standard on 251 nodes.
Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the machine learning convolutional neural networks (CNNs) on multiparametric MRI to detect nodal metastasis with 18FDG-PET as ground truths.
Data were obtained via a retrospective search. Inclusion criteria were patients with bilateral breast MRI and 18FDG-PETand/or CT scans obtained before neoadjuvant chemotherapy. In total, 238 aLNs were obtained from 56 breast cancer patients with 18FDG-PET and/or CT and breast MRI data. Radiologists scored each node based on all MRI as diseased and non–diseased nodes. Five models were built using T1-W MRI, T2-W MRI, DCE MRI, T1-W + T2-W MRI, and DCE + T2-W MRI model. Performance was evaluated using receiver operating curve (ROC) analysis, including area under the curve (AUC).
All CNN models yielded similar performance with an accuracy ranging from 86.08% to 88.50% and AUC ranging from 0.804 to 0.882. The CNN model using T1-W MRI performed better than that using T2-W MRI in detecting nodal metastasis. CNN model using combined T1- and T2-W MRI performed the best compared to all other models (accuracy = 88.50%, AUC = 0.882), but similar in AUC to the DCE + T2-W MRI model (accuracy = 88.02%, AUC = 0.880). All CNN models performed better than radiologists in detecting nodal metastasis (accuracy = 65.8%).
xxxxxx
Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI
2020, Clinical Breast Cancer
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Our prediction performance indices were comparable or compared favorably with previous reports using different imaging methods and data (Table 2). MRI and ultrasound staging yielded ROC AUC of 0.727 and 0.732 for MRI and ultrasound, respectively.43 In a retrospective study, Zhang et al analyzed the performance of a nomogram in detection of aLN metastasis on 4211 patients and found that it had a ROC AUC of 0.701 and accuracy of 70.9%.42
Axillary lymph node status is important for breast cancer staging and treatment planning as the majority of breast cancer metastasis spreads through the axillary lymph nodes. There is currently no reliable noninvasive imaging method to detect nodal metastasis associated with breast cancer.
Magnetic resonance imaging (MRI) data were those from the peak contrast dynamic image from 1.5 Tesla MRI scanners at the pre-neoadjuvant chemotherapy stage. Data consisted of 66 abnormal nodes from 38 patients and 193 normal nodes from 61 patients. Abnormal nodes were those determined by expert radiologist based on ¹⁸Fluorodeoxyglucose positron emission tomography images. Normal nodes were those with negative diagnosis of breast cancer. The convolutional neural network consisted of 5 convolutional layers with filters from 16 to 128. Receiver operating characteristic analysis was performed to evaluate prediction performance. For comparison, an expert radiologist also scored the same nodes as normal or abnormal.
The convolutional neural network model yielded a specificity of 79.3% ± 5.1%, sensitivity of 92.1% ± 2.9%, positive predictive value of 76.9% ± 4.0%, negative predictive value of 93.3% ± 1.9%, accuracy of 84.8% ± 2.4%, and receiver operating characteristic area under the curve of 0.91 ± 0.02 for the validation data set. These results compared favorably with scoring by radiologists (accuracy of 78%).
The results are encouraging and suggest that this approach may prove useful for classifying lymph node status on MRI in clinical settings in patients with breast cancer, although additional studies are needed before routine clinical use can be realized. This approach has the potential to ultimately be a noninvasive alternative to lymph node biopsy.
Evolving imaging techniques for staging axillary lymph nodes in breast cancer
2018, Clinical Radiology
Citation Excerpt :
Similar findings were reported in a subsequent study using axial non-enhanced T1-weighted MRI in patients with newly diagnosed breast cancer, with sensitivity and specificity values of 88% and 82%.49 An observer-performance study, however, found that MRI was not significantly different to ultrasound in terms of sensitivity, specificity, PPV, or NPV at detecting metastatic nodes, although when both techniques are combined, there are statistically significant improvements in specificity and PPV compared with either technique on its own.50 In clinical practice, the majority of patients undergoing breast MRI with a known breast cancer will already have had an initial ultrasound of the axilla, and if further suspicious findings are demonstrated on MRI then a “second look” ultrasound may be indicated to characterise, and if appropriate, biopsy the abnormality, if this will influence further management.
The presence and extent of axillary nodal metastases at the time of breast cancer diagnosis is a critical factor in disease prognosis and plays a central role in deciding the best treatment for patients. Accurate assessment of the axilla is therefore an essential component in staging breast cancer. Over the years, axillary staging has evolved from surgical axillary lymph node dissection (ALND), with its numerous associated long-term complications, to the much less-radical surgical sentinel lymph node excision biopsy (SLNB), the current reference standard. In parallel, radiological staging of the axilla has become increasingly more useful as our knowledge and techniques have improved. Preoperative axillary ultrasound is used widely to stage patients with breast cancer, providing an evaluation of node morphology and allowing targeted biopsy of abnormal nodes. This is important in helping stratify which patients should proceed directly to ALND and which should undergo SLNB first. Grey-scale ultrasound on its own is not perfect and can over- and underestimate axillary disease. Newer ultrasound techniques such as elastography may help to improve diagnostic confidence when visually assessing axillary nodes; for example, in more accurately assessing the extent of axillary disease burden or in differentiating benign reactive nodes from malignant nodes in equivocal cases. The use of intradermal “microbubbles” has shown great promise in being able to locate and biopsy the sentinel lymph node under ultrasound guidance, and raises the possibility that in the future such techniques may obviate the need for surgical SLNB in select patient populations.
Using ultrasound and palpation for predicting axillary lymph node status following neoadjuvant chemotherapy – Results from the multi-center SENTINA trial
2017, Breast
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To determine cN status in clinical practice palpation and ultrasound is widely used as a standard of care [1]. While mammography and/or MRI or even PET imaging can provide further information about axillary lymph nodes [2], ultrasound is regarded as the most useful technique to determine the clinical axillary nodal status. Furthermore ultrasound allows for image-guided fine-needle-aspiration (FNA)/core-needle-biopsy (CNB) in patients with suspicious nodes to confirm presence of malignant cells among cN1 patients [3].
With the growing importance of neoadjuvant systemic therapy (NST) the assessment of post neoadjuvant axillary status is of increasing importance especially in patients who presented initially with suspicious nodes (cN1). This study aims to investigate the predictive value of palpation and axillary ultrasound of formerly cN1 patients following NST.
The SENTINA trial (SENTinel NeoAdjuvant) is a 4-arm prospective multicenter study designed to evaluate the role of sentinel node biopsy (SLNB) in the context of neoadjuvant systemic treatment (NST) of breast cancer patients.
1240 patients from 103 institutions entered the trial. 715 (arm C n = 592; arm D n = 123) patients, who presented initially cN1 underwent clinical evaluation of lymph node status following NST. Palpation alone demonstrated a sensitivity of 8.3%, specifity of 94.8% and a negative predictive value (NPV) of 46.6%. Ultrasound alone revealed a sensitivity of 23.9%, specificity 91.7%, and a NPV of 50.3%.The investigators combined classification (palpation and ultrasound) resulted in a sensitivity of 24.4%, specificity 91.4%, and a NPV of 50.3%. Investigators classified the axilla nodes as being unsuspicious (cN0) following NST in 592/715 patients; of them 298 (50.3%) were pN0, 151 (25.5%) had 1-2 histologically involved nodes and 143 (24.2%) had >2 histologically involved nodes.
The diagnostic accuracy of ultrasound and palpation following NST is unacceptably low and additional tools for evaluation of the axillary lymph node status following NST are urgently needed.
Pre-operative MRI exhibits limited utility in axillary staging for breast cancer
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Citation Excerpt :
These studies have shown no difference in accuracy between modalities with percentages similar to our findings. Interestingly though, if positive findings are concordant between the two modalities the sensitivity and PPV are improved [11]. Further MRI is also superior in determining the number of abnormal appearing nodes.
Magnetic resonance imaging (MRI) is commonly utilized in treatment planning of breast cancer patients. While axillary lymph node findings are routinely reported in these studies, the utility of these findings remains unclear.
In this retrospective study from 2008–2014, women diagnosed with invasive breast cancer who did not undergo neoadjuvant therapy were reviewed. MRI characteristics of axillary findings were compared to the final pathologic results.
210 of 338 female patients met inclusion criteria and comprised our patient cohort. MRI was found to have a sensitivity and specificity of 45% and 84%, respectively. The negative predictive value was 78% with an accuracy of 72% and a false negative rate of 14%. MRI was more often accurate in younger patients (p<0.04, CI 0.52–1.19) and those whom had a larger number of lymph nodes harvested (p<0.0001, CI −10.8 to −0.2). True positives had significantly larger primary tumors and a larger number of positive lymph nodes on final pathology.
MRI of the axilla is not a reliable tool for axillary staging in women with breast cancer.
The significance of magnetic resonance imaging (MRI) findings of the axilla after routine preoperative imaging is poorly understood. We evaluated the perioperative course including axillary findings on MRI and compared them to the final axillary pathology of 210 women with invasive breast cancer. MRI did not show adequate predictive capability in determining women with invasive cancer progression to the axilla.
Preoperative magnetic resonance imaging of the breast is often obtained for women diagnosed with breast cancer. Findings in the axilla are often commented on in the radiology reports of these studies. There is limited data evaluating the significance of axillary finding in breast cancer imaging. The current literature differs in two important ways from the findings revealed in this study. First, the majority of the current literature focuses on imaging obtained using axillary specific protocols. These findings to not contribute transferable information for the typical clinical practice as these protocols are not commonly ordered or performed. Second, currently available studies have small cohorts, typically less than one hundred patients, or are systematic reviews. This study provides analysis of 210 patients over 6 years and represents the largest single study cohort that evaluates the clinical significance of axillary findings obtained during preoperative MRI of the breast.
The findings reported here will aid clinicians when completing the preoperative work up for women diagnosed with breast cancer. Further, the subgroup analysis of our true positives presents an opportunity to potentially identify a new set of breast cancer patients that would have a greater benefit from neoadjuvant chemotherapy and thus spare them the morbidity of axillary lymph node dissection.
The value of quantitative shear wave elastography combined with conventional ultrasound in evaluating and guiding fine needle aspiration biopsy of axillary lymph node for early breast cancer: implication for axillary surgical stage
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View all citing articles on Scopus

¹: Current institution: Saga University, 5-1-1 Nabeshima, Saga, 849-8501 Japan.

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Original investigationAccuracy of Axillary Lymph Node Staging in Breast Cancer Patients: An Observer-Performance Study Comparison of MRI and Ultrasound

Purpose

Materials and Methods

Results

Conclusions

Section snippets

Patients

Results

Discussion

Conclusions

Breast

Clin Radiol

Eur J Cancer

Eur J Surg Oncol

Clin Radiol

Eur J Surg Oncol

Contin Educ Anaesth Crit Care Pain

Relation of number of positive axillary nodes to the prognosis of patients with primary breast cancer: an NSABP update

Cancer

Tree-based model for breast cancer prognostication

J. Clin Oncol

Prognostic and predictive factors on early-stage breast cancer

Oncologist

Sentinel Lymph Node Biopsy and Axillary Dissection in Breast Cancer: Results in a Large Series

J Natl Cancer Inst

Comparison of side effects between sentinel lymph node and axillary lymph node dissection for breast cancer

Ann Surg Oncol

Randomized multicenter trial of sentinel node biopsy versus standard axillary treatment in operable breast cancer: the ALMANAC Trial

J Natl Cancer Inst

A randomized comparison of sentinel-node biopsy with routine axillary dissection in breast cancer

N Engl J Med

Accuracy of predicting axillary lymph node positivity by physical examination, mammography, ultrasonography, and magnetic resonance imaging

Ann Surg Oncol

Original investigation
Accuracy of Axillary Lymph Node Staging in Breast Cancer Patients: An Observer-Performance Study Comparison of MRI and Ultrasound