Preoperative axillary lymph node evaluation in breast cancer patients by breast magnetic resonance imaging (MRI): Can breast MRI exclude advanced nodal disease? Eur Radiol. 2016;26:3865-3873. [PMID: 26843011 DOI: 10.1007/s00330-016-4235-4]

De-escalation of Axillary Surgery After Neoadjuvant Therapy

Surgical de-escalation of the axilla has evolved over the past 28 years since the emergence of sentinel lymph node surgery. Well-documented complications of the once standard of care axillary lymph node dissection (ALND), including lymphedema, led physician scientists towards a progressive push to study and incorporate less invasive techniques in the axilla. Many trials have justified oncologic safety of axillary de-escalation in patients who are spared neoadjuvant treatment. The applicability in the neoadjuvant setting, however, is less clear and axillary surgical approaches in this patient population have evolved at a slower pace. This review aims to analyze current data in axillary management for patients undergoing neoadjuvant treatment and to discuss current surgical approaches based on nodal pathologic response.

Multi-modality radiomics model predicts axillary lymph node metastasis of breast cancer using MRI and mammography

OBJECTIVES

We aimed to develop a multi-modality model to predict axillary lymph node (ALN) metastasis by combining clinical predictors with radiomic features from magnetic resonance imaging (MRI) and mammography (MMG) in breast cancer. This model might potentially eliminate unnecessary axillary surgery in cases without ALN metastasis, thereby minimizing surgery-related complications.

METHODS

We retrospectively enrolled 485 breast cancer patients from two hospitals and extracted radiomics features from tumor and lymph node regions on MRI and MMG images. After feature selection, three random forest models were built using the retained features, respectively. Significant clinical factors were integrated with these radiomics models to construct a multi-modality model. The multi-modality model was compared to radiologists' diagnoses on axillary ultrasound and MRI. It was also used to assist radiologists in making a secondary diagnosis on MRI.

RESULTS

The multi-modality model showed superior performance with AUCs of 0.964 in the training cohort, 0.916 in the internal validation cohort, and 0.892 in the external validation cohort. It surpassed single-modality models and radiologists' ALN diagnosis on MRI and axillary ultrasound in all validation cohorts. Additionally, the multi-modality model improved radiologists' MRI-based ALN diagnostic ability, increasing the average accuracy from 70.70 to 78.16% for radiologist A and from 75.42 to 81.38% for radiologist B.

CONCLUSION

The multi-modality model can predict ALN metastasis of breast cancer accurately. Moreover, the artificial intelligence (AI) model also assisted the radiologists to improve their diagnostic ability on MRI.

CLINICAL RELEVANCE STATEMENT

The multi-modality model based on both MRI and mammography images allows preoperative prediction of axillary lymph node metastasis in breast cancer patients. With the assistance of the model, the diagnostic efficacy of radiologists can be further improved.

KEY POINTS

• We developed a novel multi-modality model that combines MRI and mammography radiomics with clinical factors to accurately predict axillary lymph node (ALN) metastasis, which has not been previously reported. • Our multi-modality model outperformed both the radiologists' ALN diagnosis based on MRI and axillary ultrasound, as well as single-modality radiomics models based on MRI or mammography. • The multi-modality model can serve as a potential decision support tool to improve the radiologists' ALN diagnosis on MRI.

Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics

OBJECTIVES

Accurate axillary evaluation plays an important role in prognosis and treatment planning for breast cancer. This study aimed to develop and validate a dynamic contrast-enhanced (DCE)-MRI-based radiomics model for preoperative evaluation of axillary lymph node (ALN) status in early-stage breast cancer.

METHODS

A total of 410 patients with pathologically confirmed early-stage invasive breast cancer (training cohort, N = 286; validation cohort, N = 124) from June 2018 to August 2022 were retrospectively recruited. Radiomics features were derived from the second phase of DCE-MRI images for each patient. ALN status-related features were obtained, and a radiomics signature was constructed using SelectKBest and least absolute shrinkage and selection operator regression. Logistic regression was applied to build a combined model and corresponding nomogram incorporating the radiomics score (Rad-score) with clinical predictors. The predictive performance of the nomogram was evaluated using receiver operator characteristic (ROC) curve analysis and calibration curves.

RESULTS

Fourteen radiomic features were selected to construct the radiomics signature. The Rad-score, MRI-reported ALN status, BI-RADS category, and tumour size were independent predictors of ALN status and were incorporated into the combined model. The nomogram showed good calibration and favourable performance for discriminating metastatic ALNs (N + (≥1)) from non-metastatic ALNs (N0) and metastatic ALNs with heavy burden (N + (≥3)) from low burden (N + (1-2)), with the area under the ROC curve values of 0.877 and 0.879 in the training cohort and 0.859 and 0.881 in the validation cohort, respectively.

CONCLUSIONS

The DCE-MRI-based radiomics nomogram could serve as a potential non-invasive technique for accurate preoperative evaluation of ALN burden, thereby assisting physicians in the personalized axillary treatment for early-stage breast cancer patients.

ADVANCES IN KNOWLEDGE

This study developed a potential surrogate of preoperative accurate evaluation of ALN status, which is non-invasive and easy-to-use.

Diagnostic performance of MRI for assessing axillary lymph node status after neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis

OBJECTIVE

This systematic review examined the diagnostic performance of magnetic resonance imaging (MRI) for assessing axillary lymph node status (ALNS) after neoadjuvant chemotherapy (NAC) in breast cancer patients.

METHODS

We searched PubMed, Embase, Cochrane Library, and Web of Science to identify relevant studies and used the QUADAS-2 tool to assess methodological quality of eligible studies. We used STATA version 12.0 to perform data pooling, heterogeneity testing, subgroup analysis, and sensitivity analysis.

RESULTS

For the 21 enrolled studies, including 2875 patients, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were respectively 0.63 (95% CI: 0.53-0.72), 0.75 (95% CI: 0.68-0.81), 2.52 (95% CI: 1.98-3.19), 0.50 (95% CI: 0.39-0.63), and 5.08 (95% CI: 3.38-7.63). The AUC was 0.76 (95% CI: 0.72-0.79). I2 values of sensitivity (I2 = 94.41%) and specificity (I2 = 88.97%) were both > 50%. For the initial positive ALN patients, the pooled sensitivity and specificity were 0.64 (95% CI: 0.53-0.75) and 0.74 (95% CI: 0.64-0.82), respectively. Sensitivity analyses by focusing on studies with MRI performed post-NAC, studies using DCE-MRI, or studies with low risk of bias showed similar results to the primary analyses.

CONCLUSION

MRI may have suboptimal diagnostic value in assessing ALNS after NAC for breast cancer patients. Due to the inconsistency of NAC regimens, the variability of axillary surgery, and the lack of time interval between MRI and surgery, further studies are needed to confirm our findings.

CLINICAL RELEVANCE STATEMENT

Our study provided the diagnostic value of MRI in assessing axillary lymph node status after neoadjuvant chemotherapy for breast cancer patients.

KEY POINTS

• MRI may have suboptimal diagnostic value in assessing axillary lymph node status after NAC for general breast cancer patients. • The initial axillary lymph node status has little impact on the diagnostic efficacy of MRI. • The substantial heterogeneity among studies highlights the need for further studies to provide more high-quality evidence in this field.

Evaluation of Lymphatic Vessel Invasion Determined by D2-40 Using Preoperative MRI-Based Radiomics for Invasive Breast Cancer

RATIONALE AND OBJECTIVES

Preoperative prediction of LVI status can facilitate personalized therapeutic planning. This study aims to investigate the efficacy of preoperative MRI-based radiomics for predicting lymphatic vessel invasion (LVI) determined by D2-40 in patients with invasive breast cancer.

MATERIALS AND METHODS

A total of 203 patients with pathologically confirmed invasive breast cancer, who underwent preoperative breast MRI, were retrospectively enrolled and randomly assigned to the following cohorts: training cohort (n=141) and test cohort (n=62). Then, univariate and multivariate logistic regression were performed to select independent risk factors and build a clinical model. Afterwards, least absolute shrinkage and selection operator (LASSO) logistic regression was performed to select predictive features extracted from the early and delay enhancement dynamic contrast-enhanced (DCE)-MRI images, and a radiomics signature was established. Subsequently, a nomogram model was constructed by incorporating the radiomics score and risk factors. Receiver operating characteristic curves were performed to determine the performance of various models. The efficacy of the various models was evaluated using calibration and decision curves.

RESULTS

Fourteen radiomics features were selected to construct the radiomics model. The size of the lymph node was identified as an independent risk factor of the clinical model. The nomogram model demonstrated the best calibration and discrimination performance in both the training and test cohorts, with an area under the curve of 0.873 (95% confidence interval [CI]: 0.807-0.923) and 0.902 (95% CI: 0.800-0.963), respectively. The decision curve illustrated that the nomogram model added more net benefits, when compared to the radiomics signature and clinical model.

CONCLUSION

The nomogram model based on preoperative DCE-MRI images exhibits satisfactory efficacy for the noninvasive prediction of LVI determined by D2-40 in invasive breast cancer.

Diagnostic accuracy of pre-operative breast magnetic resonance imaging (MRI) in predicting axillary lymph node metastasis: variations in intrinsic subtypes, and strategy to improve negative predictive value-an analysis of 2473 invasive breast cancer patients

BACKGROUND

The value and utility of axillary lymph node (ALN) evaluation with MRI in breast cancer were not clear for various intrinsic subtypes. The aim of the current study is to test the potential of combining breast MRI and clinicopathologic factors to identify low-risk groups of ALN metastasis and improve diagnostic performance.

MATERIAL AND METHODS

Patients with primary operable invasive breast cancer with pre-operative breast MRI and post-operative pathologic reports were retrospectively collected from January 2009 to December 2021 in a single institute. The concordance of MRI and pathology of ALN status were determined, and also analyzed in different intrinsic subtypes. A stepwise strategy was designed to improve MRI-negative predictive value (NPV) on ALN metastasis.

RESULTS

2473 patients were enrolled. The diagnostic performance of MRI in detecting metastatic ALN was significantly different between intrinsic subtypes (p = 0.007). Multivariate analysis identified tumor size and histologic type as independent predictive factors of ALN metastases. Patients with HER-2 (MRI tumor size ≤ 2 cm), or TNBC (MRI tumor size ≤ 2 cm) were found to have MRI-ALN-NPV higher than 90%, and these false cases were limited to low axillary tumor burden.

CONCLUSION

The diagnostic performance of MRI to predict ALN metastasis varied according to the intrinsic subtype. Combined pre-operative clinicopathologic factors and intrinsic subtypes may increase ALN MRI NPV, and further identify some groups of patients with low risks of ALN metastasis, high NPV, and low burdens of axillary disease even in false-negative cases.

Future Directions in the Assessment of Axillary Lymph Nodes in Patients with Breast Cancer

Background and Objectives: Breast cancer (BC) is a leading cause of morbidity and mortality worldwide, and accurate assessment of axillary lymph nodes (ALNs) is crucial for patient management and outcomes. We aim to summarize the current state of ALN assessment techniques in BC and provide insights into future directions. Materials and Methods: This review discusses various imaging techniques used for ALN evaluation, including ultrasound, computed tomography, magnetic resonance imaging, and positron emission tomography. It highlights advancements in these techniques and their potential to improve diagnostic accuracy. The review also examines landmark clinical trials that have influenced axillary management, such as the Z0011 trial and the IBCSG 23-01 trial. The role of artificial intelligence (AI), specifically deep learning algorithms, in improving ALN assessment is examined. Results: The review outlines the key findings of these trials, which demonstrated the feasibility of avoiding axillary lymph node dissection (ALND) in certain patient populations with low sentinel lymph node (SLN) burden. It also discusses ongoing trials, including the SOUND trial, which investigates the use of axillary ultrasound to identify patients who can safely avoid sentinel lymph node biopsy (SLNB). Furthermore, the potential of emerging techniques and the integration of AI in enhancing ALN assessment accuracy are presented. Conclusions: The review concludes that advancements in ALN assessment techniques have the potential to improve patient outcomes by reducing surgical complications while maintaining accurate disease staging. However, challenges such as standardization of imaging protocols and interpretation criteria need to be addressed. Future research should focus on large-scale clinical trials to validate emerging techniques and establish their efficacy and cost-effectiveness. Over-all, this review provides valuable insights into the current status and future directions of ALN assessment in BC, highlighting opportunities for improving patient care.

Axillary Lymph Nodes in Breast Cancer Patients After COVID-19 Vaccine

One of the side effects of vaccines used to end the COVID-19 epidemic is non-specifically enlarged axillary lymph nodes. Such lymphadenopathy detected during clinical examination of breast cancer patients may require additional imaging or interventional procedures that should not normally be performed. This study has been designed to estimate the incidence of palpable enlarged axillary lymph node in breast cancer patients who had received COVID-19 vaccination in the past 3 months in the same arm as compared to those without vaccination. Breast cancer patients admitted to M.U. Medical Faculty Breast polyclinic between January 2021 and March 2022 were screened, and clinical staging was performed after thorough clinical examination. Among these patients with suspected enlarged axillary lymph node and those undergoing sentinel lymph node biopsy (SLNB), they were divided into two groups as vaccinated and unvaccinated. Age, menopausal status, tumor size, tumor location, surgery, pathology results, hormonal receptor status, and SLNB results were statistically compared with groups. There was no significant difference between groups in terms of age, menopause, tumor size, tumor location, surgery, pathological results, and hormone receptor status. The SLNB being reported as reactive only was 89.1% in the vaccinated group and 73.2% in the non-vaccinated group which was statistically significant different. Reactive lymph nodes were commonly found with an excess of 16% in patients who had received COVID-19 vaccination in the past 3 months. This required caution and additional examination of the axillary lymph nodes in this period.

Diagnostic accuracy of magnetic resonance imaging to evaluate axillary lymph node status in breast cancer patients receiving neoadjuvant chemotherapy

OBJECTIVES

Axillary lymph node status is an important prognostic factor for breast cancer patients. This study aimed to assess the accuracy of MRI in assessing the axillary nodal status in breast cancer patients receiving neo-adjuvant chemotherapy (NACT).

METHODS

Data were retrospectively collected for 88 patients between 2011 and 2016 from the hospital records. All patients had baseline MRI, followed by the end of neoadjuvant chemotherapy MRI. Patient demographics, cancer type, grade, stage, receptor status, and the number of positive lymph nodes identified on the baseline and preoperative MRI were recorded. The imaging results were compared to post-operative histopathological lymph node findings. The median patient age of the patients was 54 years (32-77 years).

RESULTS

There were 67 (76.1%) patients with histologically proven positive axillary lymph nodes on baseline MRI. The overall conversion from abnormal to normal axillary nodes following chemotherapy (ypN0) was 38.8% (26 patients out of 67). The sensitivity and specificity of MRI for predicting axillary status was 68.85 and 85.71%, respectively, with an overall MRI diagnostic accuracy of 73.07%.

CONCLUSION

MRI has low sensitivity and diagnostic accuracy in predicting axillary nodal status in breast cancer patients receiving neoadjuvant chemotherapy. Given the low NPV of MRI of the axilla, a negative MRI does not obviate the need for definitive axillary surgery.

ADVANCES IN KNOWLEDGE

In its current state, MRI cannot obviate the need for axillary surgery in patients receiving NACT. Long: short axis ratio (L: S) of the axillary lymph node is not a good predictor of axillary metastases.

Magnetic resonance imaging evaluation of single axillary lymph node metastasis in breast cancer: Emphasis on the location of lymph nodes

To evaluate the frequency and location of abnormal lymph nodes (LNs) in breast cancer patients with a single axillary lymph node (ALN) metastasis on breast magnetic resonance imaging (MRI). We retrospectively reviewed the MRI findings of 219 consecutive patients with breast cancer with single ALN metastasis who were surgically confirmed at our institution between January 2018 and December 2018. The morphological features and locations of the abnormal LN on MRI were analyzed. Pathology reports were reviewed to evaluate the size of the metastases and whether they were sentinel LNs (SLNs). Of the 219 patients with a single ALN metastasis, 56 (25.6%) showed abnormal MRI findings. Of these, 54 (96.4%) had either the lowest or second-lowest LN in the level I axilla. In 184 (91.5%) of 201 patients who underwent SLN biopsy, the metastatic LN were SLN. Macrometastases were found more frequently in cases with abnormal LNs than in those with normal-looking LNs (P = .004). The most frequent morphological feature of metastatic ALNs was a diffuse cortical thickening of 3 to 5 mm (37.5%). Although MRI findings of single ALN metastasis in breast cancer patients are none or minimal, abnormalities are observed in the lowest or second-lowest LN in the lower axilla when present, suggesting the location of the SLNs.

Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer

Purpose

The goal of this study is to develop and validate a radiomics nomogram integrating the radiomics features from DCE-MRI and clinical factors for the preoperative diagnosis of axillary lymph node (ALN) metastasis in breast cancer patients.

Procedures

A total of 432 patients with breast cancer were enrolled in this retrospective study and divided into a training cohort (n = 296) and a validation cohort (n = 136). Radiomics features were extracted from the second phase of dynamic contrast enhanced (DCE) MRI images. The least absolute shrinkage and selection operator (LASSO) regression method was used to screen optimal features and construct a radiomics signature in the training cohort. Multivariable logistic regression analysis was used to establish a radiomics nomogram model based on the radiomics signature and clinical factors. The predictive performance of the nomogram was quantified with respect to discrimination and calibration, which was further evaluated in the independent validation cohort.

Results

Fourteen ALN metastasis-related features were selected to construct the radiomics signature, with an area under the curve (AUC) of 0.847 and 0.805 in the training and validation cohorts, respectively. The nomogram was established by incorporating the histological grade, multifocality, MRI report lymph node status and radiomics signature and showed good calibration and excellent performance for ALN detection (AUC of 0.907 and 0.874 in the training and validation cohorts, respectively). The decision curve, which demonstrated the radiomics nomogram, displayed promising clinical utility.

Conclusions

The radiomics nomogram can be used as a noninvasive and reliable tool to assist clinicians in accurately predicting ALN metastasis in breast cancer preoperatively.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-022-00450-w.

Diagnostic performance of T2-weighted imaging and intravoxel incoherent motion diffusion-weighted MRI for predicting metastatic axillary lymph nodes in T1 and T2 stage breast cancer

BACKGROUND

Non-invasive modalities for assessing axillary lymph node (ALN) are needed in clinical practice.

PURPOSE

To investigate the suspicious ALN on unenhanced T2-weighted (T2W) imaging and intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) for predicting ALN metastases (ALNM) in patients with T1-T2 stage breast cancer and clinically negative ALN.

MATERIAL AND METHODS

Two radiologists identified the most suspicious ALN or the largest ALN in negative axilla by T2W imaging features, including short axis (Size-S), long axis (Size-L)/S ratio, fatty hilum, margin, and signal intensity on T2W imaging. The IVIM parameters of these selected ALNs were also obtained. The Mann-Whitney U test or t-test was used to compare the metastatic and non-metastatic ALN groups. Finally, logistic regression analysis with T2W imaging and IVIM features for predicting ALNM was conducted.

RESULTS

This study included 49 patients with metastatic ALNs and 50 patients with non-metastatic ALNs. Using the above conventional features on T2W imaging, the sensitivity and specificity in predicting ALNM were not high. Compared with non-metastatic ALNs, metastatic ALNs had lower pseudo-diffusion coefficient (D*) (P = 0.043). Logistic regression analysis showed that the most useful features for predicting ALNM were signal intensity and D*. The sensitivity and specificity predicting ALNM that satisfied abnormal signal intensity and lower D* were 73.5% and 84%, respectively.

CONCLUSIONS

The abnormal signal intensity on T2W imaging and one IVIM feature (D*) were significantly associated with ALNM, with sensitivity of 73.5% and specificity of 84%.

The impact of body mass index (BMI) on MRI diagnostic performance and surgical management for axillary lymph node in breast cancer

Background

We hypothesized that different BMI might have different impact on pre-operative MRI axillary lymph node (ALN) prediction accuracy and thereby subsequent surgical lymph node management. The aim of this study is to evaluate the effect of BMI on presentation, surgical treatment, and MRI performance characteristics of breast cancer with the main focus on ALN metastasis evaluation.

Methods

The medical records of patients with primary invasive breast cancer who had pre-operative breast MRI and underwent surgical resection were retrospectively reviewed. They were categorized into 3 groups in this study: underweight (BMI < 18.5), normal (BMI of 18.5 to 24), and overweight (BMI > 24). Patients’ characteristics, surgical management, and MRI performance for axillary evaluation between the 3 groups were compared.

Results

A total of 2084 invasive breast cancer patients with a mean age of 53.4 ± 11.2 years were included. Overweight women had a higher rate of breast conserving surgery (56.7% vs. 54.5% and 52.1%) and initial axillary lymph node dissection (15.9% vs. 12.2% and 8.5%) if compared to normal and underweight women. Although the post-operative ALN positive rates were similar between the 3 groups, overweight women were significantly found to have more axillary metastasis on MRI compared with normal and underweight women (50.2% vs 37.7% and 18.3%). There was lower accuracy in terms of MRI prediction in overweight women (65.1%) than in normal and underweight women (67.8% and 76.1%).

Conclusion

Our findings suggest that BMI may influence the diagnostic performance on MRI on ALN involvement and the surgical management of the axilla in overweight to obese women with breast cancer.

Non-invasive prediction of lymph node status for patients with early-stage invasive breast cancer based on a morphological feature from ultrasound images

Background

This study aimed to estimate the value of a morphological feature on ultrasound (US) for preoperative diagnosis of axillary lymph node (ALN) status in patients with early-stage invasive breast cancer (ESIBC).

Methods

In this retrospective work, a total of 239 ESIBC patients, were recruited, and their preoperative US images and postoperative pathology results were collected. The relationship between US images based on morphological features and ALN metastasis was investigated. The tumor circularity and US-reported ALN status were developed as a nomogram to predict the ALN status.

Results

Among the 239 participants, 82 (34.31%) had ALN metastasis, and 157 (65.69%) did not. There was a statistically significant difference in tumors between participants diagnosed with and without ALN metastasis. The median value was 0.47 vs. 0.62 (P<0.001) in the training group, respectively, and the value was 0.50 vs. 0.60 (P<0.001) in the validation group, respectively. The clinical model nomogram was shown to have high efficiency in predicting ALN status among our research population. The area under the curve (AUC) was 0.89 in the training group and 0.90 in the validation group and the accuracy was 85.79% and 81.63%, respectively.

Conclusions

The clinical model nomogram based on tumor circularity and US-reported ALN status is a non-invasive approach for ALN metastasis prediction in ESIBC patients with high efficacy.

Sterilization Rate of the Axilla After Neoadjuvant Chemotherapy: The Scope for Conservative Surgery

PURPOSE

The role of axillary conservation after neoadjuvant chemotherapy (NACT) is debatable. We routinely carry out complete axillary lymph node dissection (ALND). This study was conducted to understand the pathologic axillary complete response (pAxCR) after NACT.

MATERIALS AND METHODS

We evaluated a prospective database of patients with breast cancer who underwent surgery after NACT in the year 2017 at our institution. NACT was administered to downstage locally advanced breast cancer or facilitate breast-conservation surgery.

RESULTS

Of 793 patients who underwent surgery after NACT, 97(12.2%) had cN0 disease, 407 (51.3%) had cN1, 262 (32%) had cN2, and 27 (3.4%) had cN3 at presentation. Eighty-eight patients (11.1%) had cT1-2 primary tumor stage, and 623 patients (78.6%) had cT3-4 primary tumor stage; primary tumor stage details were unavailable for 82 patients (10.3%). The median age was 46 years (range, 21-74 years). On histopathology, the overall pAxCR rate was 52.8%. In the cN1 and cN2 settings, 58.7% and 36.6% of patients achieved ypN0 status, respectively. The overall pathologic complete response rate was 22.64% (161 of 711 patients). On univariable analysis, cN stage, histologic grade, hormone receptor status, NACT duration, and lymphovascular invasion were significantly associated with pAxCR (P <.001). On logistic regression, prechemotherapy cN status (odds ratio [OR], 3.08; 95% CI, 2.18 to 4.37; P <.001), estrogen and progesterone receptor status (OR, 0.34; 95% CI, 0.3 to 0.4; P <.001), and administration of both chemotherapy regimens preoperatively (OR, 0.66; 95% CI, 0.45 to 0.97; P <.05) predicted pAxCR.

CONCLUSION

At least half of patients with cN1 and a third of patients with cN2 breast cancer who develop pAxCR may be suitable candidates for axillary conservation. A careful postchemotherapy assessment followed by a conservative axillary procedure may be an alternative to ALND, but this needs to be studied prospectively.

Prediction of the number of metastatic axillary lymph nodes in breast cancer by radiomic signature based on dynamic contrast-enhanced MRI

BACKGROUND

The number of metastatic axillary lymph nodes (ALNs) play a crucial role in the staging, prognosis and therapy of patients with breast cancer.

PURPOSE

To predict the number of metastatic ALNs in breast cancer via radiomics.

MATERIAL AND METHODS

We enrolled 197 patients with breast cancer who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A total of 3386 radiomic features were extracted from the early- and delayed-phase subtraction images. To classify the number of metastatic ALNs, logistic regression was used to develop a radiomic signature and nomogram.

RESULTS

The radiomic signature were constructed to distinguish the N₀ group from the N₊ (metastatic ALNs ≥ 1) group, which yielded area under the curve (AUC) values of 0.82 and 0.81 in the training and test group, respectively. Based on the radiomic signature and BI-RADS category, a nomogram was further developed and showed excellent predictive performance with AUC values of 0.85 and 0.89 in the training and test groups, respectively. Another radiomic signature was constructed to distinguish the N₁ (1-3 ALNs) group from the N_2-3 (≥4 metastatic ALNs) group and showed encouraging performance with AUC values of 0.94 and 0.84 in training and test group, respectively.

CONCLUSIONS

We developed a nomogram and a radiomic signature that can be used to predict ALN metastasis and distinguish the N₁ from the N_2-3 group. Both nomogram and radiomic signature may be potential tools to assist clinicians in assessing ALN metastasis in patients with breast cancer.

Added Value of MRI for Invasive Breast Cancer including the Entire Axilla for Evaluation of High-Level or Advanced Axillary Lymph Node Metastasis in the Post-ACOSOG Z0011 Trial Era

Background In the post-American College of Surgeons Oncology Group Z0011 trial era, radiologists have increasingly focused on excluding high-level or advanced axillary lymph node metastasis (ALNM) by using an additional MRI scan positioned higher than lower axillae; however, the value of these additional scans remains undetermined. Purpose To evaluate whether a standard MRI protocol is sufficient to exclude high-level or advanced ALNM in breast cancer or additional MRI of entire axilla is needed. Materials and Methods This retrospective study evaluated women with invasive breast cancer who underwent breast MRI from April 2015 to December 2016. Some underwent neoadjuvant chemotherapy (NAC) and others underwent upfront surgery. Standard (routine axial scans including the lower axillae) and combined (routine axial scans plus additional scans including the entire axilla) MRI protocols were compared for high-level or advanced ALNM detection. Clinical-pathologic characteristics were analyzed. Uni- and multivariable logistic regression was performed to identify predictors of high-level or advanced ALNM. Results A total of 435 women (mean age ± standard deviation, 52 years ± 11) were evaluated (65 in the NAC group, 370 in the non-NAC group). With the standard MRI protocol, predictors of high-level ALNM were peritumoral edema (odds ratio [OR], 12.3; 95% CI: 3.9, 39.4; P < .001) and positive axilla (OR, 5.9; 95% CI: 2.0, 15.2; P < .001). Only three of 289 women with negative axillae without peritumoral edema had high-level ALNM. Predictors of advanced ALNM were positive axillae (OR, 8.9; 95% CI: 3.7, 21.5; P < .001) and peritumoral edema (OR, 2.8; 95% CI: 1.1, 6.9; P = .03). Only six of 310 women who had negative axillae without peritumoral edema had advanced ALNM. Conclusion The performance of standard MRI was satisfactory in excluding high-level and advanced axillary lymph node metastasis in most patients with breast cancer. However, the presence of peritumoral edema or positive axillae in the MRI findings emphasizes the benefits of a combined MRI protocol. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Abe in this issue.

Diagnostic Performance of Noninvasive Imaging for Assessment of Axillary Response After Neoadjuvant Systemic Therapy in Clinically Node-positive Breast Cancer: A Systematic Review and Meta-analysis

OBJECTIVE

The purpose of this study was to perform a systematic review and meta-analysis to determine the diagnostic performance of current noninvasive imaging modalities for assessment of axillary response after neoadjuvant systemic therapy (NST) in clinically node-positive breast cancer patients.

SUMMARY OF BACKGROUND DATA

NST can lead to downstaging of axillary lymph node disease. Imaging can potentially provide information about the axillary response to NST and, consequently, tailor the surgical management.

METHODS

PubMed and Embase were searched for studies that compared noninvasive imaging after NST with axillary surgery outcome to identify axillary response in patients with initial pathologically proven axillary lymph node metastasis. Two reviewers independently screened the studies and extracted the data. A meta-analysis was performed by computing the pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

Thirteen studies describing 2380 patients were included for final analysis. Of these patients, 1322 had undergone axillary ultrasound, 849 breast MRI, and 209 whole-body 18F-FDG PET-CT. The overall axillary pathologic complete response rate was 39.5% (941/2380). For axillary ultrasound, the pooled sensitivity, specificity, PPV, and NPV were 65%, 69%, 77%, 50%, respectively. For breast MRI, the pooled sensitivity, specificity, PPV, and NPV were 60%, 76%, 78%, 58%, respectively. For whole-body 18F-FDG PET-CT, the pooled sensitivity, specificity, PPV, and NPV were 38%, 86%, 78%, 49%, respectively.

CONCLUSIONS

The diagnostic performance of current noninvasive imaging modalities is limited to accurately assess axillary response after NST in clinically node-positive breast cancer patients.

Extra-axillary nodal metastases in breast cancer: comparison of ultrasound, MRI, PET/CT, and CT

PURPOSE

To evaluate how ultrasound (US), MRI, PET/CT, and CT predict extra-axillary nodal metastases.

SUBJECTS AND METHODS

This IRB approved, retrospective study consisted of 124 suspicious supraclavicular and 88 internal mammary (IM) nodal cases with US and at least one additional cross-sectional examination (MRI, PET/CT or CT) from a total of 1472 invasive cancers with staging nodal US between January 2016-January 2019. Imaging findings were compared with the true node status, determined by fine needle aspirate (FNA) biopsy or evidence of response to chemotherapy on follow up imaging.

RESULTS

In the supraclavicular region, US had accuracy 98.2%, consisting of 97 true positives (TP), 27 false positives (FP), and 1348 true negative (TN). 93.5% of suspicious supraclavicular nodes had FNA for a PPV 78.2%. PET/CT had accuracy 88.6% (26 TP, 5 TN and 4 false negatives (FN)). CT exams had accuracy 61.7% (42 TP, 16 TN, 7 FP, and 29 FN). In the IM region, US had accuracy 93.2% (82 TP, 1 FP, 5 FN, and 1384 TN) but only 43.2% of suspicious IM nodes had FNA for a PPV 98.8%. MRI had accuracy 100.0% (all 47 TP). PET/CT exams had accuracy 96.8% (30 TP and 1FN). CT exams had accuracy 62.7% (36 TP, 1 TN, and 22 FN).

CONCLUSION

US/FNA has accuracy 98.2% and 93.2% in the supraclavicular and IM regions, however only 43.2% of suspicious IM nodes are directly sampled. In these cases, MRI or PET/CT can be used to problem solve and guide treatment decisions.

Prediction of axillary nodal burden in patients with invasive lobular carcinoma using MRI

PURPOSE

To investigate clinical and imaging features associated with a high nodal burden (≥ 3 metastatic lymph nodes [LNs]) and compare diagnostic performance of US and MRI in patients with invasive lobular carcinoma (ILC) and invasive ductal carcinoma (IDC).

METHODS

Retrospective search revealed 239 patients with ILC and 999 with IDC who underwent preoperative US and MRI between January 2016 and June 2019. Patients with ILC were propensity-score-matched with patients with IDC. Univariate and multivariate logistic regression analyses were performed to determine factors associated with ≥ 3 metastatic LNs.

RESULTS

412 patients (206 ILC and 206 IDC) were evaluated. Of all patients with ILC, 27.2% (56/206) were node-positive and 7.8% (16/206) showed a high nodal burden. In multivariate analysis, the clinical N stage was the only independent factor associated with a high nodal burden in patients with IDC (odds ratio [OR] 6.24; 95% confidence interval [CI] 1.57-24.73; P = 0.009), but not in patients with ILC. Increased cortical thickness with loss of fatty hilum on US was associated with a high nodal burden in patients with ILC (OR 58.40; 95% CI 5.09-669.71; P = 0.001) and IDC (OR 24.14; 95% CI 3.52-165.37; P = 0.001), while suspicious LN findings at MRI were independently associated with a high nodal burden in ILC only (OR 13.94; 95% CI 2.61-74.39; P = 0.002).

CONCLUSION

In patients with ILC, MRI findings of suspicious LNs were helpful to predict a high nodal disease burden.

Fat fractions from high-resolution 3D radial Dixon MRI for predicting metastatic axillary lymph nodes in breast cancer patients

•

High-Resolution 3D radial Dixon MRI allows for the creation of quantitative fat fraction images.

•

Lymph node fat fractions improves diagnostic performance of MRI to detect axillary lymph node metastases.

•

Lymph node fat fractions are a promising quantitative indicator of metastases in axillary lymph nodes.

Purpose

To assess diagnostic performance of fat fractions (FF) from high-resolution 3D radial Dixon MRI for differentiating metastatic and non-metastatic axillary lymph nodes in breast cancer patients.

Method

High-resolution 3D radial Dixon MRI was prospectively performed on 1.5 T in 70 biopsy-verified breast cancer patients. 35 patients were available for analysis with histopathologic and imaging data. FF images were calculated as fat / in-phase. Two radiologists measured lymph node FF and assessed morphological features in one ipsilateral and one contralateral lymph node in consensus. Diagnostic performance of lymph node FF and morphological criteria were compared using histopathology as reference.

Results

22 patients had metastatic axillary lymph nodes. Mean lymph node FF were 0.20 ± 0.073, 0.31 ± 0.079, and 0.34 ± 0.15 (metastatic, non-metastatic ipsi- and non-metastatic contralateral lymph nodes, respectively). Metastatic lymph node FF were significantly lower than non-metastatic ipsi- (p <  0.001) and contralateral lymph nodes (p <  0.001). Area under the receiver operating characteristics curve for lymph node FF was 0.80 compared to 0.76 for morphological criteria (p =  0.29). Lymph node FF yielded sensitivity 0.91, specificity 0.69, positive predictive value (PPV) 0.83, and negative predictive value (NPV) 0.82, while morphological criteria yielded sensitivity 0.91, specificity 0.62, PPV 0.80, and NPV 0.80 (p =  0.71). Combining lymph node FF and morphological criteria increased diagnostic performance with sensitivity 1.00, specificity 0.67, PPV 0.86, NPV 1.00, and AUC 0.83.

Conclusions

Lymph node FF from high-resolution 3D Dixon images are a promising quantitative indicator of metastases in axillary lymph nodes.

Oncologic Safety of Sentinel Lymph Node Biopsy Alone After Neoadjuvant Chemotherapy for Breast Cancer

BACKGROUND

The oncologic safety of sentinel lymph node biopsy (SLNB) alone for clinically node-positive (cN1-2) patients who convert to pathologic node-negativity (ypN0) after neoadjuvant chemotherapy (NAC) is not well established.

METHODS

This study retrospectively identified 244 consecutive patients with a diagnosis of cT1-3cN0-2 breast cancer who underwent NAC followed by SLNB at the authors' institution between 2013 and 2018. The patients were categorized as clinically node-negative (cN0) or cN1-2 before the onset of NAC, and the Kaplan-Meier method was used to compare locoregional and distant recurrence rates after SLNB alone for ypN0 patients.

RESULTS

Among 244 patients who underwent NAC followed by surgery with SLNB for axillary staging, 112 (45.9%) were cN0 at presentation, whereas 132 (54.5%) had biopsy-proven cN1-2 disease and converted to cN0 after treatment. Of the patients presenting with cN0 disease, 102 (91.1%) were ypN0 on SLNB pathology compared with 60 cN1/2 patients (45.5%; p < 0.001). Regional nodal irradiation was administered to 5% of the cN0/ypN0 patients compared with 70.7% of the cN1-2/ypN0 patients (p < 0.001). Overall, 211 patients were treated with SLNB alone and had a median follow-up period of 36 months (interquartile range [IQR], 24-53 months). For 101 cN0/ypN0 patients who underwent SLNB alone, the 5-year local and regional recurrence rates were respectively 5.7% (95% confidence interval [CI], 2.4-13.8) and 1% (95% CI 0.1-7.0). For 58 cN1-2/ypN0 patients who underwent SLNB alone, the 5-year local and regional recurrence rates were respectively 4.1% (95% CI 1.0-15.5) and 0%, with no axillary recurrences noted.

CONCLUSION

For ypN0 patients, SLNB alone after NAC is associated with low and acceptable short-term axillary recurrence rates. Additional follow-up data from prospective clinical trials are needed to confirm long-term oncologic safety and define optimal local therapy recommendations.

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Carcinoma Using Radiomics Features Based on the Fat-Suppressed T2 Sequence

RATIONALE AND OBJECTIVES

To investigate the value of radiomics method based on the fat-suppressed T2 sequence for preoperative predicting axillary lymph node (ALN) metastasis in breast carcinoma.

MATERIALS AND METHODS

The data of 329 invasive breast cancer patients were divided into the primary cohort (n = 269) and validation cohort (n = 60). Radiomics features were extracted from the fat-suppressed T2-weighted images on breast MRI, and ALN metastasis-related radiomics feature selection was performed using Mann-Whitney U-test and support vector machines with recursive feature elimination; then a radiomics signature was constructed by linear support vector machine. The predictive models were constructed using a linear regression model based on the clinicopathologic factors and radiomics signature, and nomogram was used for a visual prediction of the combined model. The predictive performances are evaluated with the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve.

RESULTS

A total of 647 radiomics features were extracted from each patient. About 23 ALN metastasis-related radiomics features were selected to construct the radiomics signature, including 17 texture features, 5 first-order statistical features, and one shape feature; patient age, tumor size, HER2 status, and vascular cancer thrombus accompanied or not were selected to construct the cilinicopathologic feature model. The sensitivity, specificity, accuracy, and are under the curve value of radiomics signature, clinicopathologic feature model, and the nomogram were 65.22%, 81.08%, 75.00%, and 0.819 (95% confidence interval [CI]: 0.776-0.861), 30.44%, 81.08%, 61.67%, and 0.605 (95% CI: 0.571-0.624) and 60.87%, 89.19%, 78.33%, and 0.810 (95% CI: 0.761-0.855), respectively.

CONCLUSION

Radiomics methods based on the fat-suppressed T2 sequence and the nomogram are helpful for preoperative accurate predicting ALN metastasis.

Breast dynamic contrast-enhanced-magnetic resonance imaging and radiomics: State of art

Breast cancer represents the most common malignancy in women, being one of the most frequent cause of cancer-related mortality. Ultrasound, mammography, and magnetic resonance imaging (MRI) play a pivotal role in the diagnosis of breast lesions, with different levels of accuracy. Particularly, dynamic contrast-enhanced MRI has shown high diagnostic value in detecting multifocal, multicentric, or contralateral breast cancers. Radiomics is emerging as a promising tool for quantitative tumor evaluation, allowing the extraction of additional quantitative data from radiological imaging acquired with different modalities. Radiomics analysis may provide novel information through the quantification of lesions heterogeneity, that may be relevant in clinical practice for the characterization of breast lesions, prediction of tumor response to systemic therapies and evaluation of prognosis in patients with breast cancers. Several published studies have explored the value of radiomics with good-to-excellent diagnostic and prognostic performances for the evaluation of breast lesions. Particularly, the integrations of radiomics data with other clinical and histopathological parameters have demonstrated to improve the prediction of tumor aggressiveness with high accuracy and provided precise models that will help to guide clinical decisions and patients management. The purpose of this article in to describe the current application of radiomics in breast dynamic contrast-enhanced MRI.

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.

Axillary Nodal Burden Assessed with Pretreatment Breast MRI Is Associated with Failed Sentinel Lymph Node Identification after Neoadjuvant Chemotherapy for Breast Cancer

Background After publication of the findings of the American College of Surgeons Oncology Group Z1071 trial, sentinel lymph node biopsy (SLNB) has been increasingly performed in patients with breast cancer after neoadjuvant chemotherapy (NAC). Purpose To investigate the pretreatment breast MRI and clinical-pathologic characteristics associated with failed sentinel node identification after NAC in patients with breast cancer. Materials and Methods Patients who underwent SLNB after NAC between January 2015 and January 2019 were retrospectively identified. Two radiologists independently reviewed the characteristics of axillary nodes (number, perinodal infiltration, cortical thickness, and maximal diameter) at pretreatment breast MRI. The associations of the clinical-pathologic and imaging characteristics of the axillary nodes with sentinel node identification were assessed by using the χ² test and/or the χ² test for trend and multivariable logistic regression with odds ratio (OR) calculation. Results A total of 276 women (mean age ± standard deviation, 48 years ± 9; range, 27-68 years) were included. Sentinel nodes were identified in 252 of the 276 patients (91%). Multivariable analysis showed that higher (stage 3 or 4) clinical T stages (OR = 5.2, P = .004 for radiologist 1; OR = 4.6, P = .01 for radiologist 2), use of a single tracer (OR = 4.3, P = .04 for radiologist 1; OR = 3.9, P = .046 for radiologist 2), a greater number (10 or more) of suspicious axillary nodes (OR = 11.5, P = .002 for radiologist 1; OR = 8.3, P = .01 for radiologist 2), and the presence of perinodal infiltration (OR = 7.0, P = .002 for radiologist 1; OR = 7.5, P = .003 for radiologist 2) were associated with failed sentinel node identification. Conclusion A greater number of suspicious axillary nodes and the presence of perinodal infiltration at pretreatment MRI, higher clinical T stages, and use of a single tracer were independently associated with failed sentinel node identification after neoadjuvant chemotherapy in patients with breast cancer. © RSNA, 2020 See also the editorial by Imbriaco in this issue.

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.

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

Background

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

Purpose

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

Methods

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

Conclusion

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

Is Clinical Exam of the Axilla Sufficient to Select Node-Positive Patients Who Downstage After NAC for SLNB? A Comparison of the Accuracy of Clinical Exam Versus MRI

BACKGROUND

The National Comprehensive Cancer Network (NCCN) endorses sentinel lymph node biopsy (SLNB) in patients with clinically positive axillary nodes who downstage after neoadjuvant chemotherapy (NAC). In this study, we compared the accuracy of post-NAC MRI to clinical exam alone in predicting pathologic status of sentinel lymph nodes in cN1 patients.

METHODS

We identified patients with T0-3, N1 breast cancer who underwent NAC and subsequent SLNB from March 2014 to July 2017. Patients were grouped based on whether a post-NAC MRI was done. MRI accuracy in predicting SLN status was assessed versus clinical exam alone.

RESULTS

A total of 450 patients met initial study criteria; 269 were analyzed after excluding patients without biopsy-confirmed nodal disease, palpable disease after NAC, and failed SLN mapping. Median age was 49 years. Post-NAC MRI was done in 68% (182/269). Patients undergoing lumpectomy vs mastectomy more frequently received a post-NAC MRI (88 vs 54%, p < 0.001). All other clinicopathologic parameters were comparable between those who did and did not have a post-NAC MRI. Thirty percent (55/182) had abnormal lymph nodes on MRI. Among these, 58% (32/55) had a positive SLN on final pathology versus 42% (53/127) of patients with no abnormal lymph nodes on MRI and 52% (45/87) of patients who had clinical exam alone (p = 0.09). MRI sensitivity was 38%, specificity was 76%, and overall SLN status prediction accuracy was 58%.

CONCLUSIONS

Post-NAC MRI is no more accurate than clinical exam alone in predicting SLN pathology in patients presenting with cN1 disease. Abnormal lymph nodes on MRI should not preclude SLNB.

Ultrasound-based radiomics nomogram: A potential biomarker to predict axillary lymph node metastasis in early-stage invasive breast cancer

PURPOSE

To establish a radiomics nomogram integrating clinical factors and radiomics features from ultrasound for the preoperative diagnosis axillary lymph node (ALN) status in patients with early-stage invasive breast cancer (EIBC).

MATERIALS AND METHODS

Between September 2016 and December 2018, four hundred twenty-six ultrasound manually segmented images of patients with EIBC were enrolled in our retrospective study, which were divided into a primary cohort (n = 300) and a validation cohort (n = 126). A radiomics signature was built with the least absolute shrinkage and selection operator (LASSO) algorithm in the primary cohort. Multivariable logistic regression analysis was used to establish a radiomics nomogram model based on radiomics signature and clinical variables. The performance of nomogram was quantified with respect to discrimination and calibration. The radiomics model was further evaluated in the internal validation cohort.

RESULTS

The radiomics signature, consisted of fourteen selected ALN-status-related features, achieved moderate prediction efficacy with an area under the curve (AUC) of 0.78 and 0.71 in the primary and validation cohorts respectively. The radiomics nomogram, comprising tumor size, US-reported LN status and radiomics signature, showed good calibration and favorite performance for ALN detection (AUC 0.84 and 0.81 in the primary and validation cohort). The decision curve which was demonstrated the radiomics nomogram displayed good clinical utility.

CONCLUSION

The radiomics nomogram could hold promise as a non-invasive and reliable tool in predicting ALN metastasis and may facilitate to develop more effective preoperative decision-making.

MRI evaluation of axillary and intramammary lymph nodes in the postoperative period

Our study aimed to evaluate if breast‐conserving surgery and adjuvant treatment could affect the morphological features of axillary and intramammary lymph nodes on magnetic resonance imaging (MRI) in patients with invasive breast cancer and clinically negative axilla. In this single‐center study, we retrospectively evaluated 50 patients who had (a) breast‐conserving surgery, (b) clinically negative axilla, (c) preoperative MRI within 3 months before surgery, and (d) postoperative MRI within 12 months after surgery. Axillary and intramammary lymph nodes on postoperative MRI were identified and then compared with preoperative MRI by two breast radiologists with regards to the following: enlargement, cortical thickening, presence of fatty hilum, irregularity, heterogeneity, matting, and axillary lymph node asymmetry. Three hundred and two axillary and eight intramammary lymph nodes were evaluated. Enlargement and cortical thickening were seen in 5/50 (10%) patients in three axillary and two intramammary lymph nodes. None of the lymph nodes on postoperative MRI demonstrated occurrence of lack of fatty hilum, irregularity, heterogeneity, matting or axillary lymph node asymmetry. No evidence of recurrence was observed on 2‐year follow‐up. Lymph node enlargement and cortical thickening may be observed in a few patients in the postoperative period. Nevertheless, in patients with clinically negative axilla, these changes in morphology are often related to treatment rather than malignancy and favor short‐term follow‐up as an alternative to lymph node biopsy.

Axillary Pathologic Complete Response to Neoadjuvant Chemotherapy in Clinically Node-Positive Breast Cancer Patients: A Predictive Model Integrating the Imaging Characteristics of Ultrasound Restaging with Known Clinicopathologic Characteristics

The goal of this study was to evaluate various clinicopathologic and imaging characteristics as independent predictors of axillary pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) and to determine the added value of a model that integrates imaging characteristics of ultrasound (US) restaging with known clinicopathologic characteristics. A total of 227 clinically node-positive breast cancer patients underwent axillary US after NAC (termed US restaging) before surgery. We constructed a clinicopathologic model with independent predictors of clinicopathologic characteristics in multivariate analyses. A combined model was created by integrating imaging characteristics with clinicopathologic characteristics. The predictive values of the models were compared using the area under the receiver operating characteristic curve. Of the 227 patients, 106 (46.7%) achieved axillary pCR. Multivariate analysis revealed that higher histologic grades (odds ratio [OR] = 4.21 and 10.11 for moderate and high grade, respectively), negative hormonal receptor status (OR = 2.88), smaller (≤1.5 cm) residual tumor size (OR = 2.83), absence of fatty hilum loss (OR = 14.06) and absence of eccentric cortical thickening of the axillary lymph node (OR = 4.42) were independently associated with the axillary pCR (all p values < 0.05). Integrating the imaging characteristics of the US restaging significantly increased the predictive capability of the model that applied only the clinicopathologic characteristics (c-index, 0.783 vs. 0.657; p < 0.001). Imaging characteristics of the US restaging were independently associated with axillary pCR after NAC and they significantly improved the predictive capability of the model that used only the clinicopathologic characteristics.

Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics

BACKGROUND

Lymphovascular invasion (LVI) status facilitates the selection of optimal therapeutic strategy for breast cancer patients, but in clinical practice LVI status is determined in pathological specimens after resection.

PURPOSE

To explore the use of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI)-based radiomics for preoperative prediction of LVI in invasive breast cancer.

STUDY TYPE

Prospective.

POPULATION

Ninety training cohort patients (22 LVI-positive and 68 LVI-negative) and 59 validation cohort patients (22 LVI-positive and 37 LVI-negative) were enrolled.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T, T₁ -weighted DCE-MRI.

ASSESSMENT

Axillary lymph node (ALN) status for each patient was evaluated based on MR images (defined as MRI ALN status), and DCE semiquantitative parameters of lesions were calculated. Radiomic features were extracted from the first postcontrast DCE-MRI. A radiomics signature was constructed in the training cohort with 10-fold cross-validation. The independent risk factors for LVI were identified and prediction models for LVI were developed. Their prediction performances and clinical usefulness were evaluated in the validation cohort.

STATISTICAL TESTS

Mann-Whitney U-test, chi-square test, kappa statistics, least absolute shrinkage and selection operator (LASSO) regression, logistic regression, receiver operating characteristic (ROC) analysis, DeLong test, and decision curve analysis (DCA).

RESULTS

Two radiomic features were selected to construct the radiomics signature. MRI ALN status (odds ratio, 10.452; P < 0.001) and the radiomics signature (odds ratio, 2.895; P = 0.031) were identified as independent risk factors for LVI. The value of the area under the curve (AUC) for a model combining both (0.763) was higher than that for MRI ALN status alone (0.665; P = 0.029) and similar to that for the radiomics signature (0.752; P = 0.857). DCA showed that the combined model added more net benefit than either feature alone.

DATA CONCLUSION

The DCE-MRI-based radiomics signature in combination with MRI ALN status was effective in predicting the LVI status of patients with invasive breast cancer before surgery.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:847-857.

Restaging the axilla after neo-adjuvant chemotherapy for breast cancer: Predictive factors for residual metastatic lymph node disease with negative imaging findings

To evaluate predictive factors for residual metastatic axillary lymph node (ALN) disease in patients with negative imaging findings after neo-adjuvant chemotherapy (NAC) for breast cancer. From January 2011 to December 2015, 206 patients underwent imaging including ultrasonography, MRI, and PET/CT for restaging the axilla after NAC. Data collected included preoperative information regarding histologic grade, hormone receptor (HR) status, and human epidermal growth factor receptor 2 (HER2) status. Multivariate logistic regression analysis was performed to compare patients with and without residual metastatic ALN disease among patients who showed negative imaging findings after NAC. Of the 181 and 25 patients with initially node-positive and node-negative disease, 131 (72.4%) and 23 (92.0%), respectively, showed negative imaging findings after NAC. Among these 131 and 23 patients, 53 (40.5%) and two patients (8.7%), respectively, had residual metastatic ALN disease. Low to moderate tumor grade (odds ratio [OR] = 5.2, P = 0.009), positive HR status (OR = 6.6, P = 0.003), and negative HER2 status (OR = 2.6, P = 0.048) were associated with residual metastatic ALN disease. Low to moderate histologic grade, positive HR status, and negative HER2 status may serve as predictors of residual metastatic ALN disease in patients with negative imaging findings after NAC for breast cancer.

Prediction of high nodal burden with ultrasound and magnetic resonance imaging in clinically node-negative breast cancer patients

Background

Although the role of axillary imaging has been redirected for predicting high nodal burden rather than predicting nodal metastases since ACOSOG Z1011 trial, it remains unclear whether and how axillary lymph node (ALN) characteristics predicts high nodal burden. Our study was aimed to evaluate the predictive value of imaging characteristics of ALNs at ultrasound and magnetic resonance imaging (MRI) for prediction of high nodal burden (≥3 metastatic ALNs) in clinically node-negative breast cancer patients.

Methods

Clinicopathological and imaging characteristics were evaluated in patients with ultrasound (n = 312) and MRI (n = 256). Imaging characteristics include number of suspicious ALNs and cortical morphologic changes (grade 1, cortical thickness < 2 mm; grade 2, 2–5 mm; grade 3, ≥5 mm or fatty hilum loss). Odds ratios (ORs) were calculated using multivariate analysis.

Results

For ultrasound, higher (≥2) T stage (OR = 5.65, P = .005), higher number of suspicious ALNs (2 suspicious ALNs, OR = 6.52, P = .019; ≥ 3 suspicious ALNs, OR = 21.08, P = .005), and grade 3 of cortical morphologic changes (OR = 9.85, P = .023) independently associated with high nodal burden. For MRI, higher (≥2) T stage (OR = 5.17, P = .011) and higher number of suspicious ALNs (2 suspicious ALNs, OR = 69.00, P = .001; ≥ 3 suspicious ALNs, OR = 93.55, P < .001) were independently associated with high nodal burden. Among patients with 2 suspicious ALNs, those with grade 3 cortical morphologic change at ultrasound had a higher rate of high nodal burden than those with grade 2 (60.0% [3/5] vs. 25.0% [2/8]).

Conclusions

A higher number of suspicious ALNs is an independent predictor for high nodal burden. Further stratification can be achieved by incorporating assessment of ultrasound-based cortical morphologic changes.

L’exploration axillaire en pratique quotidienne dans le parcours diagnostique d’un cancer du sein

Lors de la découverte d’un cancer du sein, la qualité du bilan préthérapeutique est essentielle afin d’orienter la décision thérapeutique. L’exploration axillaire est primordiale, car elle évalue l’extension régionale de la maladie, ce qui en fait un des facteurs pronostiques majeurs. Différents examens d’imagerie préopératoires peuvent révéler une atteinte de ces ganglions axillaires. Cependant, l’imagerie de référence reste l’échographie axillaire, qui permet également de guider des prélèvements. Depuis l’étude ACOSOGZ0011, nous sommes face à une désescalade thérapeutique de la chirurgie axillaire. Selon des résultats récents, on constate que la place de l’imagerie axillaire est encore plus importante. Le but de l’échographie est d’éviter un curage en deux temps après un ganglion sentinelle positif lorsque les critères de l’ACOSOG-Z0011 ne sont pas remplis.

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

OBJECTIVE:

Although axillary imaging has recently received renewed interest for preoperative staging in tandem with the evolving minimally invasive surgical approaches, axillary imaging is limited by the lack of standardization in the interpretation. We aimed to classify imaging features in ultrasound and MRI into quantitative and semantic features and evaluate predictive value of each feature for predicting nodal metastases.

METHODS:

A total of 316 breast cancers patients who underwent ultrasound and MRI prior to axillary surgery were included. Retrospective reviews of our breastimaging database were done for the quantitative features [cortical thickness (CT) and CT-derived parameters, long diameter (LD), short diameter (SD), and LD/SD ratio] and semantic features (eccentricity, loss of fatty hilum, and irregularity) of the axillary lymph node in images. Odd ratios (ORs) for each imaging feature were calculated with adjustment for clinicopathological characteristics significantly associated with nodal metastases.

RESULTS:

All CT-derived parameters were significantly associated with nodal metastases in both ultrasound and MRI (OR, 3.3-3.5 for ultrasound and 3.3-3.9 for MRI, respectively; Ps < .05). For the ultrasound, LD/SD ratio (OR, 2.1), eccentricity (OR, 2.4), and fatty hilum loss (OR, 27.2) were significantly associated with nodal metastases (Ps < .05). For the MRI, SD (OR, 2.1) and eccentricity (OR, 3.0) were significantly associated with nodal metastases (Ps < .05).

CONCLUSION:

Among the quantitative features, all CT-derived parameters can be used for predicting nodal metastases. Significant predictors of semantic features were heterogeneous between ultrasound and MRI.

ADVANCES IN KNOWLEDGE:

(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.

Accuracy of a nomogram to predict the survival benefit of surgical axillary staging in T1 breast cancer patients

T1 breast cancer patients have favorable clinical outcomes, so that whether axillary stating (AS) surgery can be omitted in these patients is still unclear. This retrospective cohort study developed a nomogram to predict the cancer-specific survival (CSS) of T1 breast cancer patients with and without AS and estimate the survival benefit of AS in these patients.We used surveillance, epidemiology, and end results (SEER) database to identify 232,195 breast cancer patients with T1 tumors diagnosed between 1990 and 2008. In the training cohort, we used the Kaplan-Meier method and the competing risk analysis, with non-CSS as the competing risk, to screen for prognostic factors for CSS. A nomogram to predict the CSS, with receiving AS or not as one of the predictors, was developed and externally validated, using the C-index and calibration plots. The survival benefit of AS can be estimated by the difference of 2 predicted CSS, when the patient was considered as having and not having AS.With a median follow-up of 109 months, the CSS of the study population were 96.3%, 92.3%, and 88.5% at 5, 10, and 15 years, respectively. Significant predictors for CSS identified in the training cohort were used to develop a nomogram, which was validated internally [C-index = 0.707, 95% confidence interval (95% CI) 0.702-0.712] and externally (C-index = 0.704, 95% CI 0.698-0.710). The nomogram was well calibrated. With this nomogram, AS was predicted to have less than 2% benefit of 5-, 10-, and 15-year CSS in 60.6% (140,599/232,195), 15.5% (36,074/232,195), and 8.6% (20,043/232,195) of the entire study population, respectively.The new nomogram can accurately predict the CSS of T1 breast cancer patients, and also be able to estimate the survival benefit of AS in these patients. Prospective studies are needed to confirm our findings.

Prediction of Advanced Axillary Lymph Node Metastases (ypN2-3) Using Breast MR imaging and PET/CT after Neoadjuvant Chemotherapy in Invasive Ductal Carcinoma Patients

We aimed to investigate the value of breast magnetic resonance (MR) imaging and positron emission tomography-computed tomography (PET/CT) in predicting advanced axillary lymph node (ALN) metastases (ypN2-3) after neoadjuvant chemotherapy (NAC) in invasive ductal carcinoma patients. A total of 108 patients with invasive ductal carcinoma underwent breast MR imaging and PET/CT both before and after NAC (termed initial staging and restaging, respectively). The number of positive ALNs and the short diameter (SD) of the largest ALN on breast MR imaging and maximal standardized uptake value (SUVmax) in the ALNs on PET/CT were evaluated. Odds ratio (OR) for prediction of advanced ALN metastases was calculated. The negative predictive value (NPV) of restaging imaging for exclusion of advanced ALN metastases was also calculated. Patients with advanced ALN metastases were more likely to have a higher number (≥2) of positive LNs (OR, 8.06; P = 0.015) on restaging MR imaging. No clinico-pathological factors were significantly associated with advanced ALN metastases. With restaging MR imaging, PET/CT, and MR imaging plus PET/CT, the NPV for excluding advanced ALN metastases was 97.3%, 94.4%, and 100.0%. A higher number of positive ALNs on restaging MR imaging was an independent predictor for advanced ALN metastases after NAC.

Ultrasound-Guided Fine-Needle Aspiration of Non-palpable and Suspicious Axillary Lymph Nodes with Subsequent Removal after Tattooing: False-Negative Results and Concordance with Sentinel Lymph Nodes

Ultrasonography-guided fine-needle aspiration (US-guided FNA) for axillary lymph nodes (ALNs) is currently used with various techniques for the initial staging of breast cancer and tagging of ALNs. With the implementation of the tattooing of biopsied ALNs, the rate of false-negative results of US-guided FNA for non-palpable and suspicious ALNs and concordance with sentinel lymph nodes were determined by node-to node analyses. A total of 61 patients with breast cancer had negative results for metastasis on US-guided FNA of their non-palpable and suspicious ALNs. The biopsied ALNs were tattooed with an injection of 1-3 mL Charcotrace (Phebra, Lane Cove West, Australia) ink and removed during sentinel lymph node biopsy or axillary dissection. We determined the rate of false-negative results and concordance with the sentinel lymph nodes by a retrospective review of surgical and pathologic findings. The association of false-negative results with clinical and imaging factors was evaluated using logistic regression. Of the 61 ALNs with negative results for US-guided FNA, 13 (21%) had metastases on final pathology. In 56 of 61 ALNs (92%), tattooed ALNs corresponded to the sentinel lymph nodes. Among the 5 patients (8%) without correspondence, 1 patient (2%) had 2 metastatic ALNs of 1 tattooed node and 1 sentinel lymph node. In multivariate analysis, atypical cells on FNA results (odds ratio = 20.7, p = 0.040) was independently associated with false-negative FNA results. False-negative ALNs after US-guided FNA occur at a rate of 21% and most of the tattooed ALNs showed concordance with sentinel lymph nodes.

Accuracy of axillary ultrasound after different neoadjuvant chemotherapy cycles in breast cancer patients

Background

This study determined whether axillary ultrasound (AUS) accurately predicted the status of axillary lymph nodes of patients who received different number of cycles of neoadjuvant chemotherapy (NAC).

Materials and Methods

From 2008 to 2015, 656 cases of patients with breast cancers who received NAC and had subsequent axillary lymph node dissection were included in this study. The findings of preoperative AUS were tested by pathological examination. We evaluated the sensitivity, specificity and accuracy of AUS for patients who received two-, four-, and six-cycle NAC.

Results

In the two-cycle subgroup, the sensitivity (Sn), specificity (Sp) and diagnostic odds ratio (DOR) were 80.2% (95% CI: 74.3%-86.2%), 61.4% (95% CI: 48.8%-74.0%) and 6.64 (95% CI: 3.36-12.4) respectively. In the four-cycle subgroup, the Sn, Sp and DOR were 69.7% (95% CI: 62.2%-77.1%), 66.1% (95% CI: 53.7%-78.5%) and 4.47 (95% CI: 2.32-8.62), respectively. In the six-cycle subgroup, the Sn, Sp and DOR were 56.7% (95% CI: 49.5%-64.0%), 74.5% (95% CI: 62.8%-87.2%) and 3.83 (95% CI: 1.863-7.86), respectively. Furthermore, the patients with normal AUS findings after six cycles of NAC have few positive nodes than patients with suspicious findings (p < 0.001).

Conclusion

Preoperative AUS is a potentially useful imaging modality to predict the pathologic status of the axillary within four cycles of NAC. Although the accuracy is lower for patients who completed six cycles of NAC than that who received four- and two- cycles, the number of positive lymph nodes for patients with normal findings on AUS is low.

Diagnostic Performance of Breast Magnetic Resonance Imaging in Non-Calcified Equivocal Breast Findings: Results from a Systematic Review and Meta-Analysis

OBJECTIVES

To evaluate the performance of MRI for diagnosis of breast cancer in non-calcified equivocal breast findings.

MATERIALS AND METHODS

We performed a systematic review and meta-analysis of peer-reviewed studies in PubMed from 01/01/1986 until 06/15/2015. Eligible were studies applying dynamic contrast-enhanced breast MRI as an adjunct to conventional imaging (mammography, ultrasound) to clarify equivocal findings without microcalcifications. Reference standard for MRI findings had to be established by histopathological sampling or imaging follow-up of at least 12 months. Number of true or false positives and negatives and other characteristics were extracted, and possible bias was determined using the QUADAS-2 applet. Statistical analyses included data pooling and heterogeneity testing.

RESULTS

Fourteen out of 514 studies comprising 2,316 lesions met our inclusion criteria. Pooled diagnostic parameters were: sensitivity (99%, 95%-CI: 93-100%), specificity (89%, 95%-CI: 85-92%), PPV (56%, 95%-CI: 42-70%) and NPV (100%, 95%-CI: 99-100%). These estimates displayed significant heterogeneity (P<0.001).

CONCLUSIONS

Breast MRI demonstrates an excellent diagnostic performance in case of non-calcified equivocal breast findings detected in conventional imaging. However, considering the substantial heterogeneity with regard to prevalence of malignancy, problem solving criteria need to be better defined.

Diagnostic accuracy of metastatic axillary lymph nodes in breast MRI

Purpose

The most important prognostic variable for early stage breast cancer is the status of axillary lymph nodes. The aim of this study was to evaluate the diagnostic accuracy of preoperative magnetic resonance imaging (MRI) for metastatic axillary lymph node in breast cancer cases with post-operative sentinel lymph node biopsy (SLNB) results.

Materials and methods

Women aged between 21 and 73 years who were diagnosed with malignant mass lesion of the breast between 2013 and 2015 were included in this study. The preoperative MR images of patients with diagnosis of breast cancer was evaluated to determine axillary lymph node status. Axillary lymph node size, long axis to short axis ratio, lymph node contours, cortical thickness to anteroposterior diameter ratio, the presence of a fatty hilum and contrast enhancement patterns (homogenous or heterogenous) was noted. Additionally, the presence of comet tail sign which a tail extending from an enhancing breast lesion into the parenchyma and might represent ductal infiltration on post-contrast series was also noted. All data obtained from this evaluation was compared with postoperative SLNB results.

Results

Metastatic nodes were found to have a longer short axis when compared to reactive nodes (p = 0.042; p < 0.05). The long axis to short axis ratio was notably lower in metastatic nodes when compared to reactive nodes. Cortical thickness was higher in metastatic nodes when compared to reactive nodes (p = 0.024; p < 0.05). Comet sign was observed in 15 of metastatic nodes (73.3 %) and in one (5 %) reactive node. This difference was statistically significant (p = 0.001; p < 0.01). While fatty hilum was seen in 40 % of metastatic nodes (n = 6), it was seen in all (n = 20) reactive nodes. This difference was statistically significant (p = 0.001; p < 0.01).

Conclusions

MRI is a non invasive sensitive and specific imaging modality for evaluating the axilla. We have shown that with the help of comet tail sign and status of fatty hilum contrast enhanced MRI has the highest sensitivity of 84.7 % for detecting axillary lymph node metastases (Singletary et al. in Semin Surg Oncol 21(1):53–59, 2003).