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

Improving Prediction Accuracy of Residual Axillary Lymph Node Metastases in Node-Positive Triple-Negative Breast Cancer: A Radiomics Analysis of Ultrasound-Guided Clip Locations Using the SHAP Method

RATIONALE AND OBJECTIVES

To construct a radiomics nomogram derived from multiparametric ultrasound (US) imaging using the SHapley Additive exPlanations (SHAP) method for the accurate identification of residual axillary lymph node metastases post-neoadjuvant chemotherapy (NAC) among patients with triple-negative breast cancer (TNBC).

METHODS

A total of 405 consecutive patients with pathologically confirmed TNBC between 2016 and 2023 were recruited in the study and were divided into training (n = 284) and validation cohorts (n = 121). Radiomics features capturing detailed tumor characteristics were extracted from pre-NAC gray-scale US images at the locations of US-guided clip placement. The least absolute shrinkage and selection operator and the maximum relevance minimum redundancy algorithm were employed to identify key features and formulate the radiomics signature (RS). A nomogram based on US radiomics was then constructed using multivariable logistic regression analysis. The predictive efficacy of this model was evaluated through receiver operating characteristic curve analysis, calibration assessment, and decision curve analysis. SHAP summary plots were used to visualize the distribution of SHAP values across all features.

RESULTS

The nomogram integrates clinical and US characteristics with RS, yielded optimal AUC of 0.922 (95% CI, 0.890-0.954) in the training cohort, 0.904 (95% CI, 0.853-0.955) in the validation cohort. The calibration and decision curves confirmed favorable calibration and clinical value of the nomogram. SHAP provided further insight into the contributions of each feature to the model's outcomes.

CONCLUSION

The combined multiparametric US based radiomics nomogram plays a potential role in predicting residual axillary lymph node metastases after NAC in TNBCs.

Residual Axillary Metastases in Node-Positive Breast Cancer Patients After Neoadjuvant Treatment: A Register-Based Study

BACKGROUND

Lymph node (LN) metastasis after neoadjuvant chemotherapy (NACT) generally warrants axillary lymph node dissection, which opposes guidelines of upfront surgery in many cases. We investigated the risk of having additional metastases in the axilla when the LNs removed by targeted axillary dissection (TAD) harbored metastases after NACT. We aimed to identify subgroups suitable for de-escalated axillary treatment.

METHODS

This register-based study used data from the Danish Breast Cancer Cooperative Group database. Data were analyzed with logistic regression models. The primary outcome was the metastatic burden in non-TAD LNs in patients with positive TAD LNs after NACT.

RESULTS

Among 383 patients, < 66.6% positive TAD LNs (adjusted odds ratio [OR] 0.34, 95% confidence interval [CI] 0.17-0.62), only isolated tumor cells (ITCs) [OR 0.11, 95% CI < 0.01-0.82], and breast pathological complete response (pCR) [OR 0.07, 95% CI < 0.01-0.56] were associated with a low risk of having more than three positive non-TAD LNs. In 315 patients with fewer than three positive non-TAD LNs, the proportion of positive TAD LNs (OR 0.45, 95% CI 0.27-0.76 for 33.3-66.6% vs. > 66.6%), size of the TAD LN metastasis (OR 0.14, 95% CI 0.04-0.54 for ITC vs. macrometastasis), tumor size at diagnosis (OR 0.30, 95% CI 0.15-0.64 for 20-49 mm vs. ≥ 50 mm) and breast pCR (OR 0.38, 95% CI 0.15-0.96) were associated with residual LN metastases in the axilla.

CONCLUSIONS

Breast pCR or ITC only in TAD LNs can, with reasonable certainty, preclude more than three positive non-TAD LNs. Additionally, patients with only ITCs in the TAD LN had a low risk of having any non-TAD LN metastases after NACT. De-escalated axillary treatment may be considered in both subgroups.

Machine learning approaches in the prediction of positive axillary lymph nodes post neoadjuvant chemotherapy using MRI, CT, or ultrasound: A systematic review

Background and objective

Neoadjuvant chemotherapy is a standard treatment approach for locally advanced breast cancer. Conventional imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound, have been used for axillary lymph node evaluation which is crucial for treatment planning and prognostication. This systematic review aims to comprehensively examine the current research on applying machine learning algorithms for predicting positive axillary lymph nodes following neoadjuvant chemotherapy utilizing imaging modalities, including MRI, CT, and ultrasound.

Methods

A systematic search was conducted across databases, including PubMed, Scopus, and Web of Science, to identify relevant studies published up to December 2023. Articles employing machine learning algorithms to predict positive axillary lymph nodes using MRI, CT, or ultrasound data after neoadjuvant chemotherapy were included. The review follows the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, encompassing data extraction and quality assessment.

Results

Seven studies were included, comprising 1502 patients. Four studies used MRI, two used CT, and one applied ultrasound. Two studies developed deep-learning models, while five used classic machine-learning models mainly based on multiple regression. Across the studies, the models showed high predictive accuracy, with the best-performing models combining radiomics and clinical data.

Conclusion

This systematic review demonstrated the potential of utilizing advanced data analysis techniques, such as deep learning radiomics, in improving the prediction of positive axillary lymph nodes in breast cancer patients following neoadjuvant chemotherapy.

Combined conventional ultrasonography with clinicopathological features to predict axillary status after neoadjuvant therapy for breast cancer: A case-control study

OBJECTIVES

This study aimed to evaluate the value of a model combining conventional ultrasonography and clinicopathologic features for predicting axillary status after neoadjuvant therapy in breast cancer.

METHODS

This retrospective study included 329 patients with lymph node-positive who underwent neoadjuvant systemic treatment (NST) from June 2019 to March 2022. Ultrasound and clinicopathological characteristics of breast lesions and axillary lymph nodes were analyzed before and after NST. The diagnostic efficacy of ultrasound, clinicopathological characteristics, and combined model were evaluated using multivariate logistic regression and receiver operator characteristic curve (ROC) analyses.

RESULTS

The area under ROC (AUC) for the ability of the combined model to predict the axillary pathological complete response (pCR) after NST was 0.882, that diagnostic effectiveness was significantly better than that of the clinicopathological model (AUC of 0.807) and the ultrasound feature model (AUC of 0.795). In addition, eight features were screened as independent predictors of axillary pCR, including clinical N stage, ERBB2 status, Ki-67, and after NST the maximum diameter reduction rate and margins of breast lesions, the short diameter, cortical thickness, and fatty hilum of lymph nodes.

CONCLUSIONS

The combined model constructed from ultrasound and clinicopathological features for predicting axillary pCR has favorable diagnostic results, which allowed more accurate identification of BC patients who had received axillary pCR after NST.

ADVANCES IN KNOWLEDGE

A combined model incorporated ultrasound and clinicopathological characteristics of breast lesions and axillary lymph nodes demonstrated favorable performance in evaluating axillary pCR preoperatively and non-invasively.

The circRNA-0001361/miR-491/FGFR4 axis is associated with axillary response evaluated by ultrasound following NAC in subjects with breast cancer

Background

miR-491-5p has been reported to regulate the expression of FGFR4 and promote gastric cancer metastasis. Hsa_circ_0001361 was demonstrated to play an oncogenic role in bladder cancer invasion and metastasis by sponging the expression of miR-491-5p. This work aimed to study the molecular mechanism of the effect of hsa_circ_0001361 on axillary response in the treatment of breast cancer.

Methods

Ultrasound examinations was performed to evaluate the response of breast cancer patients receiving NAC treatment. Quantitative real-time PCR, IHC assay, luciferase assay and Western blot were performed to analyze the molecular interaction between miR-491, circRNA_0001631 and FGFR4.

Results

Patients with low circRNA_0001631 expression had a better outcome after NAC treatment. The expression of miR-491 was remarkably higher in the tissue sample and serum collected from patients with lower circRNA_0001631 expression. On the contrary, the FGFR4 expression was notably suppressed in the tissue sample and serum collected from patients with lower circRNA_0001631 expression when compared with patients with high circRNA_0001631 expression. The luciferase activities of circRNA_0001631 and FGFR4 were effectively suppressed by miR-491 in MCF-7 and MDA-MB-231 cells. Moreover, inhibition of circRNA_0001631 expression using circRNA_0001361 shRNA effectively suppressed the expression of FGFR4 protein in MCF-7 and MDA-MB-231 cells. Up-regulation of circRNA_0001631 expression remarkably enhanced the expression of FGFR4 protein in MCF-7 and MDA-MB-231 cells.

Conclusion

Our study suggested that the up-regulation of hsa_circRNA-0001361 could up-regulate the expression of FGFR4 via sponging the expression of miR-491-5p, resulting in the alleviated axillary response after neoadjuvant chemotherapy (NAC) in breast cancer.

Outcomes of a Multidisciplinary Team in the Management of Patients with Early-Stage Breast Cancer Undergoing Neoadjuvant Chemotherapy at a Community Cancer Center

Background: The utilization of neoadjuvant chemotherapy (NAC) remains highly variable in clinical practice. The implementation of NAC requires coordination of handoffs between a multidisciplinary team (MDT). This study aims to assess the outcomes of an MDT in the management of early-stage breast cancer patients undergoing neoadjuvant chemotherapy at a community cancer center. Methods: We conducted a retrospective case series on patients receiving NAC for early-stage operable or locally advanced breast cancer coordinated by an MDT. Outcomes of interest included the rate of downstaging of cancer in the breast and axilla, time from biopsy to NAC, time from completion of NAC to surgery, and time from surgery to radiation therapy (RT). Results: Ninety-four patients underwent NAC; 84% were White and mean age was 56.5 yrs. Of them, 87 (92.5%) had clinical stage II or III cancer, and 43 (45.8%) had positive lymph nodes. Thirty-nine patients (42.9%) were triple negative, 28 (30.8%) were human epidermal growth factor receptor (HER-2)+, and 24 (26.2%) were estrogen receptor (ER) +HER-2-. Of 91 patients, 23 (25.3%) achieved pCR; 84 patients (91.4%) had downstaging of the breast tumor, and 30 (33%) had axillary downstaging. The median time from diagnosis to NAC was 37.5 days, the time from completion of NAC to surgery was 29 days, and the time from surgery to RT was 49.5 days. Conclusions: Our MDT provided timely, coordinated, and consistent care for patients with early-stage breast cancer undergoing NAC as evidenced by time to treatment outcomes consistent with recommended national trends.

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

Purpose

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

Methods

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

Results

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

Conclusion

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

Accuracy of ultrasonographic changes during neoadjuvant chemotherapy to predict axillary lymph node response in clinical node-positive breast cancer patients

Purpose

To evaluate whether changes in ultrasound features during neoadjuvant chemotherapy (NAC) could predict axillary node response in clinically node-positive breast cancer patients.

Methods

Patients with biopsy-proven node-positive disease receiving NAC between February 2009 and March 2021 were included. Ultrasound (US) images were obtained using a 5-12-MHz linear array transducer before NAC, after two cycles, and at the completion of NAC. Long and short diameter, cortical thickness, vascularity, and hilum status of the metastatic node were retrospectively reviewed according to breast imaging-reporting and data system (BI-RADS). The included population was randomly divided into a training set and a validation set at a 2:1 ratio using a simple random sampling method. Factors associated with node response were identified through univariate and multivariate analyses. A nomogram combining clinical and changes in ultrasonographic (US) features was developed and validated. The receiver operating characteristic (ROC) and calibration plots were applied to evaluate nomogram performance and discrimination.

Results

A total of 296 breast cancer patients were included, 108 (36.5%) of whom achieved axillary pathologic complete response (pCR) and 188 (63.5%) had residual nodal disease. Multivariate regression indicated that independent predictors of node pCR contain ultrasound features in addition to clinical features, clinical features including neoadjuvant HER2-targeted therapy and clinical response, ultrasound features after NAC including cortical thickness, hilum status, and reduction in short diameter ≥50%. The nomogram combining clinical features and US features showed better diagnostic performance compared to clinical-only model in the training cohort (AUC: 0.799 vs. 0.699, P=0.001) and the validation cohort (AUC: 0.764 vs. 0.638, P=0.027).

Conclusions

Ultrasound changes during NAC could improve the accuracy to predict node response after NAC in clinically node-positive breast cancer patients.

Added value of systemic inflammation markers for monitoring response to neoadjuvant chemotherapy in breast cancer patients

BACKGROUND

Complete response after neoadjuvant chemotherapy (rNACT) elevates the surgical outcomes of patients with breast cancer, however, non-rNACT have a higher risk of death and recurrence.

AIM

To establish novel machine learning (ML)-based predictive models for predicting probability of rNACT in breast cancer patients who intends to receive NACT.

METHODS

A retrospective analysis of 487 breast cancer patients who underwent mastectomy or breast-conserving surgery and axillary lymph node dissection following neoadjuvant chemotherapy at the Hubei Cancer Hospital between January 1, 2013, and October 1, 2021. The study cohort was divided into internal training and testing datasets in a 70:30 ratio for further analysis. A total of twenty-four variables were included to develop predictive models for rNACT by multiple ML-based algorithms. A feature selection approach was used to identify optimal predictive factors. These models were evaluated by the receiver operating characteristic (ROC) curve for predictive performance.

RESULTS

Analysis identified several significant differences between the rNACT and non-rNACT groups, including total cholesterol, low-density lipoprotein, neutrophil-to-lymphocyte ratio, body mass index, platelet count, albumin-to-globulin ratio, platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio. The areas under the curve of the six models ranged from 0.81 to 0.96. Some ML-based models performed better than models using conventional statistical methods in both ROC curves. The support vector machine (SVM) model with twelve variables introduced was identified as the best predictive model.

CONCLUSION

By incorporating pretreatment serum lipids and serum inflammation markers, it is feasible to develop ML-based models for the preoperative prediction of rNACT and therefore facilitate the choice of treatment, particularly the SVM, which can improve the prediction of rNACT in patients with breast cancer.

Predictors of axillary node response in node-positive patients undergoing neoadjuvant chemotherapy for breast cancer

Background:

The ability to accurately predict which patients will achieve a pathologic complete response (pCR) after neoadjuvant chemotherapy could help identify those who could safely be spared the potential morbidity of axillary lymph node dissection. We performed a retrospective analysis of a cohort of clinically node-positive patients managed with neoadjuvant chemotherapy with the goal of identifying predictors of axillary pCR.

Methods:

Eligible patients were aged 18 years or older, had clinical T1–T4, N1–N3, M0 breast cancer and received neoadjuvant chemotherapy followed by surgical axillary lymph node staging between 2001 and 2017 at Misericordia Hospital, Edmonton, Alberta. Patient data, including tumour characteristics, details of neoadjuvant chemotherapy, imaging results before and after neoadjuvant chemotherapy, and final pathologic analysis, were collected from the appropriate provincial electronic data repositories. We summarized the data using descriptive statistics. We characterized associations between clinical/tumour characteristics and pCR using univariate and multivariate regression analysis.

Results:

Of the 323 patients included in the study, 130 (40.2%) achieved axillary pCR. Absence of residual disease in the breast was associated with axillary pCR (odds ratio 6.74, 95% confidence interval 2.89–15.67). HER2-positive, triple-negative and ER-positive/PR-negative/HER2-negative tumours were significantly associated with a pCR on univariate analysis; the association trended toward significance on multivariate analysis.

Conclusion:

Our findings support the routine use of neoadjuvant chemotherapy and sentinel lymph node biopsy in patients with an absence of residual disease in the breast, and potentially in those with HER2-positive or triple-negative subtypes, and highlight the ER-positive/PR-negative biomarker subtype as a potential predictor of nodal response.

Pathological Response in the Breast and Axillary Lymph Nodes after Neoadjuvant Systemic Treatment in Patients with Initially Node-Positive Breast Cancer Correlates with Disease Free Survival: An Exploratory Analysis of the GeparOcto Trial

Simple Summary

The extent of axillary surgery has been reduced in recent years to minimize side effects. However, a negative impact of reduced surgery on outcome must be avoided. We investigated for whom the extent of surgery can be safely reduced by examining early-stage breast cancer patients converting from lymph node (LN)-positive to LN-negative disease after neoadjuvant systemic treatment (NAST). Of 242 initially LN-positive patients treated within the GeparOcto trial, 54.5% were classified as LN-negative after NAST, 31.8% as LN-positive, and for 13.6% data were missing. Overall, 92.1% of patients underwent complete axillary LN dissection, with 6.6% undergoing sentinel LN dissection only. At surgery, 55.4% of patients had no signs of cancer in the LN, 45.0% had no signs of cancer in the breast (of those 8.3% had involved LN), and 41.3% had no signs of cancer at all. Patients with involved LN still had a bad prognosis. Conversion from LN-positive to LN-negative after NAST is of highest prognostic value. Surgical axillary staging after NAST is essential in these patients to offer tailored treatment.

Abstract

Background: The conversion of initially histologically confirmed axillary lymph node-positive (pN+) to ypN0 after neoadjuvant systemic treatment (NAST) is an important prognostic factor in breast cancer (BC) patients and may influence surgical de-escalation strategies. We aimed to determine pCR rates in lymph nodes (pCR-LN), the breast (pCR-B), and both (tpCR) in women who present with pN+ BC, to assess predictors for response and the impact of pCR-LN, pCR-B, and tpCR on invasive disease-free survival (iDFS). Methods: Retrospective, exploratory analysis of 242 patients with pN+ at diagnosis from the multicentric, randomized GeparOcto trial. Results: Of 242 patients with initially pN+ disease, 134 (55.4%) had a pCR-LN, and 109 (45.0%) a pCR-B. Of the 109 pCR-B patients, 9 (8.3%) patients had involved LN, and 100 (41.3%) patients had tpCR. Those with involved LN still had a bad prognosis. As expected, pCR-B and intrinsic subtypes (TNBC and HER2+) were identified as independent predictors of pCR-LN. pCR-LN (ypN0; hazard ratio 0.42; 95%, CI 0.23–0.75; p = 0.0028 for iDFS) was the strongest independent prognostic factor. Conclusions: In initially pN+ patients undergoing NAST, the conversion to ypN0 is of high prognostic value. Surgical axillary staging after NAST is still essential in these patients to offer tailored treatment.

Nomogram for predicting axillary lymph node pathological response in node-positive breast cancer patients after neoadjuvant chemotherapy

Background:

Pathological complete response (pCR) of axillary lymph nodes (ALNs) is frequently achieved in patients with clinically node-positive breast cancer after neoadjuvant chemotherapy (NAC), and ALN status is an important prognostic factor for breast cancer patients. This study aims to develop a new predictive clinical model to assess the ALN pCR rate after NAC.

Methods:

This was a retrospective series of 467 patients who had biopsy-proven positive ALNs at diagnosis and underwent ALN dissection from 2007 to 2014 at the National Cancer Center/Cancer Hospital of the Chinese Academy of Medical Sciences. We analyzed the clinicopathologic features of the patients and developed a nomogram to predict the probability of ALN pCR. A multivariable logistic regression stepwise model was used to construct a nomogram to predict ALN pCR in node-positive patients. The adjusted area under the receiver operating characteristic curve (AUC) was calculated to quantify the ability to rank patients by risk. Internal validation was performed using the 50/50 hold-out validation method. The nomogram was externally validated with prospective cohorts of 167 patients from 2016 to 2018 at the Cancer Hospital of the Chinese Academy of Medical Sciences and 114 patients from 2018 to 2020 at Beijing Tiantan Hospital.

Results:

In this retrospective study, 115 (24.6%) patients achieved ALN pCR after NAC. Multivariate analysis showed that clinical tumor stage (Odds ratio [OR]: 0.321, 95% confidence interval [CI]: 0.121–0.856; P = 0.023); primary tumor response (OR: 0.189; 95% CI: 0.123–0.292; P < 0.001), and estrogen receptor status (OR: 0.530, 95% CI: 0.304–0.925; P = 0.025) were independent predictors of ALN pCR. The nomogram was constructed based on the result of multivariate analysis. In the internal validation of performance of nomogram, the AUCs for the training and test sets were 0.719 and 0.753, respectively. The nomogram was validated in external cohorts with AUCs of 0.720, which demonstrated good discriminatory power in these data sets.

Conclusion:

We developed a nomogram to predict the likelihood of axillary pCR in node-positive breast cancer patients after NAC. The predictive model performed well in multicenter prospective external validation. This practical tool could provide information to surgeons regarding whether to perform additional ALN dissection after NAC.

Trial registration:

ChiCTR.org.cn, ChiCTR1800014968.

A Practical Predictive Model Based on Ultrasound Imaging and Clinical Indices for Estimation of Response to Neoadjuvant Chemotherapy in Patients with Breast Cancer

Purpose

Clinical responses of neoadjuvant chemotherapy (NACT) are associated with prognosis in patients with breast cancer. The selection of suitable variables for the prediction of clinical responses remains controversial. Herein, we developed a predictive model based on ultrasound imaging and clinical indices to identify patients most likely to benefit from NACT.

Patients and Methods

We recruited a total of 225 consecutive patients who underwent NACT followed by surgery and axillary lymph node dissection at the Sixth Hospital of Ning Bo City of Zhe Jiang Province between January 1, 2018, and March 31, 2021. All patients had been diagnosed with breast cancer following the clinical examination. First, we created a training cohort of patients who underwent NACT+surgery (N=180) to develop a nomogram. We then validated the performance of the nomogram in a validation cohort of patients who underwent NACT+ surgery (N=45). Multivariate logistic regression was then used to identify independent risk factors that were associated with the response to NACT; these were then incorporated into the nomogram.

Results

Multivariate logistic regression analysis identified several significant differences as to clinical responses of NACT, including neutrophil–lymphocyte ratio (NLR), body mass index (BMI), pulsatility index (PI), resistance index (RI), blood flow, Ki67, histological type, molecular subtyping, and tumor size. The performance of the nomogram score exhibited a robust C-index of 0.89 (95% confidence interval [CI]: 0.83 to 0.95) in the training cohort and a high C-index of 0.87 (95% CI: 0.81 to 0.93) in the validation cohort. Clinical impact curves showed that the nomogram had a good predictive ability.

Conclusion

We successfully established an accurate and optimized nomogram incorporated ultrasound imaging and clinical indices that could be used preoperatively to predict clinical responses of NACT. This model can be used to evaluate the risk of clinical responses to NACT and therefore facilitate the choice of personalized therapy.

Axillary Nodal Evaluation in Breast Cancer: State of the Art

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

Axillary ultrasound for prediction of response to neoadjuvant therapy in the context of surgical strategies to axillary dissection in primary breast cancer: a systematic review of the current literature

PURPOSE

Data on the optimal treatment strategy for patients undergoing neoadjuvant therapy (NAT) who initially presented with metastatic nodes and convert to node-negative disease (cN+ → ycN0) are limited. Since NAT leads to axillary downstaging in 20-60% of patients, the question arises whether these patients might be offered less-invasive procedures than axillary dissection, such as sentinel node biopsy or targeted removal of lymph nodes marked before therapy.

METHODS

We performed a systematic review of clinical studies on the use of axillary ultrasound for prediction of response to NAT and ultrasound-guided marking of metastatic nodes for targeted axillary dissection.

RESULTS

The sensitivity of ultrasound for prediction of residual node metastasis was higher than that of clinical examination and MRI/PET in most studies; specificity ranged in large trials from 37 to 92%. The diagnostic performance of ultrasound after NAT seems to be associated with tumor subtype: the positive predictive value was highest in luminal, the negative in triple-negative tumors. Several trials evaluated the usefulness of ultrasound for targeted axillary dissection. Before NAT, nodes were most commonly marked using ultrasound-guided clip placement, followed by ultrasound-guided placement of a radioactive seed. After chemotherapy, the clip was detected on ultrasound in 72-83% of patients; a comparison of sonographic visibility of different clips is lacking. Detection rate after radioactive seed placement was ca. 97%.

CONCLUSION

In conclusion, ultrasound improves prediction of axillary response to treatment in comparison to physical examination and serves as a reliable guiding tool for marking of target lymph nodes before the start of treatment. High quality and standardization of the examination is crucial for selection of patients for less-invasive surgery.

Ultrasound-guided dual-localization for axillary nodes before and after neoadjuvant chemotherapy with clip and activated charcoal in breast cancer patients: a feasibility study

Background

We report on our experience of ultrasound (US)-guided dual-localization for axillary nodes before and after neoadjuvant chemotherapy (NAC) with clip and activated charcoal to guide axillary surgery in breast cancer patients.

Methods

Between November 2017 and May 2018, a dual-localization procedure was performed under US guidance for the most suspicious axillary nodes noted at initial staging (before NAC, with clip) and restaging (after NAC, with activated charcoal) in 28 cytologically proven node-positive breast cancer patients. Patients underwent axillary sampling or dissection, which involved removing not only the sentinel nodes (SNs), but also clipped nodes (CNs) and tattooed nodes (TNs). Success (or failure) rates of biopsies of SNs, CNs, and TNs and inter-nodal concordance rates were determined. Sensitivities for the individual and combined biopsies were calculated.

Results

SN biopsy failed in four patients (14%), whereas the CN biopsy failed in one patient (4%). All TNs were identified in the surgical field. Concordance rates were 79% for CNs–TNs, 63% for CNs–SNs, and 58% for TNs–SNs. Sensitivity for SN, CN, and TN biopsy was 73%, 67%, and 67%, respectively. Sensitivity was 80% for any combination of biopsies (SN plus CN, SN plus TN, SN plus CN plus TN).

Conclusions

US-guided dual-localization of axillary nodes before and after NAC with clip and activated charcoal was a feasible approach that might facilitate more reliable nodal staging with less-invasive strategies in node-positive breast cancer patients.

Does Tumor Size Predict Response to Neoadjuvant Chemotherapy in the Modern Era of Biologically Driven Treatment? A Nationwide Study of US Breast Cancer Patients

BACKGROUND

Tumor size has historically been used to stage breast cancer and guide treatment recommendations. The importance of tumor biology in long-term outcomes is increasingly being acknowledged. No large studies have examined the relative roles of tumor size and receptor status on response to neoadjuvant chemotherapy (NAC) in breast cancer.

PATIENTS AND METHODS

The National Cancer Database was queried for women who underwent NAC and surgery for unilateral clinical stage I to III (cT1-3) invasive breast cancer from 2010 to 2013. Multivariable logistic regression models were used to assess the relation between receptor status, tumor size, and pathologic complete response (pCR) while controlling for other biologic, sociodemographic, diagnosis, and treatment factors.

RESULTS

We included 38,864 women in this study, most presented with cT2 disease (55%). Patients predominantly had estrogen receptor (ER)/progesterone receptor (PR)-positive (ER/PR⁺) HER2^- (45%) or ER/PR^- HER2^- (28%) disease. Nineteen percent (7432 patients) had a pCR. cT3 (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.59-0.70) but not cT2 cancers (OR, 0.95; 95% CI, 0.89-1.02) were associated with lower pCR rates compared with cT1 disease. HER2⁺ (ER/PR⁺ HER2⁺: OR, 2.94; 95% CI, 2.72-3.18; ER/PR^- HER2⁺: OR, 6.45; 95% CI, 5.92-7.02) and ER/PR^- HER2^- cancers (OR, 3.94; 95% CI, 3.68-4.22) were more likely to experience pCR than those with ER/PR⁺ HER2^- cancers. Receptor status was more strongly associated with pCR than tumor size.

CONCLUSION

Tumor size is independently associated with pCR after NAC after controlling for receptor status, although the effect of receptor status is stronger. These data reinforce the importance of receptor status as well as tumor size, each of which might act as surrogates for tumor biology, in setting expectations for outcomes in patients who undergo NAC.