MRI does not predict pathologic complete response after neoadjuvant chemotherapy for breast cancer

Precision Oncology in Breast Cancer Surgery

Outcomes for patients with breast cancer have improved over time due to increased screening and the availability of more effective therapies. It is important to recognize that breast cancer is a heterogeneous disease that requires treatment based on molecular characteristics. Early endpoints such as pathologic complete response correlate with event-free survival, allowing the opportunity to consider de-escalation of certain cancer treatments to avoid overtreatment. This article discusses clinical trials of tailoring treatment (eg, I-SPY2) and screening (eg, WISDOM) to individual patients based on their unique risk features.

Evaluating persistent T1-weighted lesions without concurrent abnormal enhancement on breast MRI in neoadjuvant chemotherapy patients: implications for complete pathological response

OBJECTIVE

This study aims to determine whether persistent T1-weighted lesions signify a complete pathological response (pCR) in breast cancer patients treated with neoadjuvant chemotherapy and surgery, and to evaluate their correlation with imaging responses on MRI.

MATERIALS AND METHODS

A retrospective review was conducted on data from breast cancer patients treated between January 2011 and December 2018. Patients who underwent breast MRI and pre- and post-neoadjuvant chemotherapy followed by surgery were included. Those with distant metastasis, no planned surgery, pre-surgery radiation, ineligibility for neoadjuvant chemotherapy, or unavailable surgical pathology were excluded. Groups with and without persistent T1-weighted lesions were compared using the chi-square test for categorical variables and the Student t test or Wilcox rank sum test for continuous variables. Univariate logistic regression was used to evaluate the association of the final pathological response with the presence of T1-persistent lesion and other characteristics.

RESULTS

Out of 319 patients, 294 met the inclusion criteria (breast cancer patients treated with neoadjuvant chemotherapy and subsequent surgery); 157 had persistent T1 lesions on post-chemotherapy MRI and 137 did not. A persistent T1 lesion indicated reduced likelihood of complete pathological response (14% vs. 39%, p < 0.001) and imaging response (69% vs. 93%, p < 0.001). Multivariable analysis confirmed these findings: OR 0.37 (95% CI 0.18-0.76), p = 0.007. No other characteristics correlated with T1 residual lesions.

CONCLUSION

Persistent T1-weighted lesions without associated abnormal enhancement on post-treatment breast MRI correlate with lower complete pathological and imaging response rates.

CLINICAL RELEVANCE STATEMENT

The study underscores the importance of persistent T1-weighted lesions on breast MRI as vital clinical markers, being inversely related to a complete pathological response following neoadjuvant chemotherapy; they should be a key factor in guiding post-neoadjuvant chemotherapy treatment decisions.

KEY POINTS

• Persistent T1 lesions on post-chemotherapy breast MRI indicate a reduced likelihood of achieving a complete pathological response (14% vs. 39%, p < 0.001) and imaging response (69% vs. 93%, p < 0.001). • Through multivariable analysis, it was confirmed that the presence of a persistent T1 lesion on breast MRI post-chemotherapy is linked to a decreased likelihood of complete pathological response, with an odds ratio (OR) of 0.37 (95% CI 0.18-0.76; p = 0.007). • In addition to the convention of equating the absence of residual enhancement to complete imaging response, our results suggest that the presence or absence of residual T1 lesions should also be considered.

The accuracy of MRI in detecting pathological complete response following neoadjuvant chemotherapy in different breast cancer subtypes

BACKGROUND

Pathological complete response (pCR) following neo-adjuvant chemotherapy (NACT) for breast cancer is associated with improved disease-free and overall survival in certain breast cancer subtypes. Magnetic Resonance Imaging (MRI) is increasingly used as standard to assess treatment response in patients receiving NACT. The aim of this study was to determine the clinical utility of MRI in accurately predicting pCR post-NACT.

METHODS

A single-centre, retrospective study was conducted in breast cancer patients, who received NACT between 2013 and 2020. Patients who had an MRI before and after NACT were included. Pathological and MRI radiological response rates to NACT were analyzed and MRI accuracy assessed in detecting pCR according to breast cancer subtype.

RESULTS

One hundred and sixty-seven patients were included in the study. Forty-one of the 167 patients achieved pCR (24.6 %), with the highest proportion in HR- HER2+ subgroup (58.3 %), followed by triple negative breast cancer (TNBC) (35 %). Only 22.2 % and 10.5 % of patients with HR + HER2+ and HR + HER2-respectively achieved pCR. The overall accuracy of MRI in predicting pCR after NACT was 77.3 %. The greatest accuracy was in TNBC (87.5 %) with a specificity and positive predictive value (PPV) of 100 % and the highest number of correctly diagnosed complete responses (14 of 40). MRI was less accurate in predicting response rates in HR + HER2- (PPV 91.2 %) and HR + HER2+ groups (PPV 90.5 %). MRI performed significantly better in predicting complete response in TNBC compared to HR + HER2-subtype (p = 0.0057).

CONCLUSION

MRI is a clinically useful adjunct in assessing pCR following NACT and appears to predict pathological response more accurately in TNBC compared to HR + HER2-breast cancer subtypes. This has significant clinical implications in terms of surgical planning, adjuvant treatment options and prognosis.

Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review

Breast cancer stands out as the most frequently identified malignancy, ranking as the fifth leading cause of global cancer-related deaths. The American College of Radiology (ACR) introduced the Breast Imaging Reporting and Data System (BI-RADS) as a standard terminology facilitating communication between radiologists and clinicians; however, an update is now imperative to encompass the latest imaging modalities developed subsequent to the 5th edition of BI-RADS. Within this review article, we provide a concise history of BI-RADS, delve into advanced mammography techniques, ultrasonography (US), magnetic resonance imaging (MRI), PET/CT images, and microwave breast imaging, and subsequently furnish comprehensive, updated insights into Molecular Breast Imaging (MBI), diagnostic imaging biomarkers, and the assessment of treatment responses. This endeavor aims to enhance radiologists' proficiency in catering to the personalized needs of breast cancer patients. Lastly, we explore the augmented benefits of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in segmenting, detecting, and diagnosing breast cancer, as well as the early prediction of the response of tumors to neoadjuvant chemotherapy (NAC). By assimilating state-of-the-art computer algorithms capable of deciphering intricate imaging data and aiding radiologists in rendering precise and effective diagnoses, AI has profoundly revolutionized the landscape of breast cancer radiology. Its vast potential holds the promise of bolstering radiologists' capabilities and ameliorating patient outcomes in the realm of breast cancer management.

Development and External Validation of 18F-FDG PET-Based Radiomic Model for Predicting Pathologic Complete Response after Neoadjuvant Chemotherapy in Breast Cancer

The aim of our retrospective study is to develop and externally validate an 18F-FDG PET-derived radiomics model for predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients. A total of 87 breast cancer patients underwent curative surgery after NAC at Soonchunhyang University Seoul Hospital and were randomly assigned to a training cohort and an internal validation cohort. Radiomic features were extracted from pretreatment PET images. A radiomic-score model was generated using the LASSO method. A combination model incorporating significant clinical variables was constructed. These models were externally validated in a separate cohort of 28 patients from Soonchunhyang University Buscheon Hospital. The model performances were assessed using area under the receiver operating characteristic (AUC). Seven radiomic features were selected to calculate the radiomic-score. Among clinical variables, human epidermal growth factor receptor 2 status was an independent predictor of pCR. The radiomic-score model achieved good discriminability, with AUCs of 0.963, 0.731, and 0.729 for the training, internal validation, and external validation cohorts, respectively. The combination model showed improved predictive performance compared to the radiomic-score model alone, with AUCs of 0.993, 0.772, and 0.906 in three cohorts, respectively. The 18F-FDG PET-derived radiomic-based model is useful for predicting pCR after NAC in breast cancer.

Can breast MRI predict pathologic response following neoadjuvant chemotherapy for breast cancer? A retrospective cohort study

PURPOSE

For patients treated with neoadjuvant chemotherapy (NAC) for breast cancer, it is standard of care to perform pre- and post-NAC imaging to evaluate response to therapy prior to surgery. In this study we assess outcome metrics of magnetic resonance imaging (MRI) following NAC.

METHODS

We conducted a retrospective analysis of patients with invasive breast cancer who underwent a breast MRI before and after NAC between 2016 and 2021 at a single, multisite academic institution. All breast MRI studies were characterized as either radiologic complete response (rCR) or non-rCR. Corresponding surgical pathology reports were reviewed and categorized as pathologic complete response (pCR) or non-pCR. We defined a positive test as having residual enhancement on MRI (non-rCR) and a positive outcome as having residual disease on final surgical pathology (non-pCR).

RESULTS

There were 225 patients included in the study (mean age 52 ± 12 years). Breast cancer receptor distribution was HR+/HER2- (n = 71, 32%), HR+/HER2+ (n = 51, 23%), HR-/HER2- (n = 72, 32%), and HR-/HER2+ (n = 31, 14%). In total, 78 (35%) had rCR and 77 (34%) had pCR; 43 (19%) had both rCR and pCR. The overall accuracy rate was 69% (156/225), sensitivity 76% (113/148), specificity 56% (43/77), positive predictive value 77% (113/147), and negative predictive value 55% (43/78). The PPV was significantly associated with receptor status (p = 0.004). No patient or imaging characteristics were associated with sensitivity.

CONCLUSION

Breast MRI only moderately predicts pathologic response for invasive breast cancer treated with NAC (overall accuracy 69%). PPV is significantly associated with receptor status.

Correlation of Mammographic Microcalcifications with Final Surgical Pathology After Neoadjuvant Chemotherapy for Breast Cancer

INTRODUCTION

Imaging guidelines for post-neoadjuvant chemotherapy (NAC) breast cancer patients lack specificity on appropriateness and utility of individual modalities for surgical planning. Microcalcifications confound mammographic interpretation. We examined the correlation between the mammographic extent of microcalcifications present post-NAC, corresponding magnetic resonance imaging (MRI) lesions, and definitive surgical pathology.

METHODS

In this retrospective cohort study, patients with calcifications on mammography were collected from a database of consecutive breast cancer patients receiving NAC. The primary objective was to determine the correlation between maximum dimension of post-NAC calcifications with surgical pathology (invasive disease, tumor bed, and ductal carcinoma in situ [DCIS]), stratified by tumor receptor subgroup. Secondarily, we examined the correlation of residual disease with MRI mass enhancement (ME) and non-ME (NME). Pearson's correlation coefficient was used to evaluate statistical significance (strong: R² ≥70%; moderate: R²=25-70%; weak: R² ≤25%).

RESULTS

Overall, 186 patients met the inclusion criteria. Mammographic calcifications correlated poorly with invasive disease (R² = 10.8%), overestimating by 57%. In patients with calcifications on mammography, MRI ME and NME correlated weakly with the maximum dimension of invasive disease and DCIS. In triple-negative breast cancer (TNBC) patients, invasive disease correlated strongly with the maximum dimension of calcifications (R² = 83%) and moderately with ME (R² = 37.7%) and NME (R² = 28.4%).

CONCLUSION

Overall, current imaging techniques correlate poorly and overestimate final surgical pathology. This poor correlation may lead to uncertainty in the extent of required surgical excision and the exclusion of potential candidates for non-surgical management in ongoing trials. TNBCs would be good candidates for these trials given the stronger observed correlations between pathology and imaging.

A review of studies on omitting surgery after neoadjuvant chemotherapy in breast cancer

The advancement in systemic neoadjuvant therapy has significantly increased the pathological complete response (pCR) rate in breast cancer. As surgeries inevitably affect patients physically and psychologically and the accuracy of pCR prediction and diagnosis by minimal invasive biopsy is improving, the necessity of surgery in neoadjuvant chemotherapy (NAC) patients who achieve pCR is under debate. Thus, we conducted a literature review of studies on the selective omission of breast surgery after NAC for breast cancer patients. We summarized the existing predictive models and technologies to predict and diagnose pCR after NAC. Our research indicates that, for nearly half a century, the extent of surgery on both breast and axillary lymph nodes is decreasing, while more precise systematic treatments are increasing. NAC has advanced significantly and its pCR rates have improved, so surgery may be omitted in certain patients. However, accurately predicting pCR after NAC is still a challenge. We also described the design for a randomized clinical trial and the potential problems of omitting surgical treatment after NAC. In summary, the decrease in breast cancer surgery is an unavoidable trend, and more high-quality clinical trials need to be conducted.

Visual Evaluation of Ultrafast MRI in the Assessment of Residual Breast Cancer after Neoadjuvant Systemic Therapy: A Preliminary Study Association with Subtype

The purpose of this study was to investigate the diagnostic performance of ultrafast DCE (UF-DCE) MRI after the completion of neoadjuvant systemic therapy (NST) in breast cancer. In this study, MR examinations of 55 post-NST breast cancers were retrospectively analyzed. Residual tumor sizes were measured in the 20th phase of UF-DCE MRI, early and delayed phases of conventional DCE MRI, and high spatial-resolution CE MRI (UF, early, delayed, and HR, respectively). The diagnostic performance for the detection of residual invasive cancer was calculated by ROC analysis. The size difference between MRI and pathological findings was analyzed using the Wilcoxon signed-rank test with the Bonferroni correction. The overall AUC was highest for UF (0.86 and 0.88 for readers 1 and 2, respectively). The difference in imaging and pathological sizes for UF (5.7 ± 8.2 mm) was significantly smaller than those for early, delayed, and HR (p < 0.01). For luminal subtype breast cancer, the size difference was significantly smaller for UF and early than for delayed (p < 0.01). UF-DCE MRI demonstrated higher AUC and specificity for the more accurate detection of residual cancer and the visualization of tumor extent than conventional DCE MRI.

Plasma Cell-Free DNA Integrity Assessed by Automated Electrophoresis Predicts the Achievement of Pathologic Complete Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer

PURPOSE

The study of plasma cell-free DNA integrity (cfDI) has shown potential for providing useful information in neoplastic patients. The aim of this study is to estimate the accuracy of an electrophoresis-based method for cfDI evaluation in the assessment of pathologic complete response (pCR) in patients with breast cancer (BC) undergoing neoadjuvant chemotherapy (NACT).

PATIENTS AND METHODS

Fifty-one patients with BC undergoing anthracycline-/taxane-based NACT were recruited. Plasma samples were collected from each patient at diagnosis (t0), after anthracycline administration (t1), and after NACT completion (t2). The concentration of differently sized cell-free DNA fragments was assessed by automated electrophoresis. cfDI, expressed as cfDI index, was calculated as the ratio of 321-1,000 bp sized fragment concentration to 150-220 bp sized fragment concentration assessed at t2. cfDI index was then used to build an exploratory classifier for BC response to NACT, directly comparing its sensitivity and specificity with magnetic resonance imaging (MRI), through bootstrapped logistic regression.

RESULTS

cfDI index was assessed on 38 plasma samples collected from as many patients at t2, maintaining a 30/70 ratio between pCR and non-pCR patients. cfDI index showed an area under the receiver operating characteristic curve in predicting the achievement of pCR of 81.6, with a cutoff above 2.71 showing sensitivity = 81.8 and specificity = 81.5. The combination of cfDI index and MRI showed, in case of concordance, an area under the receiver operating characteristic curve of 92.6 with a predictive value of complete response of 87.5 and a predictive value of absence of complete response of 94.7.

CONCLUSION

cfDI index measured after NACT completion shows great potential in the assessment of pCR in patients with BC. The evaluation of its use in combination with MRI is strongly warranted in prospective studies.

Plasma DNA fragmentation assessment predicts response to neoadjuvant chemotherapy in breast cancer.

Abbreviated and Standard Breast MRI in Neoadjuvant Chemotherapy Response Evaluation: A Comparative Study

OBJECTIVES

To investigate the efficacy of abbreviated breast magnetic resonance imaging (MRI) in neoadjuvant chemotherapy (NAC) response evaluation.

METHODS

MR images of 50 locally advanced breast cancer patients who underwent standard protocol (SP) breast MRI before and after NAC, were re-evaluated retrospectively. Abbreviated protocol (AP) was obtained by extracting images from SP and then evaluating them in a separate session. Protocols were compared with the histological findings after surgery as the reference standard.

RESULTS

A statistically significant difference was found between two protocols in response evaluation by the McNemar test (p=0.018). But, the Kappa value was 0.62 (p<0.001) which indicates substantial agreement. No statistically significant differences were found between the two protocols (AP and SP) and pathological results in the McNemar test (p=0.12, p=0.60, respectively). Kappa values were 0.48 (p<0.001), 0.60 (p<0.001), respectively which indicates moderate agreement for both protocols with higher values by SP evaluation. The residual maximum median diameters were smaller than the pathology, with both protocols (p<0.001).

CONCLUSION

Although statistical difference, there was a substantial correlation between the two protocols in response evaluation. Both protocols were moderately correlated with pathological results with slightly higher in SP. However, the residual maximum median diameters were smaller than the pathology, with both protocols. These results may limit the use of AP in evaluating the local extent of the tumor, especially in patients who will undergo breast-conserving surgery.

Role of MRI in predicting response to neo-adjuvant systemic therapy (NAST) in breast cancer

BACKGROUND AND OBJECTIVES

MRI is generally performed to assess response to Neo-adjuvant systemic therapy (NAST) in breast cancer.

OBJECTIVE

To assess role of MRI in determining the probability of having residual disease in patients undergoing NAST. We also evaluated synchronous cancers diagnosed following MRI.

METHODS

This is a retrospective study which included all patients who had pre-and post-NAST MRI between June 2014 and December 2019. Data on demographics, tumour characteristics and pathology were collected and analysed. Pre- and post-MRI probability were calculated and depicted on nomograms.

RESULTS

The study included 205 patients. Overall pre-MRI probability of having residual disease was 55% (OR:1.2). The post-MRI probability was 78% (95% CI 72-83%; OR:3.5) if MRI showed residual disease and 23% (95% CI 16-31%, OR:0.3) if imaging showed complete response. The absolute benefit was higher in TNBC and HR-HER2. Additional cancers were identified in 8.78% of patients.

CONCLUSION

MRI is beneficial in evaluating response to NAST specifically in TNBC and HR-HER2 cancers. Pre- and post-MRI probabilities of residual disease depicted on nomograms are a useful tool for clinicians. MRI can potentially impact the treatment decisions by identification of synchronous cancers.

Computer-aided classification of MRI for pathological complete response to neoadjuvant chemotherapy in breast cancer

Background: To determine suitable optimal classifiers and examine the general applicability of computer-aided classification to compare the differences between a computer-aided system and radiologists in predicting pathological complete response (pCR) from patients with breast cancer receiving neoadjuvant chemotherapy. Methods: We analyzed a total of 455 masses and used the U-Net network and ResNet to execute MRI segmentation and pCR classification. The diagnostic performance of radiologists, the computer-aided system and a combination of radiologists and computer-aided system were compared using receiver operating characteristic curve analysis. Results: The combination of radiologists and computer-aided system had the best performance for predicting pCR with an area under the curve (AUC) value of 0.899, significantly higher than that of radiologists alone (AUC: 0.700) and computer-aided system alone (AUC: 0.835). Conclusion: An automated classification system is feasible to predict the pCR to neoadjuvant chemotherapy in patients with breast cancer and can complement MRI.

Innovative Standards in Surgery of the Breast after Neoadjuvant Systemic Therapy

BACKGROUND

The goal of neoadjuvant systemic therapy (NST) in breast cancer is to downstage tumors and downgrade treatment. Indications are constantly evolving. These changes raise practical questions for planning of surgery after NST.

SUMMARY

In this review we discuss current evolving aspects of surgery of the breast after NST. Breast-conserving surgery (BCS) eligibility increases after NST - both neoadjuvant chemotherapy (NAC) and neoadjuvant endocrine therapy. Adequate margin width in NST and upfront surgery are similar - "no tumor on ink" for invasive cancer. Oncoplastic breast surgery after NST is feasible - both for BCS and mastectomy with reconstruction. There is increasing interest in the possibility of omitting surgery in patients with a complete response to NAC. Several trials are being conducted in aim of achieving acceptable prediction of pathological complete response, by combination of imaging and percutaneous biopsy of the tumor bed, as well as assessing the safety of such an approach.

KEY MESSAGES

Surgery of the breast after NST should be determined not only according to biologic and anatomic parameters at diagnosis, but is dynamic, and must be tailored according to the response to therapy. The omission of surgery in exceptional responders after NAC is being explored.

Factors associated with relapse-free survival after neoadjuvant chemotherapy for breast cancer at a safety net medical center

BACKGROUND

This study was designed to assess prognostic factors associated with relapse-free survival (RFS) after neoadjuvant chemotherapy (NAC) for breast cancer.

METHODS

A single-institution retrospective analysis was performed including clinical, radiographic, and pathologic parameters for all breast cancer patients treated with NAC from 2015 to 2018. All patients had pre-and post-NAC MRI.

RESULTS

For 102 patients, median follow-up was 47.4 months, and the five-year RFS was 74%. The 41 (40%) patients who achieved pathologic complete response (pCR) after NAC had a significantly higher five-year RFS than the 61 not achieving pCR. For 31 patients with triple-negative cancers, the five-year RFS was significantly higher in those achieving pCR vs. no pCR. The 44 (43%) patients who achieved radiographic complete response (rCR) after NAC had similar five-year RFS to the 58 (57%) not achieving rCR.

CONCLUSION

pCR, node-negativity after NAC, and triple-negative subtype were prognostic factors associated with relapse-free survival after NAC.

Contrast-Enhanced Mammography: Technique, Indications, and Review of Current Literature

Purpose of Review

To provide an update on contrast-enhanced mammography (CEM) regarding current technique and interpretation, the performance of this modality versus conventional breast imaging modalities (mammography, ultrasound, and MRI), existing clinical applications, potential challenges, and pitfalls.

Recent Findings

Multiple studies have shown that the low-energy, non-contrast-enhanced images obtained when performing CEM are non-inferior to full-field digital mammography with the added benefit of recombined post-contrast images, which have been shown to provide comparable information compared to MRI without sacrificing sensitivity and negative predictive values. While CEMs' usefulness for further diagnostic characterization of indeterminate breast findings is apparent, additional studies have provided strong evidence of potential roles in screening intermediate to high-risk populations, evaluation of disease extent, and monitoring response to therapy, particularly in patients in whom MRI is either unavailable or contraindicated. Others have shown that some patients prefer CEM over MRI given the ease of performance and patient comfort. Additionally, some health systems may find significantly reduced costs compared to MRI. Currently, CEM is hindered by the limited availability of CEM-guided tissue sampling and issues of intravenous contrast administration. However, commercially available CEM-guided biopsy systems are on the horizon, and small changes in practice workflow can be quickly adopted. As of now, MRI remains a mainstay of high-risk screening, evaluation of the extent of disease, and monitoring response to therapy, but smaller studies have suggested that CEM may be equivalent to MRI for these indications, and larger confirmatory studies are needed.

Summary

CEM is an emerging problem-solving breast imaging modality that provides complementary information to conventional imaging modalities and may potentially be used in place of MRI for specific indications and/or patient populations.

Pre-treatment MRI tumor features and post-treatment mammographic findings: may they contribute to refining the prediction of pathologic complete response in post-neoadjuvant breast cancer patients with radiologic complete response on MRI?

PURPOSE

Radiologic complete response (rCR) in breast cancer patients after neoadjuvant chemotherapy (NAC) does not necessarily correlate with pathologic complete response (pCR), a marker traditionally associated with better outcomes. We sought to verify if data extracted from two important steps of the imaging workup (tumor features at pre-treatment MRI and post-treatment mammographic findings) might assist in refining the prediction of pCR in post-NAC patients showing rCR.

METHODS

A total of 115 post-NAC women with rCR on MRI (2010-2016) were retrospectively assessed. Pre-treatment MRI (lesion morphology, size, and distribution) and post-treatment mammographic findings (calcification, asymmetry, mass, architectural distortion) were assessed, as well as clinical and molecular variables. Bivariate and multivariate analyses evaluated correlation between such variables and pCR. Post-NAC mammographic findings and their correlation with ductal in situ carcinoma (DCIS) were evaluated using Pearson's correlation.

RESULTS

Tumor distribution at pre-treatment MRI was the only significant predictive imaging feature on multivariate analysis, with multicentric lesions having lower odds of pCR (p = 0.035). There was no significant association between tumor size and morphology with pCR. Mammographic residual calcifications were associated with DCIS (p = 0.009). The receptor subtype remained as a significant predictor, with HR-HER2 + and triple-negative status demonstrating higher odds of pCR on multivariate analyses.

CONCLUSIONS

Multicentric lesions on pre-NAC MRI were associated with a lower chance of pCR in post-NAC rCR patients. The receptor subtype remained a reliable predictor of pCR. Residual mammographic calcifications correlated with higher odds of malignancy, making the correlation between mammography and MRI essential for surgical planning. Key Points • The presence of a multicentric lesion on pre-NAC MRI, even though the patient reaches a radiologic complete response on MRI, is associated with a lower chance of pCR. • Molecular status of the tumor remained the only significant predictor of pathologic complete response in such patients in the present study. • Post-neoadjuvant residual calcifications found on mammography were related to higher odds of residual malignancy, making the correlation between mammography and MRI essential for surgical planning.

Characterizing Occult Nodal Disease Within a Clinically Node-Negative, Neoadjuvant Breast Cancer Population

BACKGROUND

Neoadjuvant therapy aims to preoperatively downstage breast cancer patients. We evaluated nodal upstaging in clinically node-negative (cN0) patients receiving neoadjuvant chemotherapy (NAC) and neoadjuvant endocrine therapy (NET).

METHODS

cN0 patients undergoing neoadjuvant therapy from 2009 to 2018 were reviewed. Univariate and multivariate analyses evaluated rates of nodal upstaging.

RESULTS

A total of 228 cN0 patients with a mean age of 55 years underwent neoadjuvant therapy for Stage I-III invasive carcinoma. Subtypes included ER+/HER2- = 93 (40%), HER2+ = 61 (27%), and triple negative (TNBC) = 74 (33%). Among ER+/HER2- patients, 65 (70%) underwent NET. Overall, 49 patients (21%) were upstaged due to occult nodal disease. Factors associated with higher rates of occult nodal disease included advanced stage on initial presentation (P = .008), larger presenting tumor size (P = .009), low/intermediate tumor grade (P = .025), and ER+/HER2- subtype (P < .001); incidence of occult nodal disease by subtype included: ER+/HER2- = 37%, HER2+ = 15%, TNBC = 8%. Patients experiencing a breast pCR had a significantly lower rate of nodal upstaging compared to those with residual tumor (4% vs. 96%, P < .001). On multivariate analysis, ER+/HER- patients exhibited higher risk of occult nodal disease when compared to patients with HER2+ (odds ratio [OR] = 3.4, 95% CI, 1.2-9.8, P = .003) and TNBC (OR = 5.7, 95% CI, 1.7-19.6, P = .003). Comparing NAC vs. NET in ER+/HER2- patients showed no difference in rates of occult nodal disease (39% vs. 35%, P = .13).

CONCLUSIONS

ER+/HER2- subtype carries higher risk for occult nodal disease after neoadjuvant therapy; NAC versus NET in these patients does not affect nodal upstaging.

Is pathological complete response predictable after neoadjuvant chemotherapy in breast cancer? A single institution's retrospective experience

BACKGROUND

Pathological complete response (pCR), in breast cancers, after neoadjuvant chemotherapy is linked to improved survival. Determining complete response to chemotherapy prior to surgery has remained elusive even using a combination of pathological factors and imaging modalities, making surgery still a necessity.

METHODS

A retrospective analysis was performed from a single institution from 2013 to 2018. Breast cancer patients treated with neoadjuvant chemotherapy with pre- and post-chemotherapy magnetic resonance imaging (MRI) were included. Patients receiving other neoadjuvant modalities were excluded. Imaging characteristics, including response to chemotherapy and pathological factors, were recorded.

RESULTS

Analysis showed 134 patients were identified with 40/134 (29.9%) noted to have radiological complete response and 34/134 (25.6%) had pCR. The positive predictive value for MRI to detect pCR was greatest for oestrogen receptor (ER) negative and human epidermal growth factor receptor 2 (HER2) negative tumours at 81.8% and worst for ER+ HER2- tumours at 25%. The negative predictive value was greatest for ER+ HER2- tumours at 93.9% and worst for ER- HER2- tumours at 77.4%.

CONCLUSION

MRI after neoadjuvant chemotherapy for breast cancer even combined with tumour factors is not an accurate predictor of pCR.

Axillary response rates to neoadjuvant chemotherapy in breast cancer patients with advanced nodal disease

PURPOSE

Utilization of sentinel lymph node biopsy (SLNB) in breast cancer patients with positive nodes after neoadjuvant chemotherapy (NAC) has increased. We examine axillary response rates after NAC in patients with clinical N2-3 disease to determine whether SLNB should be considered.

METHODS

Breast cancer patients with clinical N2-3 (AJCC 7th Edition) disease who received NAC followed by surgery were selected from our institutional tumor registry (2009-2018). Axillary response rates were assessed.

RESULTS

Ninety-nine patients with 100 breast cancers were identified: 59 N2 (59.0%) and 41 (41.0%) N3 disease; 82 (82.0%) treated with axillary lymph node dissection (ALND) and 18 (18.0%) SLNB. The majority (99.0%) received multiagent NAC. In patients undergoing ALND, cCR was observed in 20/82 patients (24.4%), pathologic complete response (pCR) in 15 patients (18.3%), and axillary pCR in 17 patients (20.7%). In patients with a cCR, pCR was identified in 60.0% and was most common in HER2+ patients (34.6%).

CONCLUSION

In this analysis of patients with clinical N2-3 disease receiving NAC, 79.3% of patients had residual nodal disease at surgery. However, 60.0% of patients with a cCR also had a pCR. This provides the foundation to consider evaluating SLNB and less extensive axillary surgery in this select group.

Prediction of pathological complete response after neoadjuvant chemotherapy in breast cancer by combining magnetic resonance imaging and core needle biopsy

BACKGROUND

Pathological complete response (pCR) is often achieved by neoadjuvant chemotherapy (NAC), particularly in hormone receptor-negative breast cancer. Contrast-enhanced magnetic resonance imaging (cMRI) is the most reliable imaging modality to evaluate the pathological effect of NAC. Ultrasonography is indispensable to collect representative specimens from the target lesion by core needle biopsy (CNB). This study aimed to evaluate the accuracy of predicting pCR by adding CNB after NAC, in cases with complete clinical response (cCR) diagnosed by cMRI.

METHODS

In this prospective multicentre study, we evaluated patients diagnosed with cCR by cMRI after NAC. Ultrasound-guided CNB (uCNB) using a 14G needle was performed without clip markers under general anaesthesia as planned surgery. Specimens collected by uCNB were compared to those resected surgically and were categorized as (i) no carcinoma (ypT0), (ii) no invasive carcinoma and only residual carcinoma in situ (ypTis) and (iii) residual invasive carcinoma. The concordance of pathological results between the uCNB and surgical specimens was evaluated.

RESULTS

Of the 83 patients evaluated, 41 (49.4%) and 17 (20.5%) of them had ypT0 and ypTis, respectively. The false negative rates (FNR), sensitivity and specificity for predicting ypT0 by uCNB were 50.0%, 50.0%, 100%, respectively, and those for predicting ypT0+ypTis were 28.0%, 72.0% and 98.3%, respectively. The concordance rates were 74.7% (62/83) for ypT0 and 90.4% (75/83) for ypT0+ypTis.

CONCLUSION

In cCR cases diagnosed by cMRI, uCNB was not accurate enough to predict pCR. Additional modalities like clip placements and/or thicker core needles may be required for better prediction.

Radiogenomics of magnetic resonance imaging and a new multi-gene classifier for predicting recurrence prognosis in estrogen receptor-positive breast cancer: A preliminary study

To examine the correlation of qualitative and quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) results with 95-gene classifier or Curebest 95-gene classifier Breast (95GC) results for recurrence prediction in estrogen receptor-positive breast cancer (ERPBC).This retrospective study included 78 ERPBC patients (age range, 24-74 years) classified into high- (n = 33) and low- (n = 45) risk groups for recurrence based on 95GC and who underwent DCE-MRI between July 2006 and November 2012. For qualitative evaluation, mass shape, margin, and internal enhancement based on BI-RADS MRI lexicon and multiplicity were determined by consensus interpretation by 2 breast radiologists. For quantitative evaluation, mass size, volume ratios of the DCE-MRI kinetics, and both the kurtosis and the skewness of the intensity histogram for the whole mass in the initial and delayed phases were determined. Differences between the 2 risk-groups were analyzed using univariate logistic regression analyses and multiple logistic regression analyses. Receiver-operating characteristic curve cut-off values were used to define the groups.As for the qualitative findings, the difference between the 2 groups was not significant. For the quantitative data, the volume ratio of "medium" in the initial phase differed significantly between the 2 groups (P = .049). The volume ratio of "medium" (P = .006) and of "slow-persistent" (P = .005), and the delayed phase kurtosis (P = .012) in the univariate logistic regression analyses, and in the multiple logistic regression, volume ratio of "medium" >38.9% and delayed phase kurtosis >3.31 were identified as significant high-risk indicators (odds ratio, 5.83 and 3.55; 95% confidence interval, 1.58 to 21.42 and 1.24 to 10.15; P = .008 and P = .018, respectively).A high volume ratio of "medium" in the initial phase and/or high kurtosis in the delayed phase for quantitative evaluation could predict high ERPBC recurrence risk based on 95GC.

The diagnostic accuracy of magnetic resonance imaging in predicting pathologic complete response after neoadjuvant chemotherapy in patients with different molecular subtypes of breast cancer

Background

Patients treated with neoadjuvant chemotherapy (NAC) who achieve a pathologic complete response (pCR) can be identified preoperatively and can potentially be spared the morbidity of surgery. The objective of this retrospective study was to estimate the diagnostic accuracy of preoperative magnetic resonance imaging (MRI) in predicting pCR in patients with different molecular subtypes of breast cancer and to provide a basis for the selection of surgical methods.

Methods

We retrospectively reviewed breast MRI data from August 2015 to December 2018 of patients who underwent four or more cycles of NAC. Factors associated with radiological complete response (rCR) and pCR were analyzed in univariable and multivariable settings. The accuracy of MRI and the correlation between rCR and pCR were also analyzed in each tumor subtype.

Results

A total of 177 women with a primary tumor fulfilled the study criteria; 18 of these patients (10.2%) achieved rCR, and 21 (11.9%) achieved a pCR. MRI diagnosis of rCR was significantly correlated with pCR with a Spearman's correlation coefficient of 0.686 in the entire population. The sensitivity, specificity, accuracy, pCR predictive value (PPV), and non-pCR predictive value (NPV) were estimated to be 66.67%, 97.44%, 93.79%, 77.78%, and 95.60%, respectively. Statistically significant correlations between rCR and pCR were found in Luminal B high Ki67% (P<0.001), HER2-positive (P=0.0035), and triple-negative (P<0.001) subtypes, but not in Luminal A and Luminal B low Ki67% subtypes. On univariate analysis, the tumor characteristics significantly associated with both rCR and pCR were small tumor, lymph node metastasis (LNM) negativity, early clinical stage, high grade, high Ki67% index, and different molecular subtype. On multivariate logistic regression analysis, grade 3 tumors (P=0.013), Ki67% ≥40% (P<0.000), and stage I tumor (P=0.006) were independently associated with rCR. However, grade 3 tumors (P=0.001), triple-negative breast cancer (TNBC), and clinical stages I and II tumors (P=0.003; P=0.030) were independently associated with the likelihood of attaining a pCR.

Conclusions

The overall accuracy of MRI in predicting pCR in invasive breast cancer patients who received NAC was 93.8%. The performance of MRI differed among molecular subtypes, and the highest PPV was found in TNBC (100%) and Luminal B high Ki67% (75%) subtypes.