MR and US imaging for breast cancer patients who underwent conservation surgery after neoadjuvant chemotherapy: comparison of triple negative breast cancer and other intrinsic subtypes

The modified shrinkage classification modes could help to guide breast conserving surgery after neoadjuvant therapy in breast cancer

Purpose

The traditional shrinkage classification modes might not suitable for guiding breast conserving surgery (BCS) after neoadjuvant therapy (NAT). Aim was to explore the modified shrinkage classification modes to guide BCS after NAT.

Methods

From April 2010 to 2018, 104 patients were included. All patients underwent MRI examinations before and after NAT. Residual tumors were removed and divided into more than 30 tissue blocks at 5-mm intervals. After performing routine procedures for paraffin-embedded histology, we made semiserial sections (6-μm thick). The MRI and pathology 3D models were reconstructed with 3D-DOCTOR software. Combined with traditional shrinkage modes and efficacy of NAT, we derived modified shrinkage classification modes which oriented by BCS purpose: modified concentric shrinkage modes (MCSM) and modified non concentric shrinkage modes (MNCSM). The MCSM means the longest diameter of residual tumor was less than 50% and ≤2cm in comparison with the primary tumor before NAT. Other shrinkage modes were classified as MNCSM.

Results

According to traditional shrinkage modes, 50 (48.1%) cases were suitable for BCS;while 70 (67.3%) cases were suitable for BCS according to the modified shrinkage modes (p=0.007). The consistency of MRI 3D reconstruction in assessing modified shrinkage classification modes was 93.2%, while it was 61.5% when assessing traditional shrinkage modes. Multivariate analysis showed that primary tumor stage, mammographic malignant calcification, molecular subtypes and nodal down-staging after NAT were independent predictors of modified shrinkage modes (all p<0.05). A nomogram was created based on these four predictors. With a median follow-up time of 77 months, the recurrence/metastasis rate in the MCSM and MNCSM group was 7.1% and 29.4%, respectively.

Conclusion

Modified shrinkage classification modes could help to guide the individualized selection of BCS candidates and scope of resection after NAT. MRI 3D reconstruction after NAT could accurately predict modified shrinkage modes and extent of residual tumor.

Diagnostic Accuracy of MRI in Evaluating Response After Neoadjuvant Systemic Therapy in Operable Breast Cancer

Background

Neoadjuvant chemotherapy (NAC) is an important step in the treatment of various types of breast cancer by downsizing the tumor to make it operable. Determining disease extent after NAC is essential for accurate surgical planning. MRI has been the gold standard for detecting tumors that are usually difficult to detect on ultrasound or mammography. However, the use of MRI after NAC is controversial. Therefore, we aimed to evaluate the diagnostic accuracy of post-NAC MRI in the detection of residual disease preoperatively and to investigate the factors associated with pathological complete response (pCR).

Methodology

This retrospective review study was approved by the institutional review board with waiving of the informed consent. A total of 90 charts between January 2016 and January 2019 were reviewed. Baseline lesion size was measured as the maximal diameter in a single dimension by pretreatment MRI. To assess the diagnostic accuracy of MRI in detecting residual disease, we used two different definitions of pCR in the breast. The first is the resolution of both invasive disease and ductal carcinoma in situ. The second is the resolution of the invasive disease only. As a secondary objective of the study, we assessed the association between different patients’ characteristics and both MRI and pathologic response using univariate and multivariate analysis.

Results

A total of 52 women (mean age: 47.4 years; range: 28-74) with 56 breast masses were eligible for the study. Complete MRI response was noted in 22 (39%) masses. pCR was achieved in 14 (25%) and 25 (44.6%) masses using the first and second pCR definitions, respectively. The negative predictive value (NPV) and overall accuracy of MRI for detecting residual disease were 50% and 75%, respectively, using the first pCR definition. With the second pCR definition, NPV and accuracy were 77.3% and 76.8%, respectively. Positive axillary lymph nodes were the only significant factor associated with incomplete MRI and pathological responses.

Conclusions

MRI NPV for residual disease was higher with the second pCR definition; however, overall accuracy was not different. MRI accuracy in detecting residual disease after NAC is not adequate to replace pathological assessment.

Magnetic resonance imaging and ultrasound for prediction of residual tumor size in early breast cancer within the ADAPT subtrials

Background

Prediction of histological tumor size by post-neoadjuvant therapy (NAT) ultrasound and magnetic resonance imaging (MRI) was evaluated in different breast cancer subtypes.

Methods

Imaging was performed after 12-week NAT in patients enrolled into three neoadjuvant WSG ADAPT subtrials. Imaging performance was analyzed for prediction of residual tumor measuring ≤10 mm and summarized using positive (PPV) and negative (NPV) predictive values.

Results

A total of 248 and 588 patients had MRI and ultrasound, respectively. Tumor size was over- or underestimated by < 10 mm in 4.4% and 21.8% of patients by MRI and in 10.2% and 15.8% by ultrasound. Overall, NPV (proportion of correctly predicted tumor size ≤10 mm) of MRI and ultrasound was 0.92 and 0.83; PPV (correctly predicted tumor size > 10 mm) was 0.52 and 0.61. MRI demonstrated a higher NPV and lower PPV than ultrasound in hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-positive and in HR−/HER2+ tumors. Both methods had a comparable NPV and PPV in HR−/HER2− tumors.

Conclusions

In HR+/HER2+ and HR−/HER2+ breast cancer, MRI is less likely than ultrasound to underestimate while ultrasound is associated with a lower risk to overestimate tumor size. These findings may help to select the most optimal imaging approach for planning surgery after NAT.

Trial registration

Clinicaltrials.gov, NCT01815242 (registered on March 21, 2013), NCT01817452 (registered on March 25, 2013), and NCT01779206 (registered on January 30, 2013).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01413-y.

Direct comparison of magnetic resonance imaging and pathological shrinkage patterns of triple-negative breast cancer after neoadjuvant chemotherapy

Background

We aimed to investigate the usefulness of magnetic resonance imaging (MRI) and histopathological shrinkage patterns to formulate a predictive equation for estimating residual tumor size after neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients.

Methods

We enrolled 34 TNBC patients who underwent MRI before and after NAC. The MRI and histopathological shrinkage patterns were analyzed and classified into five categories—types I and II (concentric shrinkage without or with surrounding lesions, respectively), type III (shrinkage with residual multinodular lesions), type IV (diffuse contrast enhancement in the entire quadrant), and non-visualization. The residual tumor sizes following MRI and histopathological examination were also compared.

Results

The most common MRI and histopathological shrinkage pattern was type I (41.2% and 38.2%, respectively), followed by non-visualization (26.5% and 32.4%, respectively); the concordance rate between MRI and histopathological shrinkage patterns was 41.2%. There was a strong correlation between MRI tumor size and pathological tumor size (r = 0.89). Based on these findings, a predictive equation for pathological tumor size was formulated as follows: pathological tumor size (mm) = 1.1502 × (MRI tumor size [mm]) + 8.4277.

Conclusions

Our equation may aid accurate preoperative assessment. Further studies are needed to determine its predictive value and applicability.

Prediction of Pathologic Complete Response by Ultrasonography and Magnetic Resonance Imaging After Neoadjuvant Chemotherapy in Patients with Breast Cancer

Purpose

To compare the diagnostic performance for pathologic complete response (pCR) in breast cancer after neoadjuvant chemotherapy (NAC) between ultrasound (US) and magnetic resonance imaging (MRI).

Patients and Methods

A total of 1,219 breast cancer patients with 1,232 tumors who accepted US and/or MRI examination after NAC and before breast surgery were included. The diagnostic performance of US, MRI, and US plus MRI in predicting pCR was compared.

Results

The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of US for pCR were 36.2%, 90.2%, 71.0%, 67.3%, and 71.9%, respectively, while for MRI they were 44.4%, 92.9%, 75.6%, 77.7%, and 75.0%, respectively. The combination of US and MRI had increased specificity (98.0%) and PPV (86.8%), decreased sensitivity (22.5%) and NPV (68.8%), but similar accuracy (70.5%) in comparison with US or MRI alone. The prediction of pCR by imaging differed in different histological, molecular subtypes and primary tumor size.

Conclusion

Neither US nor MRI could predict a pCR with sufficient accuracy. The combination of US and MRI could not predict a pCR reliably either. The explanation of imaging for pCR should take into account histological, molecular subtypes, and primary tumor size.

MRI, Clinical Examination, and Mammography for Preoperative Assessment of Residual Disease and Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer: ACRIN 6657 Trial

OBJECTIVE

The objective of our study was to determine the accuracy of preoperative measurements for detecting pathologic complete response (CR) and assessing residual disease after neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer.

SUBJECTS AND METHODS

The American College of Radiology Imaging Network 6657 Trial prospectively enrolled women with ≥ 3 cm invasive breast cancer receiving NACT. Preoperative measurements of residual disease included longest diameter by mammography, MRI, and clinical examination and functional volume on MRI. The accuracy of preoperative measurements for detecting pathologic CR and the association with final pathology size were assessed for all lesions, separately for single masses and nonmass enhancements (NMEs), multiple masses, and lesions without ductal carcinoma in situ (DCIS).

RESULTS

In the 138 women with all four preoperative measures, longest diameter by MRI showed the highest accuracy for detecting pathologic CR for all lesions and NME (AUC = 0.76 and 0.84, respectively). There was little difference across preoperative measurements in the accuracy of detecting pathologic CR for single masses (AUC = 0.69-0.72). Longest diameter by MRI and longest diameter by clinical examination showed moderate ability for detecting pathologic CR for multiple masses (AUC = 0.78 and 0.74), and longest diameter by MRI and longest diameter by mammography showed moderate ability for detecting pathologic CR for tumors without DCIS (AUC = 0.74 and 0.71). In subjects with residual disease, longest diameter by MRI exhibited the strongest association with pathology size for all lesions and single masses (r = 0.33 and 0.47). Associations between preoperative measures and pathology results were not significantly influenced by tumor subtype or mammographic density.

CONCLUSION

Our results indicate that measurement of longest diameter by MRI is more accurate than by mammography and clinical examination for preoperative assessment of tumor residua after NACT and may improve surgical planning.

Comparing Accuracy of Mammography and Magnetic Resonance Imaging for Residual Calcified Lesions in Breast Cancer Patients Undergoing Neoadjuvant Systemic Therapy

BACKGROUND

Neoadjuvant systemic therapy (NST) is performed to increase the rate of breast-conserving surgery in advanced breast cancer patients. Although magnetic resonance imaging (MRI) is accurate in predicting residual cancer, if calcification remains, the issue of whether to perform the surgery on the basis of the residual tumor prediction range in mammography (MMG) or MRI has not yet been elucidated. This study aimed to estimate the accuracy of predicting residual tumor after NST for residual microcalcification on mammographic and enhancing lesion on MRI.

PATIENTS AND METHODS

This was a single-center, retrospective study. We included breast cancer patients who underwent NST, had microcalcifications in the post-NST MMG, and underwent surgery from January 2, 2013 to December 30, 2014 at Asan Medical Center. Patients with post-NST MMG as well as MRI were included. Final pathologic tumor size with histopathology and biomarker status were obtained postoperatively.

RESULTS

In total, 151 patients were included in this study. Overall, MRI correlated better than MMG in predicting the tumor size (intraclass correlation coefficient [ICC], 0.769 vs. 0.651). For hormone receptor (HR)-positive (HR⁺)/HER2^- subtype, MMG had higher correlation than MRI (ICC = 0.747 vs. 0.575). In HR^- subtype, MRI had a strong correlation with pathology (HR^-/HER2⁺ or triple negative (TN), ICC = 0.939 vs. 0.750), whereas MMG tended to overestimate the tumor size (HR^-/HER2⁺ or TN, ICC = 0.543 vs. 0.479).

CONCLUSION

Post-NST residual microcalcifications on MMG have a lower correlation with residual tumor size than MRI. Other than HR⁺/HER2^- subtype, the extent of calcifications on preoperative evaluation might not be accurate in evaluating the residual extent of the tumor after NST.

Discrepancies Between Pathological Tumor Responses and Estimations of Complete Response by Magnetic Resonance Imaging After Neoadjuvant Chemotherapy Differ by Breast Cancer Subtype

INTRODUCTION

The influence of breast cancer (BC) subtype in discrepancies between pathologic complete response (pCR) and complete response by magnetic resonance imaging (MRI-CR) after neoadjuvant chemotherapy (NAC) have not been discussed well. We evaluated the association between BC subtype and pCR or only residual in situ lesion without invasive cancer (pCR/in situ⁺) in patients with MRI-CR (positive predictive value [PPV]).

MATERIAL AND METHODS

From the data of 716 patients with primary BC who were diagnosed with invasive cancer and treated with NAC and then surgery from January 2009 to May 2014 at St. Luke's International Hospital, 180 patients were determined to have MRI-CR by retrospective chart review. BC subtypes at baseline were classified into 6 subtypes, as strong estrogen receptor (ER⁺⁺), moderately positive ER (ER⁺), negative ER (ER^-), and HER2 status expression.

RESULTS

Three subtypes had PPV (pCR) ≥ 50%: ER^-/HER2⁺ (56.3%, 27/48), ER^-/HER2^- (57.6%, 34/59), and ER⁺/HER2⁺ (56.2%, 9/16). However, PPV (pCR) for the ER⁺⁺/HER2^- and ER⁺⁺/HER2⁺ subtypes was < 30%; notably, only 12.0% (3/25) for the ER⁺⁺/HER2^- subtype, which was significantly low (P < .001) compared with ER⁺⁺/HER2^- and other subtypes. PPV (pCR/in situ⁺) was significantly low at 20.0% in the ER⁺⁺/HER2^- subtype (P < .001 compared with other subtypes). PPV (pCR/in situ⁺) in other subtypes was collectively greater than 60%, and was 91.7% in the ER^-/HER2⁺ subtype.

CONCLUSION

We should interpret carefully MRI-CR of NAC to evaluate residual disease for ER⁺⁺/HER2^- BC.

Performance of Mid-Treatment Breast Ultrasound and Axillary Ultrasound in Predicting Response to Neoadjuvant Chemotherapy by Breast Cancer Subtype

BACKGROUND

The primary objective was to determine whether mid-treatment ultrasound measurements of index breast tumors and index axillary nodes of different cancer subtypes associate with residual cancer burden (RCB).

METHODS

Patients with invasive breast cancer who underwent neoadjuvant chemotherapy and had pre-treatment and mid-treatment breast and axillary ultrasound were included in this single-institution, retrospective cohort study. Linear regression analysis assessed associations between RCB with (a) change in index breast tumor size, (b) change in index node size, and (c) absolute number of abnormal nodes at mid-treatment. Multivariate linear regression was used to calculate best-fit models for RCB.

RESULTS

One hundred fifty-nine patients (68 triple negative breast cancer [TNBC], 45 hormone receptor [HR]+/human epidermal growth factor receptor 2 [HER2]-, and 46 HR-/HER2+) were included. Median age at diagnosis was 50 years, range 30-76. Median tumor size was 3.4 cm, range 0.9-10.4. Pathological complete response/RCB-I rates were 36.8% (25/68) for TNBC patients, 24.4% (11/45) for HR+/HER2- patients, and 71.7% (33/46) for HR-/HER2+ patients. Linear regression analyses demonstrated associations between percent change in tumor ultrasound measurements at mid-treatment with RCB index score in TNBC and HR+/HER2- (p < .05) but not in HR-/HER2+ (p > .05) tumors and an association between axillary ultrasound assessment of number of abnormal nodes at mid-treatment with RCB index score across all subtypes (p < .05).

CONCLUSION

Performance characteristics of breast ultrasound associated with RCB vary by cancer subtype, whereas the performance characteristics of axillary ultrasound associated with RCB are consistent across cancer subtype. Breast and axillary ultrasound may be valuable in monitoring response to neoadjuvant therapy. The Oncologist 2017;22:394-401 IMPLICATIONS FOR PRACTICE: The differential performance characteristics of breast ultrasound by molecular subtype and the consistent performance characteristics of axillary ultrasound across molecular subtypes can have clinical utility in monitoring response to neoadjuvant therapy.

Combination of shear wave elastography and Ki-67 index as a novel predictive modality for the pathological response to neoadjuvant chemotherapy in patients with invasive breast cancer

PURPOSE

This study evaluated shear wave elastography (SWE) and SWE combined with the Ki-67 index as novel predictive modalities for the pathological response of invasive breast cancer to neoadjuvant chemotherapy (NAC).

METHODS

The prospective study recruited 66 eligible patients from July 2014 to November 2015. Tumour stiffness, which corresponds with tumour progression and invasiveness, was assessed by quantitative SWE 1 d before biopsy (time point t0, elasticity E0), 1 d before next NAC cycle (t1-t5, E1-E5), and 1 d before surgery (t6, E6). The relative changes in SWE parameters after the first and second NAC cycles were considered as the variables [ΔE (t1), ΔE (t2)]. The pathological response was classified according to the residual cancer burden (RCB) protocol. Correlations between RCB scores and variables were evaluated. The predictive diagnostic performances of SWE parameters, Ki-67 index, and the predictive RCB (predRCB) score determined by a linear regression model were compared.

RESULTS

Some immunohistochemical and molecular factors and SWE parameters were significantly different among the three RCB groups. The ΔEmean (t2) and Ki-67 had significantly better diagnostic performance than other parameters regarding predicting the pathological response (the RCB-I response and RCB-III resistance). However, the correlation between ΔEmean (t2) and Ki-67 index was significantly weaker as a diagnostic predictor (r = 0.29). We generated a new predictive modality, predRCB, which is a multivariable linear regression model that combines ΔEmean (t2) and the Ki-67 index. The predRCB modality showed better diagnostic performance than SWE parameters and Ki-67 index alone.

CONCLUSION

Our findings highlight the potential utility for adding the Ki-67 index to the SWE results, which may improve the predictive power of SWE and facilitate personalising the treatment regimens of patients with breast cancer. These results should be validated in the future by performing a multicentre prospective study with a larger cohort.

Residual Mammographic Microcalcifications and Enhancing Lesions on MRI After Neoadjuvant Systemic Chemotherapy for Locally Advanced Breast Cancer: Correlation with Histopathologic Residual Tumor Size

PURPOSE

To evaluate the accuracy of residual microcalcifications on mammogram (MG) in predicting the extent of the residual tumor after neoadjuvant systemic treatment (NST) in patients with locally advanced breast cancer and to evaluate factors affecting the accuracy of MG microcalcifications using magnetic resonance imaging (MRI) as a reference.

METHODS

The patients who underwent NST and showed suspicious microcalcifications on MG comprised our study population. Clinicopathologic and imaging (MG, MRI) findings were investigated. Agreement between image findings and pathology was assessed and factors affecting the discrepancy were analyzed.

RESULTS

Among 207 patients, 196 had residual invasive ductal carcinoma or ductal carcinoma-in-situ (mean size, 3.78 cm). The overall agreement of residual microcalcifications on MG predicting residual tumor extents was lower than MRI in all tumor subtypes (intraclass correlation coefficient [ICC] = 0.368 and 0.723, p < 0.0001). The agreement of residual MG microcalcifications and pathology was highest in HR(+)/HER2(+) tumors and lowest in the triple-negative tumors (ICC = 0.417 and 0.205, respectively). Multivariate linear regression analysis revealed that a size discrepancy between microcalcifications and histopathology was correlated with molecular subtype (p = 0.005). In HR(+)/HER2(-) and triple-negative subtypes, the mean extents of residual microcalcification were smaller than residual cancer, and overestimation of tumor extent was more frequent in HR(+)/HER2(+) and HR(-)/HER2(+) tumors.

CONCLUSIONS

The extent of microcalcifications on MG after NST showed an overall lower correlation with the extent of the pathologic residual tumor than enhancing lesions on MRI. The accuracy of residual tumor evaluation after NST with MG and MRI is affected by their molecular subtype.

Agreement between MRI and pathologic breast tumor size after neoadjuvant chemotherapy, and comparison with alternative tests: individual patient data meta-analysis

Background

Magnetic resonance imaging (MRI) may guide breast cancer surgery by measuring residual tumor size post-neoadjuvant chemotherapy (NAC). Accurate measurement may avoid overly radical surgery or reduce the need for repeat surgery. This individual patient data (IPD) meta-analysis examines MRI’s agreement with pathology in measuring the longest tumor diameter and compares MRI with alternative tests.

Methods

A systematic review of MEDLINE, EMBASE, PREMEDLINE, Database of Abstracts of Reviews of Effects, Heath Technology Assessment, and Cochrane databases identified eligible studies. Primary study authors supplied IPD in a template format constructed a priori. Mean differences (MDs) between tests and pathology (i.e. systematic bias) were calculated and pooled by the inverse variance method; limits of agreement (LOA) were estimated. Test measurements of 0.0 cm in the presence of pathologic residual tumor, and measurements >0.0 cm despite pathologic complete response (pCR) were described for MRI and alternative tests.

Results

Eight studies contributed IPD (N = 300). The pooled MD for MRI was 0.0 cm (LOA: +/−3.8 cm). Ultrasound underestimated pathologic size (MD: −0.3 cm) relative to MRI (MD: 0.1 cm), with comparable LOA. MDs were similar for MRI (0.1 cm) and mammography (0.0 cm), with wider LOA for mammography. Clinical examination underestimated size (MD: −0.8 cm) relative to MRI (MD: 0.0 cm), with wider LOA. Tumors “missed” by MRI typically measured 2.0 cm or less at pathology; tumors >2.0 cm were more commonly “missed” by clinical examination (9.3 %). MRI measurements >5.0 cm occurred in 5.3 % of patients with pCR, but were more frequent for mammography (46.2 %).

Conclusions

There was no systematic bias in MRI tumor measurement, but LOA are large enough to be clinically important. MRI’s performance was generally superior to ultrasound, mammography, and clinical examination, and it may be considered the most appropriate test in this setting. Test combinations should be explored in future studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1664-4) contains supplementary material, which is available to authorized users.

Evaluation with 3.0-T MR imaging: predicting the pathological response of triple-negative breast cancer treated with anthracycline and taxane neoadjuvant chemotherapy

BACKGROUND

Triple-negative breast cancer (TNBC) which expresses neither hormonal receptors nor HER-2 is associated with poor prognosis and shorter survival. Several studies have suggested that TNBC patients attaining pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) show a longer survival than those without pCR.

PURPOSE

To assess the accuracy of 3.0-T breast magnetic resonance imaging (MRI) in predicting pCR and to evaluate the clinicoradiologic factors affecting the diagnostic accuracy of 3.0-T breast MRI in TNBC patients treated with anthracycline and taxane (ACD).

MATERIAL AND METHODS

This retrospective study was approved by the institutional review board; patient consent was not required. Between 2009 and 2012, 35 TNBC patients with 3.0-T breast MRI prior to (n = 26) or after (n = 35) NAC were included. MRI findings were reviewed according to pCR to chemotherapy. The diagnostic accuracy of 3.0-T breast MRI for predicting pCR and the clinicoradiological factors affecting MRI accuracy and response to NAC were analyzed.

RESULTS

3.0-T MRI following NAC with ACD accurately predicted pCR in 91.4% of TNBC patients. The residual tumor size between pathology and 3.0-T MRI in non-pCR cases showed a higher correlation in the Ki-67-positive TNBC group (r = 0.947) than in the Ki-67 negative group (r = 0.375) with statistical trends (P = 0.069). Pre-treatment MRI in the non-pCR group compared to the pCR group showed a larger tumor size (P = 0.030) and non-mass presentation (P = 0.015).

CONCLUSION

3.0-T MRI in TNBC patients following NAC with ACD showed a high accuracy for predicting pCR to NAC. Ki-67 can affect the diagnostic accuracy of 3.0-T MRI for pCR to NAC with ACD in TNBC patients.

Meta-analysis on the association between pathologic complete response and triple-negative breast cancer after neoadjuvant chemotherapy

Background

Triple-negative breast cancer (TNBC) is a special subtype of breast cancer that is characterized by poor prognosis, strong tumor invasion and a high pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC). The pCR rate is a prognostic factor for TNBC. We aimed to evaluate the relationship between pCR and TNBC after NAC and originally tried to identify factors related to achieving pCR for TNBC using a meta-analysis.

Methods

We systematically searched the literature for pCR and breast cancer after NAC and carefully identified eligibility criteria. The association between pCR and breast cancer subtypes was estimated using Review Manager, while pCR rates for TNBC and non-TNBC were determined using Meta-Analyst.

Results

This analysis included a total of 9,460 cases from 27 studies. The summary odds ratio estimating the relationship between pCR and breast cancer subtypes (TNBC vs non-TNBC) was 3.02 (95% confidence interval (CI), 2.66 to 3.42). The TNBC pCR rate was 28.9% (95% CI, 27.0 to 30.8%) and the non-TNBC was 12.5% (95% CI, 11.7 to 13.4%). From subgroup analyses, we identified the factors associated with the highest pCR rates for TNBC.

Conclusions

TNBC has a higher pCR rate than non-TNBC. In the NAC setting, these factors of platinum-containing, more than six cycles, four kinds of drugs, 16 weeks’ treatment duration and sequential chemotherapy may contribute to increasing the pCR rate.

Impact of factors affecting the residual tumor size diagnosed by MRI following neoadjuvant chemotherapy in comparison to pathology

BACKGROUND AND OBJECTIVES

To investigate accuracy of magnetic resonance imaging (MRI) for measuring residual tumor size in breast cancer patients receiving neoadjuvant chemotherapy (NAC).

METHODS

Ninety-eight patients were studied. Several MRI were performed during NAC for response monitoring, and the residual tumor size was measured on last MRI after completing NAC. Covariates, including age, tumor characteristics, biomarkers, NAC regimens, MRI scanners, and time from last MRI to operation, were analyzed. Univariate and Multivariate linear regression models were used to determine the predictive value of these covariates for MRI-pathology size discrepancy as the outcome measure.

RESULTS

The mean (±SD) of the absolute difference between MRI and pathological residual tumor size was 1.0 ± 2.0 cm (range, 0-14 cm). Univariate regression analysis showed tumor type, morphology, HR status, HER2 status, and MRI scanner (1.5 T or 3.0 T) were significantly associated with MRI-pathology size discrepancy (all P < 0.05). Multivariate regression analyses demonstrated that only tumor type, tumor morphology, and biomarker status considering both HR and HER-2 were independent predictors (P = 0.0014, 0.0032, and 0.0286, respectively).

CONCLUSION

The accuracy of MRI in evaluating residual tumor size depends on tumor type, morphology, and biomarker status. The information may be considered in surgical planning for NAC patients.

Research and progress in magnetic resonance imaging of triple-negative breast cancer

Triple-negative breast cancer (TNBC), which characterized by distinct biological and clinical pathological features, has a worse prognosis because the lack of effective therapeutic targets. Breast MR is the most accurate imaging modality for diagnosis of breast cancer currently. MR imaging recognition could assist in diagnosis, pretreatment planning and prognosis evaluation of TNBC. MR findings of a larger solitary lesion, mass with smooth mass margin, high signal intensity on T2-weighted images and rim enhancement are typical MRI features associated with TNBC. Further work is necessary about the clinical application of dynamic contrast-enhanced MR imaging (DCE-MRI), DWI and MRS.

Meta-analysis of agreement between MRI and pathologic breast tumour size after neoadjuvant chemotherapy

BACKGROUND

Magnetic resonance imaging (MRI) has been proposed to guide breast cancer surgery by measuring residual tumour after neoadjuvant chemotherapy. This study-level meta-analysis examines MRI's agreement with pathology, compares MRI with alternative tests and investigates consistency between different measures of agreement.

METHODS

A systematic literature search was undertaken. Mean differences (MDs) in tumour size between MRI or comparator tests and pathology were pooled by assuming a fixed effect. Limits of agreement (LOA) were estimated from a pooled variance by assuming equal variance of the differences across studies.

RESULTS

Data were extracted from 19 studies (958 patients). The pooled MD between MRI and pathology from six studies was 0.1 cm (95% LOA: -4.2 to 4.4 cm). Similar overestimation for MRI (MD: 0.1 cm) and ultrasound (US) (MD: 0.1 cm) was observed, with comparable LOA (two studies). Overestimation was lower for MRI (MD: 0.1 cm) than mammography (MD: 0.4 cm; two studies). Overestimation by MRI (MD: 0.1 cm) was smaller than underestimation by clinical examination (MD: -0.3 cm). The LOA for mammography and clinical examination were wider than that for MRI. Percentage agreement between MRI and pathology was greater than that of comparator tests (six studies). The range of Pearson's/Spearman's correlations was wide (0.21-0.92; 16 studies). Inconsistencies between MDs, percentage agreement and correlations were common.

CONCLUSION

Magnetic resonance imaging appears to slightly overestimate pathologic size, but measurement errors may be large enough to be clinically significant. Comparable performance by US was observed, but agreement with pathology was poorer for mammography and clinical examination. Percentage agreement can provide supplementary information to MDs and LOA, but Pearson's/Spearman's correlation does not provide evidence of agreement and should be avoided. Further comparisons of MRI and other tests using the recommended methods are warranted.

Clinical application of magnetic resonance imaging in management of breast cancer patients receiving neoadjuvant chemotherapy

Neoadjuvant chemotherapy (NAC), also termed primary, induction, or preoperative chemotherapy, is traditionally used to downstage inoperable breast cancer. In recent years it has been increasingly used for patients who have operable cancers in order to facilitate breast-conserving surgery, achieve better cosmetic outcome, and improve prognosis by reaching pathologic complete response (pCR). Many studies have demonstrated that magnetic resonance imaging (MRI) can assess residual tumor size after NAC, and that provides critical information for planning of the optimal surgery. NAC also allows for timely adjustment of administered drugs based on response, so ineffective regimens could be terminated early to spare patients from unnecessary toxicity while allowing other effective regimens to work sooner. This review article summarizes the clinical application of MRI during NAC. The use of different MR imaging methods, including dynamic contrast-enhanced MRI, proton MR spectroscopy, and diffusion-weighted MRI, to monitor and evaluate the NAC response, as well as how changes of parameters measured at an early time after initiation of a drug regimen can predict final treatment outcome, are reviewed. MRI has been proven a valuable tool and will continue to provide important information facilitating individualized image-guided treatment and personalized management for breast cancer patients undergoing NAC.

Breast cancer molecular phenotype and the use of HER2-targeted agents influence the accuracy of breast MRI after neoadjuvant chemotherapy

OBJECTIVE

To investigate whether the accuracy of magnetic resonance imaging (MRI) after neoadjuvant systemic therapy (NST) is affected by molecular features of primary breast cancer and the use of human epidermal growth factor receptor 2 (HER2)-targeted agents.

BACKGROUND

Improved understanding of factors affecting the accuracy of breast MRI after NST can lead to more tailored use of MRI in deciding surgical extent after NST.

METHODS

We analyzed the imaging and clinicopathological data of 463 patients who underwent NST. We aimed to investigate whether the molecular subtypes, and the use of targeted therapies, were associated with changes in the accuracy of MRI predicting residual tumor extent.

RESULTS

The accuracy of MRI predicting the residual tumor extent was most accurate in triple-negative breast cancer and was least accurate in Luminal A subtype (Pearson correlation coefficient of 0.754 and 0.531, respectively). Multivariate analysis suggested estrogen receptor (ER) status as an independent factor influencing the MRI accuracy. In HER2-amplified tumors, the use of HER2-targeted agents was associated with a less accurate MRI prediction.

CONCLUSIONS

The accuracy of MRI in predicting residual tumor extent was lowest in ER-positive tumors treated with NST. In HER2-positive tumors, the use of HER2-targeted agents resulted in a less accurate MRI after NST. These factors should be considered for deciding the extent of breast conservation after neoadjuvant chemotherapy.

Magnetic resonance imaging as a predictor of pathologic response in patients treated with neoadjuvant systemic treatment for operable breast cancer. Translational Breast Cancer Research Consortium trial 017

BACKGROUND

Increased pathologic complete response (pCR) rates observed with neoadjuvant chemotherapy (NCT) for some subsets of patients with invasive breast cancer have prompted interest in whether patients who achieved a pCR can be identified preoperatively and potentially spared the morbidity of surgery. The objective of this multicenter, retrospective study was to estimate the accuracy of preoperative magnetic resonance imaging (MRI) in predicting a pCR in the breast.

METHODS

MRI studies at baseline and after the completion of NCT plus data regarding pathologic response were collected retrospectively from 746 women who received treatment at 8 institutions between 2002 and 2011. Tumors were characterized by immunohistochemical phenotype into 4 categories based on receptor expression: hormone (estrogen and progesterone) receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative (n = 327), HR-positive/HER2-positive, (n = 148), HR-negative/HER2-positive, (n = 101), and triple-negative (HR-negative/HER2 negative; n = 155). In all, 194 of 249 patients (78%) with HER2-positive tumors received trastuzumab. Univariate and multivariate analyses of factors associated with radiographic complete response (rCR) and pCR were performed.

RESULT

For the total group, the rCR and pCR rates were 182 of 746 patients (24%) and 179 of 746 patients (24%), respectively, and the highest pCR rate was observed for the triple-negative subtype (57 of 155 patients; 37%) and the HER2-positive subtype (38 of 101 patients; 38%). The overall accuracy of MRI for predicting pCR was 74%. The variables sensitivity, negative predictive value, positive predictive value, and accuracy differed significantly among tumor subtypes, and the greatest negative predictive value was observed in the triple-negative (60%) and HER2-positive (62%) subtypes.

CONCLUSIONS

The overall accuracy of MRI for predicting pCR in invasive breast cancer patients who were receiving NCT was 74%. The performance of MRI differed between subtypes, possibly influenced by differences in pCR rates between groups. Future studies will determine whether MRI in combination with directed core biopsy improves the predictive value of MRI for pathologic response.

The role of magnetic resonance imaging in assessing residual disease and pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy: a systematic review

OBJECTIVES

This systematic review aimed to assess the role of magnetic resonance imaging (MRI) in evaluating residual disease extent and the ability to detect pathologic complete response (pCR) after neoadjuvant chemotherapy for invasive breast cancer.

METHODS

PubMed, the Cochrane Library, MEDLINE, and Embase databases were searched for relevant studies published until 1 July 2012. After primary selection, two reviewers independently assessed the content of each eligible study using a standardised extraction form and pre-defined inclusion and exclusion criteria.

RESULTS

A total of 35 eligible studies were selected. Correlation coefficients of residual tumour size assessed by MRI and pathology were good, with a median value of 0.698. Reported sensitivity, specificity, positive predictive value and negative predictive value for predicting pCR with MRI ranged from 25 to 100 %, 50-97 %, 47-73 % and 71-100 %, respectively. Both overestimation and underestimation were observed. MRI proved more accurate in determining residual disease than physical examination, mammography and ultrasound. Diagnostic accuracy of MRI after neoadjuvant chemotherapy could be influenced by treatment regimen and breast cancer subtype.

CONCLUSIONS

Breast MRI accuracy for assessing residual disease after neoadjuvant chemotherapy is good and surpasses other diagnostic means. However, both overestimation and underestimation of residual disease extent could be observed.

MAIN MESSAGES

• Breast MRI accuracy for assessing residual disease is good and surpasses other diagnostic means. • Correlation coefficients of residual tumour size assessed by MRI and pathology were considered good. • However, both overestimation and underestimation of residual disease were observed. • Diagnostic accuracy of MRI seems to be affected by treatment regimen and breast cancer subtype.

Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL

Purpose

This study was designed to determine (1) rates of clinically meaningful tumor reduction in breast tumor size following neoadjuvant chemotherapy (NAC), (2) which receptor subtypes and MRI phenotypes are associated with clinically meaningful tumor reduction, and (3) whether MRI phenotype impacts concordance between pathologic and MRI size.

Methods

We analyzed data from the I-SPY TRIAL, a multicenter, prospective NAC trial. Reduction in tumor size from >4 to ≤4 cm was considered clinically meaningful, as crossing this threshold was considered a reasonable cutoff for potential breast conservation therapy (BCT). MRI phenotypes were scored between one (well-defined) and five (diffuse) on pre-NAC MRIs.

Results

Of 174 patients with tumors >4 cm, 141 (81 %) had clinically meaningful tumor reduction. Response to therapy varied by MRI phenotype (p = 0.003), with well-defined phenotypes more likely than diffuse phenotypes to have clinically meaningful tumor shrinkage (91 vs. 72 %, p = 0.037). Her2+ and triple-negative (Tneg) tumors had the highest rate of clinically meaningful tumor reduction (p = 0.005). The concordance between tumor diameter on MRI and surgical pathology was highest for Her2+ and Tneg tumors, especially among tumors with solid imaging phenotypes (p = 0.004).

Discussion

NAC allows most patients with large breast tumors to have clinically meaningful tumor reduction, meaning response that would impact ability to undergo BCT. However, response varies by imaging and tumor subtypes. Concordance between tumor size on MRI and surgical pathology was higher in well-defined tumors, especially those with a Tneg subtype, and lower in HR+ diffuse tumors.

Electronic supplementary material

The online version of this article (doi:10.1245/s10434-013-3038-y) contains supplementary material, which is available to authorized users.

Meta-analysis of the association of breast cancer subtype and pathologic complete response to neoadjuvant chemotherapy

BACKGROUND

Pathologic complete response (pCR) is a surrogate end-point for prognosis in neoadjuvant chemotherapy (NAC) for breast cancer. We aimed to report summary estimates of the proportion of subjects achieving pCR (pCR%) by tumour subtype, and to determine whether subtype was independently associated with pCR, in a study-level meta-analysis.

METHODS

We systematically identified NAC studies reporting pCR data according to tumour subtype, using predefined eligibility criteria. Descriptive, qualitative and quantitative data were extracted. Random effects logistic meta-regression examined whether pCR% was associated with subtype, defined using three categories for model 1 [hormone receptor positive (HR+/HER2-), HER2 positive (HER2+), triple negative (ER-/PR-/HER2-)] and 4 categories for model 2 [HER2+ further classified as HER2+/HR+ and HER2+/HR-]. Subtype-specific odds ratios (OR) were calculated and were adjusted for covariates associated with pCR in our data.

RESULTS

In model 1, based on 11,695 subjects from 30 eligible studies, overall pooled pCR% was 18.9% (16.6-21.5%), and in model 2 (20 studies, 8095 subjects) pooled pCR% was 18.5% (16.2-21.1%); tumour subtype was associated with pCR% (P<0.0001) in both models. Subtype-specific pCR% (model 2) was: 8.3% (6.7-10.2%) in HR+/HER2- [OR 1/referent], 18.7% (15.0-23.1%) in HER2+/HR+ [OR 2.6], 38.9% (33.2-44.9%) in HER2+/HR- [OR 7.1] and 31.1% (26.5-36.1%) in triple negative [OR 5.0]; pCR% was significantly higher for the HER2+/HR- compared with the triple negative subtype, however pCR% was very similar for these subtypes (and OR=5.0 both subtypes) when studies using HER2-directed therapy with NAC were excluded from the model. Neither sensitivity analysis (excluding unknown subtypes), nor adjustment for associated covariates, substantially altered our findings.

INTERPRETATION

This meta-analysis provides evidence of an independent association between breast cancer subtype and pCR; odds of pCR were highest for the triple negative and HER2+/HR- subtypes, with evidence of an influential effect on achieving pCR in the latter subtype through inclusion of HER2-directed therapy with NAC.