Locally advanced breast cancer: comparison of mammography, sonography and MR imaging in evaluation of residual disease in women receiving neoadjuvant chemotherapy

TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs

Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structures. Existing quantitative approaches, like radiomics and deep learning models, lack explicit quantification of intricate and subtle parenchymal structures, including fibroglandular tissue. To address this, we propose a novel topological approach that explicitly extracts multi-scale topological structures to better approximate breast parenchymal structures, and then incorporates these structures into a deep-learning-based prediction model via an attention mechanism. Our topology-informed deep learning model, TopoTxR, leverages topology to provide enhanced insights into tissues critical for disease pathophysiology and treatment response. We empirically validate TopoTxR using the VICTRE phantom breast dataset, showing that the topological structures extracted by our model effectively approximate the breast parenchymal structures. We further demonstrate TopoTxR's efficacy in predicting response to neoadjuvant chemotherapy. Our qualitative and quantitative analyses suggest differential topological behavior of breast tissue in treatment-naïve imaging, in patients who respond favorably to therapy as achieving pathological complete response (pCR) versus those who do not. In a comparative analysis with several baselines on the publicly available I-SPY 1 dataset (N = 161, including 47 patients with pCR and 114 without) and the Rutgers proprietary dataset (N = 120, with 69 patients achieving pCR and 51 not), TopoTxR demonstrates a notable improvement, achieving a 2.6% increase in accuracy and a 4.6% enhancement in AUC compared to the state-of-the-art method.

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.

Customised 3D-Printed Surgical Guide for Breast-Conserving Surgery after Neoadjuvant Chemotherapy and Its Clinical Application

For patients eligible to undergo breast-conserving surgery (BCS) after neoadjuvant chemotherapy, accurate preoperative localisation of tumours is vital to ensure adequate tumour resection that can reduce recurrence probability effectively. For this reason, we have developed a 3D-printed personalised breast surgery guide (BSG) assisted with supine magnetic resonance imaging (MRI) and image 3D reconstruction technology, capable of mapping the tumour area identified on MRI onto the breast directly using dual positioning based on the manubrium and nipple. In addition, the BSG allows the colour dye to be injected into the breast to mark the tumour region to be removed, yielding more accurate intraoperative resection and satisfactory cosmetic outcomes. The device has been applied to 14 patients from January 2018 to July 2023, with two positive margins revealed by the intraoperative biopsy. This study showed that the BSG-based method could facilitate precise tumour resection of BCS by accurately localising tumour extent and margin, promoting the clinical efficacy in patients with breast cancer as well as simplifying the surgical process.

Evaluation of Treatment Response in Patients with Breast Cancer

Breast cancer (BC) remains one of the leading causes of death among women. The management and outcome in BC are strongly influenced by a multidisciplinary approach, which includes available treatment options and different imaging modalities for accurate response assessment. Among breast imaging modalities, MR imaging is the modality of choice in evaluating response to neoadjuvant therapy, whereas F-18 Fluorodeoxyglucose positron emission tomography, conventional computed tomography (CT), and bone scan play a vital role in assessing response to therapy in metastatic BC. There is an unmet need for a standardized patient-centric approach to use different imaging methods for response assessment.

Prediction of nipple involvement in breast cancer after neoadjuvant chemotherapy: Should we rely on breast MRI to preserve the nipple?

BACKGROUND

Indications for nipple sparing mastectomy (NSM) is extending to post-neoadjuvant chemotherapy (NAC) setting. Eligibility for NSM with an optimum tumor-nipple distance (TND) after NAC is unclear. We examined predictive factors for nipple tumor involvement in patients undergoing total mastectomy following NAC.

METHODS

Clinical and pathological data from prospectively collected medical records of women with invasive breast carcinoma, who were undergone NAC and total mastectomy with sentinel lymph node biopsy and/or axillary lymph node dissection were analyzed. PreNAC and postNAC magnetic resonance imaging (MRI) views were examined and a cut-off TND value for predicting the negative nipple tumor status was determined.

RESULTS

Among 180 women, the final mastectomy specimen analysis revealed that 12 (7%) had nipple involvement as invasive carcinoma. Patients with nipple involvement had more postNAC multifocal/multicentric tumors (p: 0.03), larger tumors on preNAC and postNAC images (p: 0.002 and p < 0.001), shorter median TNDs on preNAC and postNAC images (7 mm-IQR 1.5-14, p: 0.005 and 8.5 mm-IQR 3-15.5, p < 0.001, respectively), more nipple retraction on preNAC and postNAC images (p: 0.007 and p: 0.006) and more nipple areola complex skin thickening (> 2mm) on preNAC and postNAC images (p < 0.001 and p: 0.01). The best likelihood ratios (LR) belonged to the postNAC positivity of the < 20 mm TND, with a + LR of 3.40, and - LR of 0.11 for nipple involvement. PreNAC positivity of the < 20 mm TND also had a similar - LR of 0.14.

CONCLUSION

A TND-cut-off  ≥ 2 cm on preNAC and postNAC MRI was shown to be highly predictive of negative nipple tumor involvement.

Effect of Longitudinal Variation in Tumor Volume Estimation for MRI-guided Personalization of Breast Cancer Neoadjuvant Treatment

Purpose To investigate the impact of longitudinal variation in functional tumor volume (FTV) underestimation and overestimation in predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC). Materials and Methods Women with breast cancer who were enrolled in the prospective I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2) from May 2010 to November 2016 were eligible for this retrospective analysis. Participants underwent four MRI examinations during NAC treatment. FTV was calculated based on automated segmentation. Baseline FTV before treatment (FTV0) and the percentage of FTV change at early treatment and inter-regimen time points relative to baseline (∆FTV1 and ∆FTV2, respectively) were classified into high-standard or standard groups based on visual assessment of FTV under- and overestimation. Logistic regression models predicting pCR using single predictors (FTV0, ∆FTV1, and ∆FTV2) and multiple predictors (all three) were developed using bootstrap resampling with out-of-sample data evaluation with the area under the receiver operating characteristic curve (AUC) independently in each group. Results This study included 432 women (mean age, 49.0 years ± 10.6 [SD]). In the FTV0 model, the high-standard and standard groups showed similar AUCs (0.61 vs 0.62). The high-standard group had a higher estimated AUC compared with the standard group in the ∆FTV1 (0.74 vs 0.63), ∆FTV2 (0.79 vs 0.62), and multiple predictor models (0.85 vs 0.64), with a statistically significant difference for the latter two models (P = .03 and P = .01, respectively). Conclusion The findings in this study suggest that longitudinal variation in FTV estimation needs to be considered when using early FTV change as an MRI-based criterion for breast cancer treatment personalization. Keywords: Breast, Cancer, Dynamic Contrast-enhanced, MRI, Tumor Response ClinicalTrials.gov registration no. NCT01042379 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Ram in this issue.

ACR Appropriateness Criteria® Monitoring Response to Neoadjuvant Systemic Therapy for Breast Cancer: 2022 Update

Imaging plays a vital role in managing patients undergoing neoadjuvant chemotherapy, as treatment decisions rely heavily on accurate assessment of response to therapy. This document provides evidence-based guidelines for imaging breast cancer before, during, and after initiation of neoadjuvant chemotherapy. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Surgical Planning after Neoadjuvant Treatment in Breast Cancer: A Multimodality Imaging-Based Approach Focused on MRI

Neoadjuvant chemotherapy (NACT) today represents a cornerstone in the treatment of locally advanced breast cancer and highly chemo-sensitive tumors at early stages, increasing the possibilities of performing more conservative treatments and improving long term outcomes. Imaging has a fundamental role in the staging and prediction of the response to NACT, thus aiding surgical planning and avoiding overtreatment. In this review, we first examine and compare the role of conventional and advanced imaging techniques in preoperative T Staging after NACT and in the evaluation of lymph node involvement. In the second part, we analyze the different surgical approaches, discussing the role of axillary surgery, as well as the possibility of non-operative management after-NACT, which has been the subject of recent trials. Finally, we focus on emerging techniques that will change the diagnostic assessment of breast cancer in the near future.

Detectability of category 3 or higher microcalcifications on digital mammograms: a comparative study between 5-MP color and monochrome liquid crystal display monitors

This study explored the detectability of category 3 or higher microcalcifications using 5-MP color and monochrome monitors. Contrast detail mammography phantom with polymethyl methacrylate (PMMA) images were observed in color and monochrome by five radiographers, and the image quality figures (IQF) were calculated based on the gold disc locations identified. Five radiographers and two radiologists observed 200 mammograms from 100 patients (including 36 with microcalcifications) and rated the microcalcifications. The results were analyzed using area under the curve (AUC) and jackknife resampling. A paired t test was used for statistical analysis (p < 0.05). The mean IQF of color and monochrome monitors were 10.73 and 10.49 (30 mm PMMA, p = 0.653) and 8.47 and 8.74 (50 mm PMMA, p = 0.774), respectively. The mean AUC of color and monochrome monitors were 0.917 and 0.936 (p = 0.335), respectively, with windowing and magnification. The detectability of microcalcifications was not significantly different between the monitors.

MRI in the Setting of Neoadjuvant Treatment of Breast Cancer

Neoadjuvant therapy may reduce tumor burden preoperatively, allowing breast conservation treatment for tumors previously unresectable or requiring mastectomy without reducing disease-free survival. Oncologists can also use the response of the tumor to neoadjuvant chemotherapy (NAC) to identify treatment likely to be successful against any unknown potential distant metastasis. Accurate preoperative estimations of tumor size are necessary to guide appropriate treatment with minimal delays and can provide prognostic information. Clinical breast examination and mammography are inaccurate methods for measuring tumor size after NAC and can over- and underestimate residual disease. While US is commonly used to measure changes in tumor size during NAC due to its availability and low cost, MRI remains more accurate and simultaneously images the entire breast and axilla. No method is sufficiently accurate at predicting complete pathological response that would obviate the need for surgery. Diffusion-weighted MRI, MR spectroscopy, and MRI-based radiomics are emerging fields that potentially increase the predictive accuracy of tumor response to NAC.

Mid-treatment Ultrasound Descriptors as Qualitative Imaging Biomarkers of Pathologic Complete Response in Patients with Triple-Negative Breast Cancer

This study aimed to investigate mid-treatment breast tumor ultrasound characteristics that may predict eventual pathologic complete response (pCR) in triple-negative breast cancer; specifically, we examined associations between pCR and two parameters: tumor response pattern and tumor appearance. Ultrasound was performed at mid-treatment, defined as the completion of four cycles of anthracycline-based chemotherapy and before receiving taxane-based chemotherapy. Consensus imaging review was performed while blinded to pathology results (i.e., pCR/non-pCR) from surgery. Tumor response pattern was described as "complete," "concentric," "fragmented," "stable" or "progression." Tumor appearance was designated as "mass," "architectural distortion," "flat tumor bed" or "clip only." Univariate and multivariate regression analyses of 144 participants showed significant associations between mid-treatment response pattern and pCR (p = 0.0348 and p = 0.0173, respectively), with complete and concentric response patterns more likely to achieve pCR than other patterns. Univariate and multivariate regression analyses further showed significant associations between mid-treatment tumor appearance and pCR (p < 0.0001 for both), with persistent appearance of mass less likely than other appearances to achieve pCR. To conclude, our study demonstrated strong associations between pCR and both tumor response pattern and tumor appearance, thereby suggesting that these parameters have potential as qualitative imaging biomarkers of pCR in triple-negative breast cancer.

Identification of tumor biomarkers for pathological complete response to neoadjuvant treatment in locally advanced breast cancer

BACKGROUND

Therapeutic response predictors like age, nodal status, and tumor grade and markers, like ER/PR, HER2, and Ki67, are not reliable in predicting the response to a specific form of chemotherapy. The current study aims to identify and validate reliable markers that can predict pathological complete response (pCR) in fluorouracil, epirubicin, and cyclophosphamide (FEC)-based neoadjuvant therapy with (NACT/RT) and without concurrent radiation (NACT).

MATERIALS AND METHODS

Tandem mass tag (TMT) quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify differentially expressed proteins from core needle breast biopsy between pCR (n = 4) and no-pCR (n = 4). Immunoblotting of shortlisted proteins with the tissue lysates confirmed the differential expression of the markers. Further, immunohistochemistry (IHC) was performed on formalin-fixed paraffin-embedded sections of treatment-naive core needle biopsies. In the NACT, 29 pCR and 130 no-pCR and in NACT/RT, 32 pCR and 71 no-pCR were used.

RESULTS

733 and 807 proteins were identified in NACT and NACT/RT groups, respectively. Ten proteins were shortlisted for validation as potential pCR-predictive markers. THBS1, TNC, and DCN were significantly overexpressed in no-pCR in both the groups. In NACT, CPA3 was significantly upregulated in the no-pCR. In NACT/RT, HnRNPAB was significantly upregulated and HMGB1 significantly downregulated in the no-pCR. HMGB1 was the only marker to show prognostic significance.

CONCLUSION

Quantitative proteomics followed by IHC identified and validated potential biomarkers for predicting patient response to therapy. These markers can be used, following larger-scale validation, in combination with routine histological analysis providing vital indications of treatment response.

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.

The diagnostic performance of diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging in evaluating the pathological response of breast cancer to neoadjuvant chemotherapy: A meta-analysis

PURPOSE

To evaluate and compare the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the pathological response of breast cancer to neoadjuvant chemotherapy (NAC).

METHODS

We searched PubMed, EMBASE, Cochrane Library, and Web of Science systematically to identify relevant studies from inception to December 2020. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the methodological quality of the included studies. We extracted sufficient data to construct 2 × 2 tables and then used STATA 12.0 to perform data pooling, heterogeneity testing, meta-regression analysis and subgroup analysis.

RESULTS

A total of 41 articles were enrolled in this study, including 27 studies (2107 patients) on DCE-MRI and 23 studies (1321 patients) on DWI. The pooled sensitivity and specificity of DCE-MRI were 0.75 and 0.79, and the pooled sensitivity and specificity of DWI were 0.77 and 0.75. There was no significant difference in sensitivity (P = 0.598) and specificity (P = 0.218) ​​between DCE-MRI and DWI. And meta-regression analysis showed that both magnetic field strength and the time of examination had significant effects on heterogeneity.

CONCLUSIONS

DWI might be a potential substitute for DCE-MRI in predicting the pathological response of breast cancer to NAC as there was no significant difference in the diagnostic performance between the two. However, considering that not all included studies directly compared the diagnostic performance of DWI and DCE-MRI in the same patients and the heterogeneity of the included studies, caution should be exercised in applying our results.

The use of breast ultrasound for prediction of pathologic complete response in different subtypes of early breast cancer within the WSG-ADAPT subtrials

OBJECTIVE

We assessed the value of breast ultrasound (US) performed at week 3 and 6 and at the end (EOT) of neoadjuvant therapy (NAT) for prediction of pathologic complete response (pCR, ypT0/is ypN0) in patients with HR+/HER2+, HR-/HER2-or HR-/HER2+ early breast cancer enrolled in the WSG-ADAPT subtrials.

METHODS

US was performed at week 3 and 6 of NAT and at EOT in 401, 517, and 553 patients, respectively. Tumors with complete or partial response by US (RECIST 1.1) were classified as responders and those with stable or progressive disease as non-responders.

RESULTS

pCR rate was higher in US responders than in non-responders. US tended to yield the highest positive predictive value in HR-/HER2+ (69%) and HR-/HER2-tumors (65%) at week 3, and the highest negative predictive value in HR+/HER2+ tumors at week 6 and at EOT (88.9% and 86.9%, respectively) and in HR-/HER2-tumors at EOT (87.9%). Multivariable analysis of patients with US at week 3 and 6 identified tumor subtype (HR-/HER2+ vs HR+/HER2+; odds ratio (OR) 2.77, 95%CI 1.45-5.29, and OR 4.17, 95%CI 2.26-7.68, respectively) and each 10% change in lesion dimension on US from baseline (OR 1.15, 95%CI 1.08-1.24, and OR 1.25, 95%CI 1.16-1.35, respectively) as parameters associated with pCR.

CONCLUSIONS

Our data support the use of week 3 and EOT US for prediction of pCR in response-guided NAT and in planning of breast-conserving surgery. Change in tumor diameter on US as a continuous variable could be a valuable alternative to categorical RECIST 1.1 criteria.

Correlation Between Preoperative Radiological and Postoperative Pathological Tumor Size in Patients With HER2+ Breast Cancer After Neoadjuvant Chemotherapy Plus Trastuzumab and Pertuzumab

BACKGROUND

Neoadjuvant chemotherapy (NAC) in combination with anti-HER2 treatment is standard of care in patients with early HER2 positive breast cancer. Preoperative radiological evaluation is mandatory for defining the extent of surgery. In this study, we evaluated the correlation between preoperative radiological and postoperative pathological tumor size in early HER2 positive patients after neoadjuvant chemotherapy in combination with trastuzumab and pertuzumab. In a patient population with HER2 positive breast cancer, who received neoadjuvant chemotherapy and anti-HER2 treatment, the correlation between preoperative radiological and postoperative pathological tumor size was performed. Concordance of radiological and pathological tumor size was found in 55.7%, leading to more extensive breast surgery as required in 7 cases and to the underestimation of 6 neoplastic lesions before surgery, respectively.

PATIENTS AND METHODS

Seventy early HER2 positive breast cancer patients were included and retrospectively analysed. All preoperative radiological assessments as well as the tumor board decision on surgical extent and pathological evaluation were completed at the Medical University of Vienna. Preoperative radiological assessment of tumor size and lymph node status were compared with final histopathological findings. The correlation between different radiological modalities regarding tumor size was investigated.

RESULTS

Concordance of radiological and pathological tumor size was found in 55.7 % (50% by sonography and 66.7% by MRI, respectively) of patients with a nonsignificant correlation of r = 0.31 (P = .08). Of the 39 patients with pathologic complete remission (pCR), 16 were also classified as radiological complete response (rCR) while 23 of those showed a radiological stable disease or partial response. In 6 patients, radiological assessment showed a CR but invasive cancer with a tumor size range from 7 to 36 mm was found in histopathological examination. Neither menopausal status (P= .69) nor BMI (P = .60) and age (P = .50) had an impact on the correlation between radiological and histopathological tumor size. Regarding lymph node status, a statistically significant association and clinically relevant correlation between radiological and histopathological evaluation was found (r = 0.66, P < .001).

CONCLUSION

Concordance between radiology and histopathology was low regarding tumor size after NAC in combination with trastuzumab and pertuzumab, but significant regarding lymph node status.

Diffusion-weighted MRI for predicting pathologic response to neoadjuvant chemotherapy in breast cancer: evaluation with mono-, bi-, and stretched-exponential models

Background

To investigate the performance of diffusion-weighted (DW) MRI with mono-, bi- and stretched-exponential models in predicting pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) for breast cancer, and further outline a predictive model of pCR combining DW MRI parameters, contrast-enhanced (CE) MRI findings, and/or clinical-pathologic variables.

Methods

In this retrospective study, 144 women who underwent NACT and subsequently received surgery for invasive breast cancer were included. Breast MRI including multi-b-value DW imaging was performed before (pre-treatment), after two cycles (mid-treatment), and after all four cycles (post-treatment) of NACT. Quantitative DW imaging parameters were computed according to the mono-exponential (apparent diffusion coefficient [ADC]), bi-exponential (pseudodiffusion coefficient and perfusion fraction), and stretched-exponential (distributed diffusion coefficient and intravoxel heterogeneity index) models. Tumor size and relative enhancement ratio of the tumor were measured on contrast-enhanced MRI at each time point. Pre-treatment parameters and changes in parameters at mid- and post-treatment relative to baseline were compared between pCR and non-pCR groups. Receiver operating characteristic analysis and multivariate regression analysis were performed.

Results

Of the 144 patients, 54 (37.5%) achieved pCR after NACT. Overall, among all DW and CE MRI measures, flow-insensitive ADC change (ΔADC_200,1000) at mid-treatment showed the highest diagnostic performance for predicting pCR, with an area under the receiver operating characteristic curve (AUC) of 0.831 (95% confidence interval [CI]: 0.747, 0.915; P < 0.001). The model combining pre-treatment estrogen receptor and human epidermal growth factor receptor 2 statuses and mid-treatment ΔADC_200,1000 improved the AUC to 0.905 (95% CI: 0.843, 0.966; P < 0.001).

Conclusion

Mono-exponential flow-insensitive ADC change at mid-treatment was a predictor of pCR after NACT in breast cancer.

Prediction of Pathologic Complete Response in Breast Cancer Patients Comparing Magnetic Resonance Imaging with Ultrasound in Neoadjuvant Setting

BACKGROUND

Some subgroups of breast cancer patients receiving neoadjuvant chemotherapy (NACT) show high rates of pathologic complete response (pCR) in the breast, proposing the possibility of omitting surgery. Prediction of pCR is dependent on accurate imaging methods. This study investigated whether magnetic resonance imaging (MRI) is better than ultrasound (US) in predicting pCR in breast cancer patients receiving NACT.

METHODS

This institutional, retrospective study enrolled breast cancer patients receiving NACT who were examined by either MRI or combined US and mammography before surgery from 2016 to 2019. Imaging findings were compared with pathologic response evaluation of the tumor. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for prediction of pCR were calculated and compared between MRI and US.

RESULTS

Among 307 patients, 151 were examined by MRI and 156 by US. In the MRI group, 37 patients (24.5 %) had a pCR compared with 51 patients (32.7 %) in the US group. Radiologic complete response (rCR) was found in 35 patients (23.2 %) in the MRI group and 26 patients (16.7 %) in the US group. In the MRI and US groups, estimates were calculated respectively for sensitivity (87.7 % vs 91.4 %), specificity (56.8 % vs 33.3 %), PPV (86.2 % vs 73.8 %), NPV (60.0 % vs 65.4 %), and accuracy (80.1 % vs 72.4 %).

CONCLUSIONS

In predicting pCR, MRI was more specific than US, but not sufficiently specific enough to be a valid predictor of pCR for omission of surgery. As an imaging method, MRI should be preferred when future studies investigating prediction of pCR in NACT patients are planned.

Feasibility of quantitative and volumetric enhancement measurement to assess tumor response in patients with breast cancer after early neoadjuvant chemotherapy

Objective

To evaluate the feasibility of quantitative enhancing lesion volume (ELV) for evaluating the responsiveness of breast cancer patients to early neoadjuvant chemotherapy (NAC) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Methods

Seventy-five women with breast cancer underwent DCE-MRI before and after NAC. Lesions were assessed by ELV, response evaluation criteria in solid tumors 1.1 (RECIST 1.1), and total lesion volume (TLV). The diagnostic and pathological predictive performances of the methods were compared and color maps were compared with pathological results.

Results

ELV identified 29%, 67%, and 4% of cases with partial response, stable disease, and progressive disease, respectively. There was no significant difference in evaluation performances among the methods. The sensitivity, specificity, positive predictive value, negative predictive value (NPV), and accuracy of ELV for predicting pathologic response were 72%, 92%, 81.8%, 86.8%, and 85.3%, respectively, with the highest sensitivity, NPV, and accuracy of the three methods. The area under the receiver operating characteristic curve was also highest for ELV. Pre- and post-NAC color maps reflecting tumor activity were consistent with pathological necrosis.

Conclusions

ELV may help evaluate the responsiveness of breast cancer patients to NAC, and may provide a good tumor-response indicator through the ability to indicate tumor viability.

3T DCE-MRI Radiomics Improves Predictive Models of Complete Response to Neoadjuvant Chemotherapy in Breast Cancer

OBJECTIVES

To test whether 3T MRI radiomics of breast malignant lesions improves the performance of predictive models of complete response to neoadjuvant chemotherapy when added to other clinical, histological and radiological information.

METHODS

Women who consecutively had pre-neoadjuvant chemotherapy (NAC) 3T DCE-MRI between January 2016 and October 2019 were retrospectively included in the study. 18F-FDG PET-CT and histological information obtained through lesion biopsy were also available. All patients underwent surgery and specimens were analyzed. Subjects were divided between complete responders (Pinder class 1i or 1ii) and non-complete responders to NAC. Geometric, first order or textural (higher order) radiomic features were extracted from pre-NAC MRI and feature reduction was performed. Five radiomic features were added to other available information to build predictive models of complete response to NAC using three different classifiers (logistic regression, support vector machines regression and random forest) and exploring the whole set of possible feature selections.

RESULTS

The study population consisted of 20 complete responders and 40 non-complete responders. Models including MRI radiomic features consistently showed better performance compared to combinations of other clinical, histological and radiological information. The AUC (ROC analysis) of predictors that did not include radiomic features reached up to 0.89, while all three classifiers gave AUC higher than 0.90 with the inclusion of radiomic information (range: 0.91-0.98).

CONCLUSIONS

Radiomic features extracted from 3T DCE-MRI consistently improved predictive models of complete response to neo-adjuvant chemotherapy. However, further investigation is necessary before this information can be used for clinical decision making.

Concordance Between Clinical and Pathological Response Assessment After Neo-Adjuvant Chemotherapy in Patients With Invasive Lobular Carcinoma

Background Neo-adjuvant chemotherapy (NAC) is frequently administered in breast carcinoma patients. The clinical response to NAC guides further treatment. The pathological response is not only an independent prognostic factor, but it also guides further treatment and prognosis. Objectives The aim of our study was to find the degree of concordance between clinical and pathological response assessments after NAC in Invasive lobular Carcinoma (ILC) cases by using World Health Organization (WHO) criteria and different pathological systems, respectively. We also tried to identify any useful parameter of clinical assessment that could better correlate with pathologic assessment and provide a better estimation of residual tumor. Methods This retrospective study was conducted on 26 ILC tumors diagnosed in 24 patients who were treated with NAC followed by surgical resection between January 2009 and December 2020. Medical records and microscopy glass slides were reviewed for clinical and pathological response assessments, respectively. Results The pre-treatment tumor area ranged from 1.8-255 cm² and the mean±SD was 52.2±66.8 cm². After NAC, complete clinical response was observed in four (15.3%) cases. The clinically assessed mean tumor area significantly reduced from 52.2±66.8 cm² to 17.2±22.6 cm² (p-value<0.001). The pathologically assessed mean tumor area (27.4±24.1 cm²) didn't differ significantly from the clinically assessed mean tumor area (17.2±22.6 cm²) (p-value=0.114). Pathologically, the majority of the cases showed partial response, and a complete pathological response was achieved in only two (7.7%) cases. The concordance rates between clinical assessment by the WHO method and pathological assessment of the breast using the Sataloff method, Miller-Payne (MP) system, Residual Cancer Burden system, and Chevallier method were 26.7%, 15.8%, 9%, and 3.5%, respectively, with insignificant p-values. Percentage reduction in clinical size and percentage reduction in tumor cellularity differed significantly (p-value=0.038). Conclusion Clinical response assessment provides a less accurate estimation of residual disease, as it shows poor concordance with pathological assessment using different assessment systems/methods.

Value of ultrafast and standard dynamic contrast-enhanced magnetic resonance imaging in the evaluation of the presence and extension of residual disease after neoadjuvant chemotherapy in breast cancer

PURPOSE

To evaluate the diagnostic performance of ultrafast and standard dynamic contrast-enhanced (DCE)-MRI in evaluating the residual disease after neoadjuvant chemotherapy (NAC) for breast cancer.

MATERIALS AND METHODS

Sixty-seven consecutive patients underwent MRI after NAC. Visual analysis of enhancement was performed on ultrafast and standard DCE-MRI, and compared between no residual disease and residual disease groups. The lesion diameters measured on the last phase of ultrafast DCE-MRI and early and delayed phases of standard DCE-MRI were compared with pathological diameter of entire residual cancer and residual invasive ductal carcinoma (IDC).

RESULTS

The visual analysis in the delayed phase of standard DCE-MRI exhibited the highest sensitivity (90%), whereas ultrafast DCE-MRI revealed the highest positive predictive value (92%). There were no significant differences between the diameters in the delayed phase of the standard DCE-MRI and the pathological entire residual cancer (p = 0.97), and the diameters in ultrafast DCE-MRI and the pathological residual IDC (p = 0.97).

CONCLUSION

The delayed phase of standard DCE-MRI may be effective for detecting the residual disease and evaluating the extension of entire residual cancer. Enhancement in ultrafast DCE-MRI may be strongly suggestive of the presence of residual disease, and effective for evaluating the extension of residual IDC.

Automated breast volume scanner (ABVS) compared to handheld ultrasound (HHUS) and contrast-enhanced magnetic resonance imaging (CE-MRI) in the early assessment of breast cancer during neoadjuvant chemotherapy: an emerging role to monitoring tumor response?

OBJECTIVES

To investigate the role of automated breast volume scanner (ABVS) compared to handheld ultrasound (HHUS) and contrast-enhanced magnetic resonance imaging (CE-MRI) in the early detection of patients with locally advanced breast cancer who are more likely to reach a complete pathological response (pCR) during neoadjuvant chemotherapy (NAC).

METHODS

A single-institution prospective study was performed in patients with histological diagnosis of invasive breast cancer, eligible for NAC, and who were to undergo surgery in our Hospital. Imaging examinations with ABVS, HHUS and CE-MRI were performed at diagnosis (basal time) and after 3 months of chemotherapy (middle time). The tumor size of each lesion was measured at the basal and middle times, and the dimensional variation was reported. Based on this, patients were divided dichotomously by the median value, obtaining "good responders" (goodR) versus "poor responders" (poorR). The results were correlated with the histological assessment (pCR versus No-pCR) with the use of the intergroup comparison of categorical data (Fisher's exact test).

RESULT

A total of 21 patients were included; 5 obtained a pCR (23%). Both the ABVS and the CE-MRI found all 5 patients with pCR in the group of goodR (10 patients), while none of the poorR (11 patients) obtained a pCR [correlation was statistically significant (p 0.01)]. In the HHUS, goodR (10 patients) 1 obtained a pCR while in the poorR (11 patients) 4 obtained a pCR [correlation not statistically significant (p 0.31)].

CONCLUSIONS

ABVS could be a useful tool, appearing to be more reliable than HHUS, and as accurate as CE-MRI, in early detection of patients who could reach a pCR after NAC.

Muscle mass loss after neoadjuvant chemotherapy in breast cancer: estimation on breast magnetic resonance imaging using pectoralis muscle area

OBJECTIVES

The loss of skeletal muscle mass is widely considered a predictor of poor survival and toxicity in breast cancer patients. The aim of this study is to evaluate if there is pectoralis muscle area (PMA) variation, reflecting loss of skeletal muscle mass, on consecutive MRI examinations after neoadjuvant chemotherapy.

METHODS

The retrospective study protocol was approved by our institutional review board. A total of n = 110 consecutive patients (mean age 56 ± 11 years) who were treated with neoadjuvant chemotherapy (NAC) for histologically proven primary breast cancer between January 2017 and January 2019 and in whom tumor response was checked with standard breast MRI were included. Two radiologists calculated the pectoralis muscle cross-sectional area before and after NAC.

RESULTS

Time between the MRI examinations, before starting NAC and after completing NAC, was 166.8 ± 50 days. PMA calculated pre-NAC (8.14 cm2) was larger than PMA calculated post-NAC (7.03 cm2) (p < 0.001). According to the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, there were no significant differences between responders (complete or partial response) and non-responders (p = 0.362). The multivariate regression analysis did not show any significant relationships between ΔPMA and age, time between MRI exams, estrogen and progesterone receptor status, human epidermal growth factor receptor status (HER-2), Ki-67 expression, lymph node status, RECIST criteria, histological type, average lesion size, molecular categories, and grade. Inter-reader (k = 0.72) and intra-reader agreement (0.69 and 0.71) in PMA assessment were good.

CONCLUSIONS

Pectoralis muscle mass varies in breast cancer patients undergoing NAC and this difference can be estimated directly on standard breast MRI.

KEY POINTS

• Pectoralis muscle area variation reflects loss of skeletal muscle mass. • Pectoralis muscle area on MRI is reduced after NAC. • Pectoralis muscle mass loss seems independent from other variables.

Impact of MRI Protocol Adherence on Prediction of Pathological Complete Response in the I-SPY 2 Neoadjuvant Breast Cancer Trial

We investigated the impact of magnetic resonance imaging (MRI) protocol adherence on the ability of functional tumor volume (FTV), a quantitative measure of tumor burden measured from dynamic contrast-enhanced MRI, to predict response to neoadjuvant chemotherapy. We retrospectively reviewed dynamic contrast-enhanced breast MRIs for 990 patients enrolled in the multicenter I-SPY 2 TRIAL. During neoadjuvant chemotherapy, each patient had 4 MRI visits (pretreatment [T0], early-treatment [T1], inter-regimen [T2], and presurgery [T3]). Protocol adherence was rated for 7 image quality factors at T0-T2. Image quality factors confirmed by DICOM header (acquisition duration, early phase timing, field of view, and spatial resolution) were adherent if the scan parameters followed the standardized imaging protocol, and changes from T0 for a single patient's visits were limited to defined ranges. Other image quality factors (contralateral image quality, patient motion, and contrast administration error) were considered adherent if imaging issues were absent or minimal. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of FTV change (percent change of FTV from T0 to T1 and T2) in predicting pathological complete response. FTV changes with adherent image quality in all factors had higher estimated AUC than those with non-adherent image quality, although the differences did not reach statistical significance (T1, 0.71 vs. 0.66; T2, 0.72 vs. 0.68). These data highlight the importance of MRI protocol adherence to predefined scan parameters and the impact of data quality on the predictive performance of FTV in the breast cancer neoadjuvant setting.

Preoperative evaluation of mammographic microcalcifications after neoadjuvant chemotherapy for breast cancer

AIM

To assess the predictive value of preoperative residual mammographic microcalcifications for residual tumours after neoadjuvant chemotherapy (NAC) for breast cancer.

MATERIALS AND METHODS

This single-centre retrospective study included breast cancer patients who underwent NAC and demonstrated suspicious microcalcifications within or near the tumour bed on mammography from June 2015 to August 2018. The residual microcalcifications and remnant lesion on magnetic resonance imaging (MRI) were correlated with histopathological findings of residual tumours and immunohistochemical markers.

RESULTS

A total of 96 patients were included. Ten patients achieved pathological complete response (pCR) and previous suspicious microcalcifications were associated with benign pathology in 10.4% (10/96) of the patients. In the remaining 86 patients who did not achieve pCR, 61.5% (59/96) of the residual microcalcifications were associated with invasive or in situ carcinoma and 28.1% (27/96) with benign pathology. Hormone receptor-positive (HR⁺) patients had the highest proportion of residual malignant microcalcifications compared to HR^- patients (48.9% versus 13.5%, respectively; p=0.019). MRI correlated better than residual microcalcifications on mammography in predicting residual tumour extent in all subtypes (ICC=0.709 versus 0.365). MRI also showed higher correlation with residual tumour size for the HR^-/HER2⁺ and HR^-/HER2^- subtype (ICC=0.925 and 0.876, respectively).

CONCLUSION

The extent of microcalcifications on mammography after NAC did not correlate with the extent of residual cancer in 38.5% of women. Regardless of the extent of microcalcifications, residual tumour extent on MRI after NAC and molecular subtype could be an accurate tool in evaluating residual cancer after NAC.

Higher underestimation of tumour size post-neoadjuvant chemotherapy with breast magnetic resonance imaging (MRI)-A concordance comparison cohort analysis

Objectives

The aim of this study was to evaluate the diagnostic accuracy of breast MRI for detecting residual tumor and the tumor size whether it would be affected after neoadjuvant chemotherapy.

Methods

Total 109 patients with NAC and 682 patients without NAC were included in this retrospective study. Measurement of the largest diameter of tumors at pathology was chosen as gold standard and compared with preoperative breast MRI. A concordance threshold of ±25% of maximal tumor size was used. The accuracy of MRI was graded as concordant, underestimation, or overestimation rate. Further subgroup analysis with tumor stages, histologic subgroups and intrinsic subtypes was performed.

Results

The post-NAC MRI was associated with 92.5% sensitivity, 55.2% specificity, 85.1% positive predictive value, 72.7% negative predictive value, and overall 82.6% accuracy for detecting residual tumor. In determining tumor size, the overall concordance rates of the non-NAC group and the NAC group were 43.5% and 41.3%, respectively (p = 0.678). But the overestimation rate and underestimation rate were 26.6% and 32.1% for NAC group, and 52.9% and 3.5% for the non-NAC group (p<0.001). While in the subgroups analysis, the concordance rate of the NAC group (26.7%) was lower than that of the non-NAC group (82.1%) at T3 stage (p<0.001). There were no statistically significant differences between different tumor histologic subgroups and intrinsic subtypes.

Conclusions

The overall accuracy of MRI in predicting tumor size was not affected by NAC; however, it tends to underestimate tumor size after NAC, especially in patients with T3 lesions and above.

Breast cancer phenotype influences MRI response evaluation after neoadjuvant chemotherapy

PURPOSE

To evaluate which factors may influence magnetic resonance imaging (MRI) performance in the detection of pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC).

METHOD

This retrospective study included 219 patients diagnosed with invasive breast carcinoma who underwent breast MRI before and after NAC. The MRI findings were compared to gold standard pathological examinations. Resolution of invasive breast disease was defined as pCR.

RESULTS

The mean age of our cohort was 48 years (range: 20-85). The molecular subtypes included: Luminal B/Her-2 negative (n = 89; 40%), triple-negative (n = 69; 32%), Luminal B/Her-2 positive (n = 43; 20%), and Her-2 overexpression (n = 18; 8%). MRI analysis after NAC showed complete response in 76 cases (35%), while pathological analysis of surgical specimens after NAC detected pCR in 85 cases (39%). The accuracy of MRI in diagnosing pCR was 80%, with 69% sensitivity, 87% specificity, and positive and negative predictive values of 78% and 82%, respectively. The only factor statistically associated with a higher discordance rate between MRI and pathologic response was the presence of non-mass enhancement at pre-treatment MRI (p = 0.003).

CONCLUSIONS

MRI demonstrated good accuracy in predicting pCR after NAC among the breast cancer patients examined. However, non-mass enhancement at pre-treatment MRI negatively affected the diagnostic performance of MRI in assessing treatment response after NAC.

Accuracy of breast magnetic resonance imaging in evaluating the response to neoadjuvant chemotherapy: a study of 310 cases at a cancer center

Objective

To evaluate the accuracy of magnetic resonance imaging (MRI) of the breasts in the identification of a pathological complete response in patients with breast cancer undergoing neoadjuvant chemotherapy (NAC).

Materials and Methods

This was a single-center, retrospective, observational study designed to validate a diagnostic test. The following variables were evaluated: age; results of the histological and immunohistochemical analysis of the biopsy; post-NAC MRI findings; and results of the histological analysis of the surgical specimen, using the residual cancer burden index. The radiological response, as assessed by MRI, was compared with the pathological response, as assessed by histological analysis of the surgical specimen (the gold standard method).

Results

We evaluated 310 tumors in 308 patients. The mean age of the patients was 47 years (range, 27-85 years). For identifying a pathological complete response, breast MRI had an overall accuracy of 79%, with a sensitivity of 75%, specificity of 83%, positive predictive value of 75%, and negative predictive value of 83%. When that accuracy was stratified by molecular subtype, it was best for the HER2 subtype, with a sensitivity and specificity of 82% and 89%, respectively, followed by the triple-negative subtype, with a sensitivity and specificity of 78% and 83%, respectively.

Conclusion

Breast MRI showed good accuracy in the prediction of a pathological complete response after NAC. The sensitivity and positive predictive value were highest for the HER2 and triple-negative subtypes.

Accuracy of multi-parametric breast MR imaging for predicting pathological complete response of operable breast cancer prior to neoadjuvant systemic therapy

OBJECTIVES

To evaluate whether multiparametric breast-MRI, obtained before the initiation of neoadjuvant systemic therapy (NST) for operable breast cancer, predicts which cancer will achieve a pathological complete response (pCR) after the completion of NST.

METHODS

This was an IRB-approved retrospective study on 31 consecutive patients (median age, 56 years) with operable invasive breast cancer (median size: 22 mm; triple-negative: 11/31 [35%], HER2-positive: 7/31 [23%], triple-positive: 13/31 [42%]) who underwent multiparametric DCE-MRI before the initiation of NST. The MRI protocol consisted of high-resolution dynamic contrast-enhanced MRI (DCE-MRI), T2-TSE, and DWI (b-values 0, 100, 800 s/mm²). The results of surgical pathology after the completion of NST served as a standard of reference. Patient characteristics (age and menopausal status), pathological tumor characteristics (type, stage, nuclear grade, ER/PR and HER2 receptor status, and Ki-67 staining), and MRI characteristics (size, morphology, T2 signal intensity, enhancement kinetics, and ADC values) before NST were evaluated and compared between patients achieving pCR vs. non-pCR.

RESULTS

Among 31 patients, 17 achieved pCR (55%) and 14 non-pCR (45%). No correlation was observed between patient- or tumor pathology-derived characteristics and pCR vs. non-pCR. Among MRI-derived tumor characteristics, tumor growth orientation parallel to Cooper's ligaments (p = 0.002) and wash-out rates (p = 0.019) correlated with pCR. Pre-NST ADC values were lower in patients achieving pCR (P = 0.086).

CONCLUSIONS

A tumor growth pattern parallel with Cooper's ligaments and a fast wash-out rate on pre-treatment multiparametric MRI are predictive of pCR and more closely associated with pCR than ADC values.

Factors affecting the concordance of radiologic and pathologic tumor size in breast carcinoma

Background

Radiologic assessment of tumor size is an integral part of the work-up for breast carcinoma. With improved radiologic equipment, surgical decision relies profoundly upon radiologic/clinical stage. We wanted to see the concordance between radiologic and pathologic tumor size to infer how accurate radiologic/clinical staging is.

Materials and methods

The surgical pathology and ultrasonography reports of patients with breast carcinoma were reviewed. Data were collected for 406 cases. Concordance was defined as a size difference within ±2 mm.

Results

The difference between radiologic and pathologic tumor size was within ±2 mm in 40.4% cases. The mean radiologic size was 1.73 ± 1.06 cm. The mean pathologic size was 1.84 ± 1.24 cm. A paired t-test showed a significant mean difference between radiologic and pathologic measurements (0.12 ± 1.03 cm, p = 0.03). Despite the size difference, stage classification was the same in 59.9% of cases. Radiologic size overestimated stage in 14.5% of cases and underestimated stage in 25.6% of cases. The concordance rate was significantly higher for tumors ≤2 cm (pT1) (51.1%) as compared to those greater than 2 cm (≥pT2) (19.7%) (p < 0.0001). Significantly more lumpectomy specimens (47.5%) had concordance when compared to mastectomy specimens (29.8%) (p < 0.0001). Invasive ductal carcinoma had better concordance compared to other tumors (p = 0.02).

Conclusion

Mean pathologic tumor size was significantly different from mean radiologic tumor size. Concordance was in just over 40% of cases and the stage classification was the same in about 60% of cases only. Therefore, surgical decision of lumpectomy versus mastectomy based on radiologic tumor size may not always be accurate.

Changes in background parenchymal enhancement in HER2-positive breast cancer before and after neoadjuvant chemotherapy: Association with pathologic complete response

This study aimed to analyze the relationship between pathologic complete response (pCR) and changes in background parenchymal enhancement (BPE) levels in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer and who received neoadjuvant chemotherapy (NAC).The pre- and post-NAC magnetic resonance imaging results of 51 patients with confirmed unilateral HER2-positive breast cancer were retrospectively analyzed by 2 experienced radiologists. Pre- and post-NAC of contralateral BPE levels were classified into 4 categories (1 = minimal, 2 = mild, 3 = moderate, and 4 = marked). The 4 categories of BPE were defined by the visually estimated enhancement of fibroglandular tissue of the breast. Changes in BPE before and after NAC were compared between the premenopausal and postmenopausal groups and between the pCR and non-pCR groups. The associations between BPE and pCR and between BPE and tumor size were analyzed before and after NAC.Twenty-three patients achieved pCR, and 28 patients achieved non-pCR. Premenopausal patients had significantly higher baseline BPE levels than postmenopausal women (P = .023). The post-NAC BPE levels of premenopausal patients significantly decreased relative to those of postmenopausal patients (P = .027). The baseline BPE levels of the pCR group were not significantly different from those of the non-pCR group (P = .892). However, the decrease in BPE levels in the pCR group was more drastic than that in the non-pCR group (P < .001). Decreased BPE levels were directly associated with pCR and tumor size reduction (P < .05). Women with hormone receptor (HR)-negative tumors were more likely to exhibit pCR than those with HR-positive tumors (P = .007).Decreased BPE of patients with HER2-positive breast cancer may serve as an indicator of NAC effectiveness. Furthermore, women with HR-negative tumors were more likely to exhibit pCR than women with HR-positive tumors.

Diagnostic investigation of breast magnetic resonance imaging in malignant and benign mass lesions

INTRODUCTION

Breast magnetic resonance imaging (BMRI) has been identified as a valuable modality in the diagnosis of breast cancer and monitoring the response to chemotherapy. The aim of this study was to evaluate the relative importance of different descriptors of breast masses in contrast-enhanced breast MRI.

MATERIAL AND METHODS

In a database of pathologically proven breast lesions, in total 433 masses in 312 patients detected by contrast-enhanced breast MRI were selected. All images were assessed according to the MRI BI-RADS lexicon and those with significant positive MRI findings (BI-RADS categories 3, 4, 5) were enrolled in the study.

RESULTS

Mean age of patients was 45.09 ±10.5 years. The most frequent BI-RADS score was 4 (60.7%), followed by 3 (27%). Among the morphologic descriptors of the enhancing masses, the findings most strongly associated with malignancy included spiculated margin (60.6%) and irregular shape (38%). Considering the dynamic descriptors, a wash-out pattern in the time-intensity curve was the most powerful finding associated with malignancy (27.9%). Among all breast MRI descriptors, the best odds ratio (OR) in association with malignancy was noted for speculated margin (OR = 10.2) followed by wash-out or plateau curves (OR = 6.1), size greater than 1 cm (OR = 4.3) and irregular shape (OR = 3.1).

CONCLUSIONS

It seems that morphologic descriptors of MRI BI-RADS for enhancing masses are quite specific, while dynamic descriptors of the masses are highly sensitive. Appropriate consideration and combination of different BI-RADS findings could help in better characterization of enhancing masses on breast MRI, lowering the rate of false positive reports and avoiding unnecessary biopsies.

Diffusion-weighted imaging in monitoring the pathological response to neoadjuvant chemotherapy in patients with breast cancer: a meta-analysis

Background

Diffusion-weighted imaging (DWI) is suggested as an non-invasive and non-radioactive imaging modality in the identification of pathological complete response (pCR) in breast cancer patients receiving neoadjuvant chemotherapy (NACT). A growing number of trials have been investigating in this aspect and some studies found a superior performance of DWI compared with conventional imaging techniques. However, the efficiency of DWI is still in dispute. This meta-analysis aims at evaluating the accuracy of DWI in the detection of pCR to NACT in patients with breast cancer.

Methods

Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were drawn to estimate the diagnostic effect of DWI to NACT. Summary receiver operating characteristic curve (SROC), the area under the SROC curve (AUC), and Youden index (*Q) were also calculated. The possible sources of heterogeneity among the included studies were explored using single-factor meta-regression analyses. Publication bias and quality assessment were assessed using Deek’s funnel plot and QUADAS-2 form respectively.

Results

Twenty studies incorporated 1490 participants were enrolled in our analysis. Pooled estimates revealed a sensitivity of 0.89 (95% CI, 0.86–0.91), a specificity of 0.72 (95% CI, 0.68–0.75), and a DOR of 27.00 (95% CI, 15.60–46.73). The AUC of SROC curve and *Q index were 0.9088 and 0.8408, respectively. The results of meta-regression analyses showed that pCR rate, time duration of study population, and study design were not the sources of heterogeneity.

Conclusion

A relatively high sensitivity and specificity of DWI in diagnosing pCP for patients with breast cancer underwent NACT treatment was found in our meta-analysis. This finding indicated that the use of DWI might provide an accurate and precise assessment of pCR to NACT.

Pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: Perfusion metrics of dynamic contrast enhanced MRI

The purpose of this study was to investigate imaging parameters predicting pathologic complete response (pCR) in pretreatment dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in breast cancer patients who were treated with neoadjuvant chemotherapy (NAC). A total of 74 patients who received NAC followed by surgery were retrospectively reviewed. All patients underwent breast MRI before NAC. Perfusion parameters including Ktrans, Kep and Ve of tumor were measured three-dimensionally. These perfusion parameters of background parenchyma of contralateral breasts were analyzed two-dimensionally. Receiver-operating characteristic (ROC) analysis and multivariable logistic regression analysis were performed to compare the ability of perfusion parameters to predict pCR. Of 74 patients, 13 achieved pCR in final pathology. The fiftieth percentile and skewness of each perfusion parameter - Ktrans, Kep, and Ve of tumor were associated with pCR. Perfusion parameters of contralateral breast parenchyma in 2D analysis also showed predictive ability for pCR. The model combining perfusion parameters of contralateral breast background parenchyma and those of the tumor had higher predictive value than each single parameter. Thus, perfusion parameters of tumor, background parenchyma of contralateral breast and their combinations in pretreatment breast MRI allow early prediction for pCR of breast cancer.

MRI for the Staging and Evaluation of Response to Therapy in Breast Cancer

Breast magnetic resonance imaging (MRI) is the most sensitive of the available imaging modalities to characterize breast cancer. Breast MRI has gained clinical acceptance for screening high-risk patients, but its role in the preoperative imaging of breast cancer patients remains controversial. This review focuses on the current indications for staging breast MRI, the evidence for and against the role of breast MRI in the preoperative staging workup, and the evaluation of treatment response of breast cancer patients.

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.

ACR Appropriateness Criteria® Monitoring Response to Neoadjuvant Systemic Therapy for Breast Cancer

Patients with locally advanced invasive breast cancers are often treated with neoadjuvant chemotherapy prior to definitive surgical intervention. The primary aims of this approach are to: 1) reduce tumor burden thereby permitting breast conservation rather than mastectomy; 2) promptly treat possible metastatic disease, whether or not it is detectable on preoperative staging; and 3) potentially tailor future chemotherapeutic decisions by monitoring in-vivo tumor response. Accurate radiological assessment permits optimal management and planning in this population. However, assessment of tumor size and response to treatment can vary depending on the modality used, the measurement technique (such as single longest diameter, 3-D measurements, or calculated tumor volume), and varied response of different tumor subtypes to neoadjuvant chemotherapy (such as concentric shrinkage or tumor fragmentation). As discussed in further detail, digital mammography, digital breast tomosynthesis, US and MRI represent the key modalities with potential to help guide patient management. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Tumor Size in Breast Carcinoma: Gross Measurement Is Important!

Introduction. The staging of breast carcinoma is mainly dependent on tumor size and lymph node status. Small increments in tumor size upstage the patient. An accurate determination of the tumor size is therefore critically important. Although the final staging is based on microscopic size, pathologists rely on gross measurements in a considerable number of cases. Methods. We investigated the concordance between gross and microscopic measurements of breast carcinoma as well as factors affecting this concordance. This study is a retrospective review of surgical pathology reports of invasive breast carcinomas. Data were collected for 411 cases. Concordance was defined as a size difference within ±2 mm. Results. Gross and microscopic sizes were identical in 33.1% of cases. Gross and microscopic size difference was within ±2 mm in 56% of cases. Despite the size difference, stage classification ended up being the same in 68.6% of cases. Tumor stage was over estimated by gross measurement in 17.0% of cases and underestimated in 14.4% of cases. The concordance was significantly higher for those tumors in which final pathologic tumor (pT) size was greater than 2 cm (≥pT2) as compared with those less than or equal to 2 cm (≤pT1; P < .0001). A higher proportion of mastectomy specimens (61.4%) were concordant as compared with lumpectomy specimens (52.1%). Conclusion. Gross and microscopic tumor sizes were concordant in 56% of cases. Stage classification based on gross and microscopic tumor size was different in nearly one third (31.4%) of cases. Gross tumor size is critically important in accurate staging at least in cases where tumor size cannot be confirmed microscopically.

Ultrasound-based prediction of pathologic response to neoadjuvant chemotherapy in breast cancer patients

BACKGROUND

Accuracy in predicting pathologic response to neoadjuvant chemotherapy (NACT) in breast cancer is essential for the determination of therapeutic efficacy and surgical planning. This study aimed to assess the precision of ultrasound (US) for predicting pathologic complete response (pCR = ypT0) after NACT.

METHODS

This retrospective mono-center study included 124 invasive breast cancer patients treated with NACT. Patients received US before and after NACT with documentation of clinical partial response (cPR) and clinical complete response (cCR). Post-operatively, the pathologic response was defined as absence of tumor cells (ypT0), presence of non-invasive tumor cells (ypTis) or invasive tumor cells (ypTinv). Sensitivity and specificity of US as well as false negative rate (FNR), negative predictive value (NPV) and positive predictive value (PPV) were analysed for receptor subtypes. A multivariable logistic regression model assessed the influence of patient- and tumor-associated covariates as predictors for pCR.

RESULTS

50 patients (40.3%) achieved pCR, 39 (78.0%) had a corresponding cCR. Overall sensitivity was 60.8% and specificity 78.0% for US-predicted remission. NPV and FNR differed substantially between subtypes. NPV was highest (75.0%) in triple negative (TN) subtype, while FNR was low (37.5%). Therefore, pathological response was most accurately predicted for TN cancers. NPV for human-epidermal-growth-factor-receptor-2-positive/hormone-receptor-positive (HER2+/HR+) was 55.6%, for HER2+/HR- 64.3% and for HER2-/HR+ 16.7%, FNRs were 40.0%, 71.4% and 32.3%, respectively. Receptor subtypes impacted pCR significantly (p-value: 0.0033), cCR correlated positively with pCR (p-value: 0.0026).

CONCLUSION

US imaging is insufficient to predict pCR with adequate accuracy. Receptor subtypes, however, affect diagnostic precision of US and pathologic outcome.

Correlation between Magnetic Resonance Imaging and Histopathological Tumor Response after Neoadjuvant Chemotherapy in Breast Cancer

Aim

To evaluate the accuracy of magnetic resonance imaging in assessing tumor response following neoadjuvant chemotherapy in patients with locally advanced breast cancer.

Materials and Methods

Twenty-six patients entered a phase II study of neoadjuvant chemotherapy, undergoing bilateral breast magnetic resonance imaging before therapy and before surgery. Tumor response was classified using RECIST criteria, using tumor size at magnetic resonance imaging. The latter was then compared to residue found at histopathological examination.

Results

Magnetic resonance imaging showed 6 (23%) complete responses, 17 (65%) partial responses, 3 (11.5%) disease stabilizations and no disease progressions. Twenty-three tumors (88.5%) were considered responsive and 3 (11.5%) unresponsive. Pathological tumor response was: 6 complete responses (23%), 17 partial responses (65%), 2 stable disease (8%), 1 progression (4%). When results of the preoperative magnetic resonance imaging were compared to pathological tumor response, magnetic resonance imaging overestimated tumor size in 12 cases (46%) and underestimated it in 9 (35%). However, preoperative magnetic resonance imaging failed to detect invasive tumor in 2 false-negative cases (8%), 1 of which was multifocal. Mastectomy was performed in 12 cases: 1 case of disease progression even though the neoplasm appeared smaller at magnetic resonance imaging, 3 cases with stable disease, and 4 cases with T3 or T4 disease. The 9th patient was T2N2 with initial retroareolar disease and negative magnetic resonance imaging after chemotherapy. The 10th patient, affected by lobular cancer, was in partial remission but was T3N1. The 11th patient was 57 years old but was not interested in conservative surgery. The 12th patient requested bilateral prophylactic mastectomy due to her positive family history of breast cancer.

Conclusions

Magnetic resonance imaging of the breast allowed conservative surgery in 54% of the patients. This low value is primarily due to overestimation of tumor size, with a negative predictive value of 67% in our population. However, surgeons were able to choose conservative surgery with relative safety in cases of small residual disease.

Establishing and characterizing patient-derived xenografts using pre-chemotherapy percutaneous biopsy and post-chemotherapy surgical samples from a prospective neoadjuvant breast cancer study

Background

Patient-derived xenografts (PDXs) are increasingly used in cancer research as a tool to inform cancer biology and drug response. Most available breast cancer PDXs have been generated in the metastatic setting. However, in the setting of operable breast cancer, PDX models both sensitive and resistant to chemotherapy are needed for drug development and prospective data are lacking regarding the clinical and molecular characteristics associated with PDX take rate in this setting.

Methods

The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective neoadjuvant chemotherapy (NAC) trial of stage I-III breast cancer patients treated with neoadjuvant weekly taxane+/-trastuzumab followed by anthracycline-based chemotherapy. Using percutaneous tumor biopsies (PTB), we established and characterized PDXs from both primary (untreated) and residual (treated) tumors. Tumor take rate was defined as percent of patients with the development of at least one stably transplantable (passed at least for four generations) xenograft that was pathologically confirmed as breast cancer.

Results

Baseline PTB samples from 113 women were implanted with an overall take rate of 27.4% (31/113). By clinical subtype, the take rate was 51.3% (20/39) in triple negative (TN) breast cancer, 26.5% (9/34) in HER2+, 5.0% (2/40) in luminal B and 0% (0/3) in luminal A. The take rate for those with pCR did not differ from those with residual disease in TN (p = 0.999) and HER2+ (p = 0.2401) tumors. The xenografts from 28 of these 31 patients were such that at least one of the xenografts generated had the same molecular subtype as the patient. Among the 35 patients with residual tumor after NAC adequate for implantation, the take rate was 17.1%. PDX response to paclitaxel mirrored the patients’ clinical response in all eight PDX tested.

Conclusions

The generation of PDX models both sensitive and resistant to standard NAC is feasible and these models exhibit similar biological and drug response characteristics as the patients’ primary tumors. Taken together, these models may be useful for biomarker discovery and future drug development.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0920-8) contains supplementary material, which is available to authorized users.

Residual microcalcifications after neoadjuvant chemotherapy for locally advanced breast cancer: comparison of the accuracies of mammography and MRI in predicting pathological residual tumor

Background

The aims of this study were to correlate residual mammographic microcalcifications after neoadjuvant chemotherapy (NAC) with pathological results and to compare the accuracy of mammography (MG) and magnetic resonance imaging (MRI) in predicting the size of residual tumors.

Methods

The imaging findings and pathological results for 29 patients with residual microcalcifications after NAC were reviewed. We compared the agreement of the measured extent of residual microcalcifications based on MG and residual enhancement based on MRI with the residual tumor size based on pathology.

Results

At final pathology, residual microcalcifications were malignant in 55.2% of cases and benign in 44.8% of cases. In 36% of non-pCR cases, the remaining microcalcifications were benign. Compared with the measurements of residual tumor obtained from pathology, MG showed poor agreement, and MRI showed moderate agreement, for the entire group (concordance correlation coefficient [CCC] = 0.196 vs. 0.566). Regarding the receptor status, the agreement of measurements obtained by MG was superior to that obtained by MRI (CCC = 0.5629, 0.5472 vs. 0.4496, 0.4279) for ER(+) and HER2(−) tumors. In ER(−) tumors, the measurements obtained by MG showed the lowest agreement with the pathological tumor size, which had the highest agreement with those obtained by MRI (CCC = − 0.0162 vs. 0.8584).

Conclusions

Residual mammographic microcalcifications after NAC did not correlate with malignancy in 44.8% of cases. Residual microcalcifications on MG were poorly correlated with pathological tumor size, and MRI might be more reliable for predicting residual tumor size after NAC. Tumor receptor status affected the accuracy of both MG and MRI for predicting residual tumor size after NAC.

Trial registration

CRIS, KCT0002281; registered 6 April 2015, retrospectively registered

Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting

OBJECTIVE

To discuss standard-of-care and emerging imaging techniques employed for screening and detection, diagnosis and staging, monitoring response to therapy, and guiding cancer treatments.

DATA SOURCES

Published journal articles indexed in the National Library of Medicine database and relevant websites.

CONCLUSION

Imaging plays a fundamental role in the care of cancer patients and specifically, breast cancer patients in the neoadjuvant setting, providing an excellent opportunity for interprofessional collaboration between oncologists, researchers, radiologists, and oncology nurses. Quantitative imaging strategies to assess cellular, molecular, and vascular characteristics within the tumor is needed to better evaluate initial diagnosis and treatment response.

IMPLICATIONS FOR NURSING PRACTICE

Nurses caring for patients in all settings must continue to seek education on emerging imaging techniques. Oncology nurses provide education about the test, ensure the patient has appropriate pre-testing instructions, and manage patient expectations about timing of results availability.