Pre-treatment differences and early response monitoring of neoadjuvant chemotherapy in breast cancer patients using magnetic resonance imaging: a systematic review

Towards detection of early response in neoadjuvant chemotherapy of breast cancer using Bayesian intravoxel incoherent motion

Introduction

The early identification of good responders to neoadjuvant chemotherapy (NACT) holds a significant potential in the optimal treatment of breast cancer. A recent Bayesian approach has been postulated to improve the accuracy of the intravoxel incoherent motion (IVIM) model for clinical translation. This study examined the prediction and early sensitivity of Bayesian IVIM to NACT response.

Materials and methods

Seventeen female patients with breast cancer were scanned at baseline and 16 patients were scanned after Cycle 1. Tissue diffusion and perfusion from Bayesian IVIM were calculated at baseline with percentage change at Cycle 1 computed with reference to baseline. Cellular proliferative activity marker Ki-67 was obtained semi-quantitatively with percentage change at excision computed with reference to core biopsy.

Results

The perfusion fraction showed a significant difference (p = 0.042) in percentage change between responder groups at Cycle 1, with a decrease in good responders [-7.98% (-19.47-1.73), n = 7] and an increase in poor responders [10.04% (5.09-28.93), n = 9]. There was a significant correlation between percentage change in perfusion fraction and percentage change in Ki-67 (p = 0.042). Tissue diffusion and pseudodiffusion showed no significant difference in percentage change between groups at Cycle 1, nor was there a significant correlation against percentage change in Ki-67. Perfusion fraction, tissue diffusion, and pseudodiffusion showed no significant difference between groups at baseline, nor was there a significant correlation against Ki-67 from core biopsy.

Conclusion

The alteration in tumour perfusion fraction from the Bayesian IVIM model, in association with cellular proliferation, showed early sensitivity to good responders in NACT.

Clinical trial registration

https://clinicaltrials.gov/ct2/show/NCT03501394, identifier NCT03501394.

Predicting the Early Response to Neoadjuvant Therapy with Breast MR Morphological, Functional and Relaxometry Features-A Pilot Study

Aim: To evaluate the role of MR relaxometry and derived proton density analysis in the prediction of early treatment response after two cycles of neoadjuvant therapy (NAT), in patients with breast cancer. Methods: This was a prospective study that included 59 patients with breast cancer, who underwent breast MRI prior (MRI1) and after two cycles of NAT (MRI2). The MRI1 included a sequential acquisition with five different TE’s (50, 100, 150, 200 and 250 ms) and a TR of 5000 ms. Post-processing was used to obtain the T2 relaxometry map from the MR acquisition. The tumor was delineated and seven relaxometry and proton density parameters were extracted. Additional histopathology data, T2 features and ADC were included. The response to NAT was reported based on the MRI2 as responders: partial response (>30% decreased size) and complete response (no visible tumor stable disease (SD); and non-responders: stable disease or progression (>20% increased size). Statistics was done using Medcalc software. Results: There were 50 (79.3%) patients with response and 13 (20.7%) non-responders to NAT. Age, histologic type, “in situ” component, tumor grade, estrogen and progesterone receptors, ki67% proliferation index and HER2 status were not associated with NAT response (all p > 0.05). The nodal status (N) 0 was associated with early response, while N2 was associated with non-response (p = 0.005). The tumor (T) and metastatic (M) stage were not statistically significant associated with response (p > 0.05). The margins, size and ADC values were not associated with NAT response (p-value > 0.05). The T2 min relaxometry value was associated with response (p = 0.017); a cut-off value of 53.58 obtained 86% sensitivity (95% CI 73.3−94.2), 69.23 specificity (95% CI 38.6−90.9), with an AUC = 0.715 (p = 0.038). The combined model (T2 min and N stage) achieved an AUC of 0.826 [95% CI: 0.66−0.90, p-value < 0.001]. Conclusions: MR relaxometry may be a useful tool in predicting early treatment response to NAT in breast cancer patients.

Breast tumour volume and blood flow measured by MRI after one cycle of epirubicin and cyclophosphamide-based neoadjuvant chemotherapy as predictors of pathological response

OBJECTIVES

Better markers of early response to neoadjuvant chemotherapy (NACT) in patients with breast cancer are required to enable the timely identification of non-responders and reduce unnecessary treatment side-effects. Early functional imaging may better predict response to treatment than conventional measures of tumour size. The purpose of this study was to test the hypothesis that the change in tumour blood flow after one cycle of NACT would predict pathological response.

METHODS

In this prospective cohort study, dynamic contrast-enhanced MRI was performed in 35 females with breast cancer before and after one cycle of epirubicin and cyclophosphamide-based NACT (EC90). Estimates of tumour blood flow and tumour volume were compared with pathological response obtained at surgery following completion of NACT.

RESULTS

Tumour blood flow at baseline (mean ± SD; 0.32 ± 0.17 ml/min/ml) reduced slightly after one cycle of NACT (0.28 ± 0.18 ml/min/ml). Following treatment 15 patients were identified as pathological responders and 20 as non-responders. There were no relationships found between tumour blood flow and pathological response. Conversely, tumour volume was found to be a good predictor of pathological response (smaller tumours did better) at both baseline (area under the receiver operating characteristic curve 0.80) and after one cycle of NACT (area under the receiver operating characteristic curve 0.81).

CONCLUSION & ADVANCES IN KNOWLEDGE

The change in breast tumour blood flow following one cycle of EC90 did not predict pathological response. Tumour volume may be a better early marker of response with such agents.

Tumor Sphericity Predicts Response in Neoadjuvant Chemotherapy for Invasive Breast Cancer

This retrospective study examined magnetic resonance imaging (MRI)–derived tumor sphericity (SPH) as a quantitative measure of breast tumor morphology, and investigated the association between SPH and reader-assessed morphological pattern (MP). In addition, association of SPH with pathologic complete response was evaluated in patients enrolled in an adaptively randomized clinical trial designed to rapidly identify new agents for breast cancer. All patients underwent MRI examinations at multiple time points during the treatment. SPH values from pretreatment (T0) and early-treatment (T1) were investigated in this study. MP on T0 dynamic contrast-enhanced MRI was ranked from 1 to 5 in 220 patients. Mean SPH values decreased with the increased order of MP. SPH was higher in patients with pathologic complete response than in patients without (difference at T0: 0.04, 95% confidence interval [CI]: 0.02–0.05, P < .001; difference at T1: 0.03, 95% CI: 0.02–0.04, P < .001). The area under the receiver operating characteristic curve was estimated as 0.61 (95% CI, 0.57–0.65) at T0 and 0.58 (95% CI, 0.55–0.62) at T1. When the analysis was performed by cancer subtype defined by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status, highest area under the receiver operating characteristic curve were observed in HR−/HER2+: 0.67 (95% CI, 0.54–0.80) at T0, and 0.63 (95% CI, 0.51–0.76) at T1. Tumor SPH showed promise to quantify MRI MPs and as a biomarker for predicting treatment outcome at pre- or early-treatment time points.

MRI-Based Radiomics Analysis for the Pretreatment Prediction of Pathologic Complete Tumor Response to Neoadjuvant Systemic Therapy in Breast Cancer Patients: A Multicenter Study

This retrospective study investigated the value of pretreatment contrast-enhanced Magnetic Resonance Imaging (MRI)-based radiomics for the prediction of pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients. A total of 292 breast cancer patients, with 320 tumors, who were treated with neo-adjuvant systemic therapy and underwent a pretreatment MRI exam were enrolled. As the data were collected in two different hospitals with five different MRI scanners and varying acquisition protocols, three different strategies to split training and validation datasets were used. Radiomics, clinical, and combined models were developed using random forest classifiers in each strategy. The analysis of radiomics features had no added value in predicting pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients compared with the clinical models, nor did the combined models perform significantly better than the clinical models. Further, the radiomics features selected for the models and their performance differed with and within the different strategies. Due to previous and current work, we tentatively attribute the lack of improvement in clinical models following the addition of radiomics to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data (i.e., test-retest or similar) meant that this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.

Early ultrasound evaluation identifies excellent responders to neoadjuvant systemic therapy among patients with triple-negative breast cancer

BACKGROUND

Heterogeneity exists in the response of triple-negative breast cancer (TNBC) to standard anthracycline (AC)/taxane-based neoadjuvant systemic therapy (NAST), with 40% to 50% of patients having a pathologic complete response (pCR) to therapy. Early assessment of the imaging response during NAST may identify a subset of TNBCs that are likely to have a pCR upon completion of treatment. The authors aimed to evaluate the performance of early ultrasound (US) after 2 cycles of neoadjuvant NAST in identifying excellent responders to NAST among patients with TNBC.

METHODS

Two hundred fifteen patients with TNBC were enrolled in the ongoing ARTEMIS (A Robust TNBC Evaluation Framework to Improve Survival) clinical trial. The patients were divided into a discovery cohort (n = 107) and a validation cohort (n = 108). A receiver operating characteristic analysis with 95% confidence intervals (CIs) and a multivariate logistic regression analysis were performed to model the probability of a pCR on the basis of the tumor volume reduction (TVR) percentage by US from the baseline to after 2 cycles of AC.

RESULTS

Overall, 39.3% of the patients (42 of 107) achieved a pCR. A positive predictive value (PPV) analysis identified a cutoff point of 80% TVR after 2 cycles; the pCR rate was 77% (17 of 22) in patients with a TVR ≥ 80%, and the area under the curve (AUC) was 0.84 (95% CI, 0.77-0.92; P < .0001). In the validation cohort, the pCR rate was 44%. The PPV for pCR with a TVR ≥ 80% after 2 cycles was 76% (95% CI, 55%-91%), and the AUC was 0.79 (95% CI, 0.70-0.87; P < .0001).

CONCLUSIONS

The TVR percentage by US evaluation after 2 cycles of NAST may be a cost-effective early imaging biomarker for a pCR to AC/taxane-based NAST.

Early response and pathological complete remission in Breast Cancer with different molecular subtypes: a retrospective single center analysis

Purpose: To evaluate the association of clinical early response and pathological complete remission (pCR) in breast cancer patients with different molecular subtypes.

Materials and methods: Breast cancer patients who received neoadjuvant treatment (NAT) with clinical early response assessment from October 2008 to October 2018 were retrospectively analyzed. Clinical early response was defined as tumor size decreasing ≥30% evaluated by ultrasound after two cycles of NAT. Chi-square test was used to compare the pCR rates between the responder and non-responder groups with different molecular subtypes. Multivariate logistic regression was used to identify independent factors associated with the pCR.

Results: A total of 328 patients were included: 100 responders and 228 non-responders. The progesterone receptor (PR) expression was an independent factor associated with clinical early response (OR=2.39, 95%CI=1.41-4.05, P=0.001). The pCR rate of breast was 50.0% for responders and 18.0% for non-responders (P<0.001). Regarding different molecular subtypes, responders had higher pCR rates than non-responders for patients with HER2 overexpression (OR=10.66, 95%CI=2.18-52.15, P=0.001), triple negative (OR=3.29, 95%CI=1.23-8.84, P=0.016) and Luminal (HER2-) subtypes (OR=8.58, 95%CI=3.05-24.10, P<0.001) respectively. Moreover, pCR rate can be achieved as high as 88.2% in HER2 overexpression patients with early clinical response, which was significantly higher than patients without early response (41.3%, P=0.001). Multivariate analysis showed that clinical early response was an independent factor associated with the pCR rate (OR=4.87, 95%CI=2.72-8.72, P<0.001).

Conclusions: Early response was significantly associated with a higher pCR rate in breast cancer patients receiving NAT, especially for patients with HER2 overexpression subtype, which warrants further clinical evaluation.

Magnetization Transfer MRI of Breast Cancer in the Community Setting: Reproducibility and Preliminary Results in Neoadjuvant Therapy

Repeatability and reproducibility of magnetization transfer magnetic resonance imaging of the breast, and the ability of this technique to assess the response of locally advanced breast cancer to neoadjuvant therapy (NAT), are determined. Reproducibility scans at 3 different 3 T scanners, including 2 scanners in community imaging centers, found a 16.3% difference (n = 3) in magnetization transfer ratio (MTR) in healthy breast fibroglandular tissue. Repeatability scans (n = 10) found a difference of ∼8.1% in the MTR measurement of fibroglandular tissue between the 2 measurements. Thus, MTR is repeatable and reproducible in the breast and can be integrated into community imaging clinics. Serial magnetization transfer magnetic resonance imaging performed at longitudinal time points during NAT indicated no significant change in average tumoral MTR during treatment. However, histogram analysis indicated an increase in the dispersion of MTR values of the tumor during NAT, as quantified by higher standard deviation (P = .005), higher full width at half maximum (P = .02), and lower kurtosis (P = .02). Patients' stratification into those with pathological complete response (pCR; n = 6) at the conclusion of NAT and those with residual disease (n = 9) showed wider distribution of tumor MTR values in patients who achieved pCR after 2-4 cycles of NAT, as quantified by higher standard deviation (P = .02), higher full width at half maximum (P = .03), and lower kurtosis (P = .03). Thus, MTR can be used as an imaging metric to assess response to breast NAT.

Exploring breast cancer response prediction to neoadjuvant systemic therapy using MRI-based radiomics: A systematic review

PURPOSE

MRI-based tumor response prediction to neoadjuvant systemic therapy (NST) in breast cancer patients is increasingly being studied using radiomics with outcomes that appear to be promising. The aim of this study is to systematically review the current literature and reflect on its quality.

METHODS

PubMed and EMBASE databases were systematically searched for studies investigating MRI-based radiomics for tumor response prediction. Abstracts were screened by two reviewers independently. The quality of the radiomics workflow of eligible studies was assessed using the Radiomics Quality Score (RQS). An overview of the methodologies used in steps of the radiomics workflow and current results are presented.

RESULTS

Sixteen studies were included with cohort sizes ranging from 35 to 414 patients. The RQS scores varied from 0 % to 41.2 %. Methodologies in the radiomics workflow varied greatly, especially region of interest segmentation, features selection, and model development with heterogeneous outcomes as a result. Seven studies applied univariate analysis and nine studies applied multivariate analysis. Most studies performed their analysis on the pretreatment dynamic contrast-enhanced T1-weighted sequence. Entropy was the best performing individual feature with AUC values ranging from 0.83 to 0.85. The best performing multivariate prediction model, based on logistic regression analysis, scored a validation AUC of 0.94.

CONCLUSION

This systematic review revealed large methodological heterogeneity for each step of the MRI-based radiomics workflow, consequently, the (overall promising) results are difficult to compare. Consensus for standardization of MRI-based radiomics workflow for tumor response prediction to NST in breast cancer patients is needed to further improve research.

Predicting the response to neoadjuvant therapy for early-stage breast cancer: tumor-, blood-, and imaging-related biomarkers

Neoadjuvant therapy (NAT) has been used increasingly in patients with locally advanced or early-stage breast cancer. However, the accurate evaluation and prediction of response to NAT remain the great challenge. Biomarkers could prove useful to identify responders or nonresponders, or even to distinguish between early and delayed responses. These biomarkers could include markers from the tumor itself, such as versatile proteins, genes, and ribonucleic acids, various biological factors or peripheral blood cells, and clinical and pathological features. Possible predictive markers could also include multiple features from functional imaging, such as standard uptake values in positron emission tomography, apparent diffusion coefficient in magnetic resonance, or radiomics imaging biomarkers. In addition, cells that indirectly present the immune status of tumor cells and/or their host could also potentially be used as biomarkers, eg, tumor-infiltrating lymphocytes, tumor-associated macrophages, and myeloid-derived suppressor cells. Though numerous biomarkers have been widely investigated, only estrogen and/or progesterone receptors and human epidermal growth factor receptor have been proven to be reliable biomarkers to predict the response to NAT. They are the only biomarkers recommended in several international guidelines. The other aforementioned biomarkers warrant further validation studies. Some multigene profiling assays that are commercially available, eg, Oncotype DX and MammaPrint, should be used with caution when extrapolated to NAT settings. A panel of combined multilevel biomarkers might be able to predict the response to NAT more robustly than individual biomarkers. To establish such a panel and its prediction model, reliable methods and extensive clinical validation are warranted.

Early Prediction of Response to Neoadjuvant Chemotherapy Using Dynamic Contrast-Enhanced MRI and Ultrasound in Breast Cancer

Objective

To determine the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and DCE ultrasound (DCE-US) for predicting response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

Materials and Methods

This Institutional Review Board-approved prospective study was performed between 2014 and 2016. Thirty-nine women with breast cancer underwent DCE-US and DCE-MRI before the NAC, follow-up DCE-US after the first cycle of NAC, and follow-up DCE-MRI after the second cycle of NAC. DCE-MRI parameters (transfer constant [K_trans], reverse constant [k_ep], and leakage space [V_e]) were assessed with histograms. From DCE-US, peak-enhancement, the area under the curve, wash-in rate, wash-out rate, time to peak, and rise time (RT) were obtained. After surgery, all the imaging parameters and their changes were compared with histopathologic response using the Miller-Payne Grading (MPG) system. Data from minor and good responders were compared using Wilcoxon rank sum test, chi-square test, or Fisher's exact test. Receiver operating characteristic curve analysis was used for assessing diagnostic performance to predict good response.

Results

Twelve patients (30.8%) showed a good response (MPG 4 or 5) and 27 (69.2%) showed a minor response (MPG 1–3). The mean, 25th, 50th, and 75th percentiles of K_trans and K_ep of post-NAC DCE-MRI differed between the two groups. These parameters showed fair to good diagnostic performance for the prediction of response to NAC (AUC 0.76–0.81, p ≤ 0.007). Among DCE-US parameters, the percentage change in RT showed fair prediction (AUC 0.71, p = 0.023).

Conclusion

Quantitative analysis of DCE-MRI and DCE-US was helpful for early prediction of response to NAC.

Comparing the Performances of Magnetic Resonance Imaging Size vs Pharmacokinetic Parameters to Predict Response to Neoadjuvant Chemotherapy and Survival in Patients With Breast Cancer

PURPOSE

To compare the value of dynamic contrast-enhanced magnetic resonance imaging-pharmacokinetic (PK) parameters vs tumor volume in predicting breast cancer neoadjuvant chemotherapy response (NACR) and patient survival.

SUBJECTS AND METHODS

Sixty-six patients with locally advanced breast cancer who underwent breast MRI monitoring of NACR were retrospectively analyzed. We compared baseline transfer constant (K^trans), reflux rate contrast (k_ep), and extracellular extravascular volume fraction (v_e) with the same parameters obtained at early postchemotherapy MRI, and examined model-independent changes in time-intensity curves (maximum slope, contrast enhancement ratio, and IAUC90). Tumor size changes (tumor volume, single dimension, and Response Evaluation Criteria in Solid Tumors [RECIST]) were also analyzed. The Spearman correlation test was used to assess the association between size and PK parameters, and regression analysis to assess the association with 5-year disease-free survival.

RESULTS

Higher v_e values at baseline were associated with greater decreases in tumor size (P = 0.008). Changes in K^trans and IAUC90 were the strongest predictors of NACR. Changes in IAUC90 (P = 0.04) and RECIST (P = 0.003) were independently associated with pathologic response. The only parameter significantly associated with 5-year survival was change in RECIST (P = 0.001). However, there was a trend toward statistical significance for changes in v_e and K^trans, with greater changes associated with longer survival.

CONCLUSION

Changes in PK and dynamic contrast-enhanced magnetic resonance imaging kinetic parameters may have a role in predicting NACR in breast tumors. Although changes in K^trans and IAUC90 are helpful in predicting NACR, they do not show significant association with survival. Early RECIST size change measured by MRI remains the strongest predictor of overall patient survival.

Features from Computerized Texture Analysis of Breast Cancers at Pretreatment MR Imaging Are Associated with Response to Neoadjuvant Chemotherapy

Purpose To evaluate whether features from texture analysis of breast cancers were associated with pathologic complete response (pCR) after neoadjuvant chemotherapy and to explore the association between texture features and tumor subtypes at pretreatment magnetic resonance (MR) imaging. Materials and Methods Institutional review board approval was obtained. This retrospective study included 85 patients with 85 breast cancers who underwent breast MR imaging before neoadjuvant chemotherapy between April 10, 2008, and March 12, 2015. Two-dimensional texture analysis was performed by using software at T2-weighted MR imaging and contrast material-enhanced T1-weighted MR imaging. Quantitative parameters were compared between patients with pCR and those with non-pCR and between patients with triple-negative breast cancer and those with non-triple-negative cancer. Multiple logistic regression analysis was used to determine independent parameters. Results Eighteen tumors (22%) were triple-negative breast cancers. pCR was achieved in 30 of the 85 tumors (35%). At univariate analysis, mean pixel intensity with spatial scaling factor (SSF) of 2 and 4 on T2-weighted images and kurtosis on contrast-enhanced T1-weighted images showed a significant difference between triple-negative breast cancer and non-triple-negative breast cancer (P = .009, .003, and .001, respectively). Kurtosis (SSF, 2) on T2-weighted images showed a significant difference between pCR and non-pCR (P = .015). At multiple logistic regression, kurtosis on T2-weighted images was independently associated with pCR in non-triple-negative breast cancer (P = .033). A multivariate model incorporating T2-weighted and contrast-enhanced T1-weighted kurtosis showed good performance for the identification of triple-negative breast cancer (area under the receiver operating characteristic curve, 0.834). Conclusion At pretreatment MR imaging, kurtosis appears to be associated with pCR to neoadjuvant chemotherapy in non-triple-negative breast cancer and may be a promising biomarker for the identification of triple-negative breast cancer. ^© RSNA, 2017.

Serum N-glycome alterations in breast cancer during multimodal treatment and follow-up

Using our recently developed high-throughput automated platform, N-glycans from all serum glycoproteins from patients with breast cancer were analysed at diagnosis, after neoadjuvant chemotherapy, surgery, radiotherapy and up to 3 years after surgery. Surprisingly, alterations in the serum N-glycome after chemotherapy were pro-inflammatory with an increase in glycan structures associated with cancer. Surgery, on the other hand, induced anti-inflammatory changes in the serum N-glycome, towards a noncancerous phenotype. At the time of first follow-up, glycosylation in patients with affected lymph nodes changed towards a malignant phenotype. C-reactive protein showed a different pattern, increasing after first line of neoadjuvant chemotherapy, then decreasing throughout treatment until 1 year after surgery. This may reflect a switch from acute to chronic inflammation, where chronic inflammation is reflected in the serum after the acute phase response subsides. In conclusion, we here present the first time-course serum N-glycome profiling of patients with breast cancer during and after treatment. We identify significant glycosylation changes with chemotherapy, surgery and follow-up, reflecting the host response to therapy and tumour removal.

Neoadjuvant chemotherapy with MRI monitoring for breast cancer

BACKGROUND

Neoadjuvant chemotherapy (NACT) is increasingly being offered to patients with breast cancer. No survival benefit has been demonstrated for NACT, but it may serve to reduce tumour size and improve prognosis through the attainment of a pathological complete response (pCR). The role and mode of MRI monitoring during NACT remain unclear.

METHODS

Patients managed with NACT at a UK centre over 7 years were studied using a prospectively maintained database, which also included details of MRI. Clinicopathological and radiological predictors of NACT response were analysed in a univariable setting and survival analysis was undertaken using the Kaplan-Meier method.

RESULTS

A total of 278 patients underwent surgery following NACT, of whom 200 (71·9 per cent) had residual invasive disease and 78 (28·1 per cent) achieved a pCR. Attaining a pCR improved survival significantly compared with that of patients with residual invasive disease (mean 77·1 versus 66·0 months; P = 0·004) and resulted in significantly fewer recurrences (6·0 versus 24·3 per cent; P = 0·001). The pCR rate varied significantly among molecular subgroups of breast cancer (P < 0·001): luminal A, 6 per cent; luminal B/human epidermal growth factor 2 receptor (Her2)-negative, 21 per cent; luminal B/Her2-positive, 35 per cent, Her2-positive/non-luminal, 72 per cent; and triple-negative breast cancer (TNBC), 32 per cent. High-grade disease (G3) correlated with an increased rate of pCR. A radiological response seen on the mid-treatment MRI was predictive of pCR (sensitivity 77·6 per cent, but specificity only 53·3 per cent), as was complete radiological response at final MRI (specificity 97·6 per cent, but sensitivity only 32·2 per cent).

CONCLUSION

NACT allows identification of patient subgroups within TNBC and Her2-positive cohorts with a good prognosis. MRI can be used to identify patients who are responding to treatment.

Monitoring Neoadjuvant Chemotherapy for Breast Cancer by Using Three-dimensional Subharmonic Aided Pressure Estimation and Imaging with US Contrast Agents: Preliminary Experience

Purpose To determine whether three-dimensional subharmonic aided pressure estimation (SHAPE) and subharmonic imaging can help predict the response of breast cancer to neoadjuvant chemotherapy. Materials and Methods In this HIPAA-compliant prospective study, 17 women (age range, 45-70 years) scheduled to undergo neoadjuvant therapy for breast cancer underwent ultrasonography (US) immediately before therapy and at completion of 10%, 60%, and 100% of chemotherapy. All patients provided written informed consent. At each examination, radiofrequency data were collected from SHAPE and subharmonic imaging during infusion of a US contrast agent. Maximum-frequency magnitude and mean intensity were calculated for SHAPE and subharmonic imaging. The signal differences in the tumor relative to the surrounding area were compared with the final treatment response by using the Student t test. Results Four patients left the study, and data from two patients were discarded because of technical problems. Eight patients completed the entire imaging protocol, and an additional three patients dropped out after the imaging session at completion of 10% of chemotherapy as a result of disease progression (these patients were counted as nonresponders). Patients' imaging outcomes consisted of six responders (tumor volume reduction >90%) and five partial responders or nonresponders. The results at completion of 10% of therapy showed that the subharmonic signal increased more in the tumor than in the surrounding area for responders than in partial responders or nonresponders (mean ± standard deviation, 3.23 dB ± 1.41 vs -0.88 dB ± 1.46 [P = .001], respectively, for SHAPE and 1.32 dB ± 0.73 vs -0.82 dB ± 0.88 [P = .002], respectively, for subharmonic imaging). Moreover, three patients whose tumor measurements initially increased were correctly predicted to be responders with SHAPE and subharmonic imaging after completion of 10% of therapy. Conclusion SHAPE and subharmonic imaging have the potential to help predict response to neoadjuvant chemotherapy for breast cancer as early as completion of 10% of therapy, albeit on the basis of a small sample size. ^© RSNA, 2017 Online supplemental material is available for this article.

Accuracy of Contrast-Enhanced Ultrasound Compared With Magnetic Resonance Imaging in Assessing the Tumor Response After Neoadjuvant Chemotherapy for Breast Cancer

OBJECTIVES

This pilot study compared contrast enhanced ultrasound (US) with contrast-enhanced magnetic resonance imaging (MRI) in assessing the treatment response in patients with breast cancer receiving preoperative neoadjuvant chemotherapy (NAC).

METHODS

This prospective Institutional Review Board-approved and Health Insurance Portability and Accountability Act-compliant study included 30 patients, from January 2014 to October 2015, with invasive breast cancer detected by mammography, conventional US imaging, or both and scheduled for NAC. Informed consent was obtained. Contrast-enhanced US (perflutren lipid microspheres, 10 μL/kg) and MRI (gadopentetate dimeglumine, 0.1 mmol/kg) scans were performed at baseline before starting NAC and after completing NAC before surgery. Results of the imaging techniques were compared with each other and with histopathologic findings obtained at surgery using the Spearman correlation. Tumor size and enhancement parameters were compared for 15 patients with contrast-enhanced US, MRI, and surgical pathologic findings.

RESULTS

The median tumor size at baseline was 3.1 cm on both contrast-enhanced US and MRI scans. The Spearman correlation showed strong agreement in tumor size at baseline between contrast-enhanced US and MRI (r = 0.88; P < .001) but less agreement in tumor size after NAC (r = 0.66; P = .004). Trends suggested that contrast-enhanced US (r = 0.75; P < .001) had a better correlation than MRI (r = 0.42; P = .095) with tumor size at surgery. Contrast-enhanced US was as effective as MRI in predicting a complete pathologic response (4 patients; 75.0% accuracy for both) and a non-complete pathologic response (11 patients; 72.7% accuracy for both).

CONCLUSIONS

Contrast enhanced US is a valuable imaging modality for assessing the treatment response in patients receiving NAC and had a comparable correlation as MRI with breast cancer size at surgery.

Contrast-enhanced ultrasound (CEUS) in assessing early response among patients with invasive breast cancer undergoing neoadjuvant chemotherapy

Background One of the big challenges in onco-radiology is to find a reliable imaging method that may predict early response during the first cycles of any neoadjuvant chemotherapy. Purpose To evaluate the use of real-time harmonic contrast-enhanced ultrasound (CEUS) in predicting early response in breast cancer tumors under neoadjuvant chemotherapy (NAC) treatment. Material and Methods Nineteen consecutive patients with invasive breast cancer were evaluated with a bolus dose of 2.4 mL contrast agent using CEUS, before and after two cycles of epirubicin and docetaxel. The lognormal function was used for quantitative analysis of kinetic data to evaluate early response. Results There was statistically significant difference in time-to-peak ( t_p) between responders and non-responders (two sample t-test, P = 0.027) where t_p was significantly longer at the week 5 than at the baseline scan among responders when compared to non-responders. Conclusion In-flow of intravascular contrast agent in tumors is significantly slower in responders at real-time harmonic CEUS, and might be effectively used for the evaluation of early response to chemotherapy in invasive breast cancer. However, further investigations in a larger and more heterogeneous population should be performed to corroborate the reliability of the method.

Effect of Radiofrequency Transmit Field Correction on Quantitative Dynamic Contrast-enhanced MR Imaging of the Breast at 3.0 T

PURPOSE

To investigate the effects of radiofrequency transmit field (B1(+)) correction on (a) the measured T1 relaxation times of normal breast tissue and malignant lesions and (b) the pharmacokinetically derived parameters of malignant breast lesions at 3 T.

MATERIALS AND METHODS

Ethics approval and informed consent were obtained. Between May 2013 and January 2014, 30 women (median age, 58 years; range, 32-83 years) with invasive ductal carcinoma of at least 10 mm were recruited to undergo dynamic contrast material-enhanced magnetic resonance (MR) imaging before surgery. B1(+) and T1 mapping sequences were performed to determine the effect of B1(+) correction on the native tissue relaxation time (T10) of fat, parenchyma, and malignant lesions in both breasts. Pharmacokinetic parameters were calculated before and after correction for B1(+) variations. Results were correlated with histologic grade by using the Kruskal-Wallis test.

RESULTS

Measurements showed a mean 37% flip angle difference between the right and left breast, which resulted in a 61% T10 difference in fat and a 41.5% difference in parenchyma between the two breasts. The T1 of lesions in the right breast increased by 58%, whereas that of lesions in the left breast decreased by 30% after B1(+) correction. The whole-tumor transendothelial permeability across the vascular compartment(K(trans)) of lesions in the right breast decreased by 41%, and that of lesions in the left breast increased by 46% after correction. A systematic increase in K(trans) was observed, with significant differences found across the histologic grades (P < .001). The effect size of B1(+) correction on K(trans) calculation was large for lesions in the right breast and moderate for lesions in the left breast (Cohen effect size, d = 0.86 and d = 0.59, respectively).

CONCLUSION

B1(+) correction demonstrates a substantial effect on the results of quantitative dynamic contrast-enhanced analysis of breast tissue at 3 T, which propagates into the pharmacokinetic analysis of tumors that is dependent on whether the tumor is located in the right or left breast.

Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy

PURPOSE

To predict pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

In this Institutional Review Board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using 3T DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with high temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitative Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC.

RESULTS

Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast washout were statistically significant (P < 0.05) after correcting for multiple testing, with area under the receiver operating characteristic (ROC) curve (AUC) or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (P = 0.002) in leave-one-out cross-validation. This improved upon conventional imaging predictors such as tumor volume (AUC = 0.53) and texture features based on whole-tumor analysis (AUC = 0.65).

CONCLUSION

The heterogeneity of the tumor subregion associated with fast washout on DCE-MRI predicted pathological response to NAC in breast cancer. J. Magn. Reson. Imaging 2016;44:1107-1115.

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors

PURPOSE

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis.

MATERIALS AND METHODS

This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression.

RESULTS

The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression.

CONCLUSION

Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients.

KEY POINTS

• Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.

Tumor RNA disruption predicts survival benefit from breast cancer chemotherapy

In a prior substudy of the CAN-NCIC-MA.22 clinical trial (ClinicalTrials.gov identifier NCT00066443), we observed that neoadjuvant chemotherapy reduced tumor RNA integrity in breast cancer patients, a phenomenon we term "RNA disruption." The purpose of the current study was to assess in the full patient cohort the relationship between mid-treatment tumor RNA disruption and both pCR post-treatment and, subsequently, disease-free survival (DFS) up to 108 months post-treatment. To meet these objectives, we developed the RNA disruption assay (RDA) to quantify RNA disruption and stratify it into 3 response zones of clinical importance. Zone 1 is a level of RNA disruption inadequate for pathologic complete response (pCR); Zone 2 is an intermediate level, while Zone 3 has high RNA disruption. The same RNA disruption cut points developed for pCR response were then utilized for DFS. Tumor RDA identified >fourfold more chemotherapy non-responders than did clinical response by calipers. pCR responders were clustered in RDA Zone 3, irrespective of tumor subtype. DFS was about 2-fold greater for patients with tumors in Zone 3 compared to Zone 1 patients. Kaplan-Meier survival curves corroborated these findings that high tumor RNA disruption was associated with increased DFS. DFS values for patients in zone 3 that did not achieve a pCR were similar to that of pCR recipients across tumor subtypes, including patients with hormone receptor positive tumors that seldom achieve a pCR. RDA appears superior to pCR as a chemotherapy response biomarker, supporting the prospect of its use in response-guided chemotherapy.

Combined reading of Contrast Enhanced and Diffusion Weighted Magnetic Resonance Imaging by using a simple sum score

OBJECTIVE

To improve specificity of breast MRI by integrating Apparent Diffusion Coefficient (ADC) values with contrast enhanced MRI (CE-MRI) using a simple sum score.

METHODS

Retrospective analysis of a consecutive series of patients referred to breast MRI at 1.5 T for further workup of breast lesions. Reading results of CE-MRI were dichotomized into score 1 (suspicious) or 0 (benign). Lesion's ADC-values (in *10-3 mm2/s) were assigned two different scores: ADC2: likely malignant (score +1, ADC ≤ 1), indeterminate (score 0, ADC >1- ≤ 1.4) and likely benign (score -1, ADC > 1.4) and ADC1: indeterminate (score 0, ADC ≤ 1.4) and likely benign (score -1, ADC > 1.4). Final added CE-MRI and ADC scores >0 were considered suspicious. Reference standard was histology and imaging follow-up of >24 months. Diagnostic parameters were compared using McNemar tests.

RESULTS

A total of 150 lesions (73 malignant) were investigated. Reading of CE-MRI showed a sensitivity of 100 % (73/73) and a specificity of 81.8 % (63/77). Additional integration of ADC scores increased specificity (ADC2/ADC1, P = 0.008/0.001) without causing false negative results.

CONCLUSION

Using a simple sum score, ADC-values can be integrated with CE-MRI of the breast, improving specificity. The best approach is using one threshold to exclude cancer.

KEY POINTS

ADC is used to assign levels of suspicion to breast lesions. ADC values >1.4 *10 (-3)   mm (2) /s are likely benign and effectively rule out malignancy. ADC values below ≤1*10 (-3)   mm (2) /s) are likely malignant but may be false positive. CE-MRI (+1: suspicious, 0: benign) and ADC (0: indeterminate, -1: benign) scores are added. Sum scores >0 should be biopsied.

Utilisation of MR spectroscopy and diffusion weighted imaging in predicting and monitoring of breast cancer response to chemotherapy

Neoadjuvant chemotherapy (NACT) is the standard treatment option for breast cancer as more data shows that pathologic complete response (pCR) after NACT correlates with improved prognosis. MRI is accepted as the best imaging modality for evaluating the response to NACT in many studies as compared with clinical examination and other imaging modalities. In vivo magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) studies have both emerged as potential tools to provide early response indicators based on the changes in the metabolites and the apparent diffusion coefficient (ADC) respectively. In this review article, we aim to discuss the strength and limitations of MRS and DWI in monitoring of early response breast cancer to NACT.

Evaluation of the treatment response to neoadjuvant chemotherapy in locally advanced breast cancer using combined magnetic resonance vascular maps and apparent diffusion coefficient

PURPOSE

To evaluate the treatment response of locally advanced breast cancer (LABC) to neoadjuvant chemotherapy using magnetic resonance (MR) vascular maps and apparent diffusion coefficient (ADC) at 3T. Materials and Methods Thirty-one patients with LABC who underwent breast MR studies before, after the first course, and after completing neoadjuvant chemotherapy were enrolled. Vascular morphology was retrieved via Hessian matrix and the voxels of the vessels and volume of vessels were measured automatically. Whole tumor mean ADC values were calculated. Clinical responders were defined as >50% tumor reduction in the final MR studies. Pathologically complete responders were also recorded.

RESULTS

There were 21 clinical responders and 10 nonresponders. Compared to the nonresponders after the first course, the responders were characterized by more vascular reduction of the breast lesion and decreased bilateral vascular discrepancy (voxels and volume), and increments in the ADC value and ADC percentage of the lesions (all P < 0.05). There were three pathological complete responders who showed more apparent early vascular reduction of the lesion breast (voxels and volume) and increments in the ADC value than others (P = 0.02, 0.01 and 0.02, respectively).

CONCLUSION

The early changes of MR vascular maps and ADC are associated with the final treatment response of LABC.

Role of the Apparent Diffusion Coefficient in the Prediction of Response to Neoadjuvant Chemotherapy in Patients With Locally Advanced Breast Cancer

BACKGROUND

We evaluated the diagnostic performance of the baseline diffusion weighted imaging (DWI) and the apparent diffusion coefficient (ADC) in the prediction of a complete pathologic response (pCR) to neoadjuvant chemotherapy (NAC) in patients with breast cancer stratified according to the tumor phenotype.

PATIENTS AND METHODS

We retrospectively studied 225 patients with stage II, III, and IV breast cancer who had undergone contrast-enhanced magnetic resonance imaging (MRI) and DWI before and after NAC, followed by breast surgery.

RESULTS

The tumor phenotypes were luminal (n = 143; 63.6%), triple-negative (TN) (n = 37; 16.4%), human epidermal growth factor receptor 2 (HER2)-enriched (n = 17; 7.6%), and hybrid (hormone receptor-positive/HER2(+); n = 28; 12.4%). After NAC, a pCR was observed in 39 patients (17.3%). No statistically significant difference was observed in the mean ADC value between a pCR and no pCR in the general population (1.132 ± 0.191 × 10(-3) mm(2)/s vs. 1.092 ± 0.189 × 10(-3) mm(2)/s, respectively; P = .23). The optimal ADC cutoff value in the general population was 0.975 × 10(-3) mm(2)/s (receiver operating characteristic [ROC] area under the curve [AUC], 0.587 for the prediction of a pCR). After splitting the population into subgroups according to tumor phenotype, we observed a significant or nearly significant difference in the mean ADC value among the responders versus the nonresponders in the TN (P = .06) and HER2(+) subgroups (P = .05). No meaningful difference was seen in the luminal and hybrid subgroups (P = .59 and P = .53, respectively). In contrast, in the TN and HER2(+) subgroups (cutoff value, 0.995 × 10(-3) mm(2)/s and 0.971 × 10(-3) mm(2)/s, respectively), we observed adequate ROC AUCs (0.766 and 0.813, respectively).

CONCLUSION

The pretreatment ADC value is not capable of predicting the pCR in the overall population of patients with locally advanced breast cancer. Nonetheless, an ameliorated diagnostic performance was observed in specific phenotype subgroups (ie, TN and HER2(+) tumors).

Contrast-enhanced dual-energy mammography: a promising new imaging tool in breast cancer detection

Contrast-enhanced dual-energy mammography (CEDM) is a promising new breast imaging tool for breast cancer detection. In CEDM, an iodine-based contrast agent is intravenously administered and subsequently, dual-energy mammography is performed. This results in a set of images containing both a regular mammogram and an image that contains contrast enhancement information. Preliminary studies have indicated that CEDM is superior to conventional mammography and might even match the diagnostic performance of breast MRI. In this review, the imaging technique, protocol and patient handling of CEDM is presented. Furthermore, an overview of current results on CEDM and potential future indications are outlined.

[Therapy monitoring of neoadjuvant therapy with MRI. RECIST and functional imaging]

CLINICAL/METHODICAL ISSUE

Neoadjuvant chemotherapy is increasingly being applied in patients with operable breast cancer. Thus, an early prediction of response to neoadjuvant chemotherapy is of high relevance.

STANDARD RADIOLOGICAL METHODS

The interobserver variability of clinical examination, mammography and ultrasonography in the assessment of response to neoadjuvant chemotherapy is high.

METHODICAL INNOVATIONS

Magnetic resonance imaging (MRI) allows the assessment of functional parameters in addition to changes in tumor size and morphology.

PERFORMANCE

A reliable therapy response monitoring aims at optimizing individualized patient care.

ACHIEVEMENTS

This paper summarizes current guidelines for the assessment of response to neoadjuvant chemotherapy in breast cancer according to the response evaluation criteria in solid tumors (RECIST). Furthermore, the technical principles of MRI-based therapy monitoring are described and an overview of the clinical studies that have assessed the feasibility of functional MRI in response to treatment evaluation is given.

PRACTICAL RECOMMENDATIONS

The technology of functional MRI offers promising results concerning therapy response monitoring. However, the level of evidence is not sufficiently evaluated for the technologies of functional MRI presented here.

99mTc-sestamibi using a direct conversion molecular breast imaging system to assess tumor response to neoadjuvant chemotherapy in women with locally advanced breast cancer

PURPOSE

The objective of this study was to determine the ability of breast imaging with 99mTc-sestamibi and a direct conversion-molecular breast imaging (MBI) system to predict early response to neoadjuvant chemotherapy (NAC).

METHODS

Patients undergoing NAC for breast cancer were imaged with a direct conversion-MBI system before (baseline), at 3 to 5 weeks after onset, and after completion of NAC. Tumor size and tumor-to-background (T/B) uptake ratio measured from MBI images were compared with extent of residual disease at surgery using the residual cancer burden.

RESULTS

Nineteen patients completed imaging and proceeded to surgical resection after NAC. Mean reduction in T/B ratio from baseline to 3 to 5 weeks for patients classified as RCB-0 (no residual disease), RCB-1 and RCB-2 combined, and RCB-3 (extensive residual disease) was 56% (SD, 0.20), 28% (SD, 0.20), and 4% (SD, 0.15), respectively. The reduction in the RCB-0 group was significantly greater than in RCB-1/2 (P = 0.036) and RCB-3 (P = 0.001) groups. The area under the receiver operator characteristic curve for determining the presence or absence of residual disease was 0.88. Using a threshold of 50% reduction in T/B ratio at 3 to 5 weeks, MBI predicted presence of residual disease at surgery with a diagnostic accuracy of 89.5% (95% confidence interval [CI], 0.64%-0.99%), sensitivity of 92.3% (95% CI, 0.74%-0.99%), and specificity of 83.3% (95% CI, 0.44%-0.99%). The reduction in tumor size at 3 to 5 weeks was not statistically different between RCB groups.

CONCLUSIONS

Changes in T/B ratio on MBI images performed at 3 to 5 weeks following initiation of NAC were accurate at predicting the presence or absence of residual disease at NAC completion.

Magnetic resonance metabolic profiling of breast cancer tissue obtained with core needle biopsy for predicting pathologic response to neoadjuvant chemotherapy

The purpose of this study was to determine whether metabolic profiling of core needle biopsy (CNB) samples using high-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) could be used for predicting pathologic response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer. After institutional review board approval and informed consent were obtained, CNB tissue samples were collected from 37 malignant lesions in 37 patients before NAC treatment. The metabolic profiling of CNB samples were performed by HR-MAS MRS. Metabolic profiles were compared according to pathologic response to NAC using the Mann-Whitney test. Multivariate analysis was performed with orthogonal projections to latent structure-discriminant analysis (OPLS-DA). Various metabolites including choline-containing compounds were identified and quantified by HR-MAS MRS in all 37 breast cancer tissue samples obtained by CNB. In univariate analysis, the metabolite concentrations and metabolic ratios of CNB samples obtained with HR-MAS MRS were not significantly different between different pathologic response groups. However, there was a trend of lower levels of phosphocholine/creatine ratio and choline-containing metabolite concentrations in the pathologic complete response group compared to the non-pathologic complete response group. In multivariate analysis, the OPLS-DA models built with HR-MAS MR metabolic profiles showed visible discrimination between the pathologic response groups. This study showed OPLS-DA multivariate analysis using metabolic profiles of pretreatment CNB samples assessed by HR- MAS MRS may be used to predict pathologic response before NAC, although we did not identify the metabolite showing statistical significance in univariate analysis. Therefore, our preliminary results raise the necessity of further study on HR-MAS MR metabolic profiling of CNB samples for a large number of cancers.

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.

Diffusion-weighted MRI in pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer

PURPOSE

To evaluate the accuracy of the apparent diffusion coefficient (ADC) provided by diffusion-weighted imaging (DWI) in predicting the response to neoadjuvant chemotherapy (NACT) at baseline in patients according to their breast tumour phenotypes.

MATERIALS & METHODS

This retrospective study was approved by our institutional review board. One hundred eighteen consecutive women with locally advanced breast cancer who had undergone NACT followed by breast surgery were included. DWI was performed at 1.5 T less than 2 weeks before NACT. We studied the correlation between pretreatment ADC and response in pathology after surgery according to immunohistochemical features and intrinsic subtypes (luminal A, luminal B, HER2-enriched, and triple-negative tumours).

RESULTS

After surgery, the pathologist recognized 24 complete responders (CRps) and 94 non-complete responders (NCRps). No difference was identified between the pretreatment ADCs of the CRp and NCRp patients. There were differences in pretreatment ADCs among the luminal A (1.001 ± 0.143 × 10(-3) mm(2)/s), luminal B (0.983 ± 0.150 × 10(-3) mm(2)/s), HER2-enriched (1.132 ± 0.216 × 10(-3) mm(2)/s), and triple-negative (1.168 ± 0.245 × 10(-3) mm(2)/s; P = 0.0003) tumour subtypes. In triple-negative tumours, the pretreatment ADC was higher in NCRp (1.060 ± 0.143 × 10(-3) mm(2)/s) than in CRp patients (1.227 ± 0.271 × 10(-3) mm(2)/s; P = 0.047).

CONCLUSION

Pretreatment ADC can predict the response of breast cancer to NACT if tumour subtypes are considered. Key Points • Apparent diffusion coefficient helps clinicians to assess patients with breast cancer. • Pretreatment ADC is related to tumour grade and hormone receptor status. • Pretreatment ADC is lower in luminal A and B than in triple-negative tumours. • Pretreatment ADC is higher in complete than in non-complete responders to neoadjuvant chemotherapy.