Pathological Response Of Breast Cancer Research Articles

Assessment of pathological response of breast cancer in patients undergoing neoadjuvant chemotherapy in a refferal hospital in Amazonas State

Introduction: The therapeutic options for breast cancer are diverse. Increasingly, treatments are established on an individual basis, depending on a series of variables ranging from age to the molecular profile of the tumor. When neoadjuvant chemotherapy (NAC) is necessary, adequate clinical evaluation (CE) and control examinations, such as breast ultrasound (US) and mammography (MMG), are of fundamental importance, as it is necessary to reevaluate the tumor lesion to determine an individualized surgical treatment, with the aim of performing breast-conserving surgery within the available techniques. This study sought to evaluate the pathological response of patients undergoing neoadjuvant chemotherapy, analyzing the presence or absence of tumor reduction by relating the physical examination with imaging methods (MMG and US), taking the anatomopathological examination measurements as the gold standard, thus intending to identify the best method for evaluating the pathological response. Methods: This was a prospective, observational, analytical cohort study. The study included 41 patients diagnosed with breast cancer detected by mammography and ultrasound (MMG and US) followed by biopsy, who underwent neoadjuvant chemotherapy (NAC) and surgery. The measurements of the malignant breast lesions obtained by CE, MMG and US were compared with the anatomopathological measurements on biopsy as the gold standard. Results: Pearson's correlation coefficient was the statistical method used for evaluation, finding a value of 0.49 between the anatomopathological examination and CE, 0.47 between the anatomopathological examination and MMG and 0.48 between the anatomopathological examination and US (p<0.05). Conclusions: CE, MMG and US showed a moderate correlation with anatomopathological measurement, in addition to a moderate correlation between them, demonstrating equivalence in the pre-surgical definition of the size of the breast tumor after NAC, being complementary to each other to define a measure of greater accuracy of the tumor in breast cancer.

The potential role of combined shear wave elastography and superb microvascular imaging for early prediction the pathological response to neoadjuvant chemotherapy in breast cancer.

The potential role of shear wave elastography (SWE) and superb microvascular imaging (SMI) for early assessment of treatment response to neoadjuvant chemotherapy (NAC) in breast cancer remains unexplored. This study aimed to identify potential factors associated with the pathological response to NAC using these advanced ultrasound techniques. Between August 2021 and October 2022, 68 patients with breast cancer undergoing NAC were recruited. Patients underwent conventional ultrasonography, SMI, and SWE examinations at baseline and post-2nd cycle of NAC. Maximum tumor diameter (Dmax), maximum elastic value (Emax), peak systolic velocity (PSV), and resistance index (RI) at baseline and the rate of change of these parameters post-2nd cycle were recorded. After chemotherapy, all patients underwent surgery. Using the Miller-Payne's grade, patients were categorized into response (grades 3, 4, or 5) and non-response (grades 1 or 2) group. Parameters were compared using t-tests at baseline and post-2nd cycle. Binary logistic regression analysis was used to identify variables and their odds ratios (ORs) related to responses and a prediction model was established. ROC curves were drawn to analyze the efficacy of each parameter and their combined model for early NAC response prediction. Among the 68 patients, 15(22.06%) were categorized into the non-response group, whereas 53(77.94%) were categorized into the response group. At baseline, no significant differences were observed between the two groups (p>0.05). Post-2nd cycle of NAC, rates of change of Emax, PSV and RI (ΔEmax, ΔPSV and ΔRI) were higher in responders than non-responders (p<0.05). Binary logistic regression analysis revealed that ΔEmax (OR 0.797 95% CI, 0.683-0.929), ΔPSV (OR 0.926, 95%CI, 0.860-0.998), and ΔRI (OR 0.841, 95%CI, 0.736-0.960) were independently associated with the pathological response of breast cancer after NAC. The combined prediction model exhibited higher accuracy in the early evaluation of the response to NAC (AUC 0.945, 95%CI, 0.873-1.000). SWE and SMI techniques enable early identification of tumor characteristics associated with the pathological response to NAC and may be potentially indicative of an effective response. These factors may eventually be used for the early assessment of NAC treatment for clinical management.

Comparative study of pathological response evaluation systems after neoadjuvant chemotherapy for breast cancer: developing predictive models of multimodal ultrasound features including shear wave elastography combined with puncture pathology.

This study created a predictive preoperative nomogram dependent on multimodal ultrasound characteristics and primary lesion biopsy results for various pathologic response assessment systems following neoadjuvant chemotherapy (NAC). This retrospective study included 145 breast cancer patients treated at Gansu Cancer Hospital between January 2021 and June 2022 who underwent shear wave elastography (SWE) prior to completing NAC. Intra- and peritumoral SWE features, including maximum (Emax), mean (Emean), minimum (Emin), and standard deviation (Esd) elasticity, were measured individually and linked with the Miller-Payne grading system and residual cancer burden (RCB) class. Univariate analysis was used for conventional ultrasound and puncture pathology. Binary logistic regression analysis was used to screen for independent risk factors and to develop a prediction model. Intratumor Emean and peritumoral Esd differed significantly from the Miller-Payne grade [intratumor Emean: r=0.129, 95% confidence interval (CI): -0.002 to 0.260; P=0.042; peritumoral Esd: r=0.126, 95% CI: -0.010 to 0.254; P=0.047], RCB class (intratumor Emean: r=-0.184, 95% CI: -0.318 to -0.047; P=0.004; peritumoral Esd: r=-0.139, 95% CI: -0.265 to 0.000; P=0.029) and RCB score components (r=-0.277 to -0.139; P=0.001-0.041). Two prediction model nomograms-pathologic complete response (pCR)/non-pCR and good responder/nonresponder-for the RCB class were developed using binary logistic regression analysis for all significant variables in SWE, conventional ultrasound, and puncture results. The area under the receiver operating characteristic curve for the pCR/non-pCR and good responder/nonresponder models was 0.855 (95% CI: 0.787-0.922) and 0.845 (95% CI: 0.780-0.910), respectively. According to the calibration curve, the nomogram had excellent internal consistency between estimated and actual values. The preoperative nomogram can effectively guide clinicians to predict pathological response of breast cancer after NAC and has the potential to guide individualized treatment.

Assessment of Cone-Beam Breast Computed Tomography for Predicting Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Prospective Study.

Background Response surveillance of neoadjuvant chemotherapy is needed to facilitate treatment decisions. We aimed to assess the imaging features of cone-beam breast computed tomography (CBBCT) for predicting the pathologic response of breast cancer after neoadjuvant chemotherapy. Methods This prospective study included 81 women with locally advanced breast cancer who underwent neoadjuvant chemotherapy from August 2017 to January 2021. All patients underwent CBBCT before treatment, and 55 and 65 patients underwent CT examinations during the midtreatment (3 cycles) and late-treatment phases (7 cycles), respectively. Clinical information and quantitative parameters such as the diameter, volume, surface area, and CT density were compared between pathologic responders and nonresponders using the T–test and the Mann–Whitney U test. The performance of meaningful parameters was evaluated with the receiver operating characteristic curve, sensitivity, and specificity. Results The quantitative results for the segmented volume, segmented surface area, segmented volume reduction, maximum enhancement ratio, wash-in rate and two-minute enhancement value in the mid- and late-treatment periods had predictive value for pathologic complete response. The area under the curve for the prediction model after multivariate regression analysis was 0.874. Conclusion After comparing the outcomes of each timepoint, mid- and late-treatment parameters can be used to predict pathologic outcome. The late-treatment parameters showed significant value with a predictive model.

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

PurposeTo 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). MethodsWe 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. ResultsA 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. ConclusionsDWI 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.

Pathological Complete Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer: The Relationship Between Inflammatory Biomarkers and Molecular Subtypes.

PurposeAmong patients with breast cancer, pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) is an important prognostic predictor of survival. This study aimed to investigate the relationship between platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) along with overall pCR.MethodA total of 150 patients with breast cancer who were first administered NAC and then operated on were retrospectively evaluated. Neutrophil-lymphocyte ratio and PLR obtained from the complete blood count analysis performed immediately before NAC treatment were analyzed. The cut-off value was calculated as 150 for PLR and 2.24 for NLR. We studied the predictive value of NLR and PLR levels for the pathologic response of breast cancer to NAC.ResultsPathological complete response was observed in 34.7% (n = 52) of the patients, pCR in the breast in 42.7% (n = 64), and that in the axilla in 44% (n = 66). There was a statistically significant difference between the pCR rates according to the PLR levels (p = 0.013). In addition, a statistically significant difference was found in the pCR rates in the breast and axilla according to PLR levels (p = 0.018, p = 0.009). Patients with low PLR in the human epidermal growth factor receptor 2 (HER-2) group had significantly higher axillary pCR rates than in those with high PLR (p = 0.019).ConclusionsA low PLR level showed high chemotherapy sensitivity independent of molecular subtypes in the treatment of breast cancer with NAC. The PLR level can serve as a predictive marker of the therapeutic effect of NAC on the breast and axilla. Low PLR levels in HER-2 enriched groups can predict pCR in the axilla.

Quantitative analysis of contrast enhanced spectral mammography grey value for early prediction of pathological response of breast cancer to neoadjuvant chemotherapy

A quantitative analysis of contrast-enhanced spectral mammography (CESM) enhancement was conducted for the early prediction of the pathological response after neoadjuvant chemotherapy (NAC). Retrospective analysis of the data of 111 patients was conducted, and all of them underwent NAC in our hospital and surgical resection after the end of all cycles from January 2018 to May 2019. They were divided into pathological complete response (PCR) and non-PCR groups. We determined whether a statistical difference in the percentage of CESM grey value reduction (ΔCGV) was present in the PCR and non-PCR groups and whether a statistical difference was observed in the diagnostic efficiency of craniocaudal (CC) and mediolateral oblique (MLO) view subtraction images. Independent sample t-test was used to compare different groups, the receiver operating characteristic (ROC) curve was used to compare the diagnostic efficacy of CC and MLO for pathological response after NAC, and the Delong test was used to compare the area under the ROC curve (AUC). Statistical significance was considered at P < 0.05. A statistical difference was observed in the ΔCGV in the PCR and non-PCR groups. No statistical difference was observed in the AUCs of CC and MLO view subtraction images. The ΔCGV can be used as a quantitative index to predict PCR early, and no statistical difference was observed in the diagnostic efficacy of CC and MLO view subtraction images.

Abstract PS2-21: Analysis of the clinical applicability of modified residual cancer burden system in evaluating the pathological response of breast cancer after neoadjuvant treatment

Abstract Objective: To study the related factors affecting the residual cancer burden (RCB) after neoadjuvant therapy for breast cancer, and to modify the residual cancer burden system for patients after neoadjuvant therapy. To analyze the modified residual cancer burden system in predicting prognosis in patients with different molecular types. Methods: A retrospective analysis was conducted on 1274 patients who were diagnosed with invasive carcinoma of the breast by preoperative coarse needle aspiration pathology from January 2009 to December 2017, and who underwent surgical resection after neoadjuvant therapy. Follow-up was 1186. From 2009 to 2016, 837 patients were randomly assigned to the training set, and combined with HER2 expression before neoadjuvant therapy for revised residual cancer burden system (HER2-RCB). In 2017, 349 patients formed a verification set, which was used to verify the effectiveness of the analytical model. In this study, SPSS21.00 was used for statistical analysis, Spearman was used for correlation analysis, Hosmer-lemeshow test constructed model calibration degree, ROC curve was used to evaluate the efficiency comparison, Kaplan-Meier and Cox were used for survival analysis, P&amp;lt;0.05 was statistically significant. Results: All patients in this study were female, with an average age of 50+8.7 years (24-86 years). Spearman correlation analysis showed that RCB classification was positively correlated with ER, PR expression, clinical stage, and age before neoadjuvant therapy (P&amp;lt;0.05), and negatively correlated with KI67, HER2 expression before neoadjuvant therapy, postoperative vascular tumor thrombus and lymph node metastasis (P&amp;lt;0.05). In the training set and validation set groups, the HER2-RCB classification has a good and consistent calibration between the predicted value of the patient's overall survival (OS) and disease-free survival (DFS) risk and the actual observed value. Sexuality is high (P&amp;gt;0.05), and the prognostic risk stratification of patients is higher than RCB classification (AUC=0.782, 0.699; 0.819, 0.719). According to the molecular types of breast cancer, and compared with other molecular typing, the differences that the RCB classification predicts the OS of patients with HER2 over-expression and Luminal B HER2 positive breast cancer were statistically significant (P&amp;lt;0.05), but there was no statistically significant difference in DFS (P&amp;gt;0.05), while the differences that the HER2-RCB classification predicts OS and DFS in patients with HER2 over-expression, and Luminal B HER2-positive breast cancer were statistically significant (P&amp;lt;0.05). Conclusions: HER2-RCB classification is more accurate than RCB classification in predicting prognosis, and the prediction of recurrence and metastasis risk in patients with HER2 over-expression and Luminal B HER2 positive breast cancer is better than RCB classification. It is suggested that HER2-RCB classification has better clinical applicability.Key words: Neoadjuvant therapy, Residual cancer burden, Pathologic complete response, Human epidermal growth factor receptor 2, Molecular type Citation Format: Yanqi Ma, Yueping Liu. Analysis of the clinical applicability of modified residual cancer burden system in evaluating the pathological response of breast cancer after neoadjuvant treatment [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS2-21.

The diagnostic performance of CESM and CE-MRI in evaluating the pathological response to neoadjuvant therapy in breast cancer: a systematic review and meta-analysis.

Neoadjuvant chemotherapy (NAC) is an important method for breast cancer treatment. By monitoring its pathological response, the selection of clinical treatment strategies can be guided. In this study, the meta-analysis was used to compare the accuracy of contrast-enhanced MRI (CE-MRI) and contrast-enhanced spectral mammography (CESM) in detecting the pathological response of NAC. Literatures associated to CE-MRI and CESM in the evaluation of pathological response of NAC were searched from PubMed, Cochrane Library, web of science, and EMBASE databases. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used to assess the quality of studies. Pooled sensitivity, specificity, and the area under the SROC curve were calculated to evaluate the diagnostic accuracy of CE-MRI and CESM in monitoring the pathological response of NAC. There were 24 studies involved, 18 of which only underwent CE-MRI examination, three of which only underwent CESM examination, and three of which underwent both CE-MRI and CESM examination. The pooled sensitivity and specificity of CE-MRI were 0.77 (95%CI, 0.67-0.84) and 0.82 (95%CI, 0.73-0.89), respectively. The pooled sensitivity and specificity of CESM were 0.83 (95%CI, 0.66-0.93) and 0.82 (95%CI, 0.68-0.91), respectively. The AUCs of SROC curve for CE-MRI and CESM were 0.86 and 0.89, respectively. Compared to CE-MRI, CESM has equal specificity, greater sensitivity and excellent performance, which may have a brighter prospect in evaluating the pathological response of breast cancer to NAC. CESM showed equal specificity, greater sensitivity, and excellent performance than CE-MRI.

The Diagnostic Performance of DCE-MRI in Evaluating the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer: A Meta-Analysis

Background: Neoadjuvant chemotherapy (NAC) is commonly utilized in preoperative treatment for local breast cancer, and it gives high clinical response rates and can result in pathologic complete response (pCR) in 6–25% of patients. In recent years, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been increasingly used to assess the pathological response of breast cancer to NAC. In present analysis, we assess the diagnostic performance of DCE-MRI in evaluating the pathological response of breast cancer to NAC.Materials and Methods: A systematic search in PubMed, the Cochrane Library, and Web of Science for original studies was performed. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to assess the methodological quality of the included studies. Patient, study, and imaging characteristics were extracted, and sufficient data to reconstruct 2 × 2 tables were obtained. Data pooling, heterogeneity testing, forest plot construction, meta-regression analysis and sensitivity analysis were performed using Stata version 12.0 (StataCorp LP, College Station, TX).Results: Eighteen studies (969 patients with breast cancer) were included in the present meta-analysis. The pooled sensitivity and specificity of DCE-MRI were 0.80 (95% confidence interval [CI]: 0.70, 0.88) and 0.84 (95% [CI]: 0.79, 0.88), respectively. Meta-regression analysis found no significant factors affecting heterogeneity. Sensitivity analysis showed that studies that set pathological complete response (pCR) (n = 14) as a responder showed a tendency for higher sensitivity compared with those that set pCR and near pCR together (n = 5) as a responder (0.83 vs. 0.72), and studies (n = 14) that used DCE-MRI to early predict the pathological response of breast cancer had a higher sensitivity (0.83 vs. 0.71) and equivalent specificity (0.80 vs. 0.86) compared to studies (n = 5) that assessed the response after NAC completion.Conclusion: Our results indicated that DCE-MRI could be considered an important auxiliary method for evaluating the pathological response of breast cancer to NAC and used as an effective method for dynamically monitoring the efficacy during NAC. DCE-MRI also performed well in predicting the pCR of breast cancer to NAC. However, due to the heterogeneity of the included studies, caution should be exercised in applying our results.

Real-world data: evaluation of sentinel lymph node biopsy after complete pathological response of breast cancer to neoadjuvant chemotherapy in patients with triple-negative and her2 positive breast cancer in a cohort from rio grande do sul, brazil

Introduction: International publications show a high correlation of axillary response and complete pathological response (CPR) of breast cancer to neoadjuvant chemotherapy (NACT) in patients with triple-negative (TN) and HER2 positive (HER2+) tumors. The need for surgery is being questioned when percutaneous breast biopsy after NACT indicates CPR, despite recent presentations demonstrating high rates of false-negative (FN), ranging from 17–39%. The proper axillary management in patients with CPR of breast cancer is still discussed: is it possible to avoid the axillary evaluation? What is the axillary downstaging rate? Identifying any residual disease to adjust the adjuvant treatment is also a concern. Retrospective studies reveal a rate of positive lymph nodes lower than 2% in this population when CPR of breast cancer is reached. Objective: To identify the rate of complete axillary response in patients with CPR of breast cancer to NACT in TN and HER2+ tumors. Methods: This is a retrospective cohort study conducted in two health facilities in Southern Brazil. The sample consists of 130 patients who underwent NACT, followed by surgery between January 2016 and December 2018. The patients included were treated in the public health system (Sistema Único de Saúde – SUS) and private health system. Results: Among the 130 patients submitted to NACT, 76 (58%) had HER2+ and TN immunohistochemical subtypes – luminal HER2+: 23 patients, HER2+ pure: 15, TN: 38. Among these patients, 33 (43%) reached CPR of breast cancer, of which 9 corresponded to luminal HER2+, 10 to HER2+, and 14 to TN. In patients with CPR of breast cancer, 29 (87.8%) had no lymph node disease. Out of the 10 HER2+ pure with CPR of breast cancer, 100% had no lymph node disease, and 8 were positive pre-NACT. Among the 14 TN, only 1 patient had 2 positive lymph nodes (2+/10), and she was cN0 prior to NACT (with negative axillary ultrasound). Among the 5 pre-NACT clinically positive lymph nodes in TN patients (including 1 patient with cN2), all had CPR to NACT (3 axillary dissections and 2 sentinel lymph node biopsies – SLNB). Out of the 9 patients with luminal HER and CPR of breast cancer, 4 had clinically positive lymph nodes before NACT, and 3 remained positive (15% of conversion). Conclusion: In this study, CPR of breast cancer was highly correlated with negative axillary evaluation after NACT (87.8%), mainly in the TN and HER2+ pure subtypes (98%), even if the lymph node was clinically positive before NACT, with 100% of conversion of HER 2+ pure cases. SUS patients used trastuzumab as the single drug targeting anti HER2. These data agree with those found in the literature, despite the small sample. Larger studies are necessary, as around 70% of our population depend on SUS. With more published data, considering the performance of SLNB in HER2+ pure and TN patients submitted to NACT could become a common practice, reducing morbidity. The safety of this practice in the luminal HER+ subtype remains unclear.

Contrast-enhanced ultrasound for evaluating the pathologic response of breast cancer to neoadjuvant chemotherapy: A meta-analysis.

Objective:Recent reports have suggested that contrast-enhanced ultrasound (CEUS) can be used to monitor the pathologic responses of breast cancer (BC) to neoadjuvant chemotherapy (NAC); however, the diagnostic performance of CEUS in BC has yet to be confirmed. Thus, we conducted a meta-analysis of related studies to explore the relationship between CEUS and pathologic responses of BC to NAC.Materials and methods:We searched PubMed, Embase, Web of Science, ScienceDirect, and China National Knowledge Infrastructure databases for studies published until September 31, 2018. Study-specific odds ratios (ORs) and 95% confidence intervals (CIs) were calculated, and then ORs with 95% CIs were pooled to estimate the prognostic role of CEUS for the pathologic responses of BC to NAC.Results:Pooled meta-analysis of the 9 eligible studies that included 424 patients indicated the high performance of CEUS for monitoring pathologic responses to NAC (OR = 31.83, 95% CI: 16.69–60.67, P < .001), with no significant heterogeneity (I2 = 0.0%, P = .529). The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 87% (95% CI: 0.81–0.92), 84% (95% CI: 0.74–0.91), 5.5 (95% CI: 3.3–9.2), 0.15 (95% CI: 0.10–0.23), and 36 (95% CI: 18–70), respectively. An area under the curve of 0.92 (95% CI: 0.89–0.94) suggests a high ability for prognostic detection. Although Begg's funnel plot (P = .057) indicated the presence of publication bias among the included studies, the trim-and-fill method verified the stability of the pooled outcomes. Sensitivity analysis suggested that the pooled OR was robust.Conclusion:Our results suggest that CEUS has a high diagnostic performance for the pathologic responses of BC to NAC. Further and better-designed studies should be performed to verify the clinical applications of CEUS for monitoring BC responses to NAC.

Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features.

BackgroundPathological response of breast cancer to chemotherapy is a prognostic indicator for long-term disease free and overall survival. Responses of locally advanced breast cancer in the neoadjuvant chemotherapy (NAC) settings are often variable, and the prediction of response is imperfect. The purpose of this study was to detect primary tumor responses early after the start of neoadjuvant chemotherapy using quantitative ultrasound (QUS), textural analysis and molecular features in patients with locally advanced breast cancer.MethodsThe study included ninety six patients treated with neoadjuvant chemotherapy. Breast tumors were scanned with a clinical ultrasound system prior to chemotherapy treatment, during the first, fourth and eighth week of treatment, and prior to surgery. Quantitative ultrasound parameters and scatterer-based features were calculated from ultrasound radio frequency (RF) data within tumor regions of interest. Additionally, texture features were extracted from QUS parametric maps. Prior to therapy, all patients underwent a core needle biopsy and histological subtypes and biomarker ER, PR, and HER2 status were determined. Patients were classified into three treatment response groups based on combination of clinical and pathological analyses: complete responders (CR), partial responders (PR), and non-responders (NR). Response classifications from QUS parameters, receptors status and pathological were compared. Discriminant analysis was performed on extracted parameters using a support vector machine classifier to categorize subjects into CR, PR, and NR groups at all scan times.ResultsOf the 96 patients, the number of CR, PR and NR patients were 21, 52, and 23, respectively. The best prediction of treatment response was achieved with the combination mean QUS values, texture and molecular features with accuracies of 78%, 86% and 83% at weeks 1, 4, and 8, after treatment respectively. Mean QUS parameters or clinical receptors status alone predicted the three response groups with accuracies less than 60% at all scan time points. Recurrence free survival (RFS) of response groups determined based on combined features followed similar trend as determined based on clinical and pathology.ConclusionsThis work demonstrates the potential of using QUS, texture and molecular features for predicting the response of primary breast tumors to chemotherapy early, and guiding the treatment planning of refractory patients.

Evaluation of the EGFR polymorphism R497K in two cohorts of neoadjuvantly treated breast cancer patients.

Pathological response of breast cancer to neoadjuvant chemotherapy (NAC) presents great variability, and new prognostic biomarkers are needed. Our aim was to evaluate the association of the epidermal growth factor receptor gene (EGFR) polymorphism R497K (rs2227983) with prognostic features and clinical outcomes of breast cancer, including the pathological response to NAC and the recurrence-free survival (RFS). Tumoral complete response (tCR) was defined by no remaining invasive cancer in the excised breast, whereas pathological complete response (pCR) was defined by no remaining invasive cancer both in the excised breast and lymph nodes. Two independent cohorts were analyzed: one from Brazil (INCA, n = 288) and one from The Netherlands (NKI-AVL, n = 255). In the INCA cohort, the variant (Lys-containing) genotypes were significantly associated with lower proportion of tCR (ORadj = 0.92; 95%CI = 0.85–0.99), whereas in the NKI-AVL cohort they were associated with tumor grade 3 (p = 0.035) and with triple-negative subtype (p = 0.032), but not with clinical outcomes. Such distinct prognostic associations may have arisen due to different neoadjuvant protocols (p < 0.001), or to lower age at diagnosis (p < 0.001) and higher proportion of tumor grade 3 (p = 0.018) at the NKI-AVL cohort. Moreover, NKI-AVL patients achieved better proportion of pCR (21.2% vs 8.3%, p < 0.001) and better RFS (HRadj = 0.48; 95% adjCI = 0.26–0.86) than patients from INCA. In conclusion, large scale studies comprehending different populations are needed to evaluate the impact of genome variants on breast cancer outcomes.

Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities

Anti-cancer therapies including chemotherapy aim to induce tumour cell death. Cell death introduces alterations in cell morphology and tissue micro-structures that cause measurable changes in tissue echogenicity. This study investigated the effectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heterogeneity and monitor the pathological response of breast cancer to chemotherapy in a large cohort of patients (n = 100). Results demonstrated that QUS imaging can non-invasively monitor pathological response and outcome of breast cancer patients to chemotherapy early following treatment initiation. Specifically, QUS biomarkers quantifying spatial heterogeneities in size, concentration and spacing of acoustic scatterers could predict treatment responses of patients with cross-validated accuracies of 82 ± 0.7%, 86 ± 0.7% and 85 ± 0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75 ± 0.1, 0.80 ± 0.1 and 0.89 ± 0.1 at 1, 4 and 8 weeks after the start of treatment, respectively. The patients classified as responders and non-responders using QUS biomarkers demonstrated significantly different survivals, in good agreement with clinical and pathological endpoints. The results form a basis for using early predictive information on survival-linked patient response to facilitate adapting standard anti-cancer treatments on an individual patient basis.

Evaluating pathologic response of breast cancer to neoadjuvant chemotherapy with computer-extracted features from contrast-enhanced ultrasound videos

PurposeTo extract quantitative perfusion and texture features with computer assistance from contrast-enhanced ultrasound (CEUS) videos of breast cancer before and after neoadjuvant chemotherapy (NAC), and to evaluate pathologic response to NAC with these features. MethodsForty-two CEUS videos with 140,484 images were acquired from 21 breast cancer patients pre- and post-NAC. Time-intensity curve (TIC) features were calculated including the difference between area under TIC within a tumor and that within a computer-detected reference region (AUT_T-R). Four texture features were extracted including Homogeneity and Contrast. All patients were identified as pathologic responders by Miller and Payne criteria. The features between pre- and post-treatment in these responders were statistically compared, and the discrimination between pre- and post-treatment cancers was assessed with a receiver operating characteristic (ROC) curve. ResultsCompared with the pre-treatment cancers, the post-treatment cancers had significantly lower Homogeneity (p<0.001) and AUT_T-R (p=0.014), as well as higher Contrast (p<0.001), indicating the intratumoral contrast enhancement decreased and became more heterogeneous after NAC in responders. The combination of Homogeneity and AUT_T-R achieved an accuracy of 90.5% and area under ROC curve of 0.946 for discrimination between pre- and post-chemotherapy cancers without cross validation. The accuracy still reached as high as 85.7% under leave-one-out cross validation. ConclusionsThe computer-extracted CEUS features show reduced and more heterogeneous neovascularization of cancer after NAC. The features achieve high accuracy for discriminating between pre- and post-chemotherapy cancers in responders and thus are potentially valuable for tumor response evaluation in clinical practice.

TU‐D‐207B‐05: Intra‐Tumor Partitioning and Texture Analysis of DCE‐MRI Identifies Relevant Tumor Subregions to Predict Early Pathological Response of Breast Cancer to Neoadjuvant Chemotherapy

Purpose:To predict early pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multi‐region analysis of dynamic contrast enhancement magnetic resonance imaging (DCE‐MRI).Methods:In this institution review board‐approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using 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 a 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 wash‐out were statistically significant (p&lt; 0.05) after correcting for multiple testing, with area under the ROC curve 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 wash‐out on DCE‐MRI predicted early pathological response to neoadjuvant chemotherapy in breast cancer.

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.

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). 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. 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). 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.

Abstract P3-06-33: Comparison of pathologic response evaluation systems after neoadjuvant chemotherapy among different molecular subtypes of breast cancers

Abstract Background: Several ways to assess pathologic response of breast cancer after neoadjuvant chemotherapy (NAC) are currently available. However, clinical usefulness of assessment systems in each molecular subtype of breast cancer is unclear. Therefore, we compared four pathologic response assessment systems predicting patients’ clinical outcome in specific subtypes of breast cancer. Methods: In total, 598 tumors from 590 female breast cancer patients who received anthracycline and taxane-based NAC and subsequent surgery from 2010 to 2012 were analyzed. Molecular subtypes were defined by immunohistochemistry (HER2 and hormone receptor (HR): estrogen receptor and progesterone receptor). Miller-Payne grading, Residual Cancer Burden, Residual Disease in Breast and Nodes and ypTNM stage were evaluated. Results of each assessment system were analyzed for survival with Kaplan-Meier and Cox hazard model. Median follow-up period was 35.2 months (range 21.1-54.4 months). Results: Pathologic complete response was achieved in 4.4% (12/275) of HR+/HER2-, 10.7% (8/75) of HR+/HER2+, 17.8% (16/90) of HR-/HER2+, and 29.7% (47/158) of triple negative (TN) tumors. Results of all four examined assessment systems were significantly correlated with disease-free and overall survival in all tumors. In HR+/HER2- and TN tumors, all systems were associated with disease-free and overall survival. Comparison of pathologic response assessment systems after neoadjuvant chemotherapy for disease-free and overall survivalDisease-free survivalHR+/HER2-HR+/HER2+HR-/HER2+TNMiller Payne gradeHR (95% CI)0.629 (0.429-0.925)0.310 (0.159-0.607)0.647 (0.428-0.977)0.451 (0.343-0.593)P value.018&amp;lt;0.001.039&amp;lt;0.001RCB classHR (95% CI)2.621 (1.398-4.914)2.454 (0.917-6.564)1.696 (0.929-3.094)2.966 (1.982-4.441)P value.003.074.085&amp;lt;0.001RDBN levelHR (95% CI)2.892 (1.642-5.093)2.587 (1.015-6.595)2.189 (1.118-4.286)3.065 (2.108-4.456)P value&amp;lt;0.001.047.022&amp;lt;0.001ypTNM StageHR (95% CI)2.975 (1.606-5.512)2.062 (0.918-4.632)2.004 (1.121-3.582)2.950 (2.152-4.044)P value.001.080.019&amp;lt;0.001Overall survivalMiller Payne gradeHR (95% CI)0.416 (0.222-0.778)0.399 (0.177-0.896)0.633 (0.357-1.124)0.397 (0.294-0.537)P value.006.026.119&amp;lt;0.001RCB classHR (95% CI)8.611 (1.924-38.531)2.971 (0.733-12.032)1.900 (0.771-4.680)2.976 (1.927-4.594)P value.005.127.163&amp;lt;0.001RDBN levelHR (95% CI)11.369 (2.618-49.375)3.042 (0.801-11.550)1.970 (0.805-4.821)3.262 (2.145-4.961)P value.001.102.138&amp;lt;0.001ypTNM StageHR (95% CI)5.812 (1.666-20.270)2.623 (0.851-8.080)1.619 (0.739-3.546)3.040 (2.150-4.300)P value.006.093.228&amp;lt;0.001RCB, residual cancer burden; RDBN; residual disease breast and nodes. Especially in TN, Kaplan-Meier survival curves for disease-free survival were clearly separated by all assessment methods. However, in HR+/HER2+ and HR-/HER2+ tumors, the association of patients’ survival with response assessment results was variable according to the examined systems. Conclusion: By the available pathologic assessment systems after neoadjuvant chemotherapy, HR+/HER2- and TN breast cancers could be effectively classified into groups showing different prognosis. However, for the evaluation of pathologic response of HR+/HER2+ and HR-/HER2+ tumors, the development of effective assessment methods is warranted. Citation Format: In Ah Park, Hee Jin Lee, In Hye Song, Gyungyub Gong. Comparison of pathologic response evaluation systems after neoadjuvant chemotherapy among different molecular subtypes of breast cancers [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-33.

Role of breast ultrasound, mammography, magnetic resonance imaging and diffusion weighted imaging in predicting pathologic response of breast cancer after neoadjuvant chemotherapy

BackgroundBreast cancer is the most common cancer affecting females worldwide, patient who present with late stage disease, will be treated initially with neoadjuvant chemotherapy to downstage the disease. AimTo evaluate the ability of mammography, US and MRI in assessment of residual tumor and the real extent of the disease after neoadjuvant chemotherapy. MethodsThirty patients proved with locally advanced breast cancer and received neoadjuvant chemotherapy. All patients underwent mammograms, US, MRI of both breast before and after 3 cycles chemotherapy. Results at end of treatment mammography detect 20 operable lesions ranging size (3–9.5cm) with mean 5.7cm. Ultrasound detect 30 lesions ranging size (2–6.8cm) with mean size 2.75cm. MRI detected 30 lesions ranging size (1.8–7.4cm) with mean 3.5cm. Mammography overestimated the actual size of residual tumor in 16 cases (80%) and underestimated the size in 4 cases (20%). US overestimated the actual size in 6 (20%), underestimated size in 22 lesions (73.3%). MRI overestimated the actual size in 20 lesions (66.7%), underestimated in 7 lesion (23.3%). ConclusionMRI is accurate than mammography and ultrasound in detection the actual pathologic size of cancer breast and also in predicting the residual disease after neoadjuvant chemotherapy.