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Objectives To determine if combined measurements from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and diffusion weighted MRI (DW-MRI), obtained before and after the first cycle of neoadjuvant chemotherapy (NAC), are superior to single parameter measurements for predicting pathological complete response (pCR) in breast cancer patients. Materials and Methods Patients with Stage II/III breast cancer were enrolled in an IRB-approved study in which 3T DCE- and DW-MRI data were acquired before (n = 37) and after one cycle (n = 33) of NAC. Estimates of Ktrans, ve, vp, and kep (= Ktrans/ve) were generated from the DCE-MRI data using the Extended Tofts-Kety (ETK) model. The apparent diffusion coefficient (ADC) was estimated from the DW-MRI data. The derived parameter kep/ADC was compared to single parameter measurements for its ability to predict pCR after the first cycle of NAC. Results kep/ADC after the first cycle of NAC discriminated patients who went on to achieve a pCR (P < 0.001), and achieved a sensitivity, specificity, positive predictive value, and area under the receiver operator curve (AUC) of 0.92, 0.75, 0.69, and 0.86, respectively. These values were superior to the single parameters kep (AUC = 0.77) and ADC (AUC = 0.81). The AUCs between kep/ADC and kep were significantly different based on the bootstrapped 95% CIs (0.0062, 0.20), while the AUCs between kep/ADC and ADC trended towards significance (−0.12, 0.24). Conclusions A combined analysis of DCE-MRI and DW-MRI parameters was superior to single-parameter measurements for predicting pCR after the first cycle of NAC.

Purpose The purpose of this pilot study is to determine 1) if early changes in both semi-quantitative and quantitative DCE-MRI parameters, observed after the first cycle of neoadjuvant chemotherapy in breast cancer patients, show significant difference between responders and non-responders, and 2) if these parameters can be used as a prognostic indicator of the eventual response. Methods Twenty-eight patients were examined using DCE-MRI pre-, post-one cycle, and just prior to surgery. The semi-quantitative parameters included longest dimension, tumor volume, initial area under the curve (iAUC), and signal enhancement ratio (SER) related parameters, while quantitative parameters included Ktrans, ve, kep, vp, and τi estimated using the standard Tofts-Kety (TK), extended Tofts-Kety (ETK), and fast exchange regime (FXR) models. Results Our preliminary results indicated that the SER washout volume and kep were significantly different between pathologic complete responders from non-responders (P < 0.05) after a single cycle of chemotherapy. Receiver operator characteristic (ROC) analysis showed that the AUC of the SER washout volume was 0.75, and the AUCs of kep estimated by three models were 0.78, 0.76, and 0.73, respectively. Conclusion In summary, the SER washout volume and kep appear to predict breast cancer response after one cycle of neoadjuvant chemotherapy. This observation should be confirmed with additional prospective studies.

Background Due to inherent disease heterogeneity, targeted therapies have eluded TNBC, and biomarkers predictive of treatment response have not yet been identified. This study was designed to determine if the mTOR inhibitor everolimus with cisplatin and paclitaxel would provide synergistic anti-tumor effects in TNBC. Methods Stage II/III patients with TNBC were enrolled in a randomized phase II trial of preoperative weekly cisplatin, paclitaxel and daily everolimus or placebo for 12 weeks, until definitive surgery. Tumor specimens were obtained at baseline, cycle 1 and surgery. Primary endpoint was pathological complete response (pCR); secondary endpoints included clinical responses, breast conservation rate, safety, and discovery of molecular features associated with outcome. Results Between 2009 and 2013, 145 patients were accrued; 36% patients in the everolimus arm and 49% patients in the placebo arm achieved pCR; in each arm, 50% of patients achieved complete responses by imaging. Higher rates of neutropenia, mucositis and transaminase elevation were seen with everolimus. Clinical response to therapy and long-term outcome correlated with increased frequency of DNA damage response (DDR) gene mutations, Basal-like1 and Mesenchymal TNBC-subtypes, AR-negative status and high Ki67, but not with tumor infiltrating lymphocytes. Conclusion The paclitaxel/cisplatin combination was well tolerated and active, but addition of everolimus was associated with more adverse events without improvement in pCR or clinical response. However, discoveries made from correlative studies could lead to predictive TNBC biomarkers that may impact clinical decision-making and provide new avenues for mechanistic exploration that could lead to clinical utility.

Quantitative analysis of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data requires the accurate determination of the arterial input function (AIF). A novel method for obtaining the AIF is presented here and pharmacokinetic parameters derived from individual and population based AIFs are then compared. A Philips 3.0 T Achieva MR scanner was used to obtain 20 DCE-MRI data sets from ten breast cancer patients prior to and after one cycle of chemotherapy. Using a semi-automated method to estimate the AIF from the axillary artery, we obtain the AIF for each patient, AIFind, and compute a population averaged AIF, AIFpop. The extended standard model is used to estimate the physiological parameters using the two types of AIFs. The mean concordance correlation coefficient (CCC) for the AIFs segmented manually and by the proposed AIF tracking approach is 0.96, indicating accurate and automatic tracking of an AIF in DCE-MRI data of the breast is possible. Regarding the kinetic parameters, the CCC values for Ktrans, vp, and ve as estimated by AIFind and AIFpop are 0.65, 0.74, and 0.31, respectively, based on region of interest analysis. The average CCC values for the voxel-by-voxel analysis are 0.76, 0.84, and 0.68 for Ktrans, vp, and ve, respectively. This work indicates that Ktrans and vp show a good agreement between AIFpop and AIFind while there is a weak agreement on ve.

A presurgical approach to evaluate cellular responses to new drugs is feasible in breast cancer. EGFR inhibitors are worthy of testing against ER-positive breast cancers but are unlikely to have clinical activity against HER-2-positive or triple-negative breast cancers.

Breast conserving surgery is the preferred treatment for women diagnosed with early stage invasive breast cancer. To ensure successful breast conserving surgeries, efficient tumour margin resection is required for minimizing tumour recurrence. Currently surgeons rely on touch preparation cytology or frozen section analysis to assess tumour margin status intraoperatively. These techniques have suboptimal accuracy and are time-consuming. Tumour margin status is eventually confirmed using postoperative histopathology that takes several days. Thus, there is a need for a real-time, accurate, automated guidance tool that can be used during tumour resection intraoperatively to assure complete tumour removal in a single procedure. In this paper, we evaluate feasibility of a 3-dimensional scanner that relies on Raman Spectroscopy to assess the entire margins of a resected specimen within clinically feasible time. We initially tested this device on a phantom sample that simulated positive tumour margins. This device first scans the margins of the sample and then depicts the margin status in relation to an automatically reconstructed image of the phantom sample. The device was further investigated on breast tissues excised from prophylactic mastectomy specimens. Our findings demonstrate immense potential of this device for automated breast tumour margin assessment to minimise repeat invasive surgeries.

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