Background Functional MRI techniques may be utilized for characterizing breast tumors and measuring response to neoadjuvant chemotherapy (NAC). Dynamic contrast enhanced (DCE) MRI is the most common functional breast MRI technique. Fitting DCE MRI data to an appropriate pharmacokinetic model allows noninvasive, in vivo measurement of physiological parameters related to tissue perfusion, microvascular permeability, and extracellular/extravascular volume fraction. Diffusion weighted imaging (DWI) MRI is an alternative technique that measures the mobility of water molecules in vivo and is sensitive to tissue characteristics such as cell density, membrane permeability, and microstructure. DWI provides complementary information to DCE MRI about tumor biology and has shown promise for early prediction of response. The master ISPY2 multi-center study is a process targeting the rapid, focused clinical development of paired oncologic therapies and biomarkers. Its framework is an adaptive phase II clinical trial design in the neoadjuvant setting for women with locally advanced breast cancer. As a sub-study, ACRIN 6698 will combine both DCE and DWI MRI data to generate novel imaging biomarkers that correlate with treatment response. The two studies will provide a rich data set that can be used to elucidate molecular pathways and tumor responses to novel investigational drugs with standard chemotherapy. Trial design: ACRIN 6698 will perform advanced DCE and DWI MR imaging as part of the I-SPY TRIAL. The ISPY 2 adaptive therapy design will use different tumor biomarker assays to identify patients with high risk of recurrence. Patients will receive NAC doublet chemotherapy and trastuzumab (if Her2+). Patients will be randomized and stratified into different arms receiving investigational agents of different drug classes. ACRIN 6698 patients will receive four advanced MRI exams (both DCE and DWI) at baseline, early therapy, mid therapy and prior to surgery. Specific aims: The primary aim will determine if the % change in tumor apparent diffusion coefficient (ADC) measured on DWI from baseline to early treatment timepoint is predictive of pathologic complete response (pCR). The secondary aim will determine if the combined measurement of percentage change in tumor ADC on DWI, and percentage change in tumor volume and peak signal enhancement ratio (SER) on DCE MRI is predictive of pCR. Statistical methods: Receiver operating characteristic (ROC) curve and corresponding area under the ROC curves (AUC) for the individual marker, % change in tumor ADC, and % change in tumor volume and peak SER, will be estimated. Linear score of the 3 markers will be derived by fitting the multivariate logistic regression model, where the outcome is a binary variable for pCR and the predictors are the 3 measurements. The ROC curve for the derived linear score will be constructed and its AUC value will be estimated. Target accrual: ACRIN 6698 is open to ISPY 2 sites. The target accrual is 200 of ISPY 2's planned enrollment of 800 participants. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr OT2-03-06.
#6006 Background: We are enrolling patients with locally-advanced (LABC) or inflammatory breast cancer on a phase II trial of neoadjuvant sunitinib and metronomic chemotherapy. The addition of sunitinib is hypothesized to increase rate of pathologic complete response (pCR) via its effect on tumor vasculature. Measurement of FDG PET and MRI parameters of metabolism and blood flow (BF) after a one week run-in of sunitinib alone provides an opportunity to evaluate in vivo pharmacodynamics of sunitinib which may be predictive of response and provide insight into mechanism of sunitinib activity. Materials and Methods: Patients with HER2 negative LABC participated in an imaging trial with pre-therapy [18F]-FDG PET and DCE-MRI (T0) followed by a one-week run-in of sunitinib 37.5 mg orally daily with a second PET and MRI on day 7 (T1). FDG metabolic rate (MRFDG), transport (FDG K1) and MR indices of tumor perfusion (peak enhancement (PE), signal enhancement ratio (SER), and washout volume(WV)) were assessed. Results: Metabolism and perfusion parameters are available for the first 3 patients treated on this trial. All patients presented with grade 3, HER2 negative LABC. DCI-MRI (left) and PET images (right) pre-therapy (T0, top) and after one week sunitinib (T1, bottom) are illustrated in Figure 1. DCE-MRI studies show gray-scale images with color-coded regional perfusion (SER) superimposed; red indicates high levels of perfusion and blue lower levels. Three different responses were observed and expressed as percent change T0 to T1: patient 1 had no significant change in metabolism (MRFDG) or perfusion (K1,SER, PE); patient 2 showed a decline in perfusion with decreases in K1 (-55%), SER (-19%), PE (-10%), and WV (-56%), but minimal change in MRFDG (+ 5.9%); while patient 3 had marked declines in perfusion K1 (-41%), SER (-25%), WV (-78%) and MRFDG (-59%). Discussion: These early data demonstrate the ability to measure changes in tumor metabolism and blood flow by PET and MRI and illustrate heterogeneity in tumor response to sunitinib. As patients complete neoadjuvant chemotherapy (NC), metabolism and perfusion parameters from mid-therapy (T2) and end-therapy (T3) imaging will be evaluated in the context of pCR versus other with the goal of exploiting functional imaging parameters to predict response to NC and elucidate mechanism of response to sunitinib and metronomic chemotherapy. Supported by grant from NCCN, SI11.
 
 Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 6006.
Background: Emerging data has shown that the immune system participates in both tumor development and tumor elimination and control. In breast cancer, activation of the immune system may mediate the effects of several anticancer drugs. In HER2+ and triple negative breast cancers, even 10% increases in tumor infiltrating lymphocytes (TILs) predict improved prognosis to adjuvant chemotherapy. Furthermore, the monoclonal antibody trastuzumab is known to increase peripheral Th1 immunity in women with HER2+ breast cancer, which may be reflected by increased TILs. An imaging approach to measure and monitor immune response would provide an essential non-invasive tool to select appropriate therapies based on an individual's response. Dynamic contrast-enhanced (DCE) MRI, reflecting blood flow and capillary permeability, and diffusion weighted (DW) MRI, reflecting cellularity, hold unique potential to provide quantitative imaging markers of therapy-induced immune response in breast tumors. Trial Design: We propose to use trastuzumab to invoke immune response in patients with HER2+ tumors. Each subject will undergo a multiparametric MRI exam (with DCE and DW-MRI) and tissue sampling before and after a single dose of targeted anti-HER2 therapy with trastuzumab, prior to surgery. Pretreatment tissue will be obtained form the diagnostic core biopsy, and post-trastuzumab tissue will be collected from a research biopsy or the surgical excision, requiring at most a single additional biopsy. A variety of quantitative parameters will be extracted from the MRI scans. Whole tumor characterization will be performed, to calculate histogram-based metrics and second order textural features. Functional MRI features will be compared with histologic assessment of TILs, VEGF expression, and other immune response markers in tumors treated with HER2-targeted therapy. After the study window, patients will undergo standard of care treatment at the discretion of their physician. Specific Aims: The primary objective will be to identify quantitative MRI markers of immune response to HER2-targeted treatment. We will implement a high-resolution multiparametric MRI approach and determine whether early changes on MRI after a preoperative run-in dose of trastuzumab correlate with tumor immune response markers as measured by histologic assessment. Statistical Methods: The magnitude of response will be determined for individual MRI and histologic markers following one cycle of trastuzumab, and Pearson and Spearman correlation coefficients will be used to assess associations between changes in MRI and histologic markers. With 50 patients, we will have 80% power to detect a significant correlation between MRI and histologic markers as small as r = 0.39 (R2 = 15%), based on a 2-sided test of the null hypothesis r = 0 at the 0.05 significance level. Accrual: Three patients have been accrued to date, with a target of 50 HER2+ patients. Patients may consent to either 1) preoperative run-in of a single cycle of anti-HER2 treatment or 2) neoadjuvant targeted anti-HER2 only treatment regimen (e.g., co-enrollment in TBCRC 026 or comparable trial), either of which allows for monitoring at pre and post 1 cycle of anti-HER2 treatment. Contact information: VK Gadi (vkgadi@uw.edu) or Savannah Partridge (scp3@uw.edu). Citation Format: Gadi VK, Stanton S, Dintzis SM, Calhoun KE, Hippe DS, Partridge SC. Functional MRI signatures of immune response to targeted breast cancer therapy [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr OT3-01-05.
#6053 Background: Assessment of tumor response to chemotherapy has traditionally relied on the bidimensional tumor measurement guidelines proposed by the World Health Organization (WHO, 1979) and more recently on the unidimensional Response Evaluation Criteria in Solid Tumors (RECIST, Therasse et al., 2000). MRI is being used increasingly to monitor breast cancer response to preoperative chemotherapy and allows both linear and volumetric assessment of tumor size. The purpose of this study was to compare pre- and post-treatment RECIST, WHO, and volumetric measures of tumor size on MRI for predicting recurrence free survival (RFS) in patients undergoing preoperative chemotherapy.
 Materials & Methods: 56 patients with locally advanced breast cancer were imaged with MRI (1.5T GE scanner) before and after 4 cycles of preoperative chemotherapy. Tumor longest diameter (LD) at physical exam (ClinLD) was recorded before (N=56) and after (N=48) treatment. Fat suppressed, contrast enhanced, T1-weighted sagittal 3DFGRE images (TE/TR=8/4.2ms, flip=20°, 2mm thick, 18-20cm FOV, 256x192 matrix) were acquired for tumor size measurements.
 All MRI LD measurements were made manually following RECIST and WHO guidelines. Tumor volume was measured with a semi-automated tumor segmentation algorithm based on a specific enhancement ratio calculation. Univariate Cox proportional hazards analysis was used to assess the value of clinical, pathology, RECIST, WHO, and volume measurements for predicting RFS. Variables with p<0.15 were combined in a stepwise multivariate model to determine the greatest predictive value.
 Results: 23 patients have recurred since surgery (mean time 132 weeks). The mean RFS in the non-recurrent group is 330 weeks. Results for univariate and multivariate analysis are show in the Table. Final tumor volume was most predictive of recurrence free survival, and was the only variable found to be an independent significant predictor in the multivariate analysis. Age, tumor grade, and positive lymph node status were not significant predictors.
 Discussion: Post-chemotherapy tumor volume calculated via a semi-automatic algorithm was found to be a significant predictor of RFS for patients undergoing preoperative chemotherapy, out-performing manual 1D RECIST, 2D WHO, and clinical measurements. The results support previous work demonstrating the value of MRI tumor volume for predicting patient outcome.
 
 Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 6053.
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