The optimal goal of neoadjuvant chemotherapy (NAC) for breast cancer is to achieve pathologic complete response (pCR) with the least toxicity. As more effective therapies become available, one challenge is how to evaluate the response of tumor in a timely manner, so an optimal regimen can be given to the patient. Reliable imaging methods that can monitor and predict NAC response are critically needed. In addition to therapy response monitoring, imaging parameters are associated with phenotype of cancer and may be used as prognostic markers. We have been performing NAC studies for close to 10 years, and in this renewal we will continue to develop and validate imaging markers for evaluating and predicting therapeutic response, as well as for predicting prognosis.
Three aims are proposed.
Aim -1 will follow all previously enrolled NAC patients since 2003 (more than 180 patients) to obtain their prognostic information. Other than previously analyzed imaging parameters, two novel imaging markers that are shown to have prognostic value, i.e. the change of breast density (fibroglandular tissue volume) and the stromal tissue contrast enhancement, will be analyzed using a comprehensive quantitative method developed by us. The primary analysis is to use imaging parameters to predict local recurrence, but the disease-free and overall survival will be collected and used in exploratory analyses.
Aim -2 and -3 will be performed using the prospectively collected data from a new clinical trial to enroll 75 NAC patients into an imaging monitoring study by using a combined MRI and scinti-mammography (MR-SMM) system. Despite of the research interest in investigating the role of complex multi- parametric imaging methods, there is always a need of an easy method that can measure the tumor size accurately; and SMM has a great potential.
Aim -2 will compare the diagnostic performance of SMM and MRI at different times before, during, and after NAC. Also, the diagnostic accuracy of the post-NAC residual disease measured by SMM and MRI will be determined by comparing to pathological examination results as the goldstandard.
Aim -3 will evaluate the respective and combined ability of MRI and SMM, based on pre-treatment and early changes in the first follow-up imaging, for predicting pathologic complete response (pCR). The diagnostic results obtained using MRI and SMM from tumors of varying stages at different times during NAC will provide important information for establishing the role of a standalone SMM system, as well as the combined MR-SMM system, for management of breast cancer patients.

Public Health Relevance

Neoadjuvant chemotherapy (NAC) has become an important treatment option for breast cancer patients. Imaging can provide very useful information for monitoring and predicting response, as well as prognosis. With many years of research, MRI has become a very important clinical breast imaging tool. Molecular imaging has gradually evolved as a complementary modality. In this study the NAC response of the same cancer evaluated by MRI and molecular imaging will be directly compared by using a novel MR-compatible scintimammography system. The success of this project will continue to advance the clinical role of breast imaging, not only for NAC monitoring but also for general screening and diagnosis, to aid in improved, personalized, management and care that can be provided to each individual breast cancer patient.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Cancer Biomarkers Study Section (CBSS)
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Henderson, Lori A
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University of California Irvine
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Wang, Juan; Fang, Zhiyuan; Lang, Ning et al. (2017) A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks. Comput Biol Med 84:137-146
Lang, Ning; Su, Min-Ying; Xing, Xiaoying et al. (2017) Morphological and dynamic contrast enhanced MR imaging features for the differentiation of chordoma and giant cell tumors in the Axial Skeleton. J Magn Reson Imaging 45:1068-1075
Lang, Ning; Yuan, Huishu; Yu, Hon J et al. (2017) Diagnosis of Spinal Lesions Using Heuristic and Pharmacokinetic Parameters Measured by Dynamic Contrast-Enhanced MRI. Acad Radiol 24:867-875
Chen, Jeon-Hor; Liao, Fuyi; Zhang, Yang et al. (2017) 3D MRI for Quantitative Analysis of Quadrant Percent Breast Density: Correlation with Quadrant Location of Breast Cancer. Acad Radiol 24:811-817
Chan, Siwa; Chen, Jeon-Hor; Li, Shunshan et al. (2017) Evaluation of the association between quantitative mammographic density and breast cancer occurred in different quadrants. BMC Cancer 17:274
Kim, Min Jung; Su, Min-Ying; Yu, Hon J et al. (2016) US-localized diffuse optical tomography in breast cancer: comparison with pharmacokinetic parameters of DCE-MRI and with pathologic biomarkers. BMC Cancer 16:50
Chen, Jeon-Hor; Chan, Siwa; Lu, Nan-Han et al. (2016) Opportunistic Breast Density Assessment in Women Receiving Low-dose Chest Computed Tomography Screening. Acad Radiol 23:1154-61
Chen, Jeon-Hor; Chan, Siwa; Tang, Yi-Ting et al. (2015) Impact of positional difference on the measurement of breast density using MRI. Med Phys 42:2268-75
Chen, Jeon Hor; Yu, Hon J; Hsu, Christine et al. (2015) Background Parenchymal Enhancement of the Contralateral Normal Breast: Association with Tumor Response in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy. Transl Oncol 8:204-9
Lin, Yuting; Lin, Wei-Ching; Fwu, Peter T et al. (2015) Investigation of factors affecting hypothermic pelvic tissue cooling using bio-heat simulation based on MRI-segmented anatomic models. Comput Methods Programs Biomed 122:76-88

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