# Multiparametric multimodal imaging for breast cancer neoadjuvant chemotherapy monitoring > **NIH NIH K01** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $140,826 ## Abstract Project Summary/Abstract This Mentored Research Scientist Development (K01) Award will support the training and career development of a junior investigator with prior training in near-infrared spectroscopy and multimodal x-ray/diffuse optical tomography, who is transitioning into the field of magnetic resonance (MR) and elastographic breast cancer imaging. The proposed career development plan includes training in MR imaging techniques, cancer biology, medical oncology, clinical research, and career development skills. The proposed research focuses on the development of novel breast cancer imaging techniques and sensitive, robust, and powerful multiparametric imaging markers to predict pathological outcomes early in neoadjuvant settings, thereby responding to an urgent clinical need to tailor treatment to individual diseases and improve breast cancer survival. Functional imaging is advantageous in monitoring neoadjuvant chemotherapy (NACT) since changes in tumor physiology manifest earlier than actual tumor shrinkage. However, breast tumors are complex, evolving systems characterized by profound spatial and temporal heterogeneity in their biological nature and response to treatment. Individual functional biomarkers that depict only one aspect of tumor physiology or biophysics are limited, and emerging studies have shown that their predictive performance varies among tumors with different subtypes. A multiparametric approach that combines information from functional imaging technologies with complementary sensitivities to the multifaceted underlying tumor physiology is needed to monitor NACT outcomes across different breast cancer types. To this end, the applicant has proposed to leverage a multimodal diffuse optical tomography, magnetic resonance imaging (MRI), and MR elastography imaging platform to test the main hypotheses that 1) multifunctional optical, MRI and elastography data can be acquired efficiently in healthy female volunteers using a multimodal breast MR coil; 2) the developed multiparametric imaging markers outperform individual markers from individual imaging modalities in predicting pathologic complete response as early as at the conclusion of the first cycle of treatment in breast cancer patients undergoing NACT; and 3) the predictive performance of multiparametric imaging markers is not significantly different among breast cancer subtypes. This approach will help us gain a comprehensive understanding of the multitude of simultaneous physiological changes in tumors related to microenvironment, angiogenesis, and metabolism as a result of NACT. Once validated, in the longer term, it also has the potential to advance response-guided targeted therapy, the approach demonstrated in the recent GeparTrio trial that can lead to significantly higher disease-free and overall survival rates. The success of the research project and training is ensured by a team of mentors and collaborators with complementary scientific expertise and substantia... ## Key facts - **NIH application ID:** 10020405 - **Project number:** 5K01EB027726-02 - **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL - **Principal Investigator:** Bin Deng - **Activity code:** K01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $140,826 - **Award type:** 5 - **Project period:** 2019-09-21 → 2023-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10020405 ## Citation > US National Institutes of Health, RePORTER application 10020405, Multiparametric multimodal imaging for breast cancer neoadjuvant chemotherapy monitoring (5K01EB027726-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10020405. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*