# The Duke Preclinical Research Resources for Quantitative Imaging Biomarkers > **NIH NIH U24** · DUKE UNIVERSITY · 2020 · $448,416 ## Abstract Abstract Quantitative imaging approaches are currently being standardized for clinical medicine by the Quantitative Imaging Biomarkers Alliance (QIBA). However, similar efforts for preclinical imaging do not exist although the need for standardization is even more pressing because of the high degree of diversity that exists in preclinical imaging hardware and software. Compared to clinical (human) imaging, the technical challenges are significantly more difficult for the optimization of mouse model quantitative imaging. The goal of this proposal is to design, optimize and apply preclinical quantitative imaging with micro-magnetic resonance imaging (MRI) and micro- computed tomography (CT). Specifically, we will apply our quantitative imaging methods in a co- clinical trial which mirrors an on-going, multi-institutional, randomized phase II clinical trial that has a primary objective to investigate whether neoadjuvant radiotherapy combined with pembrolizumab followed by surgical resection and adjuvant pembrolizumab improves disease-free survival for patients with high-risk soft-tissue sarcoma of the extremity (undifferentiated pleomorphic sarcoma or dedifferentiated/pleomorphic liposarcoma) compared to radiotherapy alone followed by surgical resection. The trial aims to evaluate the 2- and 5-year recurrence-free survival and overall survival. MRI is used to assess the radiation treatment response and to plan for surgery. Chest CT is used during follow up to evaluate for distant tumor recurrence (lung metastases). For preclinical studies, we will use the Cre-loxP technology to generate primary sarcomas in the hind limb of mice. Our autochthonous tumor models closely mimic human soft tissue sarcomas in histologic appearance, gene expression, and clinical behavior, including lung metastasis development. For the metastatic tumor model, the primary tumor-bearing limb will be amputated and mice will be monitored for metastases. In our first specific aim, we will develop and optimize quantitative imaging with micro-MRI for primary soft tissue sarcoma tumors and micro-CT for lung metastases. We will follow similar methodologies proposed in the QIBA framework but adapted for small animal imaging. During the second aim, we will implement our optimized quantitative imaging methods in the co-clinical trial using our genetically engineered mouse models of sarcoma. We anticipate that radiotherapy with PD-1 inhibitors will improve metastasis-free survival. The preclinical experiments will provide greater understanding of mechanisms involved in these combined therapies and will inform future clinical trials. Finally, the last specific aim will focus on creating a web- accessible research resource for archiving and disseminating small animal imaging protocols and data. Imaging and biologic data, including pathology, will be robustly integrated for correlative studies. The expected outcome of this project is the standardization of micro-MRI and micro-CT preclinical... ## Key facts - **NIH application ID:** 9980797 - **Project number:** 5U24CA220245-04 - **Recipient organization:** DUKE UNIVERSITY - **Principal Investigator:** CRISTIAN T BADEA - **Activity code:** U24 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $448,416 - **Award type:** 5 - **Project period:** 2017-09-30 → 2022-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9980797 ## Citation > US National Institutes of Health, RePORTER application 9980797, The Duke Preclinical Research Resources for Quantitative Imaging Biomarkers (5U24CA220245-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9980797. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*