Aim 1) To develop and optimize micro-MRI and micro-CT for quantitative imaging of tumors.
We will employ a similar approach as QIBA to create two profiles for small animal imaging of cancer that match the imaging requirements of the co-clinical trial in humans: i) micro-MRI primary tumor size assessments and ii) micro-CT lung metastases size assessments. These two profiles will address the bias and precision of quantitative micro-MRI and micro-CT measurements. We will formulate requirements on Animal Set-up, Image Acquisition, and Reconstruction and Analysis methods. The bias and precision will be verified by correlation with histologic analysis performed after necropsy.
Aim 2) To implement the optimized preclinical imaging profiles in a co-clinical sarcoma trial.
After optimizing our imaging, we will perform the preclinical equivalent of the SARC032 clinical trial focused on understanding the efficacy of neoadjuvant radiotherapy combined with PD-1 inhibitors followed by surgical resection and adjuvant PD-1 inhibitors. We will use a genetically engineered primary mouse model of sarcoma that closely mimics the physiology and gene expression of UPS, the most common human soft tissue sarcoma. Micro-MRI will be used to assess changes in primary tumor size before surgery, while chest micro-CT will be used to assess lung metastases. In vivo imaging data will be correlated with biologic data, such as histologic assessment of tumor size, percent necrosis and metastatic disease burden. We will test if the preclinical trial predicts the outcome of the clinical trial.
Aim 3) To provide a web-accessible research resource with micro-MRI and micro-CT tumor data, methods, and workflow documentation. We embrace the three pillars of open science: data, code, and publications. Data-sharing is crucial. At critical milestones in the projects, data will be curated and loaded into the Quantitative Imaging Network (QIN) and Quantitative Imaging Data Warehouse (QIDW), national repositories under QIBA guidance.