Recent advances in the understanding of cancer biology have led to an increased number of cancer therapies. The evaluation of these new therapies in human clinical trials is associated with high cost and potential risks. Imaging approaches can play an important role in this evaluation by identifying patients who respond to treatments. The current radiological assessment of treatment outcomes predominantly relies on changes in tumor size. This is a major limiting factor as the effects of many therapeutic agents at the microscopic level precede changes in tumor size. One such tumor property that has been extensively targeted for new cancer therapies is tumor angiogenesis (or perfusion), which has been shown to support tumor proliferation and infiltration. We have recently developed a quantitative magnetic resonance imaging (MRI) technique, called Arterial Spin Labeling (ASL) that can measure tumor perfusion non-invasively and without the administration of exogenous contrast agent. ASL MRI uses highly permeable water as a tracer, by magnetically labeling the water proton in the arterial blood and measuring their accumulation in the tissue of interest. We have used ASL to monitor therapy response in multiple clinical trials and have shown that ASL measured tumor perfusion decreased as early as 8 days after the initiation of antiangiogenic therapy in patients with renal cell carcinoma (RCC), much earlier than the tumor size changes. However, ASL has not undergone a robust and rigorous validation process to be established as a quantitative imaging method. In this project, we will validate ASL measured perfusion as a quantitative imaging marker to evaluate treatment response in patients with brain tumors (glioblastoma multiforme, GBM) and metastatic RCC, two known highly vascularized tumors.
The specific aims of the project are: 1) To demonstrate the reliability and precision of ASL measured perfusion in the brain and kidneys of 30 normal volunteers; 2) To predict clinical outcomes based on baseline (pre- treatment) perfusion and early changes in post-treatment perfusion in 40 patients with newly diagnosed GBM undergoing chemoradiation therapy; and 3) To predict long-term outcomes based on baseline (pre-treatment) perfusion and early changes in post-treatment perfusion in 40 patients with metastatic RCC undergoing antiangiogenic therapies. In the first aim, we will also develop quality-control protocols using a novel 3D printed perfusion phantom, currently available at UT Southwestern (UTSW) Medical Center to measure the reliability and precision of ASL measured flow. In the second and third aims, we will incorporate automated and semi- automated methods for tumor segmentation and analysis, such that these results can be replicated elsewhere. The patients for aims 2 and 3 will be recruited from ongoing clinical trials at UTSW. In both these aims, we will test our hypothesis that greater reduction in tumor perfusion immediately after treatment, compared to baseline correlates with improved progression free survival and overall survival. Such early changes in ASL measured perfusion may predict tumor responsiveness better than anatomical imaging, thereby affecting patient management in a timely manner by changing treatments that may be ineffective and potentially toxic.
The proposed project will validate a non-invasive perfusion technique called Arterial Spin Labeled (ASL) MRI in the evaluation of treatment response in patients with advanced brain tumors (glioma) or advanced kidney cancer (metastatic renal cell carcinoma). The current radiological assessment of treatment outcomes predominantly relies on changes in tumor size, however, the effects of many therapeutic agents at the microscopic level precede changes in tumor size. ASL can be used as an early imaging marker to predict tumor responsiveness to cancer therapy better than tumor size changes, thereby informing clinical decisions to maintain or change treatments that may be ineffective and potentially toxic.
| Wang, Xinzeng; Pirasteh, Ali; Brugarolas, James et al. (2018) Whole-body MRI for metastatic cancer detection using T2 -weighted imaging with fat and fluid suppression. Magn Reson Med 80:1402-1415 |
| Krajewski, Katherine M; Pedrosa, Ivan (2018) Imaging Advances in the Management of Kidney Cancer. J Clin Oncol :JCO2018791236 |
