The routine use of cross-sectional imaging has resulted in a significant increase in the age-adjusted incidence of renal cell carcinoma (RCC). However, this has not translated into a decrease in cancer specific deaths, suggesting the possible over treatment of small, potentially indolent renal tumors. Thus, active surveillance of RCC has been proposed for small tumors. However, the natural history of these tumors remains unknown. Angiogenesis and tumor necrosis correlate with prognosis and metastatic potential in RCC. Inactivation of the VHL gene, HIF upregulation, and VEGF over- expression form the molecular basis of the enhanced angiogenesis associated with RCC. Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI) method for measuring blood flow by manipulating the signal from inflowing arterial blood. ASL blood flow correlates tightly to vascularity in RCC. The apparent diffusion coefficient (ADC) in RCC, measured with diffusion-weighted imaging (DWI), correlates with tumor cellularity at pathology. We seek to identify vascular and diffusion MRI measures in RCC in vivo that correlate to spatially-co-registered molecular alterations promoting angiogenesis and hypoxia and predict aggressive behavior. The spatial synchronization of various tissue-based analyses with in vivo alterations in tumor perfusion and hypoxia may help develop more robust imaging biomarkers to predict the biologic behavior of RCC. If successful, these imaging biomarkers will be immediately applicable to clinical practice and will help selecting patients for active surveillance.

Public Health Relevance

The aim of the proposed research is to investigate the correlation between in vivo magnetic resonance imaging (MRI) measures of blood flow and cellularity with the molecular alterations that promote angiogenesis and necrosis in renal cell carcinoma (RCC) and to correlate these to the biologic behavior of these tumors. Quantitative measures of blood flow and cellularity will be obtained with arterial spin labeling (ASL) and diffusion weighted imaging (DWI), respectively.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-DTCS-A (81))
Program Officer
Henderson, Lori A
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Texas Sw Medical Center Dallas
Schools of Medicine
United States
Zip Code
Bowman, Isaac A; Pedrosa, Ivan; Kapur, Payal et al. (2017) Renal Cell Carcinoma With Pulmonary Metastasis and Metachronous Non-Small Cell Lung Cancer. Clin Genitourin Cancer 15:e675-e680
Diaz de Leon, Alberto; Pedrosa, Ivan (2017) Imaging and Screening of Kidney Cancer. Radiol Clin North Am 55:1235-1250
Zhang, Yue; Udayakumar, Durga; Cai, Ling et al. (2017) Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI. JCI Insight 2:
Costa, Daniel N; Chatzinoff, Yonatan; Passoni, Niccolo M et al. (2017) Improved Magnetic Resonance Imaging-Pathology Correlation With Imaging-Derived, 3D-Printed, Patient-Specific Whole-Mount Molds of the Prostate. Invest Radiol 52:507-513
Gu, Yi-Feng; Cohn, Shannon; Christie, Alana et al. (2017) Modeling Renal Cell Carcinoma in Mice: Bap1 and Pbrm1 Inactivation Drive Tumor Grade. Cancer Discov 7:900-917
Kay, Fernando U; Pedrosa, Ivan (2017) Imaging of Solid Renal Masses. Radiol Clin North Am 55:243-258
Madhuranthakam, Ananth J; Yuan, Qing; Pedrosa, Ivan (2017) Quantitative Methods in Abdominal MRI: Perfusion Imaging. Top Magn Reson Imaging 26:251-258
Nofiele, Joris; Yuan, Qing; Kazem, Mohammad et al. (2016) An MRI-compatible platform for one-dimensional motion management studies in MRI. Magn Reson Med 76:702-12
Yokoo, Takeshi; Clark, Haley R; Pedrosa, Ivan et al. (2016) Quantification of renal steatosis in type II diabetes mellitus using dixon-based MRI. J Magn Reson Imaging 44:1312-1319
Yuan, Qing; Kapur, Payal; Zhang, Yue et al. (2016) Intratumor Heterogeneity of Perfusion and Diffusion in Clear-Cell Renal Cell Carcinoma: Correlation With Tumor Cellularity. Clin Genitourin Cancer 14:e585-e594

Showing the most recent 10 out of 23 publications