Feasibility Study Using Imaging Biomarkers in Lung Cancer

The recent report of the findings of the National Lung Screening Trial indicates that screening a high-risk population using low dose CT results in a 20% reduction in lung cancer mortality. At our institution, some of positive nodules that are 1 cm or larger would be imaged using combined fluoro-deoxyglucose positron emission tomography (FDG PET)/CT. Highly suspicious nodules would be biopsied if the risks were manageable. Otherwise, the suspicious nodules not eligible for biopsy and so-called "indeterminate" nodules are followed using CT to be evaluated for interval growth.

The overall goal of this project is to assess several very promising imaging biomarkers that can reflect either the physiological or metabolic status of these nodules in order to develop more accurate imaging algorithms for follow-up that are either less invasive or do not use ionizing radiation or both. Based on our experience with other cancers and our preliminary results in lung cancer, we have identified four potential imaging studies that we believe have the potential to result in validated "imaging biomarkers" that can either individually, or in combination, characterize malignancies. Since tumors tend to exhibit angiogenesis and altered vascular permeability, we and others, have found that analyses of dynamic contrast enhanced MRI (DCEMRI) can be employed as "imaging biomarkers" for malignancy. Tumors often exhibit higher cellularity than benign or normal tissue suggesting that pixel-by-pixel ADC values derived from diffusion weighted MRI could be useful imaging biomarkers. Finally, measuring alterations in metabolic fluxes through the use of pathway specific C-13 labeled compounds, a technique pioneered here at the Advanced Imaging Research Center (AIRC) at UT Southwestern, has shown the capability of providing metabolic fingerprints for malignant and benign tissue. This approach, while invasive, could identify and validate markers that can be detected non-invasively in future studies. We will also employ advanced metabolomics methods to identify potential signature "onco-metabolites" in these lung cancers.