Despite widespread concerns over radiation dose, CT continues to be widely used for assessing response to therapy in many clinical trials settings. There have been significant developments which allow the reduction of radiation dose from CT, including advances in iterative reconstruction techniques, detector technologies and others that promise significant dose reductions (50-60 percent) to patients, while maintaining clinical image quality. While these technologies should be investigated wherever possible in a clinical environment, their effects on quantitative measures extracted from CT images are unclear and need to be investigated before they are deployed in clinical trials. Simply reducing tube current time product (mAs) will increase image noise, which may increase variability in quantitative measures. Size measures may be affected differently depending on the anatomic region;lung lesions (typically high contrast objects) may be affected differently from liver lesions (typically lower contrast). Peak values measured when contrast enhanced studies are used may also respond to dose reductions differently. In addition, because new iterative reconstruction methods reduce noise, they often also smooth the image somewhat, which may affect size and density (e.g. average HU) measures. Therefore, this application proposes to systematically investigate the effects of radiation dose reduction methods on quantitative metrics used in clinical trials. The goal is to determine how far we can decrease dose under different conditions before we increase variance to unacceptable levels in the context of clinical trials using quantitative measures to assess response to therapy. We have proposed three specific aims to carry out this research. In the first aim, we propose to create a collection of cases that represen a range of low dose acquisition and reconstruction scenarios in specific quantitative imaging tasks. This will be accomplished using a calibrated dose reduction simulation method (noise insertion tool) and then reconstructing images under a wide variety of dose reduction levels and reconstruction methods. The second specific aim will be to extract quantitative Imaging measures from these reconstructed image data sets and analyze variance of quantitative measures across dose levels and reconstruction methods. The third will use the results of the second aim's analysis to evaluate reduced dose imaging effects in a prospective clinical trial. The overall goal is to provide guidance to the QIN, and clinical trials in general, regarding the use of both standardized protocols and the use of dose reduction methods, with the ultimate goal of determining the levels of dose reduction that yield acceptable levels of measurement variance in several assessment tasks/environments.
The overall goal of the proposed research is to investigate the effects of radiation dose reduction techniques used in CT imaging on quantitative measures used in response assessment of patients in clinical trials. The goal is to be able to guide clinica trials so that they will be able to use the lowest radiation dose possible while maintaining the integrity of the quantitative measures needed to assess response. This would allow patients undergoing clinical trials to reduce and risks from radiation exposure due to their CT imaging studies.
|Young, Stefano; Lo, Pechin; Kim, Grace et al. (2017) The effect of radiation dose reduction on computer-aided detection (CAD) performance in a low-dose lung cancer screening population. Med Phys 44:1337-1346|
|Lo, P; Young, S; Kim, H J et al. (2016) Variability in CT lung-nodule quantification: Effects of dose reduction and reconstruction methods on density and texture based features. Med Phys 43:4854|
|Kalpathy-Cramer, Jayashree; Mamomov, Artem; Zhao, Binsheng et al. (2016) Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features. Tomography 2:430-437|
|Hoffman, John; Young, Stefano; Noo, Frédéric et al. (2016) Technical Note: FreeCT_wFBP: A robust, efficient, open-source implementation of weighted filtered backprojection for helical, fan-beam CT. Med Phys 43:1411-20|
|Young, Stefano; Kim, Hyun J Grace; Ko, Moe Moe et al. (2015) Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods. Med Phys 42:2679-89|