The important contribution of computed tomography (CT) to modern medicine is readily apparent. Recently, the issue of the radiation dose related to body CT has received considerable attention, in part because of its success and high rate of clinical utilization. Because the absence of a non-zero risk related to the current levels of radiation exposures from CT cannot be conclusively proven, there is a dire need for more robust dose reduction strategies at body CT. This, however, must be implemented without a significant compromise in diagnostic accuracy. The overarching objective of the proposal is to develop, optimize, and evaluate an iterative image reconstruction algorithm that holds a promise to reduce radiation dose by 70%-90% from current levels, without compromising diagnostic accuracy. By employing the proposed DR-PICCS reconstruction, sub-mSv abdominal CT scanning with preserved diagnostic accuracy may be achievable for a number of clinical applications, such as evaluation for urolithiasis and colorectal polyps. For other diagnostic imaging applications, dose reductions on the order of 70%-90% may be possible, again with preserved diagnostic performance. Preliminary results from our retrospective and prospective pilot studies have demonstrated the feasibility of the proposed study by our collaborative translational research group. The following specific aims will be carried out to accomplish our proposed overall objective: (1) Optimization of the DR-PICCS implementation for ultra-low-dose abdominal CT imaging;(2) Prospective validation of ultra-low- dose diagnostic abdominal CT images reconstructed with DR-PICCS reconstruction algorithm.
This aim i ncludes demonstration of equivalence in image noise and diagnostic accuracy between ultra-low-dose DR- PICCS reconstructions and current standard-of-care dose FBP images;and performance comparison of ultra- low-dose CT with DR-PICCS against other commercially-available reconstruction techniques;and (3) Prospective validation of sub-mSv CT imaging for virtual colonoscopy (CT colonography) screening. Successful completion of this project will provide valuable information about the clinical feasibility and utility of ultra-low-dose abdominal CT imaging, including optimization of a practical technique (Aim 1), validation of diagnostic accuracy (Aim 2), and application to colorectal cancer screening (Aim 3). The successful completion of the project will also provide a methodological paradigm and unique CT data sets needed to clinically evaluate other ultra-low-dose CT imaging reconstruction methods.

Public Health Relevance

Because a non-zero cancer risk related to radiation exposures from medical imaging is generally assumed, public concern has been appropriately raised for CT exams. Although the risk has not been conclusively proven, there is nonetheless a dire need for more robust dose reduction strategies in body CT. This project is dedicated to developing, optimizing, and evaluating an innovative image reconstruction method that holds tremendous promise to reduce the CT radiation dose levels well below the mean annual radiation dose level (3.0m mSv) received from natural background sources - sub-mSv in many cases. The success of the project will further maximize the medical benefit of CT, while minimizing its potential side effects.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA169331-03
Application #
8676482
Study Section
Special Emphasis Panel (ZRG1-DTCS-U (81))
Program Officer
Henderson, Lori A
Project Start
2012-08-08
Project End
2017-05-31
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
3
Fiscal Year
2014
Total Cost
$1
Indirect Cost
Name
University of Wisconsin Madison
Department
Physics
Type
Schools of Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Gomez-Cardona, Daniel; Cruz-Bastida, Juan Pablo; Li, Ke et al. (2016) Impact of bowtie filter and object position on the two-dimensional noise power spectrum of a clinical MDCT system. Med Phys 43:4495
Gomez-Cardona, Daniel; Li, Ke; Hsieh, Jiang et al. (2016) Can conclusions drawn from phantom-based image noise assessments be generalized to in vivo studies for the nonlinear model-based iterative reconstruction method? Med Phys 43:687-95
Bannas, Peter; Li, Yinsheng; Motosugi, Utaroh et al. (2016) Prior Image Constrained Compressed Sensing Metal Artifact Reduction (PICCS-MAR): 2D and 3D Image Quality Improvement with Hip Prostheses at CT Colonography. Eur Radiol 26:2039-46
Cruz-Bastida, Juan P; Gomez-Cardona, Daniel; Li, Ke et al. (2016) Hi-Res scan mode in clinical MDCT systems: Experimental assessment of spatial resolution performance. Med Phys 43:2399
Pooler, B Dustin; Lubner, Meghan G; Kim, David H et al. (2016) Prospective Evaluation of Reduced Dose Computed Tomography for the Detection of Low-Contrast Liver Lesions: Direct Comparison with Concurrent Standard Dose Imaging. Eur Radiol :
Pickhardt, Perry J (2016) Emerging stool-based and blood-based non-invasive DNA tests for colorectal cancer screening: the importance of cancer prevention in addition to cancer detection. Abdom Radiol (NY) 41:1441-4
Furusato Hunt, Oliver M; Lubner, Meghan G; Ziemlewicz, Timothy J et al. (2016) The Liver Segmental Volume Ratio for Noninvasive Detection of Cirrhosis: Comparison With Established Linear and Volumetric Measures. J Comput Assist Tomogr 40:478-84
Gomez-Cardona, Daniel; Nagle, Scott K; Li, Ke et al. (2015) Influence of radiation dose and reconstruction algorithm in MDCT assessment of airway wall thickness: A phantom study. Med Phys 42:5919-27
Li, Ke; Gomez-Cardona, Daniel; Hsieh, Jiang et al. (2015) Statistical model based iterative reconstruction in clinical CT systems. Part III. Task-based kV/mAs optimization for radiation dose reduction. Med Phys 42:5209-21
Pickhardt, Perry J (2015) Recent developments in colorectal imaging. Curr Opin Gastroenterol 31:76-80

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