Abstract

The lack of a coherent, evidence-based approach for determining the """"""""right"""""""" CT imaging protocol explains to a large degree the considerable variation in doses and techniques observed in clinical CT scanning and the recent injuries to patients undergoing CT brain imaging. A comprehensive, time-efficient, and translatable approach is needed to drive CT doses to the lowest levels that maintain acceptable diagnostic accuracy and to do so while keeping up with ever-changing technology. Our long term objective is to develop and validate quantitative methodsthat can quantitatively determine, for a specific diagnostic task, CT protocols that deliver the needed diagnostic accuracy at the lowest patient dose. The obiective of this project is to determine the tradeoffs between CT image quality and patient radiation dose in a way that moves beyond current simple models (e.g. standard deviation and CTDIvol) by investigating the relationships between task-based metrics of image quality, observer performance, patient size, and patient dose. This project was previously the 4th project in a POl proposal entitled Quantitative systematic development of dose-optimized CT imaging protocols {^ POl EB014221-01).

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB017095-03
Application #
8724217
Study Section
Special Emphasis Panel (ZEB1-OSR-D (M1))
Program Officer
Pai, Vinay Manjunath
Project Start
2012-09-20
Project End
2017-08-31
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
3
Fiscal Year
2014
Total Cost
$596,391
Indirect Cost
$194,663

  Institution

Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905

  Publications

Hardy, Anthony J; Bostani, Maryam; Hernandez, Andrew M et al. (2018) Estimating a size-specific dose for helical head CT examinations using Monte Carlo simulation methods. Med Phys :
Fletcher, Joel G; Fidler, Jeff L; Venkatesh, Sudhakar K et al. (2018) Observer Performance with Varying Radiation Dose and Reconstruction Methods for Detection of Hepatic Metastases. Radiology 289:455-464
Hardy, Anthony J; Bostani, Maryam; McMillan, Kyle et al. (2018) Estimating lung, breast, and effective dose from low-dose lung cancer screening CT exams with tube current modulation across a range of patient sizes. Med Phys 45:4667-4682
Gong, Hao; Yu, Lifeng; Leng, Shuai et al. (2018) Correlation between model observers in uniform background and human observers in patient liver background for a low-contrast detection task in CT. Proc SPIE Int Soc Opt Eng 10577:
Hanson, G Jay; Michalak, Gregory J; Childs, Robert et al. (2018) Low kV versus dual-energy virtual monoenergetic CT imaging for proven liver lesions: what are the advantages and trade-offs in conspicuity and image quality? A pilot study. Abdom Radiol (NY) 43:1404-1412
Ferrero, Andrea; Favazza, Christopher P; Yu, Lifeng et al. (2017) Practical implementation of Channelized Hotelling Observers: Effect of ROI size. Proc SPIE Int Soc Opt Eng 10132:
Yu, Lifeng; Chen, Baiyu; Kofler, James M et al. (2017) Correlation between a 2D channelized Hotelling observer and human observers in a low-contrast detection task with multislice reading in CT. Med Phys 44:3990-3999
Chen, Yang; Liu, Jin; Xie, Lizhe et al. (2017) Discriminative Prior - Prior Image Constrained Compressed Sensing Reconstruction for Low-Dose CT Imaging. Sci Rep 7:13868
Ferrero, Andrea; Chen, Baiyu; Li, Zhoubo et al. (2017) Technical Note: Insertion of digital lesions in the projection domain for dual-source, dual-energy CT. Med Phys 44:1655-1660
McCollough, Cynthia H; Bartley, Adam C; Carter, Rickey E et al. (2017) Low-dose CT for the detection and classification of metastatic liver lesions: Results of the 2016 Low Dose CT Grand Challenge. Med Phys 44:e339-e352

Showing the most recent 10 out of 30 publications