With the growing use of computed tomography (CT) and the increasing awareness of radiation risk, important areas of research concern (1) optimizing CT clinical applications to minimize radiation dose and (2) developing methods to accurately assess radiation risk from examinations. Due to radiation concerns in patients and the limited number of physical phantoms that do not reflect the variability of patient anatomy, such research can only be performed using a population of realistic computational phantoms, which currently does not exist. Current phantoms used in CT are limited to only a handful of models, most being adults. In the previous project, we developed the new 4D XCAT computational phantom for use in 3D and 4D CT research. Based on high-resolution imaging data, we created detailed whole-body models for the male and female XCAT adult, including the cardiac and respiratory motions, containing over 9000 anatomical structures. In part one of this renewal, we will extend the XCAT beyond these adult models by utilizing innovative methods in computational anatomy, that have long been used to characterize anatomical variations in populations, to efficiently create an unprecedented library of hundreds of highly detailed 4D XCAT phantoms. The models will realistically represent the full spectrum of the public at large including both genders, and varying ages, heights, and weights from infancy to adulthood. The ability to model anatomical variations is essential to CT imaging optimization. A population of phantoms that includes a range of anatomical variations representative of the public at large is needed to more closely mimic a clinical study or trial. Such a library of anatomically diverse phantoms also offers the only practical technique with which to estimate patient-specific CT dose and associated radiation risk. In the second part of this project, the library will be combined with an accurate Monte Carlo dose estimation program, developed and validated in this work, to investigate patient-based and population-based dose correlations in CT. The findings will be used to establish a patient-specific retrospective and prospective CT dose reporting system. Such a system will be instrumental in proper documentation of radiation risk, justifiable use of CT examination, and optimization of clinical CT applications in terms of image quality and radiation dose, particularly in vulnerable populations. It further supports the current mandate to account for cumulative radiation dose exposure from medical imaging. Distributed to the research community, the dosimetry methods and the phantom library will provide vital tools to quantitatively evaluate and improve 3D and 4D CT imaging devices and techniques.

Public Health Relevance

In this renewal, we will create an unprecedented library of hundreds of detailed 4D computational models realistically representing a wide population of subjects including both genders, and varying ages, heights and weights (10th to 90th percentile) encompassing the full range from pediatric to adult patients. The phantom series developed in this work will provide a vital tool with which to optimize clinical CT applications in terms of image quality and radiation dose and to accurately estimate patient-specific CT dose (both effective dose and organ dose) and associated radiation risk.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB001838-06
Application #
8116522
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Pai, Vinay Manjunath
Project Start
2003-12-01
Project End
2014-05-31
Budget Start
2011-06-01
Budget End
2012-05-31
Support Year
6
Fiscal Year
2011
Total Cost
$393,315
Indirect Cost
Name
Duke University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
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Robins, Marthony; Solomon, Justin; Sahbaee, Pooyan et al. (2017) Techniques for virtual lung nodule insertion: volumetric and morphometric comparison of projection-based and image-based methods for quantitative CT. Phys Med Biol 62:7280-7299
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