Photon-counting CT (PCCT) is a major technological advance in CT imaging. Using photon-counting instead of current energy-integrating detectors, PCCT can offer superior performance in terms of spatial resolution, artifact reduction, and most notably, material decomposition. PCCT?s energy differentiation utility offers an ability to more precisely distinguish different materials and optimize and expand the use of contrast agents in CT. With these abilities, PCCT can significantly facilitate quantitative imaging, reduce radiation exposure, and enable revolutionary new applications in functional and physiological imaging beyond existing CT techniques. To realize the full potential of PCCT in clinical practice, the technology needs comprehensive assessments and application-based optimizations. Effective design and deployment of PCCT depends on many design and use choices that should be made in view of the eventual clinical utility. Making these choices requires large scale trials on actual patients. However, such trials are challenging, considering the need to make many decisions prior to prototyping, the limited numbers of prototype PCCT scanners available today, and the often-unknown ground-truth in the patient images. Even for existing prototype systems, many decisions require repetitive trials with multiple acquisitions. This is both unethical and impractical considering radiation safety concerns and costs. These challenges can be overcome by utilizing virtual imaging trials (VITs) using computerized patients and imaging models. VITs provide an efficient means with which to determine the most effective and optimized design and use of imaging technologies with complete control over the study design. In our prior funded project, we developed a VIT framework to evaluate standard energy-integrating detector CT technologies. In this project, we expand the applicability of this framework to photon-counting detector CT. Specifically, we enhance our computational XCAT phantoms to model the necessary higher-resolution detail including normal and abnormal tissue heterogeneities and intra-organ contrast perfusion diversity across populations (Aim 1). To image the phantoms, we develop the first PCCT simulator capable of mimicking existing and emerging prototypes (Aim 2). The enhanced VIT framework will provide the essential foundation with which to comprehensively evaluate and optimize PCCT technologies and applications.
In Aim 3, we assess and optimize the use of PCCT for morphological, textural, and compositional quantification in select oncologic and cardiac applications, two leading health detriments in the US where PCCT can offer a notable impact. The results will be the first of their kind in comprehensively evaluating the task-based merits and capabilities of PCCT, determining optimum dose per patient size for PCCT imaging of patients for cancerous lesions and cardiac plaque/stenoses, and helping to establish the effective utility of PCCT in clinical care.

Public Health Relevance

The purpose of this project is to develop and utilize a virtual framework to comprehensively evaluate and optimize emerging photon-counting devices and applications in CT imaging. The results will be the first of their kind evaluating the task-based merits and capabilities of photon-counting CT and will help establish its effectual utility in oncologic and cardiac care.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
2R01EB001838-13
Application #
10051026
Study Section
Emerging Imaging Technologies and Applications Study Section (EITA)
Program Officer
Shabestari, Behrouz
Project Start
2005-09-22
Project End
2024-03-31
Budget Start
2020-07-01
Budget End
2021-03-31
Support Year
13
Fiscal Year
2020
Total Cost
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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Abadi, Ehsan; Segars, William P; Sturgeon, Gregory M et al. (2018) Modeling Lung Architecture in the XCAT Series of Phantoms: Physiologically Based Airways, Arteries and Veins. IEEE Trans Med Imaging 37:693-702
Sahbaee, Pooyan; Abadi, Ehsan; Segars, W Paul et al. (2017) The Effect of Contrast Material on Radiation Dose at CT: Part II. A Systematic Evaluation across 58 Patient Models. Radiology 283:749-757
Dasari, Paul K R; Könik, Arda; Pretorius, P Hendrik et al. (2017) Correction of hysteretic respiratory motion in SPECT myocardial perfusion imaging: Simulation and patient studies. Med Phys 44:437-450
Knoll, Peter; Rahmim, Arman; Gültekin, Selma et al. (2017) Improved scatter correction with factor analysis for planar and SPECT imaging. Rev Sci Instrum 88:094303
Hoye, Jocelyn; Zhang, Yakun; Agasthya, Greeshma et al. (2017) Organ dose variability and trends in tomosynthesis and radiography. J Med Imaging (Bellingham) 4:031207
Sahbaee, Pooyan; Segars, W Paul; Marin, Daniele et al. (2017) The Effect of Contrast Material on Radiation Dose at CT: Part I. Incorporation of Contrast Material Dynamics in Anthropomorphic Phantoms. Radiology 283:739-748
Sturgeon, Gregory M; Park, Subok; Segars, William Paul et al. (2017) Synthetic breast phantoms from patient based eigenbreasts. Med Phys 44:6270-6279
Carver, Diana E; Kost, Susan D; Fraser, Nicholas D et al. (2017) Realistic phantoms to characterize dosimetry in pediatric CT. Pediatr Radiol 47:691-700
Sanders, Jeremiah; Tian, Xiaoyu; Segars, William Paul et al. (2017) Automated, patient-specific estimation of regional imparted energy and dose from tube current modulated computed tomography exams across 13 protocols. J Med Imaging (Bellingham) 4:013503

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