Virtual clinical trial for quantifying the effects of beam collimation and pitch on image quality in computed tomography

Ehsan Abadi; William P. Segars; Brian Harrawood; Shobhit Sharma; Anuj Kapadia; Ehsan Samei

doi:10.1117/1.JMI.7.4.042806

Virtual clinical trial for quantifying the effects of beam collimation and pitch on image quality in computed tomography

Ehsan Abadi, William P. Segars, Brian Harrawood, Shobhit Sharma, Anuj Kapadia, Ehsan Samei

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Purpose: To utilize a virtual clinical trial (VCT) construct to investigate the effects of beam collimation and pitch on image quality (IQ) in computed tomography (CT) under different respiratory and cardiac motion rates. Approach: A computational human model [extended cardiac-torso (XCAT) phantom] with added lung lesions was used to simulate seven different rates of cardiac and respiratory motions. A validated CT simulator (DukeSim) was used in this study. A supplemental validation was done to ensure the accuracy of DukeSim across different pitches and beam collimations. Each XCAT phantom was imaged using the CT simulator at multiple pitches (0.5 to 1.5) and beam collimations (19.2 to 57.6 mm) at a constant dose level. The images were compared against the ground truth using three task-generic IQ metrics in the lungs. Additionally, the bias and variability in radiomics (morphological) feature measurements were quantified for task-specific lung lesion quantification across the studied imaging conditions. Results: All task-generic metrics degraded by 1.6% to 13.3% with increasing pitch. When imaged with motion, increasing pitch reduced motion artifacts. The IQ slightly degraded (1.3%) with changes in the studied beam collimations. Patient motion exhibited negative effects (within 7%) on the IQ. Among all features across all imaging conditions studies, compactness2 and elongation showed the largest (-26.5 %, 7.8%) and smallest (-0.8 %, 2.7%) relative bias and variability. The radiomics results were robust across the motion profiles studied. Conclusions: While high pitch and large beam collimations can negatively affect the quality of CT images, they are desirable for fast imaging. Further, our results showed no major adverse effects in morphology quantification of lung lesions with the increase in pitch or beam collimation. VCTs, such as the one demonstrated in this study, represent a viable methodology for experiments in CT.

Original language	English
Article number	042806
Journal	Journal of Medical Imaging
Volume	7
Issue number	4
DOIs	https://doi.org/10.1117/1.JMI.7.4.042806
State	Published - Jul 1 2020
Externally published	Yes

Funding

This study was supported by a research grant from the National Institutes of Health [R01EB001838]. The authors would like to thank Karl Stierstorfer, Martin Sedlmair, and Juan Carlos Ramirez from Siemens Healthcare for providing us proprietary information, which enabled us to model a Siemens CT scanner. The authors also thank Thomas Sauer for providing the lesions used in this study.

Funders	Funder number
National Institutes of Health	R01EB001838

Keywords

CT simulator
computational human phantoms
computed tomography
in silico modeling
simulation
virtual clinical trial

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10.1117/1.JMI.7.4.042806

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title = "Virtual clinical trial for quantifying the effects of beam collimation and pitch on image quality in computed tomography",

abstract = "Purpose: To utilize a virtual clinical trial (VCT) construct to investigate the effects of beam collimation and pitch on image quality (IQ) in computed tomography (CT) under different respiratory and cardiac motion rates. Approach: A computational human model [extended cardiac-torso (XCAT) phantom] with added lung lesions was used to simulate seven different rates of cardiac and respiratory motions. A validated CT simulator (DukeSim) was used in this study. A supplemental validation was done to ensure the accuracy of DukeSim across different pitches and beam collimations. Each XCAT phantom was imaged using the CT simulator at multiple pitches (0.5 to 1.5) and beam collimations (19.2 to 57.6 mm) at a constant dose level. The images were compared against the ground truth using three task-generic IQ metrics in the lungs. Additionally, the bias and variability in radiomics (morphological) feature measurements were quantified for task-specific lung lesion quantification across the studied imaging conditions. Results: All task-generic metrics degraded by 1.6% to 13.3% with increasing pitch. When imaged with motion, increasing pitch reduced motion artifacts. The IQ slightly degraded (1.3%) with changes in the studied beam collimations. Patient motion exhibited negative effects (within 7%) on the IQ. Among all features across all imaging conditions studies, compactness2 and elongation showed the largest (-26.5 %, 7.8%) and smallest (-0.8 %, 2.7%) relative bias and variability. The radiomics results were robust across the motion profiles studied. Conclusions: While high pitch and large beam collimations can negatively affect the quality of CT images, they are desirable for fast imaging. Further, our results showed no major adverse effects in morphology quantification of lung lesions with the increase in pitch or beam collimation. VCTs, such as the one demonstrated in this study, represent a viable methodology for experiments in CT.",

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author = "Ehsan Abadi and Segars, {William P.} and Brian Harrawood and Shobhit Sharma and Anuj Kapadia and Ehsan Samei",

note = "Publisher Copyright: {\textcopyright} 2020 Society of Photo-Optical Instrumentation Engineers (SPIE).",

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AU - Abadi, Ehsan

AU - Segars, William P.

AU - Harrawood, Brian

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AB - Purpose: To utilize a virtual clinical trial (VCT) construct to investigate the effects of beam collimation and pitch on image quality (IQ) in computed tomography (CT) under different respiratory and cardiac motion rates. Approach: A computational human model [extended cardiac-torso (XCAT) phantom] with added lung lesions was used to simulate seven different rates of cardiac and respiratory motions. A validated CT simulator (DukeSim) was used in this study. A supplemental validation was done to ensure the accuracy of DukeSim across different pitches and beam collimations. Each XCAT phantom was imaged using the CT simulator at multiple pitches (0.5 to 1.5) and beam collimations (19.2 to 57.6 mm) at a constant dose level. The images were compared against the ground truth using three task-generic IQ metrics in the lungs. Additionally, the bias and variability in radiomics (morphological) feature measurements were quantified for task-specific lung lesion quantification across the studied imaging conditions. Results: All task-generic metrics degraded by 1.6% to 13.3% with increasing pitch. When imaged with motion, increasing pitch reduced motion artifacts. The IQ slightly degraded (1.3%) with changes in the studied beam collimations. Patient motion exhibited negative effects (within 7%) on the IQ. Among all features across all imaging conditions studies, compactness2 and elongation showed the largest (-26.5 %, 7.8%) and smallest (-0.8 %, 2.7%) relative bias and variability. The radiomics results were robust across the motion profiles studied. Conclusions: While high pitch and large beam collimations can negatively affect the quality of CT images, they are desirable for fast imaging. Further, our results showed no major adverse effects in morphology quantification of lung lesions with the increase in pitch or beam collimation. VCTs, such as the one demonstrated in this study, represent a viable methodology for experiments in CT.

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Virtual clinical trial for quantifying the effects of beam collimation and pitch on image quality in computed tomography

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