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Spectral Detector Computed Tomography Pulmonary Angiography: Improved Diagnostic Assessment and Automated Estimation of Window Settings Angiography of Pulmonary Arteries From Novel Spectral Detector Computed Tomography Provides Improved Image Quality if Settings are Adjusted.
Journal of Computer Assisted Tomography 2018 November
OBJECTIVE: This study aimed to evaluate image quality (IQ) of virtual monoenergetic images (VMIs) from novel spectral detector computed tomography angiography of the pulmonary arteries and to identify appropriate window settings for each kiloelectron volt level.
MATERIALS: Forty consecutive patients were included in this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study.Signal- and contrast-to-noise ratios were calculated within the pulmonary trunk, and pulmonary/lobar/segmental arteries were calculated. The IQ and diagnostic certainty were rated by 2 radiologists on 5-point scales. In addition, they recorded appropriate window settings (center/width) that were linearly modeled against attenuation within the pulmonary trunk to generate generable results.
RESULTS: Signal- and contrast-to-noise ratios, IQ, and diagnostic certainty are significantly increased in low-kiloelectron volt VMIs (≤60 keV). Interrater agreement was excellent (ĸ = 0.89). We developed 2 linear models (R: 0.91-0.97 and R: 0.43-0.91, respectively, P ≤ 0.01), that suggest appropriate window settings.
CONCLUSIONS: The VMIs from spectral detector computed tomography improve objective and subjective IQ in angiography of the pulmonary arteries, if window settings are adjusted; they can be automatically estimated using reported linear models.
MATERIALS: Forty consecutive patients were included in this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study.Signal- and contrast-to-noise ratios were calculated within the pulmonary trunk, and pulmonary/lobar/segmental arteries were calculated. The IQ and diagnostic certainty were rated by 2 radiologists on 5-point scales. In addition, they recorded appropriate window settings (center/width) that were linearly modeled against attenuation within the pulmonary trunk to generate generable results.
RESULTS: Signal- and contrast-to-noise ratios, IQ, and diagnostic certainty are significantly increased in low-kiloelectron volt VMIs (≤60 keV). Interrater agreement was excellent (ĸ = 0.89). We developed 2 linear models (R: 0.91-0.97 and R: 0.43-0.91, respectively, P ≤ 0.01), that suggest appropriate window settings.
CONCLUSIONS: The VMIs from spectral detector computed tomography improve objective and subjective IQ in angiography of the pulmonary arteries, if window settings are adjusted; they can be automatically estimated using reported linear models.
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