Investigating the Small Pixel Effect in Ultra-High Resolution Photon-Counting CT of the Lung

INVESTIGATIVE RADIOLOGY(2024)

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摘要
Objectives: The aim of this study was to investigate potential benefits of ultra-high resolution (UHR) over standard resolution scan mode in ultra-low dose photon-counting detector CT (PCD-CT) of the lung. Materials and methods: Six cadaveric specimens were examined with 5 dose settings using tin prefiltration, each in UHR (120 x 0.2 mm) and standard mode (144 x 0.4 mm), on a first-generation PCD-CT scanner. Image quality was evaluated quantitatively by noise comparisons in the trachea and both main bronchi. In addition, 16 readers (14 radiologists and 2 internal medicine physicians) independently completed a browser-based pairwise forced-choice comparison task for assessment of subjective image quality. The Kendall rank coefficient ( W ) was calculated to assess interrater agreement, and Pearson's correlation coefficient ( r ) was used to analyze the relationship between noise measurements and image quality rankings. Results: Across all dose levels, image noise in UHR mode was lower than in standard mode for scan protocols matched by CTDI vol ( P < 0.001). UHR examinations exhibited noise levels comparable to the next higher dose setting in standard mode ( P >= 0.275). Subjective ranking of protocols based on 5760 pairwise tests showed high interrater agreement ( W = 0.99; P <= 0.001) with UHR images being preferred by readers in the majority of comparisons. Irrespective of scan mode, a substantial indirect correlation was observed between image noise and subjective image quality ranking ( r = -0.97; P <= 0.001). Conclusions: In PCD-CT of the lung, UHR scan mode reduces image noise considerably over standard resolution acquisition. Originating from the smaller detector element size in fan direction, the small pixel effect allows for superior image quality in ultra-low dose examinations with considerable potential for radiation dose reduction.
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关键词
low-dose imaging,lung,photon-counting computed tomography,image noise,spectral shaping
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