Physical Properties of Small Focal Spot Imaging with Deep Learning Reconstruction in Chest-abdominal Plain CT

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  • 胸腹部単純CT検査におけるdeep learning reconstructionを用いた小焦点撮影の物理特性
  • キョウ フクブ タンジュン CT ケンサ ニ オケル deep learning reconstruction オ モチイタ ショウショウテン サツエイ ノ ブツリ トクセイ

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Abstract

<p>Purpose: The aim of this study was to compare the physical properties of small focal spot imaging with deep learning reconstruction (DLR) and small or large focal spot imaging with hybrid iterative reconstruction (IR) in chest-abdominal plain computed tomography. Method: In small focal spot imaging using DLR and hybrid IR, tube currents were set at 350 mA. For the large focal spot imaging using hybrid IR, the tube current was set at 360, 400, 450, and 500 mA. The spatial frequencies with 50% task transfer function (TTF) for delrin and acrylic were calculated to compare spatial resolution properties for lung and soft tissue in the chest. Additionally, the low-contrast object-specific contrast-to-noise ratio (CNRLO) was measured as noise property was measured for a 7-mm module with a CT value contrast of 10 HU in the abdomen. Result: Spatial frequencies with 50% TTF for delrin and acrylic were found to be greater in small focal spot imaging using DLR compared to those in small and large focal spot imaging using hybrid IR. Moreover, the CNRLO obtained from small focal spot imaging with DLR was also nearly equivalent to that of large focal spot imaging with hybrid IR at tube currents of 450 and 500 mA. Conclusion: In chest-abdominal plain computed tomography, small focal spot imaging with DLR has been demonstrated to exhibit greater spatial resolution properties compared to small and large focal spot imaging with hybrid IR, with equivalent or better noise performance.</p>

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