BACKGROUND Dual-layer spectral detector CT (SDCT) may provide several theoretical advantages over pre-existing DECT approaches in terms of adjustment-free sampling number and dose modulation, beam hardening correction, and production spectral images by post-processing. In addition, by adopting noise reduction algorithm, high contrast resolution was expected even in low keV level. We surmised that this improvement would be beneficial to obese people. Therefore, our aim of study is to compare image quality of virtual monochromatic spectral images (VMI) and polychromatic images reconstructed from SDCT with different body size and radiation dose using anthropomorphic liver phantom. METHODS One small and one large size of body phantoms, each containing eight (four high- and four low-contrast) simulated focal liver lesions (FLLs) were scanned by SDCT (at 120 kVp) using different Dose Right Indexes (DRIs). VMI were reconstructed from spectral base images from 40 keV to 200 keV. Hybrid iterative reconstruction (iDose4) was used for polychromatic image reconstruction. Image noise and contrast to noise ratio (CNR) were compared. Five radiologists independently rated lesion conspicuity, diagnostic acceptability and subjective noise level in every image sets, and determined optimal keV level in VMI. RESULTS Compare with conventional polychromatic images, VMI showed superior CNR at low keV level regardless of phantom size at every examined DRIs (Ps < 0.05). As body size increased, VMI had more gradual CNR decrease and noise increase than conventional polychromatic images. For low contrast FLLs in large phantom, lesion conspicuities at low radiation dose levels (DRI 16 and 19) were significantly increased in VMI (Ps < 0.05). Subjective image noise and diagnostic acceptabilities were significantly improved at VMI in both phantom size. CONCLUSIONS VMI of dual-layer spectral detector CT with noise reduction algorithm provides improved CNR, noise reduction, and better subjective image quality in imaging of obese simulated liver phantom compared with polychromatic images. This may hold promise for improving detection of liver lesions and improved imaging of obese patients.

中文翻译：

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双层能谱探测器CT虚拟单色能谱图像降噪算法对改善肥胖模拟体模图像质量的价值

背景技术双层光谱检测器CT（SDCT）在免调整采样数量和剂量调制、束硬化校正以及通过后处理产生光谱图像方面可以提供优于现有DECT方法的多个理论优势。此外，通过采用降噪算法，即使在低keV水平下也有望获得高对比度分辨率。我们推测这种改善将对肥胖者有益。因此，我们的研究目的是比较虚拟单色光谱图像（VMI）和使用拟人肝脏模型从不同体型和辐射剂量的 SDCT 重建的多色图像的图像质量。方法 使用不同的剂量正确指数 (DRI) 通过 SDCT（120 kVp）扫描一大一小的身体模型，每个模型包含八个（四个高对比度和四个低对比度）模拟局灶性肝脏病变 (FLL)。VMI 是根据 40 keV 至 200 keV 的光谱基础图像重建的。混合迭代重建（iDose4）用于多色图像重建。比较了图像噪声和对比度噪声比（CNR）。五名放射科医生独立评估每个图像集中的病灶显着性、诊断可接受性和主观噪声水平，并确定 VMI 中的最佳 keV 水平。结果与传统的多色图像相比，VMI 在低 keV 水平下表现出优异的 CNR，无论每次检查的 DRI 的体模大小如何（Ps < 0.05）。随着身体尺寸的增加，VMI 比传统的多色图像有更逐渐的 CNR 下降和噪声增加。对于大型体模中的低对比度 FLL，VMI 中低辐射剂量水平（DRI 16 和 19）下的病变显着性显着增加（Ps < 0.05）。VMI 的两种体模尺寸的主观图像噪声和诊断可接受性均得到显着改善。结论 与多色图像相比，具有降噪算法的双层能谱探测器 CT 的 VMI 在肥胖模拟肝脏模型成像中提供了改进的 CNR、降噪和更好的主观图像质量。这可能有望改善肝脏病变的检测并改善肥胖患者的成像。