| 孙记航,王帆宁,段晓岷,刘勇,刘志敏,宋蕾,彭芸.自适应迭代重建技术结合高分辨算法提高儿童低剂量胸部CT肺脏病变显示的能力[J].中国医学影像技术,2017,33(5):773~777 |
| 自适应迭代重建技术结合高分辨算法提高儿童低剂量胸部CT肺脏病变显示的能力 |
| Improve image resolution in low-dose pediatric chest CT scans with combination of adaptive statistical iterative reconstruction and sharp recon kernel |
| 投稿时间：2016-10-07 修订日期：2016-12-07 |
| DOI：10.13929/j.1003-3289.201610011 |
| 中文关键词: 体层摄影术,X线计算机 自适应迭代技术 儿童 胸部 |
| 英文关键词:Tomography, X-ray computed Adaptive statistical iterative reconstruction Child Chest |
| 基金项目:首都临床特色应用研究（Z141107002514005）、北京儿童医院苗圃项目（BCH-YIPB-2016-06）。 |
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| 中文摘要: |
| 目的 探讨自适应迭代重建技术（ASIR）结合高分辨算法对儿童低剂量胸部CT肺部结构显示的影响。方法 回顾性分析接受低剂量胸部CT检查且存在肺内病变的患儿42例，0~12个月预设噪声指数12，>1~2岁预设噪声指数15，3~6岁预设噪声指数17，≥7岁预设噪声指数20。将所有图像应用Soft、Standard、Lung、Chest分辨率模式重建为层厚0.625 mm的图像。以10%为步涨值，重建ASIR权重为0%~100%的11组图像。由2名医师分别用5分制评分法主观评价肺窗图像质量，包括图像主观噪声、正常肺结构及病变的显示能力，5分为最佳。统计学分析比较最佳的后处理算法，以及与之匹配的最佳ASIR权重。结果 Lung模式为观察肺部病变最佳的高分辨算法，ASIR 60%权重重建图像主观评分最佳。结论 采用ASIR 60%权重结合Lung高分辨算法可更好地显示儿童低剂量胸部CT的肺部结构。 |
| 英文摘要: |
| Objective To explore the value of adaptive statistical iterative reconstruction (ASIR) and a sharp recon kernel to obtain high resolution pulmonary images in low-dose pediatric chest CT scans. Methods Totally 42 children underwent low-dose chest CT scans with ASIR were included. Age-dependent noise index (NI) was used for dose optimization:NI=12 for 0-12 months old, NI=15 for >1-2 years old, NI=17 for 3-6 years old and NI=20 for≥7 years old. Images were reconstructed to 0.625 mm using different recon kernels:Soft, Standard, Lung, and Chest kernel. ASIR blending was varied from 0-100% to provide balanced image noise and spatial resolution. Two radiologists independently evaluated images for normal lung structures, abnormal CT findings and image noise on a 5-point scale with 3 being clinically acceptable. The best kernel, as well as the match with the best ASIR weight were analyzed statistically. Results CT images with lung kernel and ASIR 60% were rated substantially better than those kernel. Conclusion ASIR 60% with a sharp lung kernel can significantly improve image quality in low-dose pediatric chest CT scans. |
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