Ultralow-dose CT with tin filtration for detection of solid and sub solid pulmonary nodules: a phantom study

超低剂量CT结合锡滤过技术检测肺实性及亚实性结节:一项体模研究

阅读:1

Abstract

OBJECTIVES: To investigate the diagnostic performance of advanced modelled iterative reconstruction (ADMIRE) to filtered back projection (FBP) when using an ultralow-dose protocol for the detection of solid and subsolid pulmonary nodules. METHODS: Single-energy CT was performed at 100 kVp with tin filtration in an anthropomorphic chest phantom with solid and subsolid pulmonary nodules (2-10 mm, attenuation, 20 to -800 HU at 120 kVp). The mean volume CT dose index (CTDIvol) of the standard chest protocol was 2.2 mGy. Subsequent scans were obtained at 1/8 (0.28 mGy), 1/20 (0.10 mGy) and 1/70 (0.03 mGy) dose levels by lowering tube voltage and tube current. Images were reconstructed with FBP and ADMIRE. One reader measured image noise; two readers determined image quality and assessed nodule localization. RESULTS: Image noise was significantly reduced using ADMIRE compared with FBP (ADMIRE at a strength level of 5 : 70.4% for 1/20; 71.6% for 1/8; p < 0.001). Interobserver agreement for image quality was excellent (k = 0.88). Image quality was considered diagnostic for all images at 1/20 dose using ADMIRE. Sensitivity of nodule detection was 97.1% (100% for solid, 93.8% for subsolid nodules) at 1/20 dose and 100% for both nodule entities at 1/8 dose using ADMIRE 5. Images obtained with 1/70 dose had moderate sensitivity (overall 85.7%; solid 95%; subsolid 73.3%). CONCLUSION: Our study suggests that with a combination of tin filtration and ADMIRE, the CTDIvol of chest CT can be lowered considerably, while sensitivity for nodule detection remains high. For solid nodules, CTDIvol was 0.10 mGy, while subsolid nodules required a slightly higher CTDIvol of 0.28 mGy. ADVANCES IN KNOWLEDGE: Detection of subsolid nodules is feasible with ultralow-dose protocols.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。