诊断学理论与实践2024，Vol.23Issue(2)：139-145,7.DOI:10.16150/j.1671-2870.2024.02.007
深度学习图像重建在虚拟平扫CT尿路成像中的应用价值
The application of deep learning image reconstruction in dual-energy CT virtual non-contrast CT urography
钱佳乐 1范婧 1朱宏 1王落桐 2孔德艳1
作者信息
- 1. 上海交通大学医学院附属瑞金医院放射科,上海 200025
- 2. GE(中国)CT影像研究中心,上海 201203
- 折叠
摘要
Abstract
Objective To investigate the effect of dual-energy CT(DECT)virtual non-contrast(VNC)images recon-structed by deep learning image reconstruction(DLIR)on the image quality and measurements of renal calculus in CT urog-raphy(CTU).Methods The clinical and imaging data of 90 patients who underwent abdominal and pelvic non-contrast CT examination followed by a nephrographic-phase DE CTU during September 2022 to April 2023 were retrospectively ana-lyzed.The non-contrast CT images were reconstructed with ASIR-V with 70%weight(TNC-AR70).Four groups of VNC im-ages were reconstructed based on medium level and high level DLIR for venous phase and delay phase,namely venous phase-VNC-DLIR medium(VP-VNC-DM),venous phase-VNC-DLIR high(VP-VNC-DH),delay phase-VNC-DLIR medium(DP-VNC-DM),and delay phase-VNC-DLIR high(DP-VNC-DH).The radiation doses of TNC and VNC in venous phase and delay phase were recorded.The mean CT value,image noise(SD),signal-to-noise ratio(SNR)and contrast-to-noise(CNR)were recorded and compared among the five groups.Two radiologists independently assessed the overall image qua-lity and lesion visibility with 5-point Likert scale.Additionally,according to results of TNC,Bland-Altman was used to ana-lyze the measurement differences between VNC and TNC in mean CT value and mean size of renal calculus.Results In the objective assessments,the image quality of the VNC-DH group was better than that of TNC-AR70,and there was no statisti-cally significant difference in CT value among the five groups of images(P＞0.05).DP-VNC-DH showed the lowest SD and the highest SNR and CNR values.In the subjective assessments,DP-VNC-DH achieved the best subject scores on image qua-lity,and VP-VNC-DH achieved the best subject scores on lesion visibility.Furthermore,Bland-Altman analysis showed that there was a strong overall agreement between VNC and TNC for renal calculus characterization(all P＞0.005).Conclu-sions VNC generated by DLIR may provide high-quality image compared with the non-contrast images reconstructed with ASIR-V 70%in CTU.The combination of the VNC images generated by DLIR-H from venous phase and delay phase could replace TNC scanning,reducing the radiation dose of CTU scans.关键词
CT尿路成像/能谱CT/深度学习/虚拟平扫/肾结石Key words
CT urography/Dual-energy/CT Deep learning image reconstruction/Virtual non-contrast image/Renal calculus分类
医药卫生引用本文复制引用
钱佳乐,范婧,朱宏,王落桐,孔德艳..深度学习图像重建在虚拟平扫CT尿路成像中的应用价值[J].诊断学理论与实践,2024,23(2):139-145,7.
