CT理论与应用研究2026，Vol.35Issue(2)：275-281,7.DOI:10.15953/j.ctta.2025.279
能谱DLIR结合MAR对腰椎金属植入物伪影的影响
Impacts of Deep Learning Image Reconstruction with Gemstone Spectral Imaging Combined with Metal Artifact Reduction on Metal Artifacts in CT Scans with Lumbar Spine Implants
钱佳乐 1范婧 1刘天豪 1董海鹏 1朱宏 1孔德艳 1石骁萌 2马媛媛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 200020
- 2. GE(中国)CT影像研究中心,上海 201203
- 折叠
摘要
Abstract
Objective:This study investigated the impact of deep learning image reconstruction(DLIR)combined with gemstone spectral imaging(GSI)CT scanning and metal artifact reduction(MAR)on metal artifacts from lumbar spine implants.Methods:A retrospective analysis was conducted on 40 patients with lumbar metal implants who underwent abdominal spectral CT scans at our hospital.After spectral abdominal scanning,images were reconstructed using Adaptive Statistical Iterative Reconstruction-V(ASiR-V)at 50%(AR50 group)and DLIR at a high level(DH group).MAR was applied to both groups to obtain reconstructions(AR50-MAR group and DH-MAR group).Regions of interest(ROI)were delineated and measured for metal artifacts and surrounding tissues on the four sets of images.CT values and standard deviations(SD)were recorded,and the signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR),and artifact index(AI)of the images were calculated and compared.Two radiologists subjectively evaluated the quality of the images,the severity of metal artifacts,and the area of the artifacts on a 4-point scale.Results:Under the same energy level of 68 keV,statistically significant differences were observed in SD,CNR,and AI values among the four groups.The SD values in the MAR groups were lower than those in the non-MAR groups.The images reconstructed with DH-MAR had the highest CNR and SNR and the lowest AI values.Conclusion:For patients with lumbar metal implants,the combination of DLIR and MAR in GSI CT can significantly reduce metal artifacts while greatly improving the signal-to-noise ratio of images of the tissue,which is more conducive to clinical diagnosis.关键词
能谱CT/深度学习图像重建/去金属伪影/腰椎金属植入物Key words
energy spectrum CT/deep learning-based image reconstruction/metal artifact reduction分类
信息技术与安全科学引用本文复制引用
钱佳乐,范婧,刘天豪,董海鹏,朱宏,孔德艳,石骁萌,马媛媛..能谱DLIR结合MAR对腰椎金属植入物伪影的影响[J].CT理论与应用研究,2026,35(2):275-281,7.
