OMAR迭代去伪影技术与双能量线性融合去伪影技术的对比性研究

Comparative Study of OMAR Iterative De-artifact Technique and Bienergy Linear Fusion De-Artifact Technique

目的对比分析OMAR迭代去伪影技术与双能量线性融合去伪影技术在椎体金属植入物及口腔内金属异物CT成像中去除金属伪影时两种技术的优缺点。方法选取腰椎植入物术后患者25例,胸椎植入物术后15例。分别行两次CT螺旋扫描并进行三维重建,首次采用常规扫描薄层重建使用OMAR重建,常规图像同样薄层重建。患者复查时第二次采用双能量扫描并薄层重建使用线性融合去伪影重建。将两次扫描所得常规薄层编为A组,OMAR迭代重建薄层图像编为B组,双能量线性融合去伪影薄层图像编为C组,图像层厚均为1 mm,层距1 mm。测量金属螺钉前后的SD值,计算SNR值,记录数据并使用统计学软件进行统计学分析。将三组图像使用MPR、MIP、VR进行后处理重建,邀请两位放射科主治医师对所得图像及薄层图像使用5分法进行双盲法打分。记录所得分数并使用统计学软件进行统计分析。结果图像得分B组>C组>A组常规组图像(P<0.05),SNR值B组>C组>A组(P<0.05)。SD值A组>C组>B组(P<0.05)。结论使用OMAR迭代重建去伪影技术不仅可以去除伪影获得高质量图像,而且比双能量线性融合去伪影技术图像质量更高。

Objective To compare and analyze the advantages and disadvantages of OMAR iterative de-artifact technique and dual-energy linear fusion de-artifact technique in removing metal artifacts in vertebral metal implants and oral metal foreign body CT imaging. Methods A total of 25 patients and 15 patients with thoracic implants were selected. Spiral CT scans were performed twice and 3 d reconstruction was performed. For the first time, conventional scanning thin layer reconstruction was performed with OMAR reconstruction, and conventional images were reconstructed with the same thin layer. Double-energy scanning and thin-layer reconstruction were used for the second time, and linear fusion was used to remove artifacts. Conventional thin layer obtained from the two scans was compiled as group A, OMAR iterative reconstruction thin layer image was compiled as group B, and dual-energy linear fusion de-artifact thin layer image was compiled as group C. The image layers were both 1 mm thick and 1 mm apart. SD values before and after metal screws were measured, SNR values were calculated, data were recorded and statistical software was used for statistical analysis. The three groups of images were reconstructed by post-processing using MPR,MIP and VR. Two attending radiologists were invited to score the obtained images and thin-layer images with a double-blind method using a 5-point method. The scores were recorded and analyzed using statistical software. Results The image scores were group B>group C>group A, conventional group(P<0.05), and SNR value was group B>group C>group A(P<0.05). The SD values of group A>group C>group B(P<0.05). Conclusion OMAR iterative reconstruction can not only remove artifacts and obtain high quality images, but also obtain higher image quality than linear fusion.