iMAR在腹部金属植入物伪影去除中的应用价值

doi:10.16150/j.1671-2870.2022.03.015

摘要/Abstract

摘要：

目的：评估迭代去金属伪影（iterative metal artifact reduction,iMAR）技术在去除腹部金属植入物伪影对CT图像质量改善中的应用价值。方法：回顾性收集32例有腹部金属植入物的受检者的CT图像,分别采用iMAR和滤波反向投影（filtered back projection,FBP）2种算法进行重建,由2名放射科医师对图像进行主观质量评分,比较2种算法获得图像间的质量评分差异。测量2种算法处理后金属植入物附近伪影最严重层面的噪声值,计算图像信噪比（signal-to-noise ratio,SNR）、对比度噪声比（contrast-to-noise ratio,CNR）和伪影指数（artifact index,AI）,并比较2种算法间以上指标差异及测量间的一致性。结果：iMAR算法重建图像的主观质量评分明显高于FBP算法,差异有统计学意义（S=232.500,P<0.050)。iMAR重建图像的SNR及CNR明显高于FBP重建图像,差异有统计学意义（SNR,1.890±1.864比0.720±1.384, P=0.002; CNR,35.872±13.154比15.245±12.362, P<0.050）;iMAR重建图像的AI明显低于FBP重建图像,差异有统计学意义（32.690±15.694比152.594±117.203, P<0.050）。结论：iMAR技术能够明显减少腹部植入物金属伪影对图像的影响,可改善图像质量,具有良好的临床应用价值。

关键词: CT成像, 金属伪影, 迭代去金属伪影

Abstract:

Objective: To explore application value of iterative metal artifact reduction (iMAR) algorithm in reducing the artifacts from abdominal metal implants. Methods: The CT images of 32 patients with abdominal metal implants were reconstructed with both iMAR and filtered back projection (FBP) algorithm, respectively. Subjective image quality was assessed by two independent radiologists. Objective image quality indic including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and artifact index (AI) were calculated by the noise values measured at the most severe level of artifacts near metal implants on images of both iMAR and FBP algorithms. Difference in subjective and objective image quality assessment between iMAR and FBP algorithms was compared. Results: The overall subjective quality score of iMAR images was significantly higher than FBP images (3.656±0.475 vs. 2.156±0.618, P<0.050). Both SNR and CNR of iMAR image were significantly higher than those of FBP images(SNR: 1.890±1.864 vs. 0.720±1.384, P=0.002; CNR: 35.872±13.154 vs. 15.245±12.362, P<0.050, respectively). AI of iMAR images was significantly lower than that of FBP images (32.690±15.694 vs. 152.594±117.203, P<0.050). Conclusions: iMAR can significantly decrease the metal artifacts and improve the image quality in clinical practice.

Key words: CT imaging, Metal artifact, Iterative metal artifact reduction

中图分类号:

R814.42

周慧赟, 吕晓宇, 李纪强, 董海鹏, 张伟华. iMAR在腹部金属植入物伪影去除中的应用价值[J]. 诊断学理论与实践, 2022, 21(03): 380-384.

ZHOU Huiyun, LÜ Xiaoyu, LI Jiqiang, DONG Haipeng, ZHANG Weihua. Application value of iMAR algorithm in reducing metal artifacts from abdominal implants[J]. Journal of Diagnostics Concepts & Practice, 2022, 21(03): 380-384.

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