Suppr超能文献

全模型迭代重建(MBIR)在腹部 CT 中提高了客观图像质量,但降低了主观接受度。

Full model-based iterative reconstruction (MBIR) in abdominal CT increases objective image quality, but decreases subjective acceptance.

机构信息

Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 29 Avenue du Maréchal de Lattre de Tassigny, 54035, Nancy Cedex, France.

Medical Radiophysical Unit, Centre Alexis-Vautrin, 6 Avenue de Bourgogne, 54129, Vandoeuvre-lès-Nancy, France.

出版信息

Eur Radiol. 2019 Aug;29(8):4016-4025. doi: 10.1007/s00330-018-5988-8. Epub 2019 Jan 30.

Abstract

OBJECTIVE

Evaluate and compare the image quality and acceptance of a full MBIR algorithm to that of an earlier full IR hybrid algorithm and filtered back projection (FBP).

METHODS

Acquisitions were performed with a 320 detector-row CT scanner with seven different dose levels. Images were reconstructed with three algorithms: FBP, full hybrid iterative reconstruction (HIR), and a full model-based iterative reconstruction algorithm (full MBIR). The sensitometry, spatial resolution, image texture, and low-contrast detectability of these algorithms were compared. Subjective analysis of low-contrast detectability was performed. Ten radiologists answered a questionnaire on image quality and confidence in full MBIR images in clinical practice.

RESULTS

The contrast-to-noise ratio of full MBIR was significantly higher than in the other algorithms (p < 0.0015). The spatial resolution was also higher with full MBIR at high frequencies (> 0.3 lp/mm). Full MBIR at low dose levels led to better low-contrast detectability and more inserts being identified with a higher confidence (p < 0.0001). Full MBIR was associated with a change in image texture compared to HIR and FBP. Eighty percent of radiologists judged general appearance and texture of full MBIR images worse than HIR. Moreover, compared with HIR, for 50% of radiologists, the diagnostic confidence on full MBIR images was worse. Questionnaire reliability was considered acceptable (Cronbach alpha 0.7).

CONCLUSION

Compared to conventional iterative reconstruction algorithms, full MBMIR presented a higher image quality and low-contrast detectability and a worse acceptance among radiologists.

KEY POINTS

• Full MBIR used led to an overall improvement in image quality compared with FBP and HIR. • Full MBIR leads to image texture change which reduces the confidence in these images among radiologists. • Awareness of the image texture change and improved quality of full MBIR reconstructed images could improve the acceptance of this technique in clinical practice.

摘要

目的

评估和比较全 MBIR 算法与早期全 IR 混合算法和滤波反投影 (FBP) 的图像质量和可接受性。

方法

使用具有 320 个探测器排的 CT 扫描仪进行采集,共有七种不同的剂量水平。使用三种算法重建图像:FBP、全混合迭代重建 (HIR) 和全基于模型的迭代重建算法 (全 MBIR)。比较这些算法的感光性、空间分辨率、图像纹理和低对比度检测能力。进行低对比度检测的主观分析。十位放射科医生回答了关于在临床实践中全 MBIR 图像的质量和信心的问卷。

结果

全 MBIR 的对比噪声比明显高于其他算法(p<0.0015)。在高频(>0.3lp/mm)时,全 MBIR 的空间分辨率也更高。在低剂量水平下,全 MBIR 可提高低对比度检测能力,并以更高的信心识别更多的插入物(p<0.0001)。与 HIR 和 FBP 相比,全 MBIR 的图像纹理发生变化。80%的放射科医生认为全 MBIR 图像的整体外观和纹理不如 HIR。此外,与 HIR 相比,50%的放射科医生对全 MBIR 图像的诊断信心更差。问卷可靠性被认为是可以接受的(Cronbach alpha 0.7)。

结论

与传统的迭代重建算法相比,全 MBIR 提供了更高的图像质量和低对比度检测能力,但在放射科医生中的接受度较差。

要点

• 与 FBP 和 HIR 相比,全 MBIR 使用导致整体图像质量提高。• 全 MBIR 导致图像纹理变化,降低了放射科医生对这些图像的信心。• 了解图像纹理变化并改善全 MBIR 重建图像的质量,可以提高该技术在临床实践中的接受度。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验