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使用低剂量腹部盆腔计算机断层扫描对正常BMI个体进行深度学习重建算法与iDose4之间的图像质量比较。

A comparison of the image quality between deep learning reconstruction algorithm and iDose4 using low dose abdominopelvic computed tomography for individuals with normal BMI.

作者信息

Marike Shivakumar Thejas, Panakkal Nitika C, Nayak Shailesh, Kadavigere Rajagopal, Kamath Tanushree R, Sukumar Suresh

机构信息

Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Karnataka, India.

Radio-Diagnosis and Imaging, Department of Radio Diagnosis and Medical Imaging, Kasturba Medical College, Manipal Academy of Higher Education, Karnataka, India.

出版信息

SAGE Open Med. 2025 Aug 22;13:20503121251336046. doi: 10.1177/20503121251336046. eCollection 2025.

DOI:10.1177/20503121251336046
PMID:40862257
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12374083/
Abstract

OBJECTIVES

Radiation exposure has been a cause of concern in computed tomography imaging. Reducing radiation dose increases the image noise which can be compensated by using reconstruction techniques. Recently artificial intelligence-based reconstruction technique has been introduced. Therefore, the purpose of the study was to prospectively compare the image quality between Idose4 and Precise Image in normal BMI individuals.

METHODS

Sixty-six consecutive patients with a normal body habitus undergoing contrast-enhanced abdomen and pelvis scan were included in the study. All scans were performed using 100 kVp and tube current modulation. The acquired images were reconstructed to iDose4 and precise imaging. Quantitatively images were analyzed by placing regions of interest in different organs to estimate the image noise, signal-to-noise ratio, and contrast-to-noise ratio. Qualitative analysis was done by two radiologists on a five-point Likert scale.

RESULTS

Image noise was significantly reduced using Precise Image across the plain (9.11 ± 1.43 vs 8.18 ± 1.2), arterial (14.34 ± 2.1 vs 10.21 ± 1.5), and portovenous phase (14.78 ± 2.30 vs 11.97 ± 2.07) with maximum noise reduction in the arterial and portovenous phases. Signal-to-noise ratio and contrast-to-noise ratio was significantly improved in all the organs across the plain, arterial, and portovenous phases. Qualitative analysis showed no significant difference between Idose4 and Precise Image with regards to visualization of large vessels in the arterial and portovenous phases. However, precise image was graded better than Idose4 with respect to visualization/conspicuity, image noise, and artifacts.

CONCLUSION

Precise Image can be useful in reducing the image noise and improving the signal-to-noise ratio and contrast-to-noise ratio in low-dose computed tomography protocol among normal BMI individuals.

摘要

目的

在计算机断层扫描成像中,辐射暴露一直是人们关注的问题。降低辐射剂量会增加图像噪声,而这可以通过使用重建技术来补偿。最近,基于人工智能的重建技术被引入。因此,本研究的目的是前瞻性地比较正常体重指数个体中Idose4和Precise Image之间的图像质量。

方法

本研究纳入了66例连续接受腹部和盆腔增强扫描、身体状况正常的患者。所有扫描均使用100 kVp和管电流调制进行。采集的图像被重建为iDose4和精确成像。通过在不同器官中放置感兴趣区域来定量分析图像,以估计图像噪声、信噪比和对比噪声比。由两名放射科医生采用五点李克特量表进行定性分析。

结果

在平扫(9.11±1.43对8.18±1.2)、动脉期(14.34±2.1对10.21±1.5)和门静脉期(14.78±2.30对11.97±2.07),使用Precise Image时图像噪声显著降低,动脉期和门静脉期的噪声降低最为明显。在平扫、动脉期和门静脉期的所有器官中,信噪比和对比噪声比均显著提高。定性分析显示,在动脉期和门静脉期大血管的可视化方面,Idose4和Precise Image之间没有显著差异。然而,在可视化/清晰度、图像噪声和伪影方面,精确成像的评分优于Idose4。

结论

在正常体重指数个体的低剂量计算机断层扫描方案中,Precise Image有助于降低图像噪声,提高信噪比和对比噪声比。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/afca1b36bb39/10.1177_20503121251336046-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/eba3372d76ea/10.1177_20503121251336046-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/379f3a413a93/10.1177_20503121251336046-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/68749e56b9b7/10.1177_20503121251336046-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/afca1b36bb39/10.1177_20503121251336046-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/eba3372d76ea/10.1177_20503121251336046-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/379f3a413a93/10.1177_20503121251336046-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/68749e56b9b7/10.1177_20503121251336046-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/12374083/afca1b36bb39/10.1177_20503121251336046-fig4.jpg

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