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先天性心脏病患儿自适应统计迭代重建-V 与深度学习重建“TrueFidelity”的心脏 CT 图像质量。

Cardiac CTA image quality of adaptive statistical iterative reconstruction-V versus deep learning reconstruction "TrueFidelity" in children with congenital heart disease.

机构信息

Department of Radiology, Pusan National University School of Medicine and Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan-si, Gyeongsangnam-do, Korea.

Barunmom Rehabilitation Medicine, Busanjin-gu, Busan, Korea.

出版信息

Medicine (Baltimore). 2022 Oct 21;101(42):e31169. doi: 10.1097/MD.0000000000031169.

Abstract

BACKGROUND

Several recent studies have reported that deep learning reconstruction "TrueFidelity" (TF) improves computed tomography (CT) image quality. However, no study has compared adaptive statistical repeated reconstruction (ASIR-V) using TF in pediatric cardiac CT angiography (CTA) with a low peak kilovoltage.

OBJECTIVE

This study aimed to determine whether ASIR-V or TF CTA image quality is superior in children with congenital heart disease (CHD).

MATERIALS AND METHODS

Fifty children (median age, 2 months; interquartile range, 0-5 months; 28 men) with CHD who underwent CTA were enrolled between June and September 2020. Images were reconstructed using 2 ASIR-V blending factors (80% and 100% [AV-100]) and 3 TF settings (low, medium, and high [TF-H] strength levels). For the quantitative analyses, 3 objective image qualities (attenuation, noise, and signal-to-noise ratio [SNR]) were measured of the great vessels and heart chambers. The contrast-to-noise ratio (CNR) was also evaluated between the left ventricle and the dial wall. For the qualitative analyses, the degree of quantum mottle and blurring at the upper level to the first branch of the main pulmonary artery was assessed independently by 2 radiologists.

RESULTS

When the ASIR-V blending factor level and TF strength were higher, the noise was lower, and the SNR was higher. The image noise and SNR of TF-H were significantly lower and higher than those of AV-100 (P < .01), except for noise in the right atrium and left pulmonary artery and SNR of the right ventricle. Regarding CNR, TF-H was significantly better than AV-100 (P < .01). In addition, in the objective assessment of the degree of quantum mottle and blurring, TF-H had the best score among all examined image sets (P < .01).

CONCLUSION

TF-H is superior to AV-100 in terms of objective and subjective image quality. Consequently, TF-H was the best image set for cardiac CTA in children with CHD.

摘要

背景

最近的几项研究报告称,深度学习重建“TrueFidelity”(TF)可提高 CT 图像质量。然而,尚无研究比较低峰值千伏时采用 TF 的自适应统计迭代重建(ASIR-V)与儿科心脏 CT 血管造影(CTA)。

目的

本研究旨在确定先天性心脏病(CHD)患儿中 ASIR-V 或 TF CTA 图像质量是否更优。

材料与方法

2020 年 6 月至 9 月,纳入 50 名 CHD 患儿(中位年龄 2 个月;四分位距,0-5 个月;28 名男性)行 CTA 检查。采用 2 种 ASIR-V 混合因子(80%和 100%[AV-100])和 3 种 TF 设置(低、中、高强度[TF-H])进行图像重建。对大血管和心腔进行 3 项客观图像质量(衰减、噪声和信噪比[SNR])的定量分析。还评估了左心室与心外膜之间的对比噪声比(CNR)。对肺动脉干第 1 分支上水平的量子斑点和模糊程度进行了 2 名放射科医生的独立定性评估。

结果

当 ASIR-V 混合因子水平和 TF 强度较高时,噪声较低,SNR 较高。TF-H 的图像噪声和 SNR 明显低于 AV-100(P<0.01),除了右心房和左肺动脉的噪声以及右心室的 SNR。关于 CNR,TF-H 明显优于 AV-100(P<0.01)。此外,在量子斑点和模糊程度的客观评估中,TF-H 在所有检查的图像组中得分最佳(P<0.01)。

结论

TF-H 在客观和主观图像质量方面均优于 AV-100。因此,TF-H 是 CHD 患儿心脏 CTA 的最佳图像组。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41eb/9592454/bec5c6c8dc2a/medi-101-e31169-g001.jpg

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