Suppr超能文献

基于深度学习重建的快速肘部磁共振成像——与标准成像相比的图像质量、诊断信心及解剖结构可视化评估

Faster Elbow MRI with Deep Learning Reconstruction-Assessment of Image Quality, Diagnostic Confidence, and Anatomy Visualization Compared to Standard Imaging.

作者信息

Herrmann Judith, Afat Saif, Gassenmaier Sebastian, Grunz Jan-Peter, Koerzdoerfer Gregor, Lingg Andreas, Almansour Haidara, Nickel Dominik, Patzer Theresa Sophie, Werner Sebastian

机构信息

Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, 72076 Tübingen, Germany.

Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, 97080 Würzburg, Germany.

出版信息

Diagnostics (Basel). 2023 Aug 24;13(17):2747. doi: 10.3390/diagnostics13172747.

Abstract

OBJECTIVE

The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the elbow regarding image quality and visualization of anatomy.

MATERIALS AND METHODS

Between October 2020 and June 2021, seventeen participants (eight patients, nine healthy subjects; mean age: 43 ± 16 (20-70) years, eight men) were prospectively included in this study. Each patient underwent two examinations: standard MRI, including TSE sequences reconstructed with a generalized autocalibrating partial parallel acquisition reconstruction (TSE), and prospectively undersampled TSE sequences reconstructed with a DL reconstruction (TSE). Two radiologists evaluated the images concerning image quality, noise, edge sharpness, artifacts, diagnostic confidence, and delineation of anatomical structures using a 5-point Likert scale, and rated the images concerning the detection of common pathologies.

RESULTS

Image quality was significantly improved in TSE (mean 4.35, IQR 4-5) compared to TSE (mean 3.76, IQR 3-4, = 0.008). Moreover, TSE showed decreased noise (mean 4.29, IQR 3.5-5) compared to TSE (mean 3.35, IQR 3-4, = 0.004). Ratings for delineation of anatomical structures, artifacts, edge sharpness, and diagnostic confidence did not differ significantly between TSE and TSE ( > 0.05). Inter-reader agreement was substantial to almost perfect (κ = 0.628-0.904). No difference was found concerning the detection of pathologies between the readers and between TSE and TSE. Using DL, the acquisition time could be reduced by more than 35% compared to TSE.

CONCLUSION

TSE provided improved image quality and decreased noise while receiving equal ratings for edge sharpness, artifacts, delineation of anatomical structures, diagnostic confidence, and detection of pathologies compared to TSE. Providing more than a 35% reduction of acquisition time, TSE may be clinically relevant for elbow imaging due to increased patient comfort and higher patient throughput.

摘要

目的

本研究的目的是评估用于肘部涡轮自旋回波(TSE)序列的深度学习(DL)重建在图像质量和解剖结构可视化方面的效果。

材料与方法

在2020年10月至2021年6月期间,前瞻性纳入了17名参与者(8名患者,9名健康受试者;平均年龄:43±16(20 - 70)岁,8名男性)。每位患者均接受了两项检查:标准MRI,包括采用广义自校准部分并行采集重建(TSE)重建的TSE序列,以及采用DL重建(TSE)重建的前瞻性欠采样TSE序列。两名放射科医生使用5分李克特量表评估图像的图像质量、噪声、边缘清晰度、伪影、诊断信心以及解剖结构的描绘,并对图像中常见病变的检测进行评分。

结果

与TSE(平均3.76,四分位间距3 - 4)相比,TSE的图像质量显著提高(平均4.35,四分位间距4 - 5,P = 0.008)。此外,与TSE(平均3.35,四分位间距3 - 4)相比,TSE的噪声降低(平均4.29,四分位间距3.5 - 5,P = 0.004)。TSE和TSE在解剖结构描绘、伪影、边缘清晰度和诊断信心方面的评分无显著差异(P>0.05)。阅片者间的一致性为实质性到几乎完美(κ = 0.628 - 0.904)。在读者之间以及TSE和TSE之间,病变检测方面未发现差异。与TSE相比,使用DL可将采集时间减少35%以上。

结论

与TSE相比,TSE在边缘清晰度、伪影、解剖结构描绘、诊断信心和病变检测方面获得相同评分的同时,提供了更高的图像质量和更低噪声。由于提高了患者舒适度和患者通量,TSE将采集时间减少了35%以上,可能在肘部成像中具有临床应用价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b85a/10486923/fcf0d9a36442/diagnostics-13-02747-g001.jpg

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