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基于深度学习重建的T2加权图像在鼻软骨中的应用价值

Usefulness of T2-Weighted Images with Deep-Learning-Based Reconstruction in Nasal Cartilage.

作者信息

Gao Yufan, Liu Weiyin Vivian, Li Liang, Liu Changsheng, Zha Yunfei

机构信息

Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China.

MR Research, GE Healthcare, Beijing 100176, China.

出版信息

Diagnostics (Basel). 2023 Sep 25;13(19):3044. doi: 10.3390/diagnostics13193044.

Abstract

OBJECTIVE

This study aims to evaluate the feasibility of visualizing nasal cartilage using deep-learning-based reconstruction (DLR) fast spin-echo (FSE) imaging in comparison to three-dimensional fast spoiled gradient-echo (3D FSPGR) images.

MATERIALS AND METHODS

This retrospective study included 190 set images of 38 participants, including axial T1- and T2-weighted FSE images using DLR (T1WI and T2WI, belong to FSE) and without using DLR (T1WI and T2WI, belong to FSE) and 3D FSPGR images. Subjective evaluation (overall image quality, noise, contrast, artifacts, and identification of anatomical structures) was independently conducted by two radiologists. Objective evaluation including signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) was conducted using manual region-of-interest (ROI)-based analysis. Coefficient of variation (CV) and Bland-Altman plots were used to demonstrate the intra-rater repeatability of measurements for cartilage thickness on five different images.

RESULTS

Both qualitative and quantitative results confirmed superior FSE to 3D FSPGR images (both < 0.05), improving the diagnosis confidence of the observers. Lower lateral cartilage (LLC), upper lateral cartilage (ULC), and septal cartilage (SP) were relatively well delineated on the T2WI, while 3D FSPGR showed poorly on the septal cartilage. For the repeatability of cartilage thickness measurements, T2WI showed the highest intra-observer (%CV = 8.7% for SP, 9.5% for ULC, and 9.7% for LLC) agreements. In addition, the acquisition time for T1WI and T2WI was respectively reduced by 14.2% to 29% compared to 3D FSPGR (both < 0.05).

CONCLUSIONS

Two-dimensional equivalent-thin-slice T1- and T2-weighted images using DLR showed better image quality and shorter scan time than 3D FSPGR and conventional construction images in nasal cartilages. The anatomical details were preserved without losing clinical performance on diagnosis and prognosis, especially for pre-rhinoplasty planning.

摘要

目的

本研究旨在评估与三维扰相梯度回波(3D FSPGR)图像相比,基于深度学习重建(DLR)的快速自旋回波(FSE)成像用于可视化鼻软骨的可行性。

材料与方法

这项回顾性研究纳入了38名参与者的190组图像,包括使用DLR的轴向T1加权和T2加权FSE图像(T1WI和T2WI,属于FSE)、未使用DLR的轴向T1加权和T2加权FSE图像(T1WI和T2WI,属于FSE)以及3D FSPGR图像。由两名放射科医生独立进行主观评估(整体图像质量、噪声、对比度、伪影以及解剖结构识别)。使用基于手动感兴趣区域(ROI)的分析进行客观评估,包括信噪比(SNR)和对比噪声比(CNR)。变异系数(CV)和Bland-Altman图用于展示在五幅不同图像上软骨厚度测量的观察者内重复性。

结果

定性和定量结果均证实FSE图像优于3D FSPGR图像(均P<0.05),提高了观察者的诊断信心。在T2WI上,下外侧软骨(LLC)、上外侧软骨(ULC)和鼻中隔软骨(SP)相对清晰可辨,而3D FSPGR在鼻中隔软骨上显示不佳。对于软骨厚度测量的重复性,T2WI显示观察者内一致性最高(SP的%CV = 8.7%,ULC的%CV = 9.5%,LLC的%CV = 9.7%)。此外,与3D FSPGR相比,T1WI和T2WI的采集时间分别减少了14.2%至29%(均P<0.05)。

结论

使用DLR的二维等效薄层T1加权和T2加权图像在鼻软骨成像方面比3D FSPGR和传统构建图像具有更好的图像质量和更短的扫描时间。在不影响诊断和预后临床性能的情况下保留了解剖细节,尤其适用于鼻整形术前规划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1fe/10572289/7171a0e6ab7f/diagnostics-13-03044-g001.jpg

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