Ultra-fast scanning scheme based on deep learning reconstruction for cervical MR examination
10.13929/j.issn.1003-3289.2024.06.010
- VernacularTitle:基于深度学习重建超快速扫描方案用于颈椎MR检查
- Author:
Xianfeng RAO
1
;
Shuwen YANG
;
Jing CHEN
;
Zhengwen KANG
;
Jianwei CHEN
;
Zetao WU
;
Tong WANG
;
Bo WANG
;
Qiusheng ZHANG
Author Information
1. 深圳大学第一附属医院深圳市第二人民医院神经外科,广东深圳 518000
- Keywords:
cervical vertebrae;
magnetic resonance imaging;
deep learning
- From:
Chinese Journal of Medical Imaging Technology
2024;40(6):843-847
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the feasibility and diagnostic value of ultra-fast scanning scheme based on deep learning-based reconstruction(DLR)for cervical MR examination.Methods Thirty-six subjects were prospectively enrolled and underwent both conventional scheme(scan time:6 min 14 s)and ultra-fast scheme(2 min)cervical spine MR scanning to acquire encompassing sagittal T1WI,sagittal adipose suppression T2WI and axial T2WI.The ultra-fast MRI were reconstructed using DLR method.The subjective and objective evaluations on imaging qualities of different MRIs were compared,along with the inter-observer agreement for diagnosing intervertebral disc degeneration and herniation.Results Compared with conventional MRI,artifacts in ultra-fast DLR images significantly reduced(P＜0.05).The subjective evaluation results of MRI had good agreement(all Kappa≥0.60).Compared with conventional MRI,the sagittal T1WI,T2WI and axial T2WI obtained with ultra-fast DLR showed significantly improved signal-to-noise ratio(SNR)of the spinal cord,cerebrospinal fluid(CSF)and vertebral body,as well as the spinal cord/CSF contrast(all P＜0.001).The Kappa value of 2 physicians for diagnosing intervertebral disc degeneration based on ultra-fast DLR and conventional scheme images was 0.94 and 1.00,respectively,of intervertebral disc herniation was 0.96 and 0.98,respectively.Conclusion Compared with conventional scanning scheme,using ultra-fast DLR scheme in cervical MR examination could shorten scanning time while achieve similar image quality and diagnostic accuracy.
