Bian Yueyan, Wang Long, Li Jin, Yang Xiaoxu, Wang Erling, Li Yingying, Liu Yuehong, Xiang Lei, Yang Qi
Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, China (Y.B., J.L., X.Y., E.W., Y. Li, Y. Liu, Q.Y.).
Department of Research and Development, Subtle Medical, Shanghai, China (L.W., L.X.).
Stroke. 2025 Jul;56(7):1843-1852. doi: 10.1161/STROKEAHA.124.050540. Epub 2025 Apr 16.
Deep learning-based synthetic super-resolution magnetic resonance imaging (SynthMRI) may improve the quantitative lesion performance of portable low-field strength magnetic resonance imaging (LF-MRI). The aim of this study is to evaluate whether SynthMRI improves the diagnostic performance of LF-MRI in assessing ischemic lesions.
We retrospectively included 178 stroke patients and 104 healthy controls with both LF-MRI and high-field strength magnetic resonance imaging (HF-MRI) examinations. Using HF-MRI as the ground truth, the deep learning-based super-resolution framework (SCUNet [Swin-Conv-UNet]) was pretrained using large-scale open-source data sets to generate SynthMRI images from LF-MRI images. Participants were split into a training set (64.2%) to fine-tune the pretrained SCUNet, and a testing set (35.8%) to evaluate the performance of SynthMRI. Sensitivity and specificity of LF-MRI and SynthMRI were assessed. Agreement with HF-MRI for Alberta Stroke Program Early CT Score in the anterior and posterior circulation (diffusion-weighted imaging-Alberta Stroke Program Early CT Score and diffusion-weighted imaging-posterior circulation Alberta Stroke Program Early CT Score) was evaluated using intraclass correlation coefficients (ICCs). Agreement with HF-MRI for lesion volume and mean apparent diffusion coefficient (ADC) within lesions was assessed using both ICCs and Pearson correlation coefficients.
SynthMRI demonstrated significantly higher sensitivity and specificity than LF-MRI (89.0% [83.3%-94.6%] versus 77.1% [69.5%-84.7%]; <0.001 and 91.3% [84.7%-98.0%] versus 71.0% [60.3%-81.7%]; <0.001, respectively). The ICCs of diffusion-weighted imaging-Alberta Stroke Program Early CT Score between SynthMRI and HF-MRI were also better than that between LF-MRI and HF-MRI (0.952 [0.920-0.972] versus 0.797 [0.678-0.876], <0.001). For lesion volume and mean apparent diffusion coefficient within lesions, SynthMRI showed significantly higher agreement (<0.001) with HF-MRI (ICC>0.85, >0.78) than LF-MRI (ICC>0.45, >0.35). Furthermore, for lesions during various poststroke phases, SynthMRI exhibited significantly higher agreement with HF-MRI than LF-MRI during the early hyperacute and subacute phases.
SynthMRI demonstrates high agreement with HF-MRI in detecting and quantifying ischemic lesions and is better than LF-MRI, particularly for lesions during the early hyperacute and subacute phases.
基于深度学习的合成超分辨率磁共振成像(SynthMRI)可能会提高便携式低场强磁共振成像(LF-MRI)对病变的定量评估性能。本研究旨在评估SynthMRI是否能提高LF-MRI在评估缺血性病变中的诊断性能。
我们回顾性纳入了178例中风患者和104例健康对照者,他们均接受了LF-MRI和高场强磁共振成像(HF-MRI)检查。以HF-MRI作为金标准,基于深度学习的超分辨率框架(SCUNet [Swin-Conv-UNet])使用大规模开源数据集进行预训练,以从LF-MRI图像生成SynthMRI图像。参与者被分为训练集(64.2%)用于对预训练的SCUNet进行微调,以及测试集(35.8%)用于评估SynthMRI的性能。评估了LF-MRI和SynthMRI的敏感性和特异性。使用组内相关系数(ICC)评估SynthMRI和LF-MRI与HF-MRI在阿尔伯塔卒中项目早期CT评分(前循环和后循环的扩散加权成像-阿尔伯塔卒中项目早期CT评分以及扩散加权成像-后循环阿尔伯塔卒中项目早期CT评分)方面的一致性。使用ICC和Pearson相关系数评估SynthMRI和LF-MRI与HF-MRI在病变体积和病变内平均表观扩散系数(ADC)方面的一致性。
SynthMRI显示出比LF-MRI显著更高的敏感性和特异性(89.0% [83.3%-94.6%] 对 77.1% [69.5%-84.7%];<0.001以及91.3% [84.7%-98.0%] 对 71.0% [60.3%-81.7%];分别为<0.001)。SynthMRI与HF-MRI之间的扩散加权成像-阿尔伯塔卒中项目早期CT评分的ICC也优于LF-MRI与HF-MRI之间的ICC(0.952 [0.920-0.972] 对 0.797 [0.678-0.876],<0.001)。对于病变体积和病变内平均表观扩散系数,SynthMRI与HF-MRI的一致性显著高于LF-MRI(<0.001)(ICC>0.85,>0.78)(ICC>0.45,>0.35)。此外,对于中风后各阶段的病变,在超急性期和亚急性期早期,SynthMRI与HF-MRI的一致性显著高于LF-MRI。
SynthMRI在检测和量化缺血性病变方面与HF-MRI具有高度一致性,且优于LF-MRI,特别是对于超急性期和亚急性期早期的病变。