Quantitative Ischemic Lesions of Portable Low-Field Strength MRI Using Deep Learning-Based Super-Resolution.

Abstract

Background: 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.

Methods: 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.

Results: SynthMRI demonstrated significantly higher sensitivity and specificity than LF-MRI (89.0% [83.3%-94.6%] versus 77.1% [69.5%-84.7%]; P<0.001 and 91.3% [84.7%-98.0%] versus 71.0% [60.3%-81.7%]; P<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], P<0.001). For lesion volume and mean apparent diffusion coefficient within lesions, SynthMRI showed significantly higher agreement (P<0.001) with HF-MRI (ICC>0.85, r>0.78) than LF-MRI (ICC>0.45, r>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.

Conclusions: 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.