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

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.