Technical Note: Real-time 3D MRI in the presence of motion for MRI-guided radiotherapy: 3D Dynamic Keyhole Imaging with Super-resolution.

Purpose The purpose of this study was to present real-time three-dimensional (3D) magnetic resonance imaging (MRI) in the presence of motion for MRI-guided radiotherapy (MRgRT) using dynamic keyhole imaging for high-temporal acquisition and super-resolution generative (SRG) model for high-spatial reconstruction. Method We propose a unique real-time 3D MRI technique by combining a data sharing technique (3D dynamic keyhole imaging) with a SRG model using cascaded deep learning technique. 3D dynamic keyhole imaging utilizes the data sharing mechanism by combining keyhole central k-space data acquired in real-time with high-spatial, high-temporal resolution prior peripheral k-space data at various motion positions prepared by the SRG model. The efficacy of the 3D dynamic keyhole imaging with super-resolution (SR_dKeyhole) was compared to the ground-truth super-resolution images with the original full k-space data. It was also compared with the zero-filling reconstruction (zero-filling), conventional keyhole reconstruction with low-spatial high-temporal prior data (LR_cKeyhole), and conventional keyhole reconstruction with super-resolution prior data (SR_cKeyhole). Results High-spatial, high-temporal resolution 3D MRI datasets (1.5 x 1.5 x 6 mm(3)) were generated from low-spatial, high-temporal resolution 3D MRI datasets (6 x 6 x 6 mm(3)) using the cascaded deep learning SRG framework (<100 ms/volume). 3D dynamic keyhole imaging with the SRG model provided high-spatial, high-temporal resolution images (1.5 x 1.5 x 6 mm(3), 455 ms) with the highest similarity to the ground-truth SR images without any noticeable artifacts. Structural similarity indices (SSIM) of the reconstructed 3D MRI to the original SR 3D MRI were 0.65, 0.66, 0.86, and 0.89 for zero-filling, LR_cKeyhole, SR_cKeyhole, and SR_dKeyhole, respectively (1 for identical image). In addition, average value of image relative error (IRE) of the reconstructed 3D MRI to the original SR 3D MRI were 0.169, 0.191, 0.079, and 0.067 for zero-filling, LR_cKeyhole, SR_cKeyhole, and SR_dKeyhole, respectively (0 for identical image). Conclusions We demonstrated that high-spatial, high-temporal resolution 3D MRI was feasible by combing 3D dynamic keyhole imaging with a SRG model in terms of image quality and imaging time. The proposed technique can be utilized for real-time 3D MRgRT.