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Frequency Schrödinger bridge diffusion model for fast MRI reconstruction in abdominal MR-guided online adaptive
Zhiqun Wang1, Shaobin Wang2,3, Nan Liu1
1Department of Radiation Oncology, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Background:
Online adaptive radiotherapy (ART) employs modalities like CBCT, CT, and MRI. For abdominal malignancies, MRI stands out with superior soft-tissue contrast, no ionizing radiation, and functional imaging capabilities. Yet, MRI-guided ART for such cases is challenged by long treatment time. Thus, boosting efficiency, especially via accelerated MRI scanning, is vital.
Purpose:
This study presents the first accurate and fast MRI reconstruction method tailored for the Unity MR-Linear system. By slashing MRI acquisition time, it aims to enhance patient compliance, reduce intra-fraction anatomical motion, and optimize clinical resource use.
Methods:
A frequency Schrödinger bridge diffusion (FSBD) model for MRI reconstruction (converting 22-second MRI to full-duration MRI) was proposed, based on a retrospective analysis of 31 fractional MRI scans from 14 patients. Its reconstruction performance was compared with state-of-the-art methods: paired diffusion-based Refusion, and unpaired CycleGAN and CSGAN. Of the initially acquired 40 fractional scans, 9 examinations were excluded following predefined exclusion criteria, leaving 31 valid cases. Dataset was split strictly at patient level: 23 fractional scans for training and the remaining independent patients for testing. An extra baseline using pairwise full-duration MRI from different fractions of identical patients was supplemented for reliability verification. All metrics were calculated on complete 3D volumetric MRI rather than individual 2D slices.
Results:
Quantitative evaluation shows the FSBD model's superiority. It achieved significantly lower error metrics: MAE (86.00) and RMSE (123.42), outperforming Refusion (MAE: 99.95, RMSE: 172.55), CycleGAN (MAE: 112.92, RMSE: 149.16), and CSGAN (MAE: 103.04, RMSE: 162.29). In image quality, FSBD's PSNR (28.44 dB) and SSIM (0.885) surpassed Refusion (26.77 dB / 0.870), CycleGAN (25.82 dB / 0.881), and CSGAN (26.34 dB / 0.878). Moreover, it delivered high-fidelity reconstruction with an efficient 20-s inference time.
Conclusions:
This study is the first to propose a sub-one-minute MRI imaging method for the Unity MR linear accelerator in an MR-guided online adaptive radiotherapy (ART) workflow. Experimental results confirm the method's significantly better reconstruction performance than state-of-the-art approaches. Total MRI imaging time dropped drastically from 3 min (full-duration) to 42 s (22 seconds for MR imaging plus 20 seconds for reconstruction). This reduction brings notable clinical benefits, including improved patient compliance and fewer intra-fractional anatomical variations.
