Related Experiment Video
Updated: Mar 2, 2026
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
SU-D-218-02: 4D-MRI Based on Body Area (BA) Surrogate and Sagittal Image Acquisition
Purpose:
4D-MRI based on body area (BA) surrogate using axial image acquisition has been demonstrated. Since respiratory motion mostly occurs in the superior-inferior (SI) direction, it is expected that sagittal acquisition may provide more robust and accurate breathing signal than axial acquisition. The aim of this study was to investigate the feasibility of extracting breathing signals from sagittal images using BA surrogate and its application in 4D-MRI.
Methods:
7 human subjects were imaged continuously in a single (n=5) or multiple (n=2) sagittal planes using a steady-state precession sequence. Imaging parameters were: TR/TE, 3.7ms/1.21ms; Matrix, 256×166; FOV, 350×300mm; flip angle, 52°; slice thickness, 5mm; frame rate: ∼3 frames/s. Imaging time per slice is 2 minutes for single slice acquisition and ∼10 seconds for multi-slice acquisition. Breathing signals were generated for all subjects by tracking the change of BA. The multi-slice sagittal acquisition was performed on a MRI- compatible motion phantom with a cylindrical gel target and was simulated on a 4D digital human phantom. Breathing signals were extracted from the sagittal images using the BA surrogate. Respiratory phases were calculated. 4D-MRI of both phantoms were retrospectively reconstructed based on the respiratory phases.
Results:
Breathing signals extracted from both single slice and multi-slice sagittal acquisitions showed stable and well- characterized patterns. 4D-MRI of the physical phantom showed clear sinusoidal motion of the gel target in all three planes with minimal artifacts. Simulated '4D-MRI' of the 4D digital phantom matched well with original images: the mean absolute difference in motion amplitude of the 'tumor' was 0.4±0.3mm. Small artifacts of discontinuity were observed in the SI direction in certain phases.
Conclusions:
It is feasible to extract breathing signals from sagittal images for 4D-MRI application. Further investigation is needed to test whether sagittal acquisition is more robust and accurate than axial acquisition for breathing signal extraction.
