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ORIGINAL ARTICLE
Year : 2015  |  Volume : 1  |  Issue : 1  |  Page : 16-20

Extracting Breathing Signal Using Fourier Transform from Cine Magnetic Resonance Imaging


1 Department of Radiation Oncology, Duke University Medical Center; Medical Physics Graduate Program, Duke University, Durham, NC, USA
2 Medical Physics Graduate Program, Duke University, Durham, NC, USA

Correspondence Address:
Dr. Jing Cai
Department of Radiation Oncology, Duke University Medical Center, Box 3295, Durham, NC 27710
USA
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Source of Support: This work was partly supported by a National Institute of Health grant (1R21CA165384) and funding from the Golfers Against Cancer foundation,, Conflict of Interest: None


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Aim: The objective of this study is to investigate the feasibility of extracting breathing signal from the cine magnetic resonance images (MRI) using Fourier transform (FT) and its application in four-dimensional-MRI. Methods: A total of 10 subjects were imaged continuously during free breathing using a true fast imaging with steady-state precession MR sequence. Breathing signal of each subject was determined by two means: (1) by tracking the displacement of a region of interest (ROI) (ROI-displacement); and (2) by tracking the phase change of pixel (0, 1) in the FT of cine MRI (FT-phase). Respiratory phases were calculated from the breathing signal and compared between the two methods. To test the application of FT-phase method in four-dimensional-MRI, an in-house built MR-compatible motion phantom was imaged using multi-slice cine MRI. Four-dimensional-MRI were retrospectively reconstructed using the breathing signal determined using the FT-phase method. Results: The mean difference in the respiratory phase between the two methods is −3.13 ± 4.85%, and the mean correlation coefficient is 0.97 ± 0.02. In the phantom study, four-dimensional-MRI clearly revealed sinusoidal motions of the object with minimal artifacts. Conclusion: Our preliminary results demonstrated that breathing signal can be extracted using FT-phase method with highly accurate respiratory phase information, and can be used for four-dimensional-MRI reconstruction.


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