Bias field correction in hyperpolarized 129 Xe ventilation MRI using templates derived by RF-depolarization mapping.
PURPOSE: To correct for RF inhomogeneity for in vivo 129 Xe ventilation MRI using flip-angle mapping enabled by randomized 3D radial acquisitions. To extend this RF-depolarization mapping approach to create a flip-angle map template applicable to arbitrary acquisition strategies, and to compare these approaches to conventional bias field correction. METHODS: RF-depolarization mapping was evaluated first in digital simulations and then in 51 subjects who had undergone radial 129 Xe ventilation MRI in the supine position at 3T (views = 3600; samples/view = 128; TR/TE = 4.5/0.45 ms; flip angle = 1.5; FOV = 40 cm). The images were corrected using newly developed RF-depolarization and templated-based methods and the resulting quantitative ventilation metrics (mean, coefficient of variation, and gradient) were compared to those resulting from N4ITK correction. RESULTS: RF-depolarization and template-based mapping methods yielded a pattern of RF-inhomogeneity consistent with the expected variation based on coil architecture. The resulting corrected images were visually similar, but meaningfully distinct from those generated using standard N4ITK correction. The N4ITK algorithm eliminated the physiologically expected anterior-posterior gradient (-0.04 ± 1.56%/cm, P < 0.001). These 2 newly introduced methods of RF-depolarization and template correction retained the physiologically expected anterior-posterior ventilation gradient in healthy subjects (2.77 ± 2.09%/cm and 2.01 ± 2.73%/cm, respectively). CONCLUSIONS: Randomized 3D 129 Xe MRI ventilation acquisitions can inherently be corrected for bias field, and this technique can be extended to create flip angle templates capable of correcting images from a given coil regardless of acquisition strategy. These methods may be more favorable than the de facto standard N4ITK because they can remove undesirable heterogeneity caused by RF effects while retaining results from known physiology.
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- Xenon Isotopes
- Respiration
- Nuclear Medicine & Medical Imaging
- Magnetic Resonance Imaging
- Lung
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- 4003 Biomedical engineering
- 0903 Biomedical Engineering
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Xenon Isotopes
- Respiration
- Nuclear Medicine & Medical Imaging
- Magnetic Resonance Imaging
- Lung
- Humans
- Algorithms
- 4003 Biomedical engineering
- 0903 Biomedical Engineering