Patient-induced susceptibility effects simulation in magnetic resonance imaging
| Autor: | Mikael Bylund, Anders Garpebring, Josef A. Lundman, Camilla Thellenberg Karlsson, Tufve Nyholm |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Physics
lcsh:Medical physics. Medical radiology. Nuclear medicine Radiation medicine.diagnostic_test lcsh:R895-920 Physics::Medical Physics food and beverages Magnetic resonance imaging equipment and supplies lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens lcsh:RC254-282 Geometric distortion 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Nuclear magnetic resonance 030220 oncology & carcinogenesis medicine Radiology Nuclear Medicine and imaging Biomedical engineering |
| Zdroj: | Physics and Imaging in Radiation Oncology, Vol 1, Iss, Pp 41-45 (2017) |
| ISSN: | 2405-6316 |
| Popis: | Background and purpose: A fundamental requirement for safe use of magnetic resonance imaging (MRI) in radiotherapy is geometrical accuracy. One factor that can introduce geometrical distortion is patient-induced susceptibility effects. This work aims at developing a method for simulating these distortions. The specific goal being to help objectively identifying a balanced acquisition bandwidth, keeping these distortions within acceptable limits for radiotherapy. Materials and methods: A simulation algorithm was implemented in Medical Interactive Creative Environment (MICE). The algorithm was validated by comparison between simulations and analytical solutions for a cylinder and a sphere. Simulations were performed for four body regions; neck, lungs, thorax with the lungs excluded, and the pelvic region. This was done using digital phantoms created from patient CT images, after converting the CT Hounsfield units to magnetic susceptibility values through interpolation between known values. Results: The simulations showed good agreement with analytical solutions, with only small discrepancies due to pixelation of the phantoms. The calculated distortions in digital phantoms based on patient CT data showed maximal 95th percentile distortions of 39%, 32%, 28%, and 25% of the fat-water shift for the neck, lungs, thorax with the lungs excluded, and pelvic region, respectively. Conclusions: The presented results show the expected pixel distortions for various body parts, and how they scale with bandwidth and field strength. This information can be used to determine which bandwidth is required to keep the patient-induced susceptibility distortions within an acceptable range for a given field strength. Keywords: MRI, Susceptibility, Radiotherapy, Distortions |
| Databáze: | OpenAIRE |
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