A role for magnetic susceptibility in synthetic computed tomography
| Autor: | Marc-Antoine Fortin, P Pater, Luis Souhami, Véronique Fortier, Ives R. Levesque |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
Biophysics General Physics and Astronomy 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Hounsfield scale medicine Humans Radiology Nuclear Medicine and imaging Cluster analysis medicine.diagnostic_test business.industry Radiotherapy Planning Computer-Assisted Quantitative susceptibility mapping Magnetic resonance imaging Pulse sequence General Medicine Magnetic susceptibility Thresholding Magnetic Resonance Imaging 3. Good health Functional imaging 030220 oncology & carcinogenesis Nuclear medicine business Tomography X-Ray Computed Head Algorithms |
| Zdroj: | Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB). 85 |
| ISSN: | 1724-191X |
| Popis: | Purpose Radiotherapy treatment planning based on magnetic resonance imaging (MRI) benefits from increased soft-tissue contrast and functional imaging. MRI-only planning is attractive but limited by the lack of electron density information required for dose calculation, and the difficulty to differentiate air and bone. MRI can map magnetic susceptibility to separate bone from air. A method is introduced to produce synthetic CT (sCT) through automatic voxel-wise assignment of CT numbers from an MRI dataset processed that includes magnetic susceptibility mapping. Methods Volumetric multi-echo gradient echo datasets were acquired in the heads of five healthy volunteers and fourteen patients with cancer using a 3 T MRI system. An algorithm for CT synthesis was designed using the volunteer data, based on fuzzy c-means clustering and adaptive thresholding of the MR data (magnitude, fat, water, and magnetic susceptibility). Susceptibility mapping was performed using a modified version of the iterative phase replacement algorithm. On patient data, the algorithm was assessed by direct comparison to X-ray computed tomography (CT) scans. Results The skull, spine, teeth, and major sinuses were clearly distinguished in all sCT, from healthy volunteers and patients. The mean absolute CT number error between X-ray CT and sCT in patients ranged from 78 and 134 HU. Conclusion Susceptibility mapping using MRI can differentiate air and bone for CT synthesis. The proposed method is automated, fast, and based on a commercially available MRI pulse sequence. The method avoids registration errors and does not rely on a priori information, making it suitable for nonstandard anatomy. |
| Databáze: | OpenAIRE |
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