Abstract
MRI is increasingly being used in radiotherapy, because of its superior contrast between the different organs and tumors in comparison to other imaging techniques. For diagnosis, MRI is already standardly used and with the recent clinical availability of hybrid MRI-linac systems, which can acquire MR images during irradiation, the role
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of MRI is expected to increase even further. There are three stages in which MRI is used, i.e. diagnosis, generation of a treatment plan and treatment guidance. During all three stages, physiological motion (e.g. breathing) is a problem. Due to physiological motion during MRI, a false representation of the anatomy is generated with distortions in the images. As a consequence, these MR images cannot be used for clinical diagnosis or treatment plan generation. During radiotherapy, physiological motion could lead to an underdosage of the tumor and/or overdosage of healthy organs.
When motion during MRI and MRI-guided radiotherapy can be measured, the negative effects can be corrected for. For diagnostic scans, the distortions in the images can be reduced. Periodic motion, such as breathing, could be incorporated into the treatment plan by estimating the motion from a 4D-MRI, which describes the anatomy during a full cycle of the periodic motion. During radiotherapy, the treatment could be altered based on the measured motion. In this thesis a novel method to detect motion during MRI and MRI-guided radiotherapy was investigated. This method is based on thermal noise that is measured simultaneous with the MR images and is called the noise navigator.
First the physics behind the noise navigator was investigated through numerical electromagnetic simulation on a realistic 4D digital human phantom containing respiratory and cardiac motion. These simulations were validated with measurements on healthy volunteers. Insight was gained on the effect of the setup on the sensitivity of the noise navigator to motion.
The second step was to investigate the behavior of the noise navigator during MRI. Practical considerations such as the effect of the number of thermal noise samples and the combination of noise measured by the different channels within an RF receive array were evaluated. Furthermore, a Kalman filter was designed that could enable prospective motion correction based on the noise navigator.
Next, the feasibility of respiratory-correlated 4D-MRI generation based on the noise navigator was demonstrated for cartesian and radial readout strategies. These 4D-MR images were compared to 4D-MRI generated with conventional methods. The noise navigator would be valuable for this application as there are at the moment no comparable methods for cartesian acquisitions.
Finally, the detection a variety of motion types with the noise navigator for three different anatomical applications of MRI-guided radiotherapy were investigated. It was feasible to simultaneously detection bulk body movement and respiration in the torso, swallowing for head-and-neck, and cardiac activity. Although the latter requires more research.
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