Improved MRI thermometry for MR-guided focused ultrasound in the brain
Abstract/Contents
- Abstract
- Focused ultrasound can be used as a therapeutic tool, to warm or ablate tissue in the body non-invasively or minimally invasively. Transcranial treatments are now possible, allowing for non-surgical interventions inside the brain. MR-guidance is critical to these interventions, both to ensure accurate targeting and to monitor treatment. MRI temperature monitoring is used to measure the heat delivered to the target of therapy, to ensure that the correct amount of energy is delivered. MRI temperature monitoring also improves patient safety by monitoring untargeted tissue to ensure heating does not occur. In this thesis, the performance boundaries of various temperature monitoring approaches are analyzed, and solutions and new methods are proposed that improve the performance of MR thermometry in the brain. Conventionally, multiple-slice thermometry is performed by interleaving the acquisitions of each slice. Interleaved thermometry suffers from poor SNR due to the very short echo times involved in fast imaging. A new multi-slice acquisition method was developed, known as MASTER or "Multiple Adjacent Slice Thermometry with Excitation Refocusing." In MASTER, the pulse sequence is modified such that each slice is measured after all slices have been excited. This results in much longer echo times than can be achieved with slice interleaving, and improves the performance of multiple-slice temperature monitoring. Simulated performance curves demonstrate significant performance gains when using MASTER for many slice acquisitions, and experimental measurements validate that performance is improved. Current monitoring sequences use low sampling bandwidths to maximize SNR, resulting in susceptibility to geometric shift artifacts in the presence of off-resonance. A simulation was developed that can evaluate performance of different sequences, and several strategies to increase sampling bandwidth (and reduce shift artifacts) were evaluated. Single-line readouts, multiple-line readouts (EPI), and multiple-echo sequences were simulated to determine the design frontier trading precision against speed for different sampling bandwidths. Multiple-echo thermometry was found to significantly improve sampling bandwidth with only minor penalties in performance. Additionally, volumetric imaging performance using EPI and using MASTER (with or without EPI) was explored. EPI was found to be sufficient for measuring multiple slices with low bandwidth, but MASTER with EPI was necessary for high bandwidth imaging of multiple slices. After having found that multiple-echo imaging would provide high performance monitoring with high sampling bandwidth, several multiple-echo thermometry sequences were implemented and validated. Multiple-echo 2DFT imaging was confirmed to perform nearly as well as single-echo imaging, while removing susceptibility to off-resonance shift artifacts. Proper reconstruction was shown to be critical for obtaining precise temperature measurements. Multiple-echo spiral acquisitions were designed and tested, and were shown to improve overall monitoring performance by more than a factor of 2x. Additionally, the multiple-echo data was used to inform multiple-frequency reconstruction which minimized off-resonance sensitivity.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2014 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Marx, Michael |
|---|---|
| Associated with | Stanford University, Department of Electrical Engineering. |
| Primary advisor | Pauly, Kim Butts (Kim Rosemary Butts) |
| Thesis advisor | Pauly, Kim Butts (Kim Rosemary Butts) |
| Thesis advisor | Nishimura, Dwight George |
| Thesis advisor | Pauly, John (John M.) |
| Advisor | Nishimura, Dwight George |
| Advisor | Pauly, John (John M.) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Michael Marx. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2014. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2014 by Michael Edward Marx
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...