University of Twente Student Theses
A Model of RF Heating around DBS leads : Predicting MRI RF heating in DBS patients for image optimization using 3D Gradient echo scans and an anthropomorphic phantom
Arts, Erik (2024) A Model of RF Heating around DBS leads : Predicting MRI RF heating in DBS patients for image optimization using 3D Gradient echo scans and an anthropomorphic phantom.
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| Abstract: | This study aims to give insight into a method to create patient specific scanning protocols to improve possibilities for clinical magnetic resonance imaging (MRI) scans in deep brain stimulation (DBS) patients. In these patients, radio frequency heating around electrodes poses mayor safety concerns [1]. To evaluate safe scanning parameters, a modelling strategy is applied and validated in a phantom. The key scanning parameter evaluated in this paper is the repetition time (TR): the interval between two consecutive excitation pulses. Increasing TR allows more heat dissipation, resulting in a lower end temperature. However, increasing TR also increases overall scan time. To remain clinically viable, the scan time cannot be extended indefinitely. A predictive model allows for the selection of an optimal TR that ensures scan safety while not unnecessarily prolonging the scan time. The model comprises two main components: calibration data and a scaling parameter. The calibration data provides the general shape of the heating curve. To obtain this, an agar phantom is scanned. The obtained curve features the temperature over time for a given sequence and configuration, which can be scaled to conform other sequences and configurations. To accurately scale the calibration curve, the orientation-specific heating is quantified using a 3D Gradient Echo scan. By analysing the location of the transmission magnetic field null artifact relative to the electrodes, the induced current is determined [2]. The power deposition of this current causes the RF heating, commonly represented using the Specific Absorption Rate (SAR). Knowledge on the magnitude of the induction current provides the necessary scaling factor. Scaling the curve provides rapid and accurate data relating repetition time to tissue heating. By abstaining from computationally heavy simulations, the model can give quick feedback to ensure smooth MRI operation. To maintain accuracy, calibration data is to be obtained from high resemblance anthropomorphic phantoms or cadavers using clinically representative sequences, such as low-SAR (Siemens). Combined with RF heating mitigation strategies, this model could prove vital for improving clinical MRI scan accessibility for DBS patients. |
| Item Type: | Essay (Bachelor) |
| Faculty: | TNW: Science and Technology |
| Subject: | 33 physics, 42 biology, 44 medicine |
| Programme: | Biomedical Technology BSc (56226) |
| Link to this item: | https://purl.utwente.nl/essays/101926 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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