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MSc Project for Implementing quality assurance tests & database on MRI Scanner
MRI scanners are complex instruments that are used daily in hospitals and research centres around the world both for high-end research as well as diagnostic radiology. To ensure that the data quality is adequate for these purposes quality assurance measures must be implemented and performed regularl
Keywords: Magnetic Resonance Imaging, MRI, Quality Assurance, QA, Database, Matlab, Programming, C++
The popularity of magnetic resonance imaging (MRI) stems from the multitude of image contrasts available to the user. While, for example, X-ray or ultrasound imaging only offer 1 or two different modes of operation an MRI scanner can measure high quality images that can be differentially sensitized to provide e.g.:
- Anatomical images for diagnostics
- Areas of neuronal functional activity (fMRI)
- The diffusion constant within the tissue
- Flow rate of blood within the blood vessels
- Perfusion of the tissue
- Bone structure
- Iron content in tissue
While MRI scanners are built to high standards, improvements are possible and even necessary to keep in step with the increasing demands of the research and clinical environments. Furthermore, to ensure that the data quality we collect with the MRI scanner is reliable for the task at hand, regular quality assurance tests must be performed. Looking at the above list of potential uses of MRI scanners it is clear that quality assurance testing is a complex and challenging task. The different image contrasts require different tests and different test objects. Look at the above figure as an example. The data is the signal intensity acquired from a test object placed in two different MRI scanners. On which scanner should we preform our functional MRI (fMRI) study for highest sensitivity for detecting brain activation in a live human? As it turns out data from Scanner 2 (red) are more suitable because the large drift over time is much slower than the signal of interest (the brain activity) so it can be eliminated by high pass filtering. The short-term fluctuations however are much more severe in the data from Scanner 1 (blue), but this we cannot easily filter out because then we would eliminate our signal of interest as well.
It must be noted that collection of quality assurance data is hardly useful unless these data can be stored in a searchable database for future reference or investigating long-term trends.
**Detailed goals and milestones of the project:**
• Thorough literature search of the relevant quality assurance tests (e.g. temporal SNR)
• Set up test procedures the relevant imaging modalities (see above list)
• Implement analysis pipeline in Matlab (preferred) or c++ to summarise QA test results
• Implement a database solution for storing data and test results
• Implement database querying to view past results and plot against newest data point
Document all steps in above step to aid future continuation of the project
The popularity of magnetic resonance imaging (MRI) stems from the multitude of image contrasts available to the user. While, for example, X-ray or ultrasound imaging only offer 1 or two different modes of operation an MRI scanner can measure high quality images that can be differentially sensitized to provide e.g.: - Anatomical images for diagnostics - Areas of neuronal functional activity (fMRI) - The diffusion constant within the tissue - Flow rate of blood within the blood vessels - Perfusion of the tissue - Bone structure - Iron content in tissue While MRI scanners are built to high standards, improvements are possible and even necessary to keep in step with the increasing demands of the research and clinical environments. Furthermore, to ensure that the data quality we collect with the MRI scanner is reliable for the task at hand, regular quality assurance tests must be performed. Looking at the above list of potential uses of MRI scanners it is clear that quality assurance testing is a complex and challenging task. The different image contrasts require different tests and different test objects. Look at the above figure as an example. The data is the signal intensity acquired from a test object placed in two different MRI scanners. On which scanner should we preform our functional MRI (fMRI) study for highest sensitivity for detecting brain activation in a live human? As it turns out data from Scanner 2 (red) are more suitable because the large drift over time is much slower than the signal of interest (the brain activity) so it can be eliminated by high pass filtering. The short-term fluctuations however are much more severe in the data from Scanner 1 (blue), but this we cannot easily filter out because then we would eliminate our signal of interest as well.
It must be noted that collection of quality assurance data is hardly useful unless these data can be stored in a searchable database for future reference or investigating long-term trends.
**Detailed goals and milestones of the project:** • Thorough literature search of the relevant quality assurance tests (e.g. temporal SNR) • Set up test procedures the relevant imaging modalities (see above list) • Implement analysis pipeline in Matlab (preferred) or c++ to summarise QA test results • Implement a database solution for storing data and test results • Implement database querying to view past results and plot against newest data point Document all steps in above step to aid future continuation of the project
The aim of this MSc project is to implement relevant quality assurance test procedures along with the analysis of the data and a database solution for storing the test results
The aim of this MSc project is to implement relevant quality assurance test procedures along with the analysis of the data and a database solution for storing the test results
Dr. Zoltan Nagy
zoltan.nagy@biomed.ee.ethz.ch
+41 44 255 4493
Dr. Zoltan Nagy zoltan.nagy@biomed.ee.ethz.ch +41 44 255 4493