Faculty
Science
Supervisor Name
Dr. Alexei Ouriadov
Keywords
MRI, hyperpolarized gas MRI, MATLAB, segmentation
Description
Hyperpolarized gas MRI using inert gases like Xe is a valuable tool in visualizing lung ventilation in patients, and can be used as a longitudinal monitoring tool for patients with lung diseases. However, use of this method requires segmentation and quantification of parameters such as ventilation defect percentage (VDP), which is often very subjective depending on the observer. This study aimed to determine the accuracy and consistency of VDP calculation using the same MRI scans from COVID-19 patients, but with high resolution and low (traditional) resolution versions. Using a MATLAB script developed previously, it was found that in general, using high-resolution images prevents overestimation of VDP.
Acknowledgements
This project would not have been possible without the aid of Dr. Alexei Ouriadov, Dr. Grace Parraga, the entire Parraga lab, and the Western USRI team.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Document Type
Poster
Included in
Comparing semi-automated segmentation of traditional-resolution and high-resolution hyperpolarized 129Xe MRI on COVID-19 survivors
Hyperpolarized gas MRI using inert gases like Xe is a valuable tool in visualizing lung ventilation in patients, and can be used as a longitudinal monitoring tool for patients with lung diseases. However, use of this method requires segmentation and quantification of parameters such as ventilation defect percentage (VDP), which is often very subjective depending on the observer. This study aimed to determine the accuracy and consistency of VDP calculation using the same MRI scans from COVID-19 patients, but with high resolution and low (traditional) resolution versions. Using a MATLAB script developed previously, it was found that in general, using high-resolution images prevents overestimation of VDP.