Correcting Image Distortion for Brain Tumor Treatments On An MRI-Linac
S Shan1,2*, D Waddington1,2, P Liu1,2, B Dong2, J Buckley2,3, D Elwadia4, T Pham4, G Liney2,3,4, P Keall1,2, (1) ACRF Image X Institute, University of Sydney School of Health Sciences, Sydney, NSW, Australia (2) Ingham Institute For Applied Medical Research, Liverpool, NSW, 2170, Australia (3) Centre for Medical Radiation Physics, University of Wollongong, Wollongong, New South Wales, Australia (4) Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
Presentations
TH-C-TRACK 3-2 (Thursday, 7/29/2021) 1:00 PM - 2:00 PM [Eastern Time (GMT-4)]
Purpose: MRI-Linac systems have been developed to enable real-time image guidance and adaptive tumor tracking during radiotherapy treatments. However, MR gradient design constraints in these hybrid systems can lead to geometric distortions and inaccurate tumor shapes and positions, risking unnecessary radiation dose to surrounding healthy tissues. Here, we quantitatively analyze and correct geometric distortions on a 1.0 T inline MRI-Linac to facilitate accurate brain tumor treatments.
Methods: A grid phantom with 3718 markers was used to measure distortion on an MRI-Linac in a 20cm×20cm×30cm volume. Based on measured distorted and undistorted marker positions, a spherical harmonic (SH) model was established to characterize and to correct the geometric distortion. A head phantom was then scanned in an MRI-Linac and a CT system to provide test MR images and CT (undistorted) reference images. The contours of head phantom MR images before and after correction were compared with CT reference images.
Results: The magnitude of geometric distortion in the MRI-Linac increased with distance from the isocenter. The maximum displacement within the head phantom volume (15cm×15cm×15cm) was 5.0±1.8 mm before correction. The slices containing the orbits, a key organ at risk, had maximum displacement 3.6±1.8 mm. Applying the SH correction model reduced distortion by a factor of 3.
Conclusion: Geometric distortion on brain images was quantitatively analyzed and the SH method was used to effectively reduce image distortion. This work will improve the accuracy of brain tumor treatments on MRI-Linacs.
Funding Support, Disclosures, and Conflict of Interest: The authors acknowledge the financial support of the NHMRC grant (grant No. 1132471). Paul Liu and David Waddington acknowledge funding from Cancer InstituteNSW fellowships.
Handouts
Keywords
MRI, Geometric Distortion, Radiation Therapy
Taxonomy
IM- MRI : Quality Control and Image Quality Assessment
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