Program Information
Image Distortion Quantification and Image Registration QA in GammaKnife Radiosurgery Using A Modus GRID3D Phantom
L Lu*, K Noa , K Woods , M Weldon , N Gupta , Ohio State University, Columbus, OH
Presentations
SU-E-J-274 Sunday 3:00PM - 6:00PM Room: Exhibit HallPurpose:
To quantify image distortion in MRI and CT images used in GammaKnife radiosurgery planning with a Modus GRID3D phantom.
Methods:
Image distortion in GammaKnife radiosurgery can affect treatment efficacy by inaccurately depicting tumors and organs at risk in the brain. It is therefore important that a quantified QA check on image distortion be performed periodically. A commercial 3-dimensional grid phantom and its associated software, GRID3D (Modus Medical Devices Inc.), was used in determining image distortion on the MRI machines and the CT-simulator that are used clinically for GammaKnife treatment planning. The GammaKnife head frame and frame box were placed on the phantom and imaged on each MRI and CT machine according to GammaKnife imaging protocols used clinically at our institution. The obtained images were imported into the GRID3D Image Distortion Analysis System where the distortion of each image set was calculated. The calculation works by quantifying the 3D spatial deviation between the reconstructed image sets and the program’s reference phantom. For registration QA, the CT and MR image sets were registered with each other. The regular analysis of grids alignment allows us to evaluate the quality of image registration from MRI to CT (commonly used in the Gamma Knife preplan scheme) and vice versa.
Results:
Distortion analysis using the GRID3D phantom numerically represented image distortion in the x, y, and z direction for each MRI machine and CT simulator used clinically for GammaKnife treatments. The spatial deviation between images in each direction is generally less than or equal to 1 mm when the imager is functioning properly. Image registration QA using the GRID3D phantom proves to be very efficient.
Conclusion:
The quantified image distortion check is important and should be incorporated into routine QA practice. It is especially important to perform this check immediately after a major machine upgrade.
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