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Clinical Evaluations of a Novel Metal Artifact Reduction Technique for Treatment Planning in Radiation Therapy


H Li

H Li1*, C Noel1, W Thorstad1, H Li1, L Yu2, D Low3, K Moore1, S Mutic1, (1) Washington University School of Medicine, SAINT LOUIS, MO, (2) Mayo Clinic, Rochester, MN, (3) UCLA, LOS ANGELES, CA

SU-E-J-176 Sunday 3:00:00 PM - 6:00:00 PM Room: Exhibit Hall

Purpose:
To evaluate the effects of a CT on-board commercially available metal artifact reduction (MAR) algorithm for the use in radiation therapy treatment planning.

Methods:
Phantom and clinical data were used for evaluation. A CIRS electron density phantom (Model 062) was scanned with Philips Brilliance BigBore 16-slice CT simulator to establish ground truth for CT Hounsfield numbers. Titanium hip prostheses were subsequently inserted into the phantom to mimic single or double hip implants. The phantom were scanned, CT images were reconstructed with and without MAR correction. Dose distributions for a 6X or an 18X beam were calculated using the three datasets and compared. CT Hounsfield number and variations were evaluated on both MAR-corrected and uncorrected images of ten clinical cases with hip implants. Dose distributions for three patients based on MAR-corrected images were compared to those of the uncorrected datasets with artifact regions density-overridden to 1.0g/cc.

Results:
Metal artifacts were reduced dramatically on MAR corrected images for all phantom and patient cases. The phantom study indicated a remarkable improvement of Hounsfield number accuracy with maximum percentage difference reduction of 45% compared to the ground truth. CT number standard variations of the critical organs for the clinical cases were reduced from 30% to 66.7%. The image geometries were not affected by the MAR algorithm. Both critical structures and targets on clinical cases went from invisible to clearly visible. For all examined phantom and clinical cases, dosimetry difference was within 3% (mostly within 1% of the target volume) of the prescription dose and was not clinical significant for dose calculations based on different image datasets.

Conclusions:
The MAR algorithm can be safely utilized in the radiation therapy treatment planning process with remarkable improvements in CT number accuracy and structure conspicuity. Dosimetry is not highly dependent on the datasets utilized for dose calculations.


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