SU‐E‐I‐75: Evaluation of An Orthopedic Metal Artifact Reduction (O‐MAR) Algorithm On Patients with Spinal Prostheses Near Spinal Tumors

Abstract

Purpose:To evaluate the impact of a commercial orthopedic metal artifact reduction (O‐MAR) algorithm on CT image quality and dose calculation for patients with spinal prostheses near spinal tumors.Methods:A CT electron density phantom was scanned twice: with tissue‐simulating inserts only, and with a titanium insert replacing solid water. A patient plan was mapped to the phantom images in two ways: with the titanium inside or outside of the spinal tumor. Pinnacle and Eclipse were used to evaluate the dosimetric effects of O‐MAR on 12‐bit and 16‐bit CT data, respectively. CT images from five patients with spinal prostheses were reconstructed with and without O‐MAR. Two observers assessed the image quality improvement from O‐MAR. Both pencil beam and Monte Carlo dose calculation in iPlan were used for the patient study. The percentage differences between non‐OMAR and O‐MAR datasets were calculated for PTV_min, PTV_max, PTV_mean, PTV_V100, PTV_D90, OAR_V10Gy, OAR_max, and OAR_D0.1cc.Results:O‐MAR improved image quality but did not significantly affect the dose distributions and DVHs for both 12‐bit and 16‐ bit CT phantom data. All five patient cases demonstrated some degree of image quality improvement from O‐MAR, ranging from small to large metal artifact reduction. For pencil beam, the largest discrepancy was observed for OARV_10Gy at 5.4%, while the other seven parameters were ≤0.6%. For Monte Carlo, the differences between non‐O‐MAR and O‐MAR datasets were ≤3.0%.Conclusion:Both phantom and patient studies indicated that O‐MAR can substantially reduce metal artifacts on CT images, allowing better visualization of the anatomical structures and metal objects. The dosimetric impact of O‐MAR was insignificant regardless of the metal location, image bit‐depth, and dose calculation algorithm. O‐MAR corrected images are recommended for radiation treatment planning on patients with spinal prostheses because of the improved image quality and no need to modify current dose constraints.This work was supported by a research grant from Philips Healthcare. Paul Klahr is an employee of Philips Healthcare.