Purpose: To develop and evaluate a fast patient localization tool using megavoltage (MV)-topograms on helical TomoTherapy.
Methods: A MV-topogram imaging workflow was created and integrated into our clinical workflow under an IRB-approved clinical trial. Prior to conducting the standard MVCT imaging workflow, the MV-topograms in AP/LAT views were acquired weekly for 16 pelvis patients. The MV-topogram imaging protocol for pelvis requires two orthogonal acquisitions at static gantry angles of 0Â°/90Â° for a programed 50 cm scan length in 12.5 seconds. A MATLAB based in-house software was developed to reconstruct the MV-topograms offline. Reference imaged (DRTs) were generated using the planning CT and Tomotherapy geometry. The MV-topogram based alignment was determined by registering the MV-topograms to the DRT using bony landmark on commercial MIM software. The daily shifts in three translational directions determined from MV-topograms were compared to the MVCT-based patient shifts. A linear-regression was performed to investigate the correlations between the two techniques in three translational directions. The imaging doses were measured with an A1SL ion chamber and cheese phantom at depth of 1 to 14 cm for both techniques.
Results: The magnitudes of alignment differences (and standard deviations) were 0.4Â±2.8 mm, 1.0Â±2.7 mm, -0.9Â±2.6 mm, and the linear regression coefficients between two imaging techniques were 0.92, 1.12, and 0.94 in the lateral, longitudinal and vertical directions, respectively. The acquisition time for a pair of MV-topograms was 4.8-10.0 times less than MVCT scans (coarse mode) with similar or longer scan length. The ratio of imaging doses of the MV-topograms were 14.7 to 26.9 smaller than the MVCTs at the same depth.
Conclusion: MV-topograms showed equivalent clinical performance to the standard MVCT with significantly less acquisition time for pelvis patients. The MV-topogram can be utilized as an alternative or complimentary tool for bony landmark-based patient alignment on TomoTherapy.
Funding Support, Disclosures, and Conflict of Interest: This work is partially supported by Accuray Inc.