(Wednesday, 7/17/2019) 10:00 AM - 10:30 AM
Room: Exhibit Hall | Forum 5
Purpose: The purpose of this study is to quantify interfractional dosimetric variations in radiotherapy of oropharyngeal cancer and investigate the application of statistical process control (SPC) to determine significantly deviated fractions for management.
Methods: Thirteen oropharyngeal cancer patients treated by IMRT or VMAT with daily CBCT were retrospectively reviewed. CBCT images of every other fraction were imported to the software Velocity and registered to planning CT using the 6DOF couch shifts generated during patient setup. Using Velocity “Adaptive Monitoring� module, the setup-corrected CBCT was matched to planning CT using a deformable registration. The module also generated dose volume histograms (DVHs) at each CBCT from planning doses for the deformed plan structure sets. Volumes and dose metrics at each fraction were calculated and rated with plan values to evaluate interfrational dosimetric variations using a SPC framework. T-tests between plan and fraction volumes were performed to find statistically insignificant fractions. Average, upper and lower process capacity limits (UCL, LCL) of each dose metric were derived from these fractions using conventional SPC guidelines.
Results: GTV and OAR volumes in first 13 fractions had no significantly changes from the plan, subsequently reduced by 10% to treatment completion, except oral cavity. There were 3-4% increases in parotid mean doses, but no significant differences in dose metrics of GTV and other OARs. The changes were organ and patient dependent. Control charts for various dose metrics were generated to assess the metrics for individual patient. The occurrences of one or several dose metrics out of the control limits warrant immediate investigation of the fraction.
Conclusion: Daily CBCT could be used to monitor dosimetric variations of targets and OARs resulting from volume changes and tissue deformation in oropharyngeal cancer radiotherapy. Treatment review with guidance of a SPC tool may enable objectively and consistently identify significantly deviated fractions.
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