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Automatic Position Determination for Qfix Couch System Using ESAPI

H Wang*, T Chen, A Rea, A Mccarthy, D Barbee, NYU Langone Health, New York University, New York, NY

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: To automatically determine treatment couch positions from the markpoints (BBs) embedded in Qfix couch tops on planning CT. This will provide initial couch positions for patient treatment setup.

Methods: The Qfix couch system (kVue and DoseMax) has a fixed couch position correspondence between CT simulation and radiation delivery based on the H to F indexes. These couches have embedded BBs indicating the indexes and couch center. With Varian Eclipse system, a C# script using ESAPI was programmed to automatically find the couch and BBs on planning CT and derive treatment couch position from their distances to the planned treatment isocenter. The script was used to extract couch positions for SBRT plans with DoseMax and conventional EBRT with kVue couch for various treatment sites. The estimated vertical, lateral and longitudinal positions were compared with those acquired on film-only or first- day treatment.

Results: Comparing BB’s 3D positions on CT images between scripting estimation and manual selection in Eclipse for 55 plans, the medians (min, max) of the differences are 0 (-0.2, 0.2), 0 (-0.3, 0.1) and 0 (-0.2, 0.2) cm in x, y and z orientations, respectively. In 11 SBRT plans using the DoseMax couch, the median (5% and 95% percentiles) differences in couch positions between estimated and acquired values are 0.2(-0.2 and 0.6), 0.0 (-0.2 and 0.4) and 0.4 (0 and 0.6) cm for vertical, longitudinal and lateral directions, respectively. For the 44 plans using kVue, the median differences are 0.1 (-0.2 and 1.0), 0.5 (-0.7 and 1.6) and 0.2 (-0.4 and 1.2).

Conclusion: We have developed a method automatically deriving treatment couch positions from simulation CT for the Qfix couch system. This automated process could increase the efficiency of patient setup and reduce plan modifications when inconsistencies are discovered at the time of patient mode up.

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