title: An efficient procedure for tomotherapy treatment plan verification using the on-board detector.
abstract: In this work, a fast and simple procedure for tomotherapy treatment plan verification using the on-board detector (OBD) has been developed. This procedure allows verification of plans with static and dynamic jaws (TomoEDGE). A convolution-based calculation model has been derived in order to link the leaf control sinogram from the treatment planning system to the data acquired by the OBD during a static couch procedure. The convolution kernel has been optimized using simple plans calculated in the Tomotherapy Cheese phantom. The optimal kernel has been found to be a lorentzian function, whose parameter Γ is 0.186 for the 1 cm jaw opening, 0.232 for the 2.5 cm jaw opening and 0.373 for the 5 cm jaw opening. The evaluation has been performed with a γ-index analysis. The dose criterion was 3% of the 95th percentile of the dose distribution and the distance-to-agreement criterion is 2 mm. In order to validate the procedure, it has been applied to around 50 clinical treatment plans, which had already been validated by the Delta4 phantom (Scandidos, Sweden). 96% of the tested plans have passed the criteria. Concerning the other 4%, significant discrepancies between the leaf pattern in the leaf control sinogram and the OBD data have been shown, which might be due to differences in the leaf open time. This corresponds also to a higher sensitivity of this method over the Delta4, adding the possibility of better monitoring the treatment delivery.
authors.affiliation: Department of Radiation Oncology, HFR-Hôpital Fribourgeois, Chemin des Pensionnats, Fribourg, Switzerland.
authors.forename: O
authors.initials: O
authors.lastname: Pisaturo
authors.forename: F
authors.initials: F
authors.lastname: Miéville
authors.forename: P-A
authors.initials: PA
authors.lastname: Tercier
authors.forename: A S
authors.initials: AS
authors.lastname: Allal
mesh_terms: D000465:Algorithms; D019047:Phantoms, Imaging; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*