Dose painting by numbers in a standard treatment planning system using inverted dose prescription maps

Marius Røthe Arnesen, Ingerid Skjei Knudtsen, Bernt Louni Rekstad, Karsten Eilertsen, Einar Dale, Kjersti Bruheim, Åslaug Helland, Ayca Muftuler Løndalen, Taran Paulsen Hellebust, Eirik Malinen
2015 Acta Oncologica  
background. Dose painting by numbers (DPBN) is a method to deliver an inhomogeneous tumor dose voxel-by-voxel with a prescription based on biological medical images. However, planning of DPBN is not supported by commercial treatment planning systems (TPS) today. Here, a straightforward method for DPBN with a standard TPS is presented. Material and methods. DPBN tumor dose prescription maps were generated from 18 F-FDG-PET images applying a linear relationship between image voxel value and dose.
more » ... An inverted DPBN prescription map was created and imported into a standard TPS where it was defined as a mock pre-treated dose. Using inverse optimization for the summed dose, a planned DPBN dose distribution was created. The procedure was tested in standard TPS for three different tumor cases; cervix, lung and head and neck. The treatment plans were compared to the prescribed DPBN dose distribution by three-dimensional (3D) gamma analysis and quality factors (QFs). Delivery of the DPBN plans was assessed with portal dosimetry (PD). results. Maximum tumor doses of 149%, 140% and 151% relative to the minimum tumor dose were prescribed for the cervix, lung and head and neck case, respectively. DPBN distributions were well achieved within the tumor whilst normal tissue doses were within constraints. Generally, high gamma pass rates ( 89% at 2%/2 mm) and low QFs ( 2.6%) were found. PD showed that all DPBN plans could be successfully delivered. conclusions. The presented methodology enables the use of currently available TPSs for DPBN planning and delivery and may therefore pave the way for clinical implementation. Acta Oncologica, 2015; 54: 1607-1613 issN 0284-186X print/issN 1651-226X online © 2015 informa Healthcare
doi:10.3109/0284186x.2015.1061690 pmid:26213311 fatcat:wiweasnrmnevhcci2snm3euzje