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Acta Oncol. 2015;54(9):1607-13. doi: 10.3109/0284186X.2015.1061690. Epub 2015 Jul 27.

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

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a Department of Medical Physics , The Norwegian Radium Hospital, Oslo University Hospital , Oslo , Norway.
b Department of Physics , University of Oslo , Oslo , Norway.
c Department of Oncology , Oslo University Hospital , Oslo , Norway.
d Department of Radiology and Nuclear Medicine , Oslo University Hospital , Oslo , Norway.



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.


DPBN tumor dose prescription maps were generated from (18)F-FDG-PET images applying a linear relationship between image voxel value and dose. 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).


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.


The presented methodology enables the use of currently available TPSs for DPBN planning and delivery and may therefore pave the way for clinical implementation.

[Indexed for MEDLINE]

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