The collapsed cone algorithm for Ir-192 dosimetry using phantom-size adaptive multiple-scatter point kernels
2015 (English)In: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 60, no 13, 5313-5323 p.Article in journal (Refereed) Published
The aim of this work was to investigate how dose distributions calculated with the collapsed cone (CC) algorithm depend on the size of the water phantom used in deriving the point kernel for multiple scatter. A research version of the CC algorithm equipped with a set of selectable point kernels for multiple-scatter dose that had initially been derived in water phantoms of various dimensions was used. The new point kernels were generated using EGSnrc in spherical water phantoms of radii 5 cm, 7.5 cm, 10 cm, 15 cm, 20 cm, 30 cm and 50 cm. Dose distributions derived with CC in water phantoms of different dimensions and in a CT-based clinical breast geometry were compared to Monte Carlo (MC) simulations using the Geant4-based brachytherapy specific MC code Algebra. Agreement with MC within 1% was obtained when the dimensions of the phantom used to derive the multiple-scatter kernel were similar to those of the calculation phantom. Doses are overestimated at phantom edges when kernels are derived in larger phantoms and underestimated when derived in smaller phantoms (by around 2% to 7% depending on distance from source and phantom dimensions). CC agrees well with MC in the high dose region of a breast implant and is superior to TG43 in determining skin doses for all multiple-scatter point kernel sizes. Increased agreement between CC and MC is achieved when the point kernel is comparable to breast dimensions. The investigated approximation in multiple scatter dose depends on the choice of point kernel in relation to phantom size and yields a significant fraction of the total dose only at distances of several centimeters from a source/implant which correspond to volumes of low doses. The current implementation of the CC algorithm utilizes a point kernel derived in a comparatively large (radius 20 cm) water phantom. A fixed point kernel leads to predictable behaviour of the algorithm with the worst case being a source/implant located well within a patient/phantom for which low doses at phantom edges can be overestimated by 2-5 %. It would be possible to improve the situation by using a point kernel for multiple-scatter dose adapted to the patient/phantom dimensions at hand.
Place, publisher, year, edition, pages
IOP Publishing , 2015. Vol. 60, no 13, 5313-5323 p.
Ir-192; model-based dose calculation algorithms; collapsed cone superposition; multiple scatter; point kernel
Radiology, Nuclear Medicine and Medical Imaging
IdentifiersURN: urn:nbn:se:liu:diva-120271DOI: 10.1088/0031-9155/60/13/5313ISI: 000356872000024PubMedID: 26108232OAI: oai:DiVA.org:liu-120271DiVA: diva2:843038
Funding Agencies|Swedish Cancer Foundation [CF 11 0495, CF 13 0470, CF 14 0641]; Canadian Cancer Society Research Institute (CCSRI) [2011-700810]2015-07-242015-07-242015-08-25