Using serial imaging data to model variabilities in organ position and shape during radiotherapy.
A model is proposed for incorporating the effects of organ motion into the calculation of dose in a statistical fashion based on serial imaging measurements of organ motion. These measurements can either come from a previously studied population of patients, or they can be specific to the particular patient undergoing therapy. The statistical distribution underlying the measurements of organ motion, including the changes in organ shape, is reconstructed non-parametrically without requiring any assumptions about its functional form. The model is thus capable of simulating organ motions that are not present in the original measurements, yet nonetheless come from the same underlying statistical distribution. The present model overcomes two particular limitations of many organ motion models: (a) the fact that they do not account for changes in organ shape, and (b) the fact that they make physically unrealistic assumptions about the functional form of the statistical distribution of organ motion, such as assuming that it is Gaussian. The present model can form the foundation of methods for the more accurate and clinically relevant calculation of the dose to the target volume and normal tissues.
Fontenla
E
E
Department of Radiation and Cellular Oncology, The University of Chicago, IL, USA. fontenla@alum.mit.edu
Pelizzari
C A
CA
Roeske
J C
JC
Chen
G T
GT
D000465:Algorithms; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D015233:Models, Statistical; D008962:Models, Theoretical; D009038:Motion; D016011:Normal Distribution; D011467:Prostate / Q000528:radiation effects; D011874:Radiometry; D011878:Radiotherapy / Q000379:methods*