Evaluating the influence of setup uncertainties on treatment planning for focal liver tumors.
OBJECTIVE
A mechanism has been developed to evaluate the influence of random setup variations on dose during treatment planning. The information available for studying these factors shifts from population-based models toward patient-specific data as treatment progresses and setup measurements for an individual patient become available. This study evaluates the influence of population as well as patient-specific setup distributions on treatment plans for focal liver tumors.


METHODS
Eight patients with focal liver tumors were treated on a protocol that involved online setup measurement and adjustment, as well as ventilatory immobilization. Summary statistics from these three-dimensional conformal treatments yielded individual and population distributions of position at initial setup for each fraction. A convolution model for evaluation of the influence of random setup variation on calculated dose distributions has been previously described and investigated for application to focal liver radiotherapy by our department. Individual patient doses based on initial setup positions were calculated by convolving the calculated dose distribution with an anisotropic probability distribution function representing the individual patient's random variations. A separate convolution using population-averaged random variations was performed. Individual beam apertures were then adjusted to provide plans that ensured proper dose to the clinical target volume following convolution with population distributions, as well as individual patient position uncertainty models.


RESULTS
Individual patient setup distributions for the course of treatment had random setup variations (sigma) that ranged from 2.5 to 5.7 mm (left-right), 2.1 to 8.3 mm (anterior-posterior), and 4.1 to 10.8 mm (cranial-caudal). The population random components were 4.2 mm (left-right), 4.1 mm (anterior-posterior), and 7.0 mm (cranial-caudal) at initial setup. The initial static planned dose distribution overestimated the volume of liver irradiated to high doses, because inclusion of setup uncertainties generally blurred the resulting doses, shifting the higher-dose region of normal liver dose-volume histograms to lower doses. Furthermore, the population-based dose convolution tended to predict a higher risk of radiation damage to the liver (based on an in-house parameterization of the Lyman normal tissue complication probability model) than the individual patient calculations. For an individual plan, application of different individual random variations yielded change in effective volume differences with a 3% range. Plan adjustment to account for random setup variations generally resulted in a lower change in effective volume than initial planning using a planning target volume followed by calculation of delivered dose based on random offsets.


CONCLUSIONS
This study hints at the factors that most strongly influence planning of liver treatments taking into account geometric variations. Given a setup verification methodology that rapidly reduces systematic offsets, the importance of realistic incorporation of geometric variations as an initial step in treatment planning, as well as possible plan refinement, is demonstrated.
Balter
James M
JM
Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA. jbalter@umich.edu
Brock
Kristy K
KK
Lam
Kwok L
KL
Tatro
Daniel
D
Dawson
Laura A
LA
McShan
Daniel L
DL
Ten Haken
Randall K
RK
D005240:Feasibility Studies; D006801:Humans; D008099:Liver / Q000528:radiation effects; D008113:Liver Neoplasms / Q000532:radiotherapy*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal; D035501:Uncertainty