BACKGROUND AND PURPOSE: Many dose-limiting normal tissues in radiotherapy (RT) display considerable internal motion between fractions over a course of treatment, potentially reducing the appropriateness of using planned dose distributions to predict morbidity.
Accounting explicitly for rectal motion could improve the predictive power of modelling rectal morbidity. To test this, we simulated the effect of motion in two cohorts.
MATERIALS AND METHODS: The included patients (232 and 159 cases) received RT for prostate cancer to 70 and 74Gy. Motion-inclusive dose distributions were introduced as simulations of random or systematic motion to the planned dose distributions. Six rectal morbidity endpoints were analysed. A probit model using the QUANTEC recommended parameters was also applied to the cohorts.
RESULTS: The differences in associations using the planned over the motion-inclusive dose distributions were modest. Statistically significant associations were obtained with four of the endpoints, mainly at high doses (55-70Gy), using both the planned and the motion-inclusive dose distributions, primarily when simulating random motion. The strongest associations were observed for GI toxicity and rectal bleeding (Rs=0.12-0.21; Rs=0.11-0.20). Applying the probit model, significant associations were found for tenesmus and rectal bleeding (Rs=0.13, p=0.02).
CONCLUSION: Equally strong associations with rectal morbidity were observed at high doses (>55Gy), for the planned and the simulated dose distributions including in particular random rectal motion. Future studies should explore patient-specific descriptions of rectal motion to achieve improved predictive power.
Written by:
Thor M, Apte A, Deasy JO, Karlsdóttir A, Moiseenko V, Liu M, Muren LP. Are you the author?
Departments of Medical Physics and Oncology, Aarhus University Hospital, Denmark; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, USA.
Reference: Radiother Oncol. 2013 Nov 11. pii: S0167-8140(13)00530-6.
doi: 10.1016/j.radonc.2013.10.021
PubMed Abstract
PMID: 24231236
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