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Simulations using patient data to evaluate systematic errors that may occur in 4D treatment planning: A proof of concept study
Author(s) -
James Sara St.,
Seco Joao,
Mishra Pankaj,
Lewis John H.
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4817244
Subject(s) - radiation treatment planning , medical physics , monte carlo method , medicine , radiation therapy , nuclear medicine , medical imaging , computer science , thorax (insect anatomy) , proof of concept , radiology , mathematics , statistics , anatomy , operating system
Purpose: The purpose of this work is to present a framework to evaluate the accuracy of four‐dimensional treatment planning in external beam radiation therapy using measured patient data and digital phantoms.Methods: To accomplish this, 4D digital phantoms of two model patients were created using measured patient lung tumor positions. These phantoms were used to simulate a four‐dimensional computed tomography image set, which in turn was used to create a 4D Monte Carlo (4DMC) treatment plan. The 4DMC plan was evaluated by simulating the delivery of the treatment plan over approximately 5 min of tumor motion measured from the same patient on a different day. Unique phantoms accounting for the patient position (tumor position and thorax position) at 2 s intervals were used to represent the model patients on the day of treatment delivery and the delivered dose to the tumor was determined using Monte Carlo simulations.Results: For Patient 1, the tumor was adequately covered with 95.2% of the tumor receiving the prescribed dose. For Patient 2, the tumor was not adequately covered and only 74.3% of the tumor received the prescribed dose.Conclusions: This study presents a framework to evaluate 4D treatment planning methods and demonstrates a potential limitation of 4D treatment planning methods. When systematic errors are present, including when the imaging study used for treatment planning does not represent all potential tumor locations during therapy, the treatment planning methods may not adequately predict the dose to the tumor. This is the first example of a simulation study based on patient tumor trajectories where systematic errors that occur due to an inaccurate estimate of tumor motion are evaluated.