Target sites affected by organ motion require a time resolved (4D) dose calculation. Typical 4D dose calculations use 4D-CT as a basis. Unfortunately, 4D-CT images have the disadvantage of being a “snap-shot” of the motion during acquisition and of assuming regularity of breathing. In addition, 4D-CT acquisitions involve a substantial additional dose burden to the patient making many, repeated 4D-CT acquisitions undesirable. Here the authors test the feasibility of an alternative approach to generate patient specific 4D-CT data sets.
In this approach motion information is extracted from 4D-MRI. Simulated 4D-CT data sets [which the authors call 4D-CT(MRI)] are created by warping extracted deformation fields to a static 3D-CT data set. The employment of 4D-MRI sequences for this has the advantage that no assumptions on breathing regularity are made, irregularities in breathing can be studied and, if necessary, many repeat imaging studies (and consequently simulated 4D-CT data sets) can be performed on patients and/or volunteers. The accuracy of 4D-CT(MRI)s has been validated by 4D proton dose calculations. Our 4D dose algorithm takes into account displacements as well as deformations on the originating 4D-CT/4D-CT(MRI) by calculating the dose of each pencil beam based on an individual time stamp of when that pencil beam is applied. According to corresponding displacement and density-variation-maps the position and the water equivalent range of the dose grid points is adjusted at each time instance.
4D dose distributions, using 4D-CT(MRI) data sets as input were compared to results based on a reference conventional 4D-CT data set capturing similar motion characteristics. Almost identical 4D dose distributions could be achieved, even though scanned proton beams are very sensitive to small differences in the patient geometry. In addition, 4D dose calculations have been performed on the same patient, but using 4D-CT(MRI) data sets based on variable breathing patterns to show the effect of possible irregular breathing on active scanned proton therapy. Using a 4D-CT(MRI), including motion irregularities, resulted in significantly different proton dose distributions.
The authors have demonstrated that motion information from 4D-MRI can be used to generate realistic 4D-CT data sets on the basis of a single static 3D-CT data set. 4D-CT(MRI) presents a novel approach to test the robustness of treatment plans in the circumstance of patient motion.
The liver 4D-CT data sets used in this study were kindly provided by the Radiation Oncology Department of Massachusetts General Hospital. The authors would like to thank Ted Hong and Harald Paganetti for providing the data. This work was part of the Swiss National Funds (Grant No. 320030-122526).
II. MATERIALS AND METHODS
II.A. Generating 4D-CT(MRI) data sets
II.A.1. Extracting motion deformation fields from 4D-MRI
II.A.2. Establishing correspondence between data sets
II.A.3. The generation of motion deformation fields
II.B. 4D dose calculation on a deforming dose grid
II.C. Input data
III.A. Visual comparison of 4D-CT, 4D-CT(sim), and 4D-CT(MRI) data sets
III.B. Dose calculation based validation of 4D-CT data sets
III.B.1. Dose based comparisons of 4D-CT and 4D-CT(sim) data
III.B.2. Dose based comparisons of 4D-CT and 4D-CT(MRI) data
III.C. 4D dose calculations based on 4D-CT(MRI) data including breathing variability
III.D. Dose distributions for re-scanning
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