Conversion of computational human phantoms into DICOM-RT for normal tissue dose assessment in radiotherapy patients

Radiotherapy treatment planning systems are designed for the fast calculation of dose to the tumor bed and nearby organs at risk using x-ray computed tomography (CT) images. However, CT images for a patient are typically available for only a small portion of the body, and in some cases, such as for retrospective epidemiological studies, no images may be available at all. When dose to organs that lie out-of-scan must be estimated, a convenient alternative for the unknown patient anatomy is to use a matching whole-body computational phantom as a surrogate. The purpose of the current work is to connect such computational phantoms to commercial radiotherapy treatment planning systems for retrospective organ dose estimation. A custom software with graphical user interface, called the DICOM-RT Generator, was developed in MATLAB to convert voxel computational phantoms into the Digital Imaging and Communications in Medicine radiotherapy (DICOM-RT) format, compatible with commercial treatment planning systems. DICOM CT image sets for the phantoms are created via a density-to-Hounsfield unit conversion curve. Accompanying structure sets containing the organ contours are automatically generated by tracing binary masks of user-specified organs on each phantom CT slice. The software was tested on a library of body size-dependent phantoms, the International Commission on Radiological Protection reference phantoms, and a canine voxel phantom, taking only a few minutes per conversion. The resulting DICOM-RT files were tested on several commercial treatment planning systems. As an example application, a library of converted phantoms was used to estimate organ doses for members of the National Wilms Tumor Study cohort. The converted phantom library, in DICOM format, and a standalone MATLAB-compiled executable of the DICOM-RT Generator are available for others to use for research purposes (http://ncidose.cancer.gov).

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