Development of an age-scalable 3D computational phantom in DICOM standard for late effects studies of childhood cancer survivors

Abstract

Purpose: We previously developed an age-scalable 3D computational phantom that has been widely used for retrospective whole-body dose reconstructions of conventional two-dimensional historic radiation therapy (RT) treatments in late effects studies of childhood cancer survivors. This phantom is modeled in the FORTRAN programming language and is not readily applicable for dose reconstructions for survivors treated with contemporary RT whose treatment plans were designed using computed tomography images and complex treatment fields. The goal of this work was to adapt the current FORTRAN model of our age-scalable computational phantom into Digital Imaging and Communications in Medicine (DICOM) standard so that it can be used with any treatment planning system (TPS) to reconstruct contemporary RT. Additionally, we report a detailed description of the phantom's age-based scaling functions, information that was not previously published.

Method: We developed a Python script that adapts our phantom model from FORTRAN to DICOM. To validate the conversion, we compared geometric parameters for the phantom modeled in FORTRAN and DICOM scaled to ages 1 month, 6 months, 1, 2, 3, 5, 8, 10, 15, and 18 years. Specifically, we calculated the percent differences between the corner points and volume of each body region and the normalized mean square distance (NMSD) between each of the organs. In addition, we also calculated the percent difference between the heights of our DICOM age-scaled phantom and the heights (50th percentile) reported by the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) for male and female children of the same ages. Additionally, we calculated the difference between the organ masses for our DICOM phantom and the organ masses for two reference phantoms (from International Comission on Radiation Protection (ICRP) 89 and the University of Florida/National Cancer Institute reference hybrid voxel phantoms) for ages newborn, 1, 5, 10, 15 and adult. Lastly, we conducted a feasibility study using our DICOM phantom for organ dose calculations in a commercial TPS. Specifically, we simulated a 6 MV photon right-sided flank field RT plan for our DICOM phantom scaled to age 3.9 years; treatment field parameters and age were typical of a Wilms tumor RT treatment in the Childhood Cancer Survivor Study. For comparison, the same treatment was simulated using our in-house dose calculation system with our FORTRAN phantom. The percent differences (between FORTRAN and DICOM) in mean dose and percent of volume receiving dose ⩾5 Gy were calculated for two organs at risk, liver and pancreas.

Results: The percent differences in corner points and the volumes of head, neck, and trunk body regions between our phantom modeled in FORTRAN and DICOM agreed within 3%. For all of the ages, the NMSDs were negliglible with a maximum NMSD of 7.80 × 10^-2 mm for occiptital lobe of 1 month. The heights of our age-scaled phantom agreed with WHO/CDC data within 7% from infant to adult, and within 2% agreement for ages 5 years and older. We observed that organ masses in our phantom are less than the organ masses for other reference phantoms. Dose calculations done with our in-house calculation system (with FORTRAN phantom) and commercial TPS (with DICOM phantom) agreed within 7%.

Conclusion: We successfully adapted our phantom model from the FORTRAN language to DICOM standard and validated its geometric consistency. We also demonstrated that our phantom model is representative of population height data for infant to adult, but that the organ masses are smaller than in other reference phantoms and need further refinement. Our age-scalable computational phantom modeled in DICOM standard can be scaled to any age at RT and used within a commercial TPS to retrospectively reconstruct doses from contemporary RT in childhood cancer survivors.

Keywords: computational phantoms; dose reconstruction; late effects; pediatric phantoms.

Figure 1.

Diagrams of our computational phantom fitted to a 3D grid of points: (a) coronal view showing +x and −y axes and (b) sagittal view showing −y and −z axes. A skeleton is overlaid on the phantom for anatomic reference. The scalable body regions (head, neck, trunk, and extremities) are delineated in frontal view.

Figure 2.

(A)–(E) Growth as a function of age from superior to inferior, left to right, and anterior to posterior for the head, neck, trunk, arms and legs for ages 1 month, 1, 3, 5, 10, 15, and 18 (adult) years (Snyder et al 1977, Huelke 1998).

Figure 3.

Flow chart explaining the adaptation of the phantom to DICOM standard.

Figure 4.

Right-sided AP/PA treatment fields simulated for Wilms’ tumor on a phantom scaled to 3.9 years in (a) FORTRAN and (b) DICOM formats. The coordinates of the field isocenters and field borders were the same in both planning systems.

Figure 5.

Illustration of TPS generated 3D renderings of age-scaled phantoms modeled in DICOM. Selected organs (brain, lungs, heart, liver, and stomach) were also rendered for each scaled phantom.

Figure 6.

Histogram showing the frequency of percent differences in the corner points of body regions (excluding legs and arms) of the DICOM phantoms.

Figure 7.

Comparison of the heights of the computational phantom modeled in DICOM with the WHO/CDC heights (Centers for Disease Control and Prevention 2000).