Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry

Abstract

We developed models of lymphatic nodes for 6 pediatric and 2 adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right), and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old, and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-, and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in 6 lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for smaller phantoms due to the shorter inter-organ distances compared to the bigger phantoms. By testing sensitivity of S values to random sampling and voxel resolution, we confirmed that the lymph node model is reasonably stable and consistent for different random samplings and voxel resolutions.

Assessment of different patient‐to‐phantom matching criteria applied in Monte Carlo–based computed tomography dosimetry

“…All anatomy that was not segmented is treated as residual soft tissue or homogenous bone (ICRP Publication 89 specifications). This varies from the computational phantoms as all organs are modeled, muscle and lymph nodes are implicitly modeled, as well as bone is separated into cortical and trabecular spongiosa …”

“…This varies from the computational phantoms as all organs are modeled, muscle and lymph nodes are implicitly modeled, as well as bone is separated into cortical and trabecular spongiosa. 19…”

“…This varies from the computational phantoms as all organs are modeled, muscle and lymph nodes are implicitly modeled, as well as bone is separated into cortical and trabecular spongiosa. 19 With regard to the CT examinations, exam ranges were based on anatomical landmarks, which is harder to define in the patient-specific phantoms. These are being compared to equivalent exam ranges in the computational phantoms that are also being manually computationally defined.…”

A first-generation physiologically based pharmacokinetic (PBPK) model of alpha-tocopherol in human influenza vaccine adjuvant

“…Parameters for the draining lymph nodes were then predicted by assuming a proportional relationship between total lymph nodes in the adult human body (n = $650) to that of upper armpit lymph nodes (n = $23) (ICRP 89, 2002;Tegenge and Mitkus, 2013). Draining lymph node parameters (inguinal lymph) for the infant model were based on recent estimates from a computational lymphatic node model (Lee et al, 2013). Briefly, the inguinal lymph nodes volume for a 1-year-old infant were estimated by hybrid computational phantoms which use the number of lymphatic nodes recommendation from ICRP89 at different locations in human (Lee et al, 2013).…”

“…Draining lymph node parameters (inguinal lymph) for the infant model were based on recent estimates from a computational lymphatic node model (Lee et al, 2013). Briefly, the inguinal lymph nodes volume for a 1-year-old infant were estimated by hybrid computational phantoms which use the number of lymphatic nodes recommendation from ICRP89 at different locations in human (Lee et al, 2013). For our purpose, we directly used the reported inguinal lymph nodes (right or left) volume for a 1-year-old infant.…”