An anatomically realistic lung model for Monte Carlo-based dose calculations.
Treatment planning for disease sites with large variations of electron density in neighboring tissues requires an accurate description of the geometry. This self-evident statement is especially true for the lung, a highly complex organ having structures with a wide range of sizes that range from about 10(-4) to 1 cm. In treatment planning, the lung is commonly modeled by a voxelized geometry obtained using computed tomography (CT) data at various resolutions. The simplest such model, which is often used for QA and validation work, is the atomic mix or mean density model, in which the entire lung is homogenized and given a mean (volume-averaged) density. The purpose of this paper is (i) to describe a new heterogeneous random lung model, which is based on morphological data of the human lung, and (ii) use this model to assess the differences in dose calculations between an actual lung (as represented by our model) and a mean density (homogenized) lung. Eventually, we plan to use the random lung model to assess the accuracy of CT-based treatment plans of the lung. For this paper, we have used Monte Carlo methods to make accurate comparisons between dose calculations for the random lung model and the mean density model. For four realizations of the random lung model, we used a single photon beam, with two different energies (6 and 18 MV) and four field sizes (1 x 1, 5 x 5, 10 x 10, and 20 x 20 cm2). We found a maximum difference of 34% of D(max) with the 1 x 1, 18 MV beam along the central axis (CAX). A "shadow" region distal to the lung, with dose reduction up to 7% of D(max), exists for the same realization. The dose perturbations decrease for larger field sizes, but the magnitude of the differences in the shadow region is nearly independent of the field size. We also observe that, compared to the mean density model, the random structures inside the heterogeneous lung can alter the shape of the isodose lines, leading to a broadening or shrinking of the penumbra region. For small field sizes, the mean lung doses significantly depend on the structures' relative locations to the beam. In addition to these comparisons between the random lung and mean density models, we also provide a preliminary comparison between dose calculations for the random lung model and a voxelized version of this model at 0.4 x 0.4 x 0.4 cm3 resolution. Overall, this study is relevant to treatment planning for lung tumors, especially in situations where small field sizes are used. Our results show that for such situations, the mean density model of the lung is inadequate, and a more accurate CT model of the lung is required. Future work with our model will involve patient motion, setup errors, and recommendations for the resolution of CT models.
Liang
Liang
L
Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, Michigan 48109-2104, USA. lliang@umich.edu
Larsen
Edward W
EW
Chetty
Indrin J
IJ
D003198:Computer Simulation; D006801:Humans; D008168:Lung / Q000473:pathology*; D008175:Lung Neoplasms / Q000532:radiotherapy*; D015233:Models, Statistical; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D017785:Photons; D011829:Radiation Dosage; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*