The effect of density variation on photon dose calculation and its impact on intensity modulated radiotherapy and stereotactic body radiotherapy

Authors


Abstract

Purpose

Inaccurate density information may introduce dose calculation errors when inhomogeneity correction is applied. The aim of the present study was to examine the effect of density variation on photon dose calculation accuracy using the convolution/superposition (CS) algorithm with the focus on newer treatment technologies including intensity modulated radiotherapy, volumetric modulated arc radiotherapy, and stereotactic body radiotherapy (SBRT).

Methods

Calculations were first performed using simple inhomogeneity phantoms in order to determine clinically relevant tolerance levels for different tissue types. The clinical validity of these tolerance levels was then demonstrated by evaluating their dosimetric impact on clinical treatment plans. The dose difference was examined by comparing the dose–volume histogram statistics and the spatial distribution of dose errors calculated on a voxel-by-voxel basis. In order to gain some insight into this issue for the Monte Carlo (MC) algorithm, the authors also performed additional validation using a MC dose calculation system.

Results

For soft tissue and bone, the tolerance levels determined from this study appear to be consistent with the values previously calculated using simpler inhomogeneity correction methods. However, the tolerance level for low density lung tissue has been found to be much smaller than what previous studies had reported. The results from this study also suggest that if density variation is restricted within ±0.02, ±0.03, and ±0.10 g/cm3 for lung, soft tissue, and bone, respectively, the resulting dose error in target volumes can be limited to <2% for most clinical cases and <3% for more challenging lung SBRT cases. When the same amount of density variation is introduced, MC algorithm yields ∼0.3%–0.9% and ∼0.0%–1.2% smaller dose errors for the target and organs-at-risk as compared to CS.

Conclusions

It is important to include lung substitute material into the periodic quality assurance of CT simulators and treatment planning systems. This study suggests that the tolerance value of CT number for lung material is ∼ ± 20 HU in order to keep the associated dose uncertainty at 2%–3% or less. Further studies with larger number of lung cases are warranted to validate this new tolerance value before it can be applied to clinical practice.

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