Influence of X-ray spectrum and bowtie filter characterisation on the accuracy of Monte Carlo simulated organ doses: Validation in a whole-body CT scanning mode
Year: 2024
Type: article
Abstract: PURPOSE: For patient-specific CT dosimetry, Monte Carlo dose simulations require an accurate description of the CT scanner. However, quantitative spectral information and information on the bowtie filter material and shape from the manufacturer is often not available. In this study, the influence of different X-ray spectra and bowtie filter characterisation methods on simulated CT organ doses is studied. METHODS: Using ImpactMC, organ doses of whole-body CTs were simulated in twenty adult whole-body voxel models, generated from PET/CT examinations previously conducted in these patients. Simulated CT organ doses based on the manufacturer X-ray spectra and bowtie filter data were compared with those obtained using alternative characterisation models, including spectrum generators and experimentally measured dose data. A total of four different X-ray spectra and one bowtie filter model were defined based on these data. RESULTS: For all X-ray spectra and bowtie filter combinations, estimated CT organ doses are within 6% from those resulting from simulations with the CT characterisation models provided by the manufacturer. While varying the bowtie filter model results in CT organ dose differences smaller than 1%, dose differences up to 6% are observed when X-ray spectra are not based on the quantitative data from the manufacturer. CONCLUSIONS: Estimated organ doses slightly depend on the applied CT characterisation model. When manufacturer's data are not available, half-value layer and dose measurements provide sufficient input to obtain equivalent X-ray spectra and bowtie filter profiles, respectively.
Source: Physica Medica
Authors: Gwenny Verfaillie, Jeff Rutten, Lore Dewulf, Yves D’Asseler, Klaus Bacher
Institutions: Ghent University, Ghent University Hospital
Language: English
Topic: Radiation Dose and Imaging
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,450
OpenAlex ID: W4403750838