ArticlePhysics in medicine and biology2019
Towards 4D dedicated breast CT perfusion imaging of cancer: development and validation of computer simulated images.
Article in Physics in medicine and biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Evaluation of quantitative accuracy in 4D DCE-bCT: Insights from a perfusion phantom study.Medical physics · 2026Article
- Radiomics in cone-beam breast CT for the prediction of axillary lymph node metastasis in breast cancer: a multi-center multi-device study.European radiology · 2024Article
- Development, validation, and simplification of a scanner-specific CT simulator.Medical physics · 2024Article
- Dedicated breast CT: state of the art-Part II. Clinical application and future outlook.European radiology · 2022Review
- A phantom study comparing low-dose CT physical image quality from five different CT scanners.Quantitative imaging in medicine and surgery · 2022Article
- Motion artifacts assessment and correction using optical tracking in synchrotron radiation breast CT.Medical physics · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Dedicated breast CT is a fully tomographic breast imaging modality with potential for various applications throughout breast cancer care. If implemented to perform dynamic contrast-enhanced (CE) imaging (4D breast CT), it could be useful to obtain functional information at high combined spatio-temporal resolution. Before developing a 4D dedicated breast CT system, a computer simulation method for breast CT perfusion imaging is proposed. The simulation uses previously developed patient-based 4D digital breast phantoms, and generates realistic images with the selected acquisition parameters, allowing to investigate the effect of different acquisition settings on image quality. The simulation pipeline includes all steps of the image generation process, from ray tracing and scatter map generation, to the addition of realistic resolution losses and noise models. The pipeline was validated against experimental measurements performed on physical phantoms with a dedicated breast CT system, in terms of average error compared to ground truth projections (6.0% ± 1.65%), Hounsfield unit (HU) values in a homogeneous phantom (acquired: -149 HU ± 2 HU; simulated: -140 HU ± 2 HU), signal-to-noise ratio (SNR) (average error 6.7% ± 4.2%), noise power spectra (NPS) (average error 4.3% ± 2.5%), modulation transfer function (MTF) (average error 8.4% ± 7.2%), and attenuation of different adipose/glandular equivalent mixtures (average error 6.9% ± 4.0%) and glandular plus iodinated contrast medium concentrations equivalent mixtures (average error of 9.1% ± 9.0%). 4D patient images were then simulated for different 4D digital breast phantoms at different air kerma levels to determine the effect of noise on the extracted tumor perfusion curves. In conclusion, the proposed pipeline could simulate images with a good level of realism, resulting in a tool that can be used for the design, development, and optimization of a 4D dedicated breast CT system.
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