ArticleScientific reports2019
Perfusion-ventilation CT via three-material differentiation in dual-layer CT: a feasibility study.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- K-Edge imaging using a clinical dual-source photon-counting CT system.Journal of applied clinical medical physics · 2026Article
- Accurate iodine quantification and residual error reduction with principal component analysis multimaterial decomposition using spectral CT.Medical physics · 2026Article
- Photon-counting CT for pulmonary embolisms-when radiologists don't have to choose between image quality or motion artifacts.European radiology · 2024Article
- Lung function measurements in preclinical research: What has been done and where is it headed?Frontiers in physiology · 2023Review
- Functional imaging for assessing regional lung ventilation in preclinical and clinical research.Frontiers in medicine · 2023Review
- Five material tissue decomposition by dual energy computed tomography.Scientific reports · 2022Article
- Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT.Journal of applied clinical medical physics · 2022Review
- Quantitative assessment of pulmonary artery occlusion using lung dynamic perfusion CT.Scientific reports · 2021Article
- Article
- CTPA with a conventional CT at 100 kVp vs. a spectral-detector CT at 120 kVp: Comparison of radiation exposure, diagnostic performance and image quality.European journal of radiology open · 2020Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dual-Energy Computed Tomography is of significant clinical interest due to the possibility of material differentiation and quantification. In current clinical routine, primarily two materials are differentiated, e.g., iodine and soft-tissue. A ventilation-perfusion-examination acquired within a single CT scan requires two contrast agents, e.g., xenon and gadolinium, and a three-material differentiation. In the current study, we have developed a solution for three-material differentiation for a ventilation-perfusion-examination. A landrace pig was examined using a dual-layer CT, and three scans were performed: (1) native; (2) xenon ventilation only; (3) xenon ventilation and gadolinium perfusion. An in-house developed algorithm was used to obtain xenon- and gadolinium-density maps. Firstly, lung tissue was segmented from other tissue. Consequently, a two-material decomposition was performed for lung tissue (xenon/soft-tissue) and for remaining tissue (gadolinium/soft-tissue). Results reveal that it was possible to differentiate xenon and gadolinium in a ventilation/perfusion scan of a pig, resulting in xenon and gadolinium density maps. By summation of both density maps, a three-material differentiation (xenon/gadolinium/soft tissue) can be performed and thus, xenon ventilation and gadolinium perfusion can be visualized in a single CT scan. In an additionally performed phantom study, xenon and gadolinium quantification showed very accurate results (r > 0.999 between measured and known concentrations).
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