ArticleJournal of medical imaging (Bellingham, Wash.)2015
Optimization of beam quality for photon-counting spectral computed tomography in head imaging: simulation study.
Article in Journal of medical imaging (Bellingham, Wash.), 2015. 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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10 citing papers in PubMed, 24 citations in OpenAlex.
- Non-contrast photon counting computed tomography of the head: optimized modeling of off-focal radiation to reduce calvarium-related tissue inhomogeneity.BMC medical imaging · 2025Article
- Spectral optimization using fast kV switching and filtration for photon counting CT with realistic detector responses: a simulation study.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Photon-counting computed tomography in radiology.Polish journal of radiology · 2024Review
- Noise correlation and its impact on the performance of multi-material decomposition-based spectral imaging in photon-counting CT.Journal of applied clinical medical physics · 2023Article
- Spectral Photon Counting CT: Imaging Algorithms and Performance Assessment.IEEE transactions on radiation and plasma medical sciences · 2021Article
- Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement.Medical physics · 2020Review
- Detective quantum efficiency of photon-counting CdTe and Si detectors for computed tomography: a simulation study.Journal of medical imaging (Bellingham, Wash.) · 2020Article
- A framework for performance characterization of energy-resolving photon-counting detectors.Medical physics · 2018Article
- Generation and analysis of clinically relevant breast imaging x-ray spectra.Medical physics · 2017Article
- Estimation of signal and noise for a whole-body research photon-counting CT system.Journal of medical imaging (Bellingham, Wash.) · 2017Article
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4 authors at 1 institution in 1 country.
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Abstract
Head computed tomography (CT) plays an important role in the comprehensive evaluation of acute stroke. Photon-counting spectral detectors, as promising candidates for use in the next generation of x-ray CT systems, allow for assigning more weight to low-energy x-rays that generally contain more contrast information. Most importantly, the spectral information can be utilized to decompose the original set of energy-selective images into several basis function images that are inherently free of beam-hardening artifacts, a potential advantage for further improving the diagnosis accuracy. We are developing a photon-counting spectral detector for CT applications. The purpose of this work is to determine the optimal beam quality for material decomposition in two head imaging cases: nonenhanced imaging and K-edge imaging. A cylindrical brain tissue of 16-cm diameter, coated by a 6-mm-thick bone layer and 2-mm-thick skin layer, was used as a head phantom. The imaging target was a 5-mm-thick blood vessel centered in the head phantom. In K-edge imaging, two contrast agents, iodine and gadolinium, with the same concentration ([Formula: see text]) were studied. Three parameters that affect beam quality were evaluated: kVp settings (50 to 130 kVp), filter materials ([Formula: see text] to 83), and filter thicknesses [0 to 2 half-value layer (HVL)]. The image qualities resulting from the varying x-ray beams were compared in terms of two figures of merit (FOMs): squared signal-difference-to-noise ratio normalized by brain dose ([Formula: see text]) and that normalized by skin dose ([Formula: see text]). For nonenhanced imaging, the results show that the use of the 120-kVp spectrum filtered by 2 HVL copper ([Formula: see text]) provides the best performance in both FOMs. When iodine is used in K-edge imaging, the optimal filter is 2 HVL iodine ([Formula: see text]) and the optimal kVps are 60 kVp in terms of [Formula: see text] and 75 kVp in terms of [Formula: see text]. A tradeoff of 65 kVp was proposed to lower the potential risk of skin injuries if a relatively long exposure time is necessarily performed in the iodinated imaging. In the case of gadolinium imaging, both SD and BD can be minimized at 120 kVp filtered with 2 HVL thulium ([Formula: see text]). The results also indicate that with the same concentration and their respective optimal spectrum, the values of [Formula: see text] and [Formula: see text] in gadolinium imaging are, respectively, around 3 and 10 times larger than those in iodine imaging. However, since gadolinium is used in much lower concentrations than iodine in the clinic, iodine may be a preferable candidate for K-edge imaging.
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