Abstract
Photon-counting detector-based computed tomography (PCD CT) offers the unique ability to capture X-ray attenuation information at multiple user-defined energy ranges. This is achieved using novel semiconductor technology where X-rays are directly converted to electronic measurements without having to first convert to visible light, as performed conventionally in current clinical CT detectors. This allows a reduction in detector pixel sizes to enable high-resolution CT imaging without any dose penalty. Acquiring energy-resolved X-ray information using PCDs provides several benefits such as electronic noise reduction, artifact reduction, improved image contrast through uniform X-ray weighting, and K-edge imaging to discriminate contrast pharmaceuticals and targeted biomarkers. In this chapter, we introduce the basic principles of PCD CT, preclinical applications pertaining to neurological imaging, and a case report demonstrating dose efficient high-resolution CT imaging using a whole-body research PCD-CT system.
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References
Baert AL, et al., editors. Dual energy CT in clinical practice. Medical radiology—diagnostic imaging. Heidelberg: Springer; 2011.
Schlomka JP, et al. Experimental feasibility of multi-energy photon-counting K-edge imaging in pre-clinical computed tomography. Phys Med Biol. 2008;53(15):4031–47.
Hubbell JH, Seltzer SM. NIST X-ray mass attenuation coefficients—NISTIR 5632; 1996.
Yu Z, et al. Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner. J Med Imaging. 2016;3(4):043503.
Rajendran K, et al. Reducing beam hardening effects and metal artefacts in spectral CT using Medipix3RX. J Instrum. 2014;9(03):P03015.
Zhou W, et al. Metal artifact reduction and dose efficiency improvement on photon counting Ct using an additional tin filter. Med Phys. 2017;44(6):3235.
Kakinuma R, et al. Ultra-high-resolution computed tomography of the lung: image quality of a prototype scanner. PLoS One. 2015;10(9):e0137165.
McCollough CH, et al. Spatial resolution improvement and dose reduction potential for inner ear CT imaging using a z-axis deconvolution technique. Med Phys. 2013;40(6):061904.
Koenig T, et al. How spectroscopic x-ray imaging benefits from inter-pixel communication. Phys Med Biol. 2014;59(20):6195–213.
Taguchi K, Iwanczyk JS. Vision 20/20: single photon counting x-ray detectors in medical imaging. Med Phys. 2013;40(10):100901.
Leng S, et al. Spectral performance of a whole-body research photon counting detector CT: quantitative accuracy in derived image sets. Phys Med Biol. 2017;62(17):7216–32.
Faby S, et al. Performance of today’s dual energy CT and future multi energy CT in virtual non-contrast imaging and in iodine quantification: a simulation study. Med Phys. 2015;42(7):4349–66.
Anderson NG, Butler AP. Clinical applications of spectral molecular imaging: potential and challenges. Contrast Media Mol Imaging. 2014;9(1):3–12.
Schirra CO, et al. Spectral CT: a technology primer for contrast agent development. Contrast Media Mol Imaging. 2014;9(1):62–70.
Rink K, et al. Investigating the feasibility of photon-counting K-edge imaging at high x-ray fluxes using nonlinearity corrections. Med Phys. 2013;40(10):101908.
Touch M, et al. A neural network-based method for spectral distortion correction in photon counting x-ray CT. Phys Med Biol. 2016;61(16):6132–53.
Yu Z, et al. How low can we go in radiation dose for the data-completion scan on a research whole-body photon-counting computed tomography system. J Comput Assist Tomogr. 2016;40(4):663–70.
Yu Z, et al. Initial results from a prototype whole-body photon-counting computed tomography system. Proc SPIE Int Soc Opt Eng. 2015;9412:94120W.
Leng S, et al. Dose-efficient ultrahigh-resolution scan mode using a photon counting detector computed tomography system. J Med Imaging (Bellingham). 2016;3(4):043504.
Krauss B, Schmidt B, Flohr TG. Dual energy CT in clinical practice. In: Baert AL, et al., editors. Medical radiology—diagnostic imaging. Heidelberg: Springer; 2011. p. 11–20.
Gutjahr R, et al. Human imaging with photon counting–based computed tomography at clinical dose levels: contrast-to-noise ratio and cadaver studies. Invest Radiol. 2016;51(7):421–9.
Symons R, et al. Photon-counting computed tomography for vascular imaging of the head and neck: first in vivo human results. Invest Radiol. 2018;53(3):135–42.
Zhou W, et al. Reduction of metal artifacts and improvement in dose efficiency using photon-counting detector computed tomography and tin filtration. Invest Radiol. 2019;54(4):204–11. https://doi.org/10.1097/RLI.0000000000000535.
Stierstorfer K, et al. Weighted FBP—a simple approximate 3D FBP algorithm for multislice spiral CT with good dose usage for arbitrary pitch. Phys Med Biol. 2004;49(11):2209–18.
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Rajendran, K., McCollough, C.H. (2020). Photon-Counting Detector-Based Computed Tomography. In: Mannil, M., Winklhofer, SX. (eds) Neuroimaging Techniques in Clinical Practice. Springer, Cham. https://doi.org/10.1007/978-3-030-48419-4_8
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DOI: https://doi.org/10.1007/978-3-030-48419-4_8
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