Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Dec;285(3):980-989.
doi: 10.1148/radiol.2017162587. Epub 2017 Jul 28.

Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans

Affiliations

Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans

Rolf Symons et al. Radiology. 2017 Dec.

Abstract

Purpose To investigate whether photon-counting detector (PCD) technology can improve dose-reduced chest computed tomography (CT) image quality compared with that attained with conventional energy-integrating detector (EID) technology in vivo. Materials and Methods This was a HIPAA-compliant institutional review board-approved study, with informed consent from patients. Dose-reduced spiral unenhanced lung EID and PCD CT examinations were performed in 30 asymptomatic volunteers in accordance with manufacturer-recommended guidelines for CT lung cancer screening (120-kVp tube voltage, 20-mAs reference tube current-time product for both detectors). Quantitative analysis of images included measurement of mean attenuation, noise power spectrum (NPS), and lung nodule contrast-to-noise ratio (CNR). Images were qualitatively analyzed by three radiologists blinded to detector type. Reproducibility was assessed with the intraclass correlation coefficient (ICC). McNemar, paired t, and Wilcoxon signed-rank tests were used to compare image quality. Results Thirty study subjects were evaluated (mean age, 55.0 years ± 8.7 [standard deviation]; 14 men). Of these patients, 10 had a normal body mass index (BMI) (BMI range, 18.5-24.9 kg/m2; group 1), 10 were overweight (BMI range, 25.0-29.9 kg/m2; group 2), and 10 were obese (BMI ≥30.0 kg/m2, group 3). PCD diagnostic quality was higher than EID diagnostic quality (P = .016, P = .016, and P = .013 for readers 1, 2, and 3, respectively), with significantly better NPS and image quality scores for lung, soft tissue, and bone and with fewer beam-hardening artifacts (all P < .001). Image noise was significantly lower for PCD images in all BMI groups (P < .001 for groups 1 and 3, P < .01 for group 2), with higher CNR for lung nodule detection (12.1 ± 1.7 vs 10.0 ± 1.8, P < .001). Inter- and intrareader reproducibility were good (all ICC > 0.800). Conclusion Initial human experience with dose-reduced PCD chest CT demonstrated lower image noise compared with conventional EID CT, with better diagnostic quality and lung nodule CNR. © RSNA, 2017 Online supplemental material is available for this article.

PubMed Disclaimer

Figures

Figure 1:
Figure 1:
Qualitative image scores for EID and PCD systems obtained by using 120-kVp dose-reduced scan settings. Scores were higher for lung tissue, lung nodules, soft tissue, bone image quality, image noise, and beam-hardening artifacts with the PCD system, whereas the EID system resulted in less streaking and fewer motion artifacts (all P < .001, paired Wilcoxon signed-rank test). Dark green indicates no artifact; green, mild artifact not interfering with diagnosis; light green, moderate artifact slightly interfering with diagnosis; yellow, pronounced artifact interfering with diagnosis; and red, artifact affecting the interpretation of a lesion or an organ of interest (based on European guidelines for image quality). For a more detailed description of the qualitative image analysis, with example images, see Appendix E1 (online).
Figure 2:
Figure 2:
Example EID and PCD CT images in a 48-year-old man (window center, −500 HU; window width, 2000 HU). Axial, A, EID and, B, PCD reconstructed images at the level of the carina. Image noise was higher in A than in B (102.9 HU vs 83.2 HU); this is best seen in the posterior lung segments (arrowheads). Sagittal, C, EID and, D, PCD reconstructed images obtained through the right lung show there is less noise on D; this is best seen in the posterior lung regions (arrowheads).
Figure 3:
Figure 3:
Example EID and PCD CT images in a 68-year-old man (window center, −500 HU; window width, 2000 HU). Axial, A, EID and, B, PCD reconstructed images of the apical lung regions. Image noise was higher in A than in B (88.0 HU vs 73.1 HU); this is best seen in the posterior lung segments (arrowheads). Details of, C, axial EID and, D, PCD reconstructions highlight the greater PCD image quality.
Figure 4:
Figure 4:
Example EID and PCD CT images in a 72-year-old man (window center, −500 HU; window width, 2000 HU). Axial, A, EID and, B, PCD reconstructed images at the level of the left lower lobe show a 5-mm incidental lung nodule (arrowhead). Details of, C, axial EID and, D, PCD reconstructions highlight greater lung nodule conspicuity and edge sharpness in D.
Figure 5:
Figure 5:
Example EID and PCD CT images in a 59-year-old man (window center, 490 HU; window width, 2500 HU). A, EID image shows low-attenuation areas in the paraspinal muscles (arrows) in the lung apices due to beam hardening. The cortex of a left upper rib (arrowheads) appears eroded. B, PCD image at the same level as A shows a more uniform appearance of the paraspinal muscles. The cortex of the upper left rib (arrowheads) is better visualized.
Figure 6:
Figure 6:
Graphs show the NPS for, A, EID and, B, PCD CT at 120 kVp and 20–200 mAs. PCD curves were consistently lower than EID curves. The difference is more prominent at lower tube currents, where electronic noise becomes more dominant in EID.
Figure 7:
Figure 7:
Graph shows image noise values for EID and PCD systems at 120- and 100-kVp dose-reduced settings. Study subjects were divided into three groups based on BMI. PCD image noise was significantly lower than EID image noise for all BMI groups for both 120- and 100-kVp dose-reduced settings (P < .010 for all three BMI groups, paired t test).

Similar articles

Cited by

References

    1. Guerra P, Santos A, Darambara DG. Development of a simplified simulation model for performance characterization of a pixellated CdZnTe multimodality imaging system. Phys Med Biol 2008;53(4):1099–1113. - PubMed
    1. Tanguay J, Kim HK, Cunningham IA. The role of x-ray Swank factor in energy-resolving photon-counting imaging. Med Phys 2010;37(12):6205–6211. - PubMed
    1. Weidinger T, Buzug TM, Flohr T, et al. . Investigation of ultra low-dose scans in the context of quantum-counting clinical CT. In: Pelc NJ, Nishikawa RM, Whiting BR, eds. Proceedings of SPIE: medical imaging 2012—physics of medical imaging. Vol 8313. Bellingham, Wash: International Society for Optics and Photonics, 2012; 83134B.
    1. Taguchi K, Iwanczyk JS. Vision 20/20: Single photon counting x-ray detectors in medical imaging. Med Phys 2013;40(10):100901. - PMC - PubMed
    1. Symons R, Cork TE, Lakshmanan MN, et al. . Dual-contrast agent photon-counting computed tomography of the heart: initial experience. Int J Cardiovasc Imaging 2017 Mar 13. [Epub ahead of print] - PubMed

Publication types

MeSH terms