Abdominal Radiology

, Volume 42, Issue 11, pp 2752–2759 | Cite as

Quality of routine diagnostic abdominal images generated from a novel detector-based spectral CT scanner: a technical report on a phantom and clinical study

  • Mojgan Hojjati
  • Steven Van Hedent
  • Negin Rassouli
  • Curtis Tatsuoka
  • David Jordan
  • Amar Dhanantwari
  • Prabhakar RajiahEmail author



To evaluate the image quality of routine diagnostic images generated from a novel detector-based spectral detector CT (SDCT) and compare it with CT images obtained from a conventional scanner with an energy-integrating detector (Brilliance iCT), Routine diagnostic (conventional/polyenergetic) images are non-material-specific images that resemble single-energy images obtained at the same radiation,


ACR guideline-based phantom evaluations were performed on both SDCT and iCT for CT adult body protocol. Retrospective analysis was performed on 50 abdominal CT scans from each scanner. Identical ROIs were placed at multiple locations in the abdomen and attenuation, noise, SNR, and CNR were measured. Subjective image quality analysis on a 5-point Likert scale was performed by 2 readers for enhancement, noise, and image quality.


On phantom studies, SDCT images met the ACR requirements for CT number and deviation, CNR and effective radiation dose. In patients, the qualitative scores were significantly higher for the SDCT than the iCT, including enhancement (4.79 ± 0.38 vs. 4.60 ± 0.51, p = 0.005), noise (4.63 ± 0.42 vs. 4.29 ± 0.50, p = 0.000), and quality (4.85 ± 0.32, vs. 4.57 ± 0.50, p = 0.000). The SNR was higher in SDCT than iCT for liver (7.4 ± 4.2 vs. 7.2 ± 5.3, p = 0.662), spleen (8.6 ± 4.1 vs. 7.4 ± 3.5, p = 0.152), kidney (11.1 ± 6.3 vs. 8.7 ± 5.0, p = 0.033), pancreas (6.90 ± 3.45 vs 6.11 ± 2.64, p = 0.303), aorta (14.2 ± 6.2 vs. 11.0 ± 4.9, p = 0.007), but was slightly lower in lumbar-vertebra (7.7 ± 4.2 vs. 7.8 ± 4.5, p = 0.937). The CNR of the SDCT was also higher than iCT for all abdominal organs.


Image quality of routine diagnostic images from the SDCT is comparable to images of a conventional CT scanner with energy-integrating detectors, making it suitable for diagnostic purposes.


Dual energy Spectral Diagnostic Blended 


Compliance with ethical standards


This study was funded by institutional research grant from Philips Healthcare.

Conflict of interest

Prabhakar Rajiah received speaker honoraria from Philips healthcare. Amar Dhanantwari is an employee of Philips Healthcare. The other authors declare that they do not have conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants who were scanned on the SDCT. There was IRB-approved waiver of consent for the retrospective review of patients scanned on the iCT.


  1. 1.
    Johnson TRC (2012) Dual-energy CT: general principles. AJR Am J Roentgenol 199:S3–S8CrossRefPubMedGoogle Scholar
  2. 2.
    Yu L, Leng S, McCollough CH (2012) Dual-energy CT based monochromatic imaging. AJR Am J Roentgenol 199:S9–S15CrossRefPubMedGoogle Scholar
  3. 3.
    Henzler T, Fink C, Schoenberg SO, Schopef J (2012) Dual-energy CT: radiation dose aspects. AJR Am J Roentgenol 199:S16–S25CrossRefPubMedGoogle Scholar
  4. 4.
    Holmes DR, Fletcher JG, Apel A, Huprich JE, et al. (2008) Evaluation of non-linear blending in dual-energy computed tomography. Eur J Radiol 68:409–413CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Darras KE, McLaughlin PD, Kang H, et al. (2016) Virtual monoenergetic reconstruction of contrast-enhanced dual energy CT at 70 keV maximizes mural enhancement in acute small bowel obstruction. Eur J Radiol 85(5):950–956CrossRefPubMedGoogle Scholar
  6. 6.
    Rajiah P, Abbara S, Halliburton SS (2017) Spectral detector CT for cardiovascular applications. Diagn Interv Radiol. doi: 10.5152/dir.2016.16255 PubMedPubMedCentralGoogle Scholar
  7. 7.
    Ananthakrishnan L, Rajiah P, Ahn R, et al. (2017) Spectral detector CT-derived virtual non-contrast images: comparison of attenuation values with unenhanced CT. Abdom Radiol 42(3):702–709CrossRefGoogle Scholar
  8. 8.
    Brooks RA, Di Chiro G (1978) Split-detector computed tomography: a preliminary report. Radiology 126(1):255–257CrossRefPubMedGoogle Scholar
  9. 9.
    Can Hamersvelt RW, Schilham AM, Engelke K, et al. (2017) Accuracy of bone mineral density quantification using dual-layer spectral detector CT: a phantom study. Eur Radiol . doi: 10.1007/s00330-017-4801-4 Google Scholar
  10. 10.
    Wellenberg RH, Boomsma MF, van Osch JA, et al. (2017) Quantifying metal artifact reduction using virtual monochromatic dual-layer detector spectral CT imaging in unilateral and bilateral total hip prostheses. Eur J Radiol 88:61–70CrossRefPubMedGoogle Scholar
  11. 11.
    Hicthethier T, Baebler B, Kroeger JR, et al. (2017) Monoenergetic reconstructions for imaging of coronary artery stents using spectral detector CT: in vitro experience and comparison to conventional images. J Ardiovasc Comput Tomogr 11(1):33–39CrossRefGoogle Scholar
  12. 12.
    Pelgrim GJ, van Hamservelt RW, Willemink MJ, et al. (2017) Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT. Eur Radiol . doi: 10.1007/s00330-017-472-9 PubMedCentralGoogle Scholar
  13. 13.
    Van Hamersvelt RW, Willemink MJ, de Jong PA, et al. (2017) Feasibility and accuracy of dual-layer spectral detector computed tomography for quantification of gadolinium: a phantom study. Eur Radiol . doi: 10.1007/s00330=017-4737-8 Google Scholar
  14. 14.
    Gabbai, M, Leichter I, Zimam R, et al. The Clinical Impact of Retrospective Analysis in Spectral Detector Dual Energy Body CT. Radiological Society of North America 2013 Scientific Assembly and Annual Meeting, December 1–December 6, 2013, Chicago.
  15. 15.
    Martinez C, Rong Rong, Gilkeson RC, et al. Incremental benefit and clinical significance of retrospectively obtained spectral data in a novel spectral detector CT technology- Initial experiences and results. Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, December 1 2014,
  16. 16.
    McCollough CH, Bruesewitz MR, McNitt-Gray MF, et al. (2004) The phantom portion of the American College of Radiology (ACR) Computed Tomography (CT) accreditation program: practical tips, artifact examples, and pitfalls to avoid. Med Phys 31(9):2423–2442CrossRefPubMedGoogle Scholar
  17. 17.
    American College of Radiology CT Accreditation Program Testing Instructions (Revised July 24, 2015)
  18. 18.
    Godoy MCB, Heller SL, Naidich DP, et al. (2011) Dual-energy MDCT: comparison of pulmonary artery enhancement on dedicated CT pulmonary angiography, routine and low contrast volume studies. Eur J Radiol 79:311–317CrossRefGoogle Scholar
  19. 19.
    Yu L, Primak AN, Liu X, McCollough CH (2009) Image quality optimization and evaluation of linearly mixed images in dual-source, dual-energy CT. Med Phys 36:1019–1024CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Megibow AJ, Sahani D (2012) Best Practice: implementation and use of abdominal dual-energy CT in routine patient care. AJR Am J Roentgenol 199:S71–S77CrossRefPubMedGoogle Scholar
  21. 21.
    Graser A, Johnson T, Chandarana H, et al. (2009) Dual energy CT: preliminary observations and potential clinical applications in the abdomen. Eur Radiol 19:13–23CrossRefPubMedGoogle Scholar
  22. 22.
    Morgan DE (2014) Dual-energy CT of the abdomen. Abdom Imaging 39:108–134CrossRefPubMedGoogle Scholar
  23. 23.
    Matsumoto K, Jinzaki M, Tanami Y, et al. (2011) Virtual monochromatic spectral imaging with fast kilovoltage switching: improved image quality as compared with that obtained with conventional 102 kVp CT. Radiology 259(1):257–262CrossRefPubMedGoogle Scholar
  24. 24.
    Patel BN, Thomas JV, Lockaart ME, et al. (2013) Single source dual-energy spectral multidetector CT of pancreatic adenocarcinoma: optimization of energy level viewing significantly increases lesion contrast. Clin Radiol 68(2):148–154CrossRefPubMedGoogle Scholar
  25. 25.
    Wang U, Qian B, Li B, et al. (2013) Metal artifacts reduction using monochromatic images from spectral CT: evaluation of pedicle screws in patients with scoliosis. Eur J Radiol 82(8):e320–e326CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of RadiologyUniversity Hospitals Cleveland Medical CenterClevelandUSA
  2. 2.Philips HealthcareClevelandUSA
  3. 3.Department of Radiology, Cardiothoracic ImagingUT Southwestern Medical CenterDallasUSA

Personalised recommendations