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Performance of four dual-energy CT platforms for abdominal imaging: a task-based image quality assessment based on phantom data

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Abstract

Objectives

To compare the spectral performance of dual-energy CT (DECT) platforms using task-based image quality assessment based on phantom data.

Materials and methods

Two CT phantoms were scanned on four DECT platforms: fast kV-switching CT (KVSCT), split filter CT (SFCT), dual-source CT (DSCT), and dual-layer CT (DLCT). Acquisitions on each phantom were performed using classical parameters of abdomen-pelvic examination and a CTDIvol at 10 mGy. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated from 40 to 140 keV of virtual monoenergetic images. A detectability index (d′) was computed to model the detection task of two contrast-enhanced lesions as function of keV.

Results

The noise magnitude decreased from 40 to 70 keV for all DECT platforms, and the highest noise magnitude values were found for KVSCT and SFCT and the lowest for DSCT and DLCT. The average NPS spatial frequency shifted towards lower frequencies as the energy level increased for all DECT platforms, smoothing the image texture. TTF values decreased with the increase of keV deteriorating the spatial resolution. For both simulated lesions, higher detectability (d′ value) was obtained at 40 keV for DLCT, DSCT, and SFCT but at 70 keV for KVSCT. The detectability of both simulated lesions was highest for DLCT and DSCT.

Conclusion

Highest detectability was found for DLCT for the lowest energy levels. The task-based image quality assessment used for the first time for DECT acquisitions showed the benefit of using low keV for the detection of contrast-enhanced lesions.

Key Points

• Detectability of both simulated contrast-enhanced lesions was higher for dual-layer CT for the lowest energy levels.

• The image noise increased and the image texture changed for the lowest energy levels.

• The detectability of both simulated contrast-enhanced lesions was highest at 40 keV for all dual-energy CT platforms except for fast kV-switching platform.

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Abbreviations

CT:

Computed tomography

CTDIvol :

Volume CT dose index

d′:

Detectability index

DECT:

Dual-energy CT

DLCT:

Dual-layer CT

DSCT:

Dual-source CT

HU:

Hounsfield unit

KVSCT:

Fast kV-switching CT

N CT :

CT number

NPS:

Noise power spectrum

SFCT:

Split filter CT

TTF:

Task-based transfer function

VMI:

Virtual monoenergetic image

References

  1. Agrawal MD, Pinho DF, Kulkarni NM, Hahn PF, Guimaraes AR, Sahani DV (2014) Oncologic applications of dual-energy CT in the abdomen. Radiographics 34:589–612

    Article  Google Scholar 

  2. De Cecco CN, Boll DT, Bolus DN et al (2017) White paper of the society of computed body tomography and magnetic resonance on dual-energy CT, part 4: abdominal and pelvic applications. J Comput Assist Tomogr 41:8–14

    Article  Google Scholar 

  3. De Cecco CN, Schoepf UJ, Steinbach L et al (2017) White paper of the society of computed body tomography and magnetic resonance on dual-energy CT, part 3: vascular, cardiac, pulmonary, and musculoskeletal applications. J Comput Assist Tomogr 41:1–7

    Article  Google Scholar 

  4. Flohr TG, McCollough CH, Bruder H et al (2006) First performance evaluation of a dual-source CT (DSCT) system. Eur Radiol 16:256–268

    Article  Google Scholar 

  5. Goo HW, Goo JM (2017) Dual-energy CT: new horizon in medical imaging. Korean J Radiol 18:555–569

    Article  Google Scholar 

  6. Marin D, Boll DT, Mileto A, Nelson RC (2014) State of the art: dual-energy CT of the abdomen. Radiology 271:327–342

    Article  Google Scholar 

  7. Matsumoto K, Jinzaki M, Tanami Y, Ueno A, Yamada M, Kuribayashi S (2011) Virtual monochromatic spectral imaging with fast kilovoltage switching: improved image quality as compared with that obtained with conventional 120-kVp CT. Radiology 259:257–262

    Article  Google Scholar 

  8. McCollough CH, Leng S, Yu L, Fletcher JG (2015) Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology 276:637–653

    Article  Google Scholar 

  9. Wang Q, Shi G, Qi X, Fan X, Wang L (2014) Quantitative analysis of the dual-energy CT virtual spectral curve for focal liver lesions characterization. Eur J Radiol 83:1759–1764

    Article  Google Scholar 

  10. Yu L, Christner JA, Leng S, Wang J, Fletcher JG, McCollough CH (2011) Virtual monochromatic imaging in dual-source dual-energy CT: radiation dose and image quality. Med Phys 38:6371–6379

    Article  Google Scholar 

  11. Zhang D, Li X, Liu B (2011) Objective characterization of GE discovery CT750 HD scanner: gemstone spectral imaging mode. Med Phys 38:1178–1188

    Article  Google Scholar 

  12. Si-Mohamed S, Douek P, Boussel L (2019) Spectral CT: dual energy towards multienergy CT. JIDI 2:32–45. https://doi.org/10.1016/j.jidi.2018.11.004

  13. Taguchi K, Iwanczyk JS (2013) Vision 20/20: Single photon counting x-ray detectors in medical imaging. Med Phys 40:100901

    Article  Google Scholar 

  14. Si-Mohamed S, Bar-Ness D, Sigovan M et al (2017) Review of an initial experience with an experimental spectral photon-counting computed tomography system. Nucl Instrum Methods Phys Res, Sect A 873:27–35

    Article  CAS  Google Scholar 

  15. Alvarez RE, Macovski A (1976) Energy-selective reconstructions in X-ray computerized tomography. Phys Med Biol 21:733–744

    Article  CAS  Google Scholar 

  16. Chandarana H, Megibow AJ, Cohen BA et al (2011) Iodine quantification with dual-energy CT: phantom study and preliminary experience with renal masses. AJR Am J Roentgenol 196:W693–W700

    Article  Google Scholar 

  17. Karcaaltincaba M, Aktas A (2011) Dual-energy CT revisited with multidetector CT: review of principles and clinical applications. Diagn Interv Radiol 17:181–194

    PubMed  Google Scholar 

  18. Soesbe TC, Lewis MA, Xi Y et al (2019) A technique to identify isoattenuating gallstones with dual-layer spectral CT: an ex vivo phantom study. Radiology 292:400–406

    Article  Google Scholar 

  19. Siegel MJ, Kaza RK, Bolus DN et al (2016) White paper of the society of computed body tomography and magnetic resonance on dual-energy CT, part 1: technology and terminology. J Comput Assist Tomogr 40:841–845

    Article  Google Scholar 

  20. Almeida IP, Schyns LE, Ollers MC et al (2017) Dual-energy CT quantitative imaging: a comparison study between twin-beam and dual-source CT scanners. Med Phys 44:171–179

    Article  CAS  Google Scholar 

  21. Ehn S, Sellerer T, Muenzel D et al (2018) Assessment of quantification accuracy and image quality of a full-body dual-layer spectral CT system. J Appl Clin Med Phys 19:204–217

    Article  Google Scholar 

  22. Euler A, Parakh A, Falkowski AL et al (2016) Initial results of a single-source dual-energy computed tomography technique using a split-filter: assessment of image quality, radiation dose, and accuracy of dual-energy applications in an in vitro and in vivo study. Invest Radiol 51:491–498

    Article  CAS  Google Scholar 

  23. Jacobsen MC, Schellingerhout D, Wood CA et al (2018) Intermanufacturer comparison of dual-energy CT iodine quantification and monochromatic attenuation: a phantom study. Radiology 287:224–234

    Article  Google Scholar 

  24. Ozguner O, Dhanantwari A, Halliburton S, Wen G, Utrup S, Jordan D (2018) Objective image characterization of a spectral CT scanner with dual-layer detector. Phys Med Biol 63:025027

    Article  Google Scholar 

  25. Sellerer T, Noel PB, Patino M et al (2018) Dual-energy CT: a phantom comparison of different platforms for abdominal imaging. Eur Radiol 28:2745–2755

    Article  Google Scholar 

  26. Washio H, Ohira S, Karino T et al (2018) Accuracy of quantification of iodine and Hounsfield unit values on virtual monochromatic imaging using dual-energy computed tomography: comparison of dual-layer computed tomography with fast kilovolt-switching computed tomography. J Comput Assist Tomogr 42:965–971

    Article  Google Scholar 

  27. Jacobsen MC, Cressman ENK, Tamm EP et al (2019) Dual-energy CT: lower limits of iodine detection and quantification. Radiology 292:414–419

    Article  Google Scholar 

  28. Richard S, Husarik DB, Yadava G, Murphy SN, Samei E (2012) Towards task-based assessment of CT performance: system and object MTF across different reconstruction algorithms. Med Phys 39:4115–4122

    Article  Google Scholar 

  29. Greffier J, Boccalini S, Beregi JP et al (2020) CT dose optimization for the detection of pulmonary arteriovenous malformation (PAVM): a phantom study. Diagn Interv Imaging. https://doi.org/10.1016/j.diii.2019.12.009

  30. Greffier J, Frandon J, Larbi A, Beregi JP, Pereira F (2020) CT iterative reconstruction algorithms: a task-based image quality assessment. Eur Radiol 30:487–500

    Article  CAS  Google Scholar 

  31. Greffier J, Frandon J, Larbi A, Beregi JP, Pereira F (2019) CT iterative reconstruction algorithms: a task-based image quality assessment. Eur Radiol. https://doi.org/10.1007/s00330-019-06359-6

  32. Greffier J, Frandon J, Pereira F et al (2020) Optimization of radiation dose for CT detection of lytic and sclerotic bone lesions: a phantom study. Eur Radiol 30:1075–1078

    Article  CAS  Google Scholar 

  33. Greffier J, Larbi A, Frandon J, Moliner G, Beregi JP, Pereira F (2019) Comparison of noise-magnitude and noise-texture across two generations of iterative reconstruction algorithms from three manufacturers. Diagn Interv Imaging 100:401–410

    Article  CAS  Google Scholar 

  34. Samei E, Bakalyar D, Boedeker KL et al (2019) Performance evaluation of computed tomography systems: summary of AAPM Task Group 233. Med Phys 46:e735–e756

    Article  Google Scholar 

  35. Samei E, Richard S (2015) Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology. Med Phys 42:314–323

    Article  Google Scholar 

  36. Verdun FR, Racine D, Ott JG et al (2015) Image quality in CT: from physical measurements to model observers. Phys Med 31:823–843

    Article  CAS  Google Scholar 

  37. Eckstein M, Bartroff J, Abbey C, Whiting J, Bochud F (2003) Automated computer evaluation and optimization of image compression of x-ray coronary angiograms for signal known exactly detection tasks. Opt Express 11:460–475

    Article  Google Scholar 

  38. Kalender WA, Perman WH, Vetter JR, Klotz E (1986) Evaluation of a prototype dual-energy computed tomographic apparatus. I. Phantom studies. Med Phys 13:334–339

    Article  CAS  Google Scholar 

  39. Greffier J, Frandon J, Hamard A et al (2020) Impact of iterative reconstructions on image quality and detectability of focal liver lesions in low-energy monochromatic images. Phys Med 77:36–42

    Article  CAS  Google Scholar 

  40. Rotzinger DC, Racine D, Beigelman-Aubry C et al (2018) Task-based model observer assessment of a partial model-based iterative reconstruction algorithm in thoracic oncologic multidetector CT. Sci Rep 8:17734

    Article  CAS  Google Scholar 

  41. Maass C, Baer M, Kachelriess M (2009) Image-based dual energy CT using optimized precorrection functions: a practical new approach of material decomposition in image domain. Med Phys 36:3818–3829

    Article  Google Scholar 

  42. Brown KM, Goshen L, Gringauz A, Zabic S (2017) Anti-correlated noise filter In: N.V KP, (ed) US 2017/0372496 A1, United States

  43. Taguchi K, Blevis I, Iniewski K (2020) Spectral, photon counting computed tomography: technology and applications. CRC Press; 1st Edition (July 15, 2020)

  44. Li B, Pomerleau M, Gupta A, Soto JA, Anderson SW (2020) Accuracy of dual-energy CT virtual unenhanced and material-specific images: a phantom study. AJR Am J Roentgenol. https://doi.org/10.2214/AJR.19.22372:1-9

Download references

Acknowledgments

We are deeply grateful to J. Solomon for support for the use of imQuest software. We also thank F. Mahinc and G. Raymond for their support in the study. We thank S. Kabani for her help in editing the manuscript.

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Department of Medical Imaging, CHU Nimes, Medical Imaging Group Nimes, EA 2415, Univ Montpellier, Bd Prof Robert Debré, 30029, Nîmes Cedex 9, France

    J. Greffier, D. Dabli, H. de Forges, A. Hamard, J. P. Beregi & J. Frandon

  2. Department of Radiology, Hospices Civils de Lyon, 69500, Lyon, France

    S. Si-Mohamed & P. Douek

  3. INSA-Lyon, Université Lyon, Université Claude-Bernard Lyon 1, UJM-Saint-Étienne, CNRS, Inserm, CREATIS UMR 5220, U1206, 69621, Lyon, France

    S. Si-Mohamed & P. Douek

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  1. J. Greffier
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Corresponding author

Correspondence to J. Greffier.

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Guarantor

The scientific guarantor of this publication is Jean Paul Beregi.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was not required for this phantom study.

Ethical approval

Institutional Review Board approval was not required for this phantom study.

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Greffier, J., Si-Mohamed, S., Dabli, D. et al. Performance of four dual-energy CT platforms for abdominal imaging: a task-based image quality assessment based on phantom data. Eur Radiol 31, 5324–5334 (2021). https://doi.org/10.1007/s00330-020-07671-2

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  • DOI: https://doi.org/10.1007/s00330-020-07671-2

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