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European Radiology

, Volume 28, Issue 10, pp 4379–4388 | Cite as

Assessment of an advanced virtual monoenergetic reconstruction technique in cerebral and cervical angiography with third-generation dual-source CT: Feasibility of using low-concentration contrast medium

  • Lu Zhao
  • Fengtan Li
  • Zewei Zhang
  • Zhang Zhang
  • Yingjian Jiang
  • Xinyu Wang
  • Jun Gu
  • Dong LiEmail author
Computed Tomography
First Online:

Abstract

Objectives

To investigate the feasibility of low-concentration contrast media (LC-CM) in cerebral and cervical dual-energy CT angiography (DE-CTA) using an advanced monoenergetic (Mono+) reconstruction technique.

Methods

Sixty-five consecutive patients prospectively selected to undergo cerebral and cervical DE-CTA were randomised into two groups: 32 patients (63.7 ± 9.7 years) in the high-concentration contrast medium (HC-CM) group with iopromide 370 and 33 patients (60.7 ± 10.8 years) in the low-concentration contrast medium (LC-CM) group with iodixanol 270. Traditional monoenergetic (Mono) and Mono+ images from 40 to 100 keV levels (at 10-keV intervals) and the standard mixed (Mixed, 120 kVp equivalent) images were reconstructed. Subjective image quality parameters included the contrast-to-noise ratio (CNR) and objective image quality parameters were evaluated and compared between the two groups.

Results

The 40-keV Mono+ images in the LC-CM group showed comparable objective CNR (common carotid arteries: 83.7 ± 24.5 vs. 78.1 ± 23.2; internal carotid arteries: 82.2 ± 26.8 vs. 76.8 ± 24.1; middle cerebral arteries: 72.5 ± 24.6 vs. 70.6 ± 19.2; all p > 0.05) and subjective image scores (3.95 ± 0.19 vs. 3.83 ± 0.35; p > 0.05) compared with Mixed images in the HC-CM group.

Conclusion

The Mono+ reconstruction technique could reduce the concentration of iodinated CM in the diagnosis of cerebral and cervical angiography.

Key Points

• Mono+ shows decreased noise and superior CNR compared with Mono.

• The 40-keV Mono+ images show the highest CNR in the LC-CM group.

• The Mono+ reconstruction technique could reduce the concentration of iodinated CM.

Keywords

Cerebral arteries Carotid arteries Computed tomography angiography Monoenergetic imaging Low-concentration contrast medium 

Abbreviations

AA

Ascending aorta

CCA

Common carotid arteries

CIN

Contrast-induced nephropathy

CM

Contrast medium

CNR

Contrast-to-noise ratio

CTA

Computed tomographic angiography

DE-CT

Dual-energy CT

DS-CT

Dual-source CT

HC-CM

High-concentration contrast medium

HU

Hounsfield units

ICA

Internal carotid arteries

LC-CM

Low-concentration contrast medium

MCA

Middle cerebral arteries

Mixed

Standard mixed

Mono

Traditional monoenergetic

Mono+

Advanced monoenergetic

ROI

Region of interest

SD

Standard deviation

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Notes

Funding

This study has received funding by the Tianjin Research Program of Application Foundation and Advanced Technology (grant 14JCZDJC57000) and National Natural Science Foundation of China (grant 81301217).

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Dong Li.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: Gu Jun is on the speakers' bureau of Siemens Healthineers, Computed Tomography division. The other 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 waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• prospective

• case-control study

• performed at one institution

Supplementary material

330_2018_5407_MOESM1_ESM.docx (137 kb)
ESM 1 (DOCX 136 kb)

References

  1. 1.
    Katzberg RW, Barrett BJ (2007) Risk of iodinated contrast material--induced nephropathy with intravenous administration. Radiology 243:622–628CrossRefGoogle Scholar
  2. 2.
    Davenport MS, Khalatbari S, Dillman JR, Cohan RH, Caoili EM, Ellis JH (2013) Contrast material-induced nephrotoxicity and intravenous low-osmolality iodinated contrast material. Radiology 267:94–105CrossRefGoogle Scholar
  3. 3.
    Waikar SS, Liu KD, Chertow GM (2008) Diagnosis, epidemiology and outcomes of acute kidney injury. Clin J Am Soc Nephrol 3:844–861CrossRefGoogle Scholar
  4. 4.
    Silver SA, Shah PM, Chertow GM, Harel S, Wald R, Harel Z (2015) Risk prediction models for contrast induced nephropathy: systematic review. BMJ 351Google Scholar
  5. 5.
    Nyman U, Bjork J, Aspelin P, Marenzi G (2008) Contrast medium dose-to-GFR ratio: a measure of systemic exposure to predict contrast-induced nephropathy after percutaneous coronary intervention. Acta Radiol 49:658–667CrossRefGoogle Scholar
  6. 6.
    Liu ZZ, Schmerbach K, Lu Y et al (2014) Iodinated contrast media cause direct tubular cell damage, leading to oxidative stress, low nitric oxide, and impairment of tubuloglomerular feedback. Am J Physiol Renal Physiol 306:F864–F872CrossRefGoogle Scholar
  7. 7.
    Kitamura O, Uemura K, Kitamura H, Sugimoto H, Akaike A, Ono T (2009) Serofendic acid protects from iodinated contrast medium and high glucose probably against superoxide production in LLC-PK1 cells. Clin Exp Nephrol 13:15–24CrossRefGoogle Scholar
  8. 8.
    Bae KT, Heiken JP (2005) Scan and contrast administration principles of MDCT. Eur Radiol 15:E46–E59CrossRefGoogle Scholar
  9. 9.
    Cademartiri F, Mollet NR, van der Lugt A et al (2005) Intravenous contrast material administration at helical 16-detector row CT coronary angiography: effect of iodine concentration on vascular attenuation. Radiology 236:661–665CrossRefGoogle Scholar
  10. 10.
    Kanematsu M, Goshima S, Miyoshi T et al (2014) Whole-body CT angiography with low tube voltage and low-concentration contrast material to reduce radiation dose and iodine load. AJR Am J Roentgenol 202:W106–W116CrossRefGoogle Scholar
  11. 11.
    Zhang C, Yu Y, Zhang Z et al (2015) Imaging quality evaluation of low tube voltage coronary CT angiography using low concentration contrast medium. PloS One 10:e0120539CrossRefGoogle Scholar
  12. 12.
    Yu L, Leng S, McCollough CH (2012) Dual-energy CT-based monochromatic imaging. AJR Am J Roentgenol 199:S9–S15CrossRefGoogle Scholar
  13. 13.
    Schneider D, Apfaltrer P, Sudarski S et al (2014) Optimization of kiloelectron volt settings in cerebral and cervical dual-energy CT angiography determined with virtual monoenergetic imaging. Acad Radiol 21:431–436CrossRefGoogle Scholar
  14. 14.
    Apfaltrer P, Sudarski S, Schneider D et al (2014) Value of monoenergetic low-kV dual energy CT datasets for improved image quality of CT pulmonary angiography. Eur J Radiol 83:322–328CrossRefGoogle Scholar
  15. 15.
    Okayama S, Seno A, Soeda T et al (2012) Optimization of energy level for coronary angiography with dual-energy and dual-source computed tomography. Int J Cardiovasc Imaging 28:901–909CrossRefGoogle Scholar
  16. 16.
    Sudarski S, Apfaltrer P, Nance JW Jr et al (2013) Optimization of keV-settings in abdominal and lower extremity dual-source dual-energy CT angiography determined with virtual monoenergetic imaging. Eur J Radiol 82:e574–e581CrossRefGoogle Scholar
  17. 17.
    Grant KL, Flohr TG, Krauss B, Sedlmair M, Thomas C, Schmidt B (2014) Assessment of an advanced image-based technique to calculate virtual monoenergetic computed tomographic images from a dual-energy examination to improve contrast-to-noise ratio in examinations using iodinated contrast media. Invest Radiol 49:586–592CrossRefGoogle Scholar
  18. 18.
    Meier A, Wurnig M, Desbiolles L, Leschka S, Frauenfelder T, Alkadhi H (2015) Advanced virtual monoenergetic images: improving the contrast of dual-energy CT pulmonary angiography. Clin Radiol 70:1244–1251CrossRefGoogle Scholar
  19. 19.
    Albrecht MH, Scholtz JE, Husers K et al (2016) Advanced image-based virtual monoenergetic dual-energy CT angiography of the abdomen: optimization of kiloelectron volt settings to improve image contrast. Eur Radiol 26:1863–1870CrossRefGoogle Scholar
  20. 20.
    Martin SS, Albrecht MH, Wichmann JL et al (2017) Value of a noise-optimized virtual monoenergetic reconstruction technique in dual-energy CT for planning of transcatheter aortic valve replacement. Eur Radiol 27:705–714CrossRefGoogle Scholar
  21. 21.
    Beeres M, Trommer J, Frellesen C et al (2016) Evaluation of different keV-settings in dual-energy CT angiography of the aorta using advanced image-based virtual monoenergetic imaging. Int J Cardiovasc Imaging 32:137–144CrossRefGoogle Scholar
  22. 22.
    Leng S, Yu L, Fletcher JG, McCollough CH (2015) Maximizing iodine contrast-to-noise ratios in abdominal ct imaging through use of energy domain noise reduction and virtual monoenergetic dual-energy CT. Radiology 276:562–570CrossRefGoogle Scholar
  23. 23.
    Albrecht MH, Trommer J, Wichmann JL et al (2016) Comprehensive comparison of virtual monoenergetic and linearly blended reconstruction techniques in third-generation dual-source dual-energy computed tomography angiography of the thorax and abdomen. Invest Radiol 51:582–590CrossRefGoogle Scholar
  24. 24.
    Riffel P, Haubenreisser H, Meyer M et al (2016) Carotid dual-energy CT angiography: Evaluation of low keV calculated monoenergetic datasets by means of a frequency-split approach for noise reduction at low keV levels. Eur J Radiol 85:720–725CrossRefGoogle Scholar
  25. 25.
    Mangold S, Cannao PM, Schoepf UJ et al (2016) Impact of an advanced image-based monoenergetic reconstruction algorithm on coronary stent visualization using third generation dual-source dual-energy CT: a phantom study. Eur Radiol 26:1871–1878CrossRefGoogle Scholar
  26. 26.
    Sigal-Cinqualbre AB, Hennequin R, Abada HT, Chen X, Paul JF (2004) Low-kilovoltage multi-detector row chest CT in adults: feasibility and effect on image quality and iodine dose. Radiology 231:169–174CrossRefGoogle Scholar
  27. 27.
    Zhang WL, Li M, Zhang B et al (2013) CT angiography of the head-and-neck vessels acquired with low tube voltage, low iodine, and iterative image reconstruction: clinical evaluation of radiation dose and image quality. PloS One 8:e81486CrossRefGoogle Scholar
  28. 28.
    Kayan M, Demirtas H, Turker Y et al (2016) Carotid and cerebral CT angiography using low volume of iodinated contrast material and low tube voltage. Diagn Interv Imaging 97:1173–1179CrossRefGoogle Scholar
  29. 29.
    Luo S, Zhang LJ, Meinel FG et al (2014) Low tube voltage and low contrast material volume cerebral CT angiography. Eur Radiol 24:1677–1685CrossRefGoogle Scholar
  30. 30.
    Almutairi A, Sun Z, Poovathumkadavi A, Assar T (2015) Dual energy CT angiography of peripheral arterial disease: feasibility of using lower contrast medium volume. PloS One 10:e0139275CrossRefGoogle Scholar
  31. 31.
    Yuan R, Shuman WP, Earls JP et al (2012) Reduced iodine load at CT pulmonary angiography with dual-energy monochromatic imaging: comparison with standard CT pulmonary angiography--a prospective randomized trial. Radiology 262:290–297CrossRefGoogle Scholar
  32. 32.
    Delesalle MA, Pontana F, Duhamel A et al (2013) Spectral optimization of chest CT angiography with reduced iodine load: experience in 80 patients evaluated with dual-source, dual-energy CT. Radiology 267:256–266CrossRefGoogle Scholar
  33. 33.
    Meier A, Higashigaito K, Martini K et al (2016) Dual energy CT pulmonary angiography with 6g iodine-A propensity score-matched study. PLoS One 11:e0167214CrossRefGoogle Scholar
  34. 34.
    Fu W, Marin D, Ramirez-Giraldo JC et al (2017) Optimizing window settings for improved presentation of virtual monoenergetic images in dual-energy computed tomography. Med PhysGoogle Scholar
  35. 35.
    De Cecco CN, Caruso D, Schoepf UJ et al (2016) Optimization of window settings for virtual monoenergetic imaging in dual-energy CT of the liver: A multi-reader evaluation of standard monoenergetic and advanced imaged-based monoenergetic datasets. Eur J Radiol 85:695–699CrossRefGoogle Scholar
  36. 36.
    Caruso D, Parinella AH, Schoepf UJ et al (2017) Optimization of window settings for standard and advanced virtual monoenergetic imaging in abdominal dual-energy CT angiography. Abdom Radiol (NY) 42:772–780CrossRefGoogle Scholar
  37. 37.
    Saba L, Mallarin G (2009) Window settings for the study of calcified carotid plaques with multidetector CT angiography. AJNR Am J Neuroradiol 30:1445–1450CrossRefGoogle Scholar
  38. 38.
    Saba L, Mallarini G (2008) MDCTA of carotid plaque degree of stenosis: evaluation of interobserver agreement. AJR Am J Roentgenol 190:W41–W46CrossRefGoogle Scholar
  39. 39.
    Weiss J, Notohamiprodjo M, Bongers M et al (2017) Effect of noise-optimized monoenergetic postprocessing on diagnostic accuracy for detecting incidental pulmonary embolism in portal-venous phase dual-energy computed tomography. Invest Radiol 52:142–147PubMedGoogle Scholar
  40. 40.
    Martin SS, Wichmann JL, Weyer H et al (2017) Endoleaks after endovascular aortic aneurysm repair: Improved detection with noise-optimized virtual monoenergetic dual-energy CT. Eur J Radiol 94:125–132CrossRefGoogle Scholar
  41. 41.
    Martin SS, Wichmann JL, Scholtz JE et al (2017) Noise-optimized virtual monoenergetic dual-energy CT improves diagnostic accuracy for the detection of active arterial bleeding of the abdomen. J Vasc Interv Radiol 28:1257–1266CrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Lu Zhao
    • 1
  • Fengtan Li
    • 1
  • Zewei Zhang
    • 1
  • Zhang Zhang
    • 1
  • Yingjian Jiang
    • 1
  • Xinyu Wang
    • 1
  • Jun Gu
    • 2
  • Dong Li
    • 1
    Email author
  1. 1.Department of RadiologyTianjin Medical University General HospitalTianjinChina
  2. 2.Siemens HealthineersBeijingChina

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