Advertisement

Evaluation of image quality and radiation dose saving comparing knowledge model–based iterative reconstruction on 80-kV CT pulmonary angiography (CTPA) with hybrid iterative reconstruction on 100-kV CT

  • Davide Ippolito
  • Andrea De Vito
  • Cammillo Talei Franzesi
  • Luca Riva
  • Anna Pecorelli
  • Rocco Corso
  • Andrea Crespi
  • Sandro Sironi
Original Article

Abstract

Objectives

To evaluate dose reduction and image quality of 80-kV CT pulmonary angiography (CTPA) reconstructed with knowledge model–based iterative reconstruction (IMR), and compared with 100-kV CTPA with hybrid iterative reconstruction (iDose4).

Materials and methods

One hundred and fifty-one patients were prospectively investigated for pulmonary embolism; a study group of 76 patients underwent low-kV setting (80 kV, automated mAs) CTPA study, while a control group of 75 patients underwent standard CTPA protocol (100 kV; automated mAs); all patients were examined on 256 MDCT scanner (Philips iCTelite). Study group images were reconstructed using IMR while the control group ones with iDose4. CTDIvol, DLP, and ED were evaluated. Region of interests placed in the main pulmonary vessels evaluated vascular enhancement (HU); signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated.

Results

Compared to iDose4-CTPA, low-kV IMR-CTPA presented lower CTDIvol (6.41 ± 0.84 vs 9.68 ± 3.5 mGy) and DLP (248.24 ± 3.2 vs 352.4 ± 3.59 mGy × cm), with ED of 3.48 ± 1.2 vs 4.93 ± 1.8 mSv. Moreover, IMR-CTPA showed higher values of attenuation (670.91 ± 9.09 HU vs 292.61 ± 15.5 HU) and a significantly higher SNR (p < 0.0001) and CNR (p < 0.0001).The subjective image quality of low-kV IMR-CTPA was also higher compared with iDose4-CTPA (p < 0.0001).

Conclusions

Low-dose CTPA (80 kV and automated mAs modulation) reconstructed with IMR represents a feasible protocol for the diagnosis of pulmonary embolism in the emergency setting, achieving high image quality with low noise, and a significant dose reduction within adequate reconstruction times(≤ 120 s).

Keywords

Radiation Tomography Pulmonary embolism 

Abbreviations

CT

Computed tomography

CTPA

Computed tomography pulmonary angiography

IMR

Knowledge model–based iterative reconstruction

iDose4

Hybrid iterative reconstruction

MDCT

Multidetector computed tomography

HU

Hounsfield unit

DLP

Dose-length product

CTDIvol

Computed tomography dose index

ED

Effective dose

SNR

Signal-to-noise ratio

CNR

Contrast-to-noise ratio

mAs

Milliamperage seconds

ROI

Region of interest

mSv

Millisievert

mGy

Milligray

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

Every patient gave his informed consent, as required by our Institution.

Disclosure

The authors have nothing to disclose.

References

  1. 1.
    Tapson VF (2008) Acute pulmonary embolism. N Engl J Med 358:1037e1052CrossRefGoogle Scholar
  2. 2.
    Nguyen PK, Wu JC (2011) Radiation exposure from imaging tests: is there an increased cancer risk? Expert Rev Cardiovasc Ther 9:177–183CrossRefGoogle Scholar
  3. 3.
    Suzuki K, Yamashita S (2012) Low-dose radiation exposure and carcinogenesis. Jpn J Clin Oncol 42:563–568CrossRefGoogle Scholar
  4. 4.
    Lauer MS (2009) Elements of danger—the case of medical imaging. N Engl J Med 361:841–843CrossRefGoogle Scholar
  5. 5.
    Kalra MK, Maher MM, Sahani DV et al (2003) Low-dose CT of the abdomen: evaluation of image improvement with use of noise reduction filters pilot study. Radiology 228:251–256CrossRefGoogle Scholar
  6. 6.
    Diel J, Perlmutter S, Venkataramanan N, Mueller R, Lane MJ, Katz DS (2000) Unenhanced helical CT using increased pitch for suspected renal colic: an effective technique for radiation dose reduction? J Comput Assist Tomogr 24:795–801CrossRefGoogle Scholar
  7. 7.
    Heyer CM, Mohr PS, Lemburg SP et al (2007) Image quality and radiation exposure at pulmonary CT angiography with 100- or 120-kVp protocol: prospective randomized study. Radiology 245:577–583CrossRefGoogle Scholar
  8. 8.
    Henes FO, Groth M, Begemann PG et al (2012) Impact of tube current-time and tube voltage reduction in 64-detector-row computed tomography pulmonary angiography for pulmonary embolism in a porcine model. J Thorac Imaging 27:113–120CrossRefGoogle Scholar
  9. 9.
    Hara AK, Paden RG, Silva AC, Kujak JL, Lawder HJ, Pavlicek W (2009) Iterative reconstruction technique for reducing body radiation dose at CT: Feasibility study. AJR Am J Roentgenol 193:764–771CrossRefGoogle Scholar
  10. 10.
    Flicek KT, Hara AK, Silva AC, Wu Q, Peter MB, Johnson CD (2010) Reducing the radiation dose for CT colonography using adaptive statistical iterative reconstruction: A pilot study. AJR Am J Roentgenol 195:126–131CrossRefGoogle Scholar
  11. 11.
    Leipsic J, Labounty TM, Heilbron B et al (2010) Adaptive statistical iterative reconstruction: Assessment of image noise and image quality in coronary CT angiography. AJR Am J Roentgenol 195:649–654CrossRefGoogle Scholar
  12. 12.
    Leipsic J, Nguyen G, Brown J, Sin D, Mayo JR (2010) A prospective evaluation of dose reduction and image quality in chest CT using adaptive statistical iterative reconstruction. AJR Am J Roentgenol 195:1095–1099CrossRefGoogle Scholar
  13. 13.
    Prakash P, Kalra MK, Digumarthy SR et al (2010) Radiation dose reduction with chest computed tomography using adaptive statistical iterative reconstruction technique: Initial experience. J Comput Assist Tomogr 34:40–45CrossRefGoogle Scholar
  14. 14.
    Prakash P, Kalra MK, Kambadakone AK et al (2010) Reducing abdominal CT radiation dose with adaptive statistical iterative reconstruction technique. Invest Radiol 45:202–210CrossRefGoogle Scholar
  15. 15.
    Sagara Y, Hara AK, Pavlicek W, Silva AC, Paden RG, Wu Q (2010) Abdominal CT: Comparison of low-dose CT with adaptive statistical iterative reconstruction and routine-dose CT with filtered back projection in 53 patients. AJR Am J Roentgenol 195:713–719CrossRefGoogle Scholar
  16. 16.
    Singh S, Kalra MK, Gilman MD et al (2011) Adaptive statistical iterative reconstruction technique for radiation dose reduction in chest CT: A pilot study. Radiology 259:565–573CrossRefGoogle Scholar
  17. 17.
    Singh S, Kalra MK, Hsieh J et al (2010) Abdominal CT: Comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. Radiology 257:373–383CrossRefGoogle Scholar
  18. 18.
    Cornfeld D, Israel G, Detroy E, Bokhari J, Mojibian H (2011) Impact of adaptive statistical iterative reconstruction (ASIR) on radiation dose and image quality in aortic dissection studies: A qualitative and quantitative analysis. AJR Am J Roentgenol 196:W336–W340CrossRefGoogle Scholar
  19. 19.
    Thibault JB, Sauer KD, Bouman CA, Hsieh J (2007) A three dimensional statistical approach to improved image quality for multislice helical CT. Med Phys 34:4526–4544CrossRefGoogle Scholar
  20. 20.
    Yu Z, Thibault JB, Bouman CA, Sauer KD, Hsieh J (2011) Fast model-based X-ray CT reconstruction using spatially nonhomogeneous ICD optimization. IEEE Trans Image Process 20:161–175CrossRefGoogle Scholar
  21. 21.
    Willemink MJ, de Jong PA, Leiner T et al (2013) Iterative reconstruction techniques for computed tomography Part 1: technical principles. Eur Radiol 23:1623–1631CrossRefGoogle Scholar
  22. 22.
    Deak Z, Grimm JM, Treitl M et al (2013) Filtered back projection, adaptive statistical iterative reconstruction, and a model-based iterative reconstruction in abdominal CT: an experimental clinical study. Radiology 266:197–206 1670 Eur Radiol (2015) 25:1665–1671CrossRefGoogle Scholar
  23. 23.
    Katsura M, Matsuda I, Akahane M et al (2013) Model-based iterative reconstruction technique for ultralow-dose chest CT: comparison of pulmonary nodule detectability with the adaptive statistical iterative reconstruction technique. Invest Radiol 48:206–212PubMedGoogle Scholar
  24. 24.
    Pickhardt PJ, Lubner MG, Kim DH et al (2012) Abdominal CTwith model-based iterative reconstruction (MBIR): initial results of a prospective trial comparing ultralow-dose with standard-dose imaging. AJR Am J Roentgenol 199:1266–1274CrossRefGoogle Scholar
  25. 25.
    Raptopoulos V, Boiselle PM (2001) Multi-detector row spiral CT pulmonary angiography: comparison with single-detector row spiral CT. Radiology 221:606–613CrossRefGoogle Scholar
  26. 26.
    Boyden EA (1995) Segmental anatomy of the lungs. McGraw-Hill, New York, NYGoogle Scholar
  27. 27.
    Jackson CL, Huber JF (1943) Correlated applied anatomy of the bronchial tree and lungs with a system of nomenclature. Dis Chest 9:319–326CrossRefGoogle Scholar
  28. 28.
    Remy-Jardin M, Remy J, Artraud D, Deschildre F, Duhamel A (1997) Peripheral pulmonary arteries: optimization of the acquisition protocol. Radiology 204:157–163CrossRefGoogle Scholar
  29. 29.
    Mc Collough (2008) “The measurement,reporting, and management of radiation dose in CT”, Report 96, American Association of Phyicist in Medicine, Report of AAPM Task Group 23, pp. 1–28Google Scholar
  30. 30.
    Litmanovich D, Boiselle PM, Bankier AA et al (2009) Dose reduction in computed tomographic angiography of pregnant patients with suspected acute pulmonary embolism. J Comput Assist Tomogr 33:961–966CrossRefGoogle Scholar
  31. 31.
    MacKenzie JD, Nazario-Larrieu J, Cai T et al (2007) Reduced-dose CT: effect on reader evaluation in detection of pulmonary embolism. AJR Am J Roentgenol 189:1371–1379CrossRefGoogle Scholar
  32. 32.
    Yuki H, Utsunomiya D, Funama Y et al (2014) Value of knowledge-based iterative model reconstruction in low-kV 256-slice coronary CT angiography. J Cardiovasc ComputTomogr 8:115Google Scholar
  33. 33.
    Uchá D, Willemink MJ, de Jong PA et al (2014) The impact of a new model-based iterative reconstruction algorithm on prosthetic heart valve related artifacts at reduced radiation dose MDCT. Int J Cardiovasc Imaging 30:785CrossRefGoogle Scholar
  34. 34.
    Zamboni GA, Guariglia S, Bonfante A et al (2012) Low voltage CTPA for patients with suspected pulmonary embolism. Eur J Radiol 81:e580–e584CrossRefGoogle Scholar
  35. 35.
    Suntharalingam S, Mikat C, Stenzel E, Erfanian Y et al (2017) Submillisievert standard-pitch CT pulmonary angiography with ultra-low dose contrast media administration: A comparison to standard CT imaging. PLoS One 12(10):e0186694.  https://doi.org/10.1371/journal.pone.0186694 eCollection 2017CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Klingerman et al (2015) Detection of pulmonary embolism on computer tomography: improvement using a model-based iterative reconstruction algorithm compared with filtered back projection and iterative reconstruction algorithm. J Thorac Imaging. 30(1):60–68CrossRefGoogle Scholar

Copyright information

© American Society of Emergency Radiology 2018

Authors and Affiliations

  • Davide Ippolito
    • 1
    • 2
  • Andrea De Vito
    • 1
    • 3
  • Cammillo Talei Franzesi
    • 1
    • 3
  • Luca Riva
    • 1
    • 3
  • Anna Pecorelli
    • 1
    • 2
  • Rocco Corso
    • 1
  • Andrea Crespi
    • 3
    • 4
  • Sandro Sironi
    • 2
    • 5
  1. 1.Department of Diagnostic Radiology“San Gerardo” HospitalMonzaItaly
  2. 2.School of MedicineUniversity of Milano-BicoccaMonzaItaly
  3. 3.School of MedicineUniversity of Milano-BicoccaMilanItaly
  4. 4.Department of Medical Physics“San Gerardo” HospitalMonzaItaly
  5. 5.Department of Diagnostic RadiologyH Papa Giovanni XIIIBergamoItaly

Personalised recommendations