European Radiology

, Volume 18, Issue 10, pp 2102–2107 | Cite as

In vivo Gd-DTPA concentration for MR lung perfusion measurements: Assessment with computed tomography in a porcine model

  • Michael PuderbachEmail author
  • Frank Risse
  • Jürgen Biederer
  • Julia Ley-Zaporozhan
  • Sebastian Ley
  • Gabor Szabo
  • Wolfhard Semmler
  • Hans-Ulrich Kauczor


A linear relationship between MR signal and contrast-agent concentration (CAC) of the arterial-input function (AIF) is crucial for MR lung-perfusion quantification. The aim was to determine the in-vivo real maximum CAC of the AIF, using cine CT measurements in a porcine model. A dilution series (Gd-DTPA, 0–20 mM) was examined by clinical time-resolved 3D-GRE MRI and by MDCT in cine CT mode. Using the CT setup, data were acquired in five pigs immediately after the injection of 0.05 mmol and 0.07 mmol/kg BW Gd-DTPA. For phantom measurements, mean signal values were determined using a region-of-interest (ROI) analysis and for animal measurements, a ROI was placed in the pulmonary trunk of the cine CT perfusion data sets. The CT phantom measurements were used to calculate the in-vivo maximum CAC corresponding to the HU values obtained in the pulmonary trunk by the cine CT study. Linearity of the AIF of the CT perfusion measurements was verified using the MR phantom measurement results. MR phantom measurements demonstrated linearity for concentrations of 0–4 mM. CT phantom measurements showed linear relation for the entire CAC range. Comparing in-vivo and in-vitro measurements, three of five CA injections at 0.05 mmol/kg and all 0.07 mmol/kg injections exceeded the range of linearity in MRI. The CA dose for quantification of lung perfusion with time-resolved MR studies must be chosen carefully since even with low doses (0.05 mmol/kg) the CAC may exceed the range of linearity in the AIF.


Lung perfusion Quantification CT MRI 



We would like to thank Andrea Breuer for providing us the dilution series for the CT and MRI measurements. We also thank the team of the experimental laboratory of cardiac surgery, especially Christiane Miesel-Gröschel and Karin Sonnenberg for the excellent animal preparation and care. We would like to thank Monika Eichinger and Wolfram Stiller for their thoughtful comments and discussions.


  1. 1.
    Amundsen T, Kvaerness J, Jones RA, Waage A, Bjermer L, Nilsen G, Haraldseth O (1997) Pulmonary embolism: detection with MR perfusion imaging of lung-a feasibility study. Radiology 203:181–185PubMedGoogle Scholar
  2. 2.
    Amundsen T, Torheim G, Kvistad KA, Waage A, Bjermer L, Nordlid KK, Johnsen H, Asberg A, Haraldseth O (2002) Perfusion abnormalities in pulmonary embolism studied with perfusion MRI and ventilation-perfusion scintigraphy: an intra-modality and inter-modality agreement study. J Magn Reson Imaging 15:386–394PubMedCrossRefGoogle Scholar
  3. 3.
    Amundsen T, Torheim G, Waage A, Bjermer L, Steen PA, Haraldseth O (2000) Perfusion magnetic resonance imaging of the lung: characterization of pneumonia and chronic obstructive pulmonary disease. A feasibility study. J Magn Reson Imaging 12:224–231PubMedCrossRefGoogle Scholar
  4. 4.
    Eichinger M, Puderbach M, Fink C, Gahr J, Ley S, Plathow C, Tuengerthal S, Zuna I, Muller FM, Kauczor HU (2006) Contrast-enhanced 3D MRI of lung perfusion in children with cystic fibrosis-initial results. Eur Radiol 16:2147–2152PubMedCrossRefGoogle Scholar
  5. 5.
    Fink C, Puderbach M, Bock M, Lodemann KP, Zuna I, Schmahl A, Delorme S, Kauczor HU (2004) Regional lung perfusion: assessment with partially parallel three-dimensional MR imaging. Radiology 231:175–184PubMedCrossRefGoogle Scholar
  6. 6.
    Fink C, Risse F, Buhmann R, Ley S, Meyer FJ, Plathow C, Puderbach M, Kauczor HU (2004) Quantitative analysis of pulmonary perfusion using time-resolved parallel 3D MRI - initial results. Rofo 176:170–174PubMedGoogle Scholar
  7. 7.
    Nikolaou K, Schoenberg SO, Brix G, Goldman JP, Attenberger U, Kuehn B, Dietrich O, Reiser MF (2004) Quantification of pulmonary blood flow and volume in healthy volunteers by dynamic contrast-enhanced magnetic resonance imaging using a parallel imaging technique. Invest Radiol 39:537–545PubMedCrossRefGoogle Scholar
  8. 8.
    Roberts TP (1997) Physiologic measurements by contrast-enhanced MR imaging: expectations and limitations. J Magn Reson Imaging 1:82–90CrossRefGoogle Scholar
  9. 9.
    Molinari F, Fink C, Risse F, Tuengerthal S, Bonomo L, Kauczor HU (2006) Assessment of differential pulmonary blood flow using perfusion magnetic resonance imaging: comparison with radionuclide perfusion scintigraphy. Invest Radiol 41:624–630PubMedCrossRefGoogle Scholar
  10. 10.
    Ohno Y, Hatabu H, Murase K, Higashino T, Kawamitsu H, Watanabe H, Takenaka D, Fujii M, Sugimura K (2004) Quantitative assessment of regional pulmonary perfusion in the entire lung using three-dimensional ultrafast dynamic contrast-enhanced magnetic resonance imaging: preliminary experience in 40 subjects. J Magn Reson Imaging 20:353–365PubMedCrossRefGoogle Scholar
  11. 11.
    Fink C, Ley S, Risse F, Eichinger M, Zaporozhan J, Buhmann R, Puderbach M, Plathow C, Kauczor HU (2005) Effect of inspiratory and expiratory breathhold on pulmonary perfusion: assessment by pulmonary perfusion magnetic resonance imaging. Invest Radiol 40:72–79PubMedCrossRefGoogle Scholar
  12. 12.
    Kalender WA (2005) Computed tomography, fundamentals, system technology, image quality, applications. Publicis Corporate Publishing, ErlangenGoogle Scholar
  13. 13.
    Griswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang J, Kiefer B, Haase A (2002) Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med 47:1202–1210PubMedCrossRefGoogle Scholar
  14. 14.
    Fink C, Ley S, Kroeker R, Requardt M, Kauczor HU, Bock M (2005) Time-resolved contrast-enhanced three-dimensional magnetic resonance angiography of the chest: combination of parallel imaging with view sharing (TREAT). Invest Radiol 40:40–48PubMedCrossRefGoogle Scholar
  15. 15.
    Jerosch-Herold M, Seethamraju RT, Swingen CM, Wilke NM, Stillman AE (2004) Analysis of myocardial perfusion MRI. J Magn Reson Imaging 19:758–770PubMedCrossRefGoogle Scholar
  16. 16.
    Schreiber WG, Schmitt M, Kalden P, Mohrs OK, Kreitner KF, Thelen M (2002) Dynamic contrast-enhanced myocardial perfusion imaging using saturation-prepared TrueFISP. J Magn Reson Imaging 16:641–652PubMedCrossRefGoogle Scholar
  17. 17.
    Li KL, Zhu XP, Waterton J, Jackson A (2000) Improved 3D quantitative mapping of blood volume and endothelial permeability in brain tumors. J Magn Reson Imaging 12:347–357PubMedCrossRefGoogle Scholar
  18. 18.
    Jerosch-Herold M, Wilke N, Stillman AE (1998) Magnetic resonance quantification of the myocardial perfusion reserve with a Fermi function model for constrained deconvolution. Med Phys 25:73–84PubMedCrossRefGoogle Scholar
  19. 19.
    Miles KA, Young H, Chica SL, Esser PD (2007) Quantitative contrast-enhanced computed tomography: is there a need for system calibration? Eur Radiol 4:919–926CrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2008

Authors and Affiliations

  • Michael Puderbach
    • 1
    • 7
    Email author
  • Frank Risse
    • 2
  • Jürgen Biederer
    • 3
  • Julia Ley-Zaporozhan
    • 1
    • 4
  • Sebastian Ley
    • 1
    • 4
  • Gabor Szabo
    • 5
  • Wolfhard Semmler
    • 2
  • Hans-Ulrich Kauczor
    • 6
  1. 1.Department of RadiologyGerman Cancer Research CenterHeidelbergGermany
  2. 2.Department of Medical Physics in RadiologyGerman Cancer Research CenterHeidelbergGermany
  3. 3.Department of Diagnostic RadiologyUniversity Hospital Schleswig-HolsteinCampus KielGermany
  4. 4.Department of Pediatric RadiologyUniversity HeidelbergHeidelbergGermany
  5. 5.Department of Cardiac SurgeryUniversity HeidelbergHeidelbergGermany
  6. 6.Department of RadiologyUniversity of HeidelbergHeidelbergGermany
  7. 7.Department of Radiology (E010)Deutsches KrebsforschungszentrumHeidelbergGermany

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