Quantification of pulmonary blood flow (PBF): Validation of perfusion MRI and nonlinear contrast agent (CA) dose correction with H  215 O positron emission tomography (PET)

Validation of quantification of pulmonary blood flow (PBF) with dynamic, contrast‐enhanced MRI is still missing. A possible reason certainly lies in difficulties based on the nonlinear dependence of signal intensity (SI) from contrast agent (CA) concentration. Both aspects were addressed in this study. Nine healthy pigs were examined by first‐pass perfusion MRI using gadolinium diethylenetriamine pentaacetic acid (Gd‐DTPA) and H  215 O positron emission tomography (PET) imaging. Calculations of hemodynamic parameters were based on a one‐compartment model (MR) and a two‐compartment model (PET). Simulations showed a significant error when assuming a linear relation between MR SI and CA dose in the arterial input function (AIF), even at low doses of 0.025 mmol/kg body weight (BW). To correct for nonlinearity, a calibration curve was calculated on the basis of the signal equation. The required accuracy of equation parameters (like longitudinal relaxation time) was evaluated. Error analysis estimates <5% over‐/underestimation of the corrected SI. Comparison of PET and MR flow values yielded a significant correlation (P < 0.001) in dorsal regions where signal‐to‐noise ratio (SNR) was sufficient. Changes in PBF due to the correction method were significant (P < 0.001) and resulted in a better agreement: mean values (standard deviation) in units of ml/min/100 ml lung tissue were 59 (15) for PET, 112 (28) for uncorrected MRI, and 80 (21) for corrected MRI. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.

[1]  P. Kellman,et al.  Nonlinear myocardial signal intensity correction improves quantification of contrast‐enhanced first‐pass MR perfusion in humans , 2008, Journal of magnetic resonance imaging : JMRI.

[2]  A. Kronfeld,et al.  Comparison of three accelerated pulse sequences for semiquantitative myocardial perfusion imaging using sensitivity encoding incorporating temporal filtering (TSENSE) , 2007, Journal of magnetic resonance imaging : JMRI.

[3]  S. Schoenberg,et al.  Measurement of signal‐to‐noise ratios in MR images: Influence of multichannel coils, parallel imaging, and reconstruction filters , 2007, Journal of magnetic resonance imaging : JMRI.

[4]  Derliz Mereles,et al.  Quantitative 3D pulmonary MR-perfusion in patients with pulmonary arterial hypertension: correlation with invasive pressure measurements. , 2007, European journal of radiology.

[5]  K. Murase,et al.  Assessment of bolus injection protocol with appropriate concentration for quantitative assessment of pulmonary perfusion by dynamic contrast‐enhanced MR imaging , 2007, Journal of magnetic resonance imaging : JMRI.

[6]  Wolfhard Semmler,et al.  Dual‐bolus approach to quantitative measurement of pulmonary perfusion by contrast‐enhanced MRI , 2006, Journal of magnetic resonance imaging : JMRI.

[7]  J. Mintorovitch,et al.  Comparison of Magnetic Properties of MRI Contrast Media Solutions at Different Magnetic Field Strengths , 2005, Investigative radiology.

[8]  Pascal Meier,et al.  The quantification of absolute myocardial perfusion in humans by contrast echocardiography: algorithm and validation. , 2005, Journal of the American College of Cardiology.

[9]  Hans-Ulrich Kauczor,et al.  Effect of Inspiratory and Expiratory Breathhold on Pulmonary Perfusion: Assessment by Pulmonary Perfusion Magnetic Resonance Imaging , 2005, Investigative radiology.

[10]  Xavier Golay,et al.  Determining the longitudinal relaxation time (T1) of blood at 3.0 Tesla , 2004, Magnetic resonance in medicine.

[11]  Kenya Murase,et al.  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 , 2004, Journal of magnetic resonance imaging : JMRI.

[12]  Konstantin Nikolaou,et al.  Quantification of Pulmonary Blood Flow and Volume in Healthy Volunteers by Dynamic Contrast-Enhanced Magnetic Resonance Imaging Using a Parallel Imaging Technique , 2004, Investigative radiology.

[13]  U. Haberkorn,et al.  Auflösungsverbessernde rekonstruktion von PET-bildern mit dem iterativen OSEM-algorithmus , 2004 .

[14]  A. O. Rodríguez,et al.  Principles of magnetic resonance imaging , 2004 .

[15]  Michael Bock,et al.  Regional lung perfusion: assessment with partially parallel three-dimensional MR imaging. , 2004, Radiology.

[16]  N Weiler,et al.  Lung density distribution in dynamic CT correlates with oxygenation in ventilated pigs with lavage ARDS. , 2003, British journal of anaesthesia.

[17]  R. Zhou,et al.  MRI estimation of the arterial input function in mice. , 2003, Academic radiology.

[18]  V. Treyer,et al.  Quantitative cerebral H215O perfusion PET without arterial blood sampling, a method based on washout rate , 2003, European Journal of Nuclear Medicine and Molecular Imaging.

[19]  M. Schmitt,et al.  Dynamic contrast‐enhanced myocardial perfusion imaging using saturation‐prepared TrueFISP , 2002, Journal of magnetic resonance imaging : JMRI.

[20]  Tilo Winkler,et al.  Topographical distribution of pulmonary perfusion and ventilation, assessed by PET in supine and prone humans. , 2002, Journal of applied physiology.

[21]  Robin M Heidemann,et al.  Generalized autocalibrating partially parallel acquisitions (GRAPPA) , 2002, Magnetic resonance in medicine.

[22]  Sverre Rosenbaum,et al.  Quantification of the effect of water exchange in dynamic contrast MRI perfusion measurements in the brain and heart , 2001, Magnetic resonance in medicine.

[23]  G. V. von Schulthess,et al.  Assessment of Myocardial Perfusion in Coronary Artery Disease by Magnetic Resonance: A Comparison With Positron Emission Tomography and Coronary Angiography , 2001, Circulation.

[24]  D. Pennell,et al.  Cardiovascular Magnetic Resonance , 2019, Cardiac CT, PET & MR.

[25]  Willi A. Kalender,et al.  Computed tomography : fundamentals, system technology, image quality, applications , 2000 .

[26]  H. Kauczor,et al.  Contrast-enhanced MRI of the lung. , 2000, European journal of radiology.

[27]  R. Glenny,et al.  Regional ventilation-perfusion distribution is more uniform in the prone position. , 2000, Journal of applied physiology.

[28]  R R Edelman,et al.  Quantitative assessment of pulmonary perfusion with dynamic contrast‐enhanced MRI , 1999, Magnetic resonance in medicine.

[29]  R. Edelman,et al.  Demonstration of gravity‐dependent lung perfusion with contrast‐enhanced magnetic resonance imaging , 1999, Journal of magnetic resonance imaging : JMRI.

[30]  G. Brix,et al.  Cerebral Blood Flow and Cerebrovascular Reserve Capacity: Estimation by Dynamic Magnetic Resonance Imaging , 1998, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[31]  G Brix,et al.  Performance evaluation of a whole-body PET scanner using the NEMA protocol. National Electrical Manufacturers Association. , 1997, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[32]  B R Rosen,et al.  Improving MR quantification of regional blood volume with intravascular T1 contrast agents: Accuracy, precision, and water exchange , 1996, Magnetic resonance in medicine.

[33]  B. Rosen,et al.  High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis , 1996, Magnetic resonance in medicine.

[34]  R R Edelman,et al.  Pulmonary perfusion: Qualitative assessment with dynamic contrast‐enhanced MRI using ultra‐short TE and inversion recovery turbo FLASH , 1996, Magnetic resonance in medicine.

[35]  H. Gudbjartsson,et al.  The rician distribution of noisy mri data , 1995, Magnetic resonance in medicine.

[36]  W. J. Lorenz,et al.  Quantification of regional cerebral blood flow and volume with dynamic susceptibility contrast-enhanced MR imaging. , 1994, Radiology.

[37]  M. Mintun,et al.  Regional lung water and hematocrit determined by positron emission tomography. , 1985, Journal of applied physiology.

[38]  N. Alpert,et al.  Strategy for the Measurement of Regional Cerebral Blood Flow Using Short-Lived Tracers and Emission Tomography , 1984, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[39]  J Andrasko,et al.  Water diffusion permeability of human erythrocytes studied by a pulsed gradient NMR technique. , 1976, Biochimica et biophysica acta.

[40]  K. Zierler Theoretical Basis of Indicator‐Dilution Methods For Measuring Flow and Volume , 1962 .

[41]  Y. Ohno,et al.  Dynamic perfusion MRI versus perfusion scintigraphy: prediction of postoperative lung function in patients with lung cancer. , 2004, AJR. American journal of roentgenology.

[42]  T. Frenzel,et al.  Comparative studies on the efficacy of MRI contrast agents in MRA. , 2002, Academic radiology.

[43]  W. Schreiber,et al.  Effect of Partial Oxygen Pressure and Hematocrit on Tl Relaxation in Human Blood , 2000 .

[44]  C Burger,et al.  A JAVA environment for medical image data analysis: initial application for brain PET quantitation. , 1998, Medical informatics = Medecine et informatique.

[45]  R. Wilson,et al.  Magnetic resonance quantification of the myocardial perfusion reserve with a Fermi function model for constrained deconvolution. , 1998, Medical physics.

[46]  R M Weisskoff,et al.  Water diffusion and exchange as they influence contrast enhancement , 1997, Journal of magnetic resonance imaging : JMRI.

[47]  H. Malcolm Hudson,et al.  Accelerated image reconstruction using ordered subsets of projection data , 1994, IEEE Trans. Medical Imaging.