PURPOSE: To improve the quantification of myocardial perfusion by registering the time series of magnetic resonance (MR) images with injection of gadolinium. MATERIALS AND METHODS: Eight patients underwent MR scans to perform myocardial perfusion exam. Two short axis views of the left ventricle (LV) were acquired in free breathing. Two masks for performing the spatial registration of the images were evaluated. The registration was based on pixel intensity in a multi-resolution scheme. The efficiency of this correction was evaluated by calculating geometric residual displacement of the LV and by fitting the data to a compartment model fit with two parameters: K1, the blood-to-myocardium transfer coefficient, and Vd, the distribution volume of the contrast media. RESULTS: The registration stage allowed a decrease in the observed motion of the LV from more than 1.98 +/- 0.68 mm to less than 0.56 +/- 0.18 mm (mean +/- SD). Variability obtained in the perfusion analysis decreased from 46 +/- 103% to 5+/- 4% for K1 parameter and from 18 +/- 21% to 5 +/- 5% for Vd parameter. CONCLUSION: As with manual correction, this automatic motion correction leads to accurate perfusion parameters in dynamic cardiac MR imaging after contrast agent injection. This automatic stage requires placing only one mask over one frame of the perfusion study instead of manually shifting each image to fit a reference image of the perfusion study. Copyright 2003 Wiley-Liss, Inc.
PURPOSE: To improve the quantification of myocardial perfusion by registering the time series of magnetic resonance (MR) images with injection of gadolinium. MATERIALS AND METHODS: Eight patients underwent MR scans to perform myocardial perfusion exam. Two short axis views of the left ventricle (LV) were acquired in free breathing. Two masks for performing the spatial registration of the images were evaluated. The registration was based on pixel intensity in a multi-resolution scheme. The efficiency of this correction was evaluated by calculating geometric residual displacement of the LV and by fitting the data to a compartment model fit with two parameters: K1, the blood-to-myocardium transfer coefficient, and Vd, the distribution volume of the contrast media. RESULTS: The registration stage allowed a decrease in the observed motion of the LV from more than 1.98 +/- 0.68 mm to less than 0.56 +/- 0.18 mm (mean +/- SD). Variability obtained in the perfusion analysis decreased from 46 +/- 103% to 5+/- 4% for K1 parameter and from 18 +/- 21% to 5 +/- 5% for Vd parameter. CONCLUSION: As with manual correction, this automatic motion correction leads to accurate perfusion parameters in dynamic cardiac MR imaging after contrast agent injection. This automatic stage requires placing only one mask over one frame of the perfusion study instead of manually shifting each image to fit a reference image of the perfusion study. Copyright 2003 Wiley-Liss, Inc.
Authors: Giacomo Tarroni; Cristiana Corsi; Patrick F Antkowiak; Federico Veronesi; Christopher M Kramer; Frederick H Epstein; James Walter; Claudio Lamberti; Roberto M Lang; Victor Mor-Avi; Amit R Patel Journal: Radiology Date: 2012-08-14 Impact factor: 11.105
Authors: Andreas Max Weng; Christian Oliver Ritter; Joachim Lotz; Meinrad Joachim Beer; Dietbert Hahn; Herbert Köstler Journal: Eur Radiol Date: 2009-12-17 Impact factor: 5.315