Yukio Fujita1, Michael Kent2, Erik Wisner2, Lynelle Johnson3, Joshua Stern3, Lihong Qi4, John Boone5, Tokihiro Yamamoto6. 1. Department of Radiation Sciences, Komazawa University, Tokyo, Japan. 2. Department of Surgical & Radiological Sciences, University of California Davis School of Veterinary Medicine, Davis, California. 3. Department of Medicine & Epidemiology, University of California Davis School of Veterinary Medicine, Davis, California. 4. Department of Public Health Sciences, University of California Davis, Davis, California. 5. Department of Radiology, University of California Davis School of Medicine, Sacramento, California. 6. Department of Radiation Oncology, University of California Davis School of Medicine, 4501 X Street, G-145, Sacramento, CA. Electronic address: toyamamoto@ucdavis.edu.
Abstract
RATIONALE AND OBJECTIVES: To establish a proof-of-principle for combined assessment of pulmonary ventilation and perfusion using single-energy computed tomography (CT) and image processing/analysis (denoted as single-energy CT ventilation/perfusion imaging). MATERIALS AND METHODS: Breath-hold CT scans were acquired at end-expiration and end-inspiration before injection of iodinated contrast agents, and repeated at end-inspiration after contrast injection for 17 canines (8 normal and 9 diseased lung subjects). Ventilation images were calculated with deformable image registration to map the end-expiratory and end-inspiratory CT images and quantitative analysis for regional volume changes as surrogates for ventilation. Perfusion images were calculated by subtracting the end-inspiratory precontrast CT from the deformably registered end-inspiratory postcontrast CT, yielding a map of regional Hounsfield unit enhancement as a surrogate for perfusion. Ventilation-perfusion matching, spatial heterogeneity, and gravitationally directed gradients were compared between two groups using a Wilcoxon rank-sum test. RESULTS: The normal group had significantly higher Dice similarity coefficients for spatial overlap of segmented functional volumes between ventilation and perfusion (median 0.40 vs. 0.33, p = 0.05), suggesting stronger ventilation-perfusion matching. The normal group also had greater Spearman's correlation coefficients based on 16 regions of interest (median 0.58 vs. 0.40, p = 0.09). The coefficients of variation were comparable (median, ventilation 0.71 vs. 0.91, p = 0.60; perfusion 0.63 vs. 0.75, p = 0.27). The linear regression slopes of gravitationally directed gradient were also comparable for ventilation (median, ventilation -0.26 vs. -0.18, p = 0.19; perfusion -0.17 vs. -0.06, p = 0.11). CONCLUSION: These findings provide proof-of-principle for single-energy CT ventilation/perfusion imaging.
RATIONALE AND OBJECTIVES: To establish a proof-of-principle for combined assessment of pulmonary ventilation and perfusion using single-energy computed tomography (CT) and image processing/analysis (denoted as single-energy CT ventilation/perfusion imaging). MATERIALS AND METHODS: Breath-hold CT scans were acquired at end-expiration and end-inspiration before injection of iodinated contrast agents, and repeated at end-inspiration after contrast injection for 17 canines (8 normal and 9 diseased lung subjects). Ventilation images were calculated with deformable image registration to map the end-expiratory and end-inspiratory CT images and quantitative analysis for regional volume changes as surrogates for ventilation. Perfusion images were calculated by subtracting the end-inspiratory precontrast CT from the deformably registered end-inspiratory postcontrast CT, yielding a map of regional Hounsfield unit enhancement as a surrogate for perfusion. Ventilation-perfusion matching, spatial heterogeneity, and gravitationally directed gradients were compared between two groups using a Wilcoxon rank-sum test. RESULTS: The normal group had significantly higher Dice similarity coefficients for spatial overlap of segmented functional volumes between ventilation and perfusion (median 0.40 vs. 0.33, p = 0.05), suggesting stronger ventilation-perfusion matching. The normal group also had greater Spearman's correlation coefficients based on 16 regions of interest (median 0.58 vs. 0.40, p = 0.09). The coefficients of variation were comparable (median, ventilation 0.71 vs. 0.91, p = 0.60; perfusion 0.63 vs. 0.75, p = 0.27). The linear regression slopes of gravitationally directed gradient were also comparable for ventilation (median, ventilation -0.26 vs. -0.18, p = 0.19; perfusion -0.17 vs. -0.06, p = 0.11). CONCLUSION: These findings provide proof-of-principle for single-energy CT ventilation/perfusion imaging.
Authors: Sven F Thieme; Thorsten R C Johnson; Maximilian F Reiser; Konstantin Nikolaou Journal: Semin Ultrasound CT MR Date: 2010-08 Impact factor: 1.875
Authors: Joseph M Reinhardt; Kai Ding; Kunlin Cao; Gary E Christensen; Eric A Hoffman; Shalmali V Bodas Journal: Med Image Anal Date: 2008-04-12 Impact factor: 8.545
Authors: Stefan Klein; Marius Staring; Keelin Murphy; Max A Viergever; Josien P W Pluim Journal: IEEE Trans Med Imaging Date: 2009-11-17 Impact factor: 10.048
Authors: Joachim Ernst Wildberger; Ernst Klotz; Hendrik Ditt; Elmar Spüntrup; Andreas H Mahnken; Rolf W Günther Journal: Eur Radiol Date: 2005-03-18 Impact factor: 5.315
Authors: Rohan S Virgincar; Zackary I Cleveland; S Sivaram Kaushik; Matthew S Freeman; John Nouls; Gary P Cofer; Santiago Martinez-Jimenez; Mu He; Monica Kraft; Jan Wolber; H Page McAdams; Bastiaan Driehuys Journal: NMR Biomed Date: 2012-10-13 Impact factor: 4.044