Anja Braune1,2, Frank Hofheinz3, Thomas Bluth4, Thomas Kiss4, Jakob Wittenstein4, Martin Scharffenberg4, Jörg Kotzerke2, Marcelo Gama de Abreu4. 1. Pulmonary Engineering Group, Department of Anesthesiology and Intensive Care Medicine, University Hospital Carl Gustav Carus at the Technische Universität Dresden, Dresden, Germany anja.braune@uniklinikum-dresden.de. 2. Department of Nuclear Medicine, University Hospital Carl Gustav Carus at the Technische Universität Dresden, Dresden, Germany; and. 3. PET Center, Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany. 4. Pulmonary Engineering Group, Department of Anesthesiology and Intensive Care Medicine, University Hospital Carl Gustav Carus at the Technische Universität Dresden, Dresden, Germany.
Abstract
PET imaging with 18F-FDG followed by mathematic modeling of the pulmonary uptake rate (Ki) is the gold standard for assessment of pulmonary inflammation in experimental studies of acute respiratory distress syndrome (ARDS). However, dynamic PET requires long imaging and allows the assessment of only 1 cranio-caudal field of view (∼15 cm). We investigated whether static 18F-FDG PET/CT and analysis of SUV or standardized uptake ratios (SURstat, uptake time-corrected ratio of 18F-FDG concentration in lung tissue and blood plasma) might be an alternative to dynamic 18F-FDG PET/CT and Patlak analysis for quantification of pulmonary inflammation in experimental ARDS. Methods: ARDS was induced by saline lung lavage followed by injurious mechanical ventilation in 14 anesthetized pigs (29.5-40.0 kg). PET/CT imaging sequences were acquired before and after 24 h of mechanical ventilation. Ki and the apparent volume of distribution were calculated from dynamic 18F-FDG PET/CT scans using the Patlak analysis. Static 18F-FDG PET/CT scans were obtained immediately after dynamic PET/CT and used for calculations of SUV and SURstat Mean Ki values of the whole imaged field of view and of 5 ventro-dorsal lung regions were compared with corresponding SUV and SURstat values, respectively, by means of linear regression and concordance analysis. The variability of the 18F-FDG concentration in blood plasma (arterial input function) was analyzed. Results: Both for the whole imaged field of view and ventro-dorsal subregions, Ki was linearly correlated with SURstat (r 2 ≥ 0.84), whereas Ki-SUV correlations were worse (r 2 ≤ 0.75). The arterial input function exhibited an essentially invariant shape across all animals and time points and can be described by an inverse power law. Compared with Ki, SURstat and SUV tracked the same direction of change in regional lung inflammation in 98.6% and 84.3% of measurements, respectively. Conclusion: The Ki-SURstat correlations were considerably stronger than the Ki-SUV correlations. The good Ki-SURstat correlations suggest that static 18F-FDG PET/CT and SURstat analysis provides an alternative to dynamic 18F-FDG PET/CT and Patlak analysis, allowing the assessment of inflammation of whole lungs, repeated measurements within the period of 18F-FDG decay, and faster data acquisition.
PET imaging with 18F-FDG followed by mathematic modeling of the pulmonary uptake rate (Ki) is the gold standard for assessment of pulmonary inflammation in experimental studies of acute respiratory distress syndrome (ARDS). However, dynamic PET requires long imaging and allows the assessment of only 1 cranio-caudal field of view (∼15 cm). We investigated whether static 18F-FDG PET/CT and analysis of SUV or standardized uptake ratios (SURstat, uptake time-corrected ratio of 18F-FDG concentration in lung tissue and blood plasma) might be an alternative to dynamic 18F-FDG PET/CT and Patlak analysis for quantification of pulmonary inflammation in experimental ARDS. Methods: ARDS was induced by saline lung lavage followed by injurious mechanical ventilation in 14 anesthetized pigs (29.5-40.0 kg). PET/CT imaging sequences were acquired before and after 24 h of mechanical ventilation. Ki and the apparent volume of distribution were calculated from dynamic 18F-FDG PET/CT scans using the Patlak analysis. Static 18F-FDG PET/CT scans were obtained immediately after dynamic PET/CT and used for calculations of SUV and SURstat Mean Ki values of the whole imaged field of view and of 5 ventro-dorsal lung regions were compared with corresponding SUV and SURstat values, respectively, by means of linear regression and concordance analysis. The variability of the 18F-FDG concentration in blood plasma (arterial input function) was analyzed. Results: Both for the whole imaged field of view and ventro-dorsal subregions, Ki was linearly correlated with SURstat (r 2 ≥ 0.84), whereas Ki-SUV correlations were worse (r 2 ≤ 0.75). The arterial input function exhibited an essentially invariant shape across all animals and time points and can be described by an inverse power law. Compared with Ki, SURstat and SUV tracked the same direction of change in regional lung inflammation in 98.6% and 84.3% of measurements, respectively. Conclusion: The Ki-SURstat correlations were considerably stronger than the Ki-SUV correlations. The good Ki-SURstat correlations suggest that static 18F-FDG PET/CT and SURstat analysis provides an alternative to dynamic 18F-FDG PET/CT and Patlak analysis, allowing the assessment of inflammation of whole lungs, repeated measurements within the period of 18F-FDG decay, and faster data acquisition.
Authors: Jakub Toczek; Jing Wu; Ansel T Hillmer; Jinah Han; Irina Esterlis; Kelly P Cosgrove; Chi Liu; Mehran M Sadeghi Journal: J Nucl Cardiol Date: 2020-02-10 Impact factor: 5.952
Authors: Jorge M C Ferreira; Robert Huhle; Sabine Müller; Christian Schnabel; Mirko Mehner; Thea Koch; Marcelo Gama de Abreu Journal: Front Physiol Date: 2022-04-11 Impact factor: 4.755
Authors: Joseph Haddad; Joseph D Latoche; Shubhanchi Nigam; Michael C Bellavia; Kathryn E Day; Qin Zhu; W Barry Edwards; Carolyn J Anderson; Sina Tavakoli Journal: J Nucl Med Date: 2020-07-17 Impact factor: 11.082
Authors: Ralph Buchert; Meike Dirks; Christian Schütze; Florian Wilke; Martin Mamach; Ann-Katrin Wirries; Henning Pflugrad; Linda Hamann; Laura B N Langer; Christian Wetzel; Mario Lukacevic; Andras Polyak; Mariella Kessler; Carlotta Petrusch; Frank M Bengel; Lilli Geworski; Rainer Rupprecht; Karin Weissenborn; Tobias L Ross; Georg Berding Journal: Eur J Nucl Med Mol Imaging Date: 2020-04-23 Impact factor: 9.236
Authors: Julian L Goggi; Carla Claser; Siddesh V Hartimath; Pei Xiang Hor; Peng Wen Tan; Boominathan Ramasamy; Husaini Abdul Rahman; Peter Cheng; Zi Wei Chang; Samantha Yee Teng Nguee; Jun Rong Tang; Edward G Robins; Laurent Renia Journal: Infect Immun Date: 2021-07-12 Impact factor: 3.441
Authors: Andrew Thornton; Francesco Fraioli; Simon Wan; Helen S Garthwaite; Balaji Ganeshan; Robert I Shortman; Raymond Endozo; Stefan Vöö; Irfan Kayani; Deena Neriman; Leon Menezes; Jamshed Bomanji; Toby Hilllman; Melissa Heightman; Joanna C Porter; Ashley M Groves Journal: J Nucl Med Date: 2021-07-16 Impact factor: 10.057