Maciej Orkisz1, Alfredo Morales Pinzón2,3, Jean-Christophe Richard2,4, Claude Guérin4,5,6,7,8, Leslie Evelyn Solórzano Vargas2,3, Daniela Florentina Sicaru2,9, Camila García Hernández3, Margarita M Gómez Ballén3, Bruno Neyran2, Eduardo E Dávila Serrano2, Marcela Hernández Hoyos3. 1. CREATIS UMR 5220, U1206, Univ Lyon, Université Claude Bernard Lyon 1, INSA-Lyon, UJM-Saint Etienne, CNRS, Inserm, 69621, Villeurbanne, France. maciej.orkisz@univ-lyon1.fr. 2. CREATIS UMR 5220, U1206, Univ Lyon, Université Claude Bernard Lyon 1, INSA-Lyon, UJM-Saint Etienne, CNRS, Inserm, 69621, Villeurbanne, France. 3. Systems and Computing Engineering Department, Universidad de los Andes, Bogotá, Colombia. 4. Service de Réanimation Médicale, Hospices Civils de Lyon, Hôpital de la Croix Rousse, Lyon, France. 5. Université de Lyon, Université Lyon 1, Lyon, France. 6. IMRB U955 Eq13, INSERM, Créteil, France. 7. HP2 U1042, INSERM, Grenoble, France. 8. Service de médecine intensive réanimation, CHU Grenoble-Alpes, Grenoble, France. 9. Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, Bucharest, Romania.
Abstract
PURPOSE: (1) To improve the accuracy of global and regional alveolar-recruitment quantification in CT scan pairs by accounting for lung-tissue displacements and deformation, (2) To propose a method for local-recruitment calculation. METHODS: Recruitment was calculated by subtracting the quantity of non-aerated lung tissues between expiration and inspiration. To assess global recruitment, lung boundaries were first interactively delineated at inspiration, and then they were warped based on automatic image registration to define the boundaries at expiration. To calculate regional recruitment, the lung mask defined at inspiration was cut into pieces, and these were also warped to encompass the same tissues at expiration. Local-recruitment map was calculated as follows: For each voxel at expiration, the matching location at inspiration was determined by image registration, non-aerated voxels were counted in the neighborhood of the respective locations, and the voxel count difference was normalized by the neighborhood size. The methods were evaluated on 120 image pairs of 12 pigs with experimental acute respiratory distress syndrome. RESULTS: The dispersion of global- and regional-recruitment values decreased when using image registration, compared to the conventional approach neglecting tissue motion. Local-recruitment maps overlaid onto the original images were visually consistent, and the sum of these values over the whole lungs was very close to the global-recruitment estimate, except four outliers. CONCLUSIONS: Image registration can compensate lung-tissue displacements and deformation, thus improving the quantification of alveolar recruitment. Local-recruitment calculation can also benefit from image registration, and its values can be overlaid onto the original image to display a local-recruitment map. They also can be integrated over arbitrarily shaped regions to assess regional or global recruitment.
PURPOSE: (1) To improve the accuracy of global and regional alveolar-recruitment quantification in CT scan pairs by accounting for lung-tissue displacements and deformation, (2) To propose a method for local-recruitment calculation. METHODS: Recruitment was calculated by subtracting the quantity of non-aerated lung tissues between expiration and inspiration. To assess global recruitment, lung boundaries were first interactively delineated at inspiration, and then they were warped based on automatic image registration to define the boundaries at expiration. To calculate regional recruitment, the lung mask defined at inspiration was cut into pieces, and these were also warped to encompass the same tissues at expiration. Local-recruitment map was calculated as follows: For each voxel at expiration, the matching location at inspiration was determined by image registration, non-aerated voxels were counted in the neighborhood of the respective locations, and the voxel count difference was normalized by the neighborhood size. The methods were evaluated on 120 image pairs of 12 pigs with experimental acute respiratory distress syndrome. RESULTS: The dispersion of global- and regional-recruitment values decreased when using image registration, compared to the conventional approach neglecting tissue motion. Local-recruitment maps overlaid onto the original images were visually consistent, and the sum of these values over the whole lungs was very close to the global-recruitment estimate, except four outliers. CONCLUSIONS: Image registration can compensate lung-tissue displacements and deformation, thus improving the quantification of alveolar recruitment. Local-recruitment calculation can also benefit from image registration, and its values can be overlaid onto the original image to display a local-recruitment map. They also can be integrated over arbitrarily shaped regions to assess regional or global recruitment.
Authors: S Crotti; D Mascheroni; P Caironi; P Pelosi; G Ronzoni; M Mondino; J J Marini; L Gattinoni Journal: Am J Respir Crit Care Med Date: 2001-07-01 Impact factor: 21.405
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