BACKGROUND: EUS is complicated because of the subtleties of US interpretation, small fields of observation, and uncertainty of probe position and orientation. OBJECTIVE: Improved EUS performance is sought by providing contextual information to support US probe positioning and identification of features in US images. Our aims were to demonstrate the feasibility of the image registered gastroscopic US (IRGUS) system in a porcine model and to compare the effectiveness and the efficiency of IRGUS with traditional EUS. DESIGN: Animal feasibility study. INTERVENTIONS: The IRGUS system uses preprocedure CT and miniature US probe trackers to create real-time synthetic displays of the position of the probe tip and a matched slice of CT data for comparison with the US image. Participants used EUS and IRGUS systems in a porcine model to evaluate the speed and accuracy of structure identification. MAIN OUTCOME MEASUREMENTS: The performance and utility of IRGUS were determined by the number of correctly identified structures in a timed trial, kinematic variables, and a structured survey. RESULTS: IRGUS was twice as effective as EUS in localizing and identifying individual structures. In timed trials, IRGUS users identified over 25% more structures than EUS users. Improvement in examination efficiency and accuracy of feature identification was statistically significant, and 90% of the users preferred IRGUS to EUS for these tasks. CONCLUSIONS: IRGUS appears feasible and may be superior to conventional EUS in efficiency and accuracy of probe positioning and in image interpretation. IRGUS has the potential to shorten the EUS learning curve and to broaden the adoption of EUS techniques by gastroenterologists.
BACKGROUND: EUS is complicated because of the subtleties of US interpretation, small fields of observation, and uncertainty of probe position and orientation. OBJECTIVE: Improved EUS performance is sought by providing contextual information to support US probe positioning and identification of features in US images. Our aims were to demonstrate the feasibility of the image registered gastroscopic US (IRGUS) system in a porcine model and to compare the effectiveness and the efficiency of IRGUS with traditional EUS. DESIGN: Animal feasibility study. INTERVENTIONS: The IRGUS system uses preprocedure CT and miniature US probe trackers to create real-time synthetic displays of the position of the probe tip and a matched slice of CT data for comparison with the US image. Participants used EUS and IRGUS systems in a porcine model to evaluate the speed and accuracy of structure identification. MAIN OUTCOME MEASUREMENTS: The performance and utility of IRGUS were determined by the number of correctly identified structures in a timed trial, kinematic variables, and a structured survey. RESULTS: IRGUS was twice as effective as EUS in localizing and identifying individual structures. In timed trials, IRGUS users identified over 25% more structures than EUS users. Improvement in examination efficiency and accuracy of feature identification was statistically significant, and 90% of the users preferred IRGUS to EUS for these tasks. CONCLUSIONS: IRGUS appears feasible and may be superior to conventional EUS in efficiency and accuracy of probe positioning and in image interpretation. IRGUS has the potential to shorten the EUS learning curve and to broaden the adoption of EUS techniques by gastroenterologists.
Authors: G Fernández-Esparrach; R San José Estépar; C Guarner-Argente; G Martínez-Pallí; R Navarro; C Rodríguez de Miguel; H Córdova; C C Thompson; A M Lacy; L Donoso; J R Ayuso-Colella; A Ginès; M Pellisé; J Llach; K G Vosburgh Journal: Endoscopy Date: 2010-10-19 Impact factor: 10.093
Authors: K L Obstein; R S Estépar; J Jayender; V D Patil; I S Spofford; M B Ryan; B I Lengyel; R Shams; K G Vosburgh; C C Thompson Journal: Endoscopy Date: 2011-03-21 Impact factor: 10.093
Authors: Keith L Obstein; Vaibhav D Patil; Jagadeesan Jayender; Raúl San José Estépar; Inbar S Spofford; Balazs I Lengyel; Kirby G Vosburgh; Christopher C Thompson Journal: Gastrointest Endosc Date: 2010-12-15 Impact factor: 9.427
Authors: D E Azagury; M Ryou; S N Shaikh; R San José Estépar; B I Lengyel; J Jagadeesan; K G Vosburgh; C C Thompson Journal: Br J Surg Date: 2012-09 Impact factor: 6.939
Authors: Simon Dimaio; Tina Kapur; Kevin Cleary; Stephen Aylward; Peter Kazanzides; Kirby Vosburgh; Randy Ellis; James Duncan; Keyvan Farahani; Heinz Lemke; Terry Peters; William Bill Lorensen; David Gobbi; John Haller; Laurence Larry Clarke; Stephen Pizer; Russell Taylor; Robert Galloway; Gabor Fichtinger; Nobuhiko Hata; Kimberly Lawson; Clare Tempany; Ron Kikinis; Ferenc Jolesz Journal: Neuroimage Date: 2007-04-24 Impact factor: 6.556