Michele Diana1, Peter Halvax2, Damien Mertz3, Andras Legner2, Jean-Marcel Brulé2, Eric Robinet2, Didier Mutter4, Patrick Pessaux2, Jacques Marescaux5. 1. Institute for Minimally Invasive Image-Guided Surgery, Strasbourg, France Research Institute Against Cancer of the Digestive System, Strasbourg, France michele.diana@ircad.fr. 2. Institute for Minimally Invasive Image-Guided Surgery, Strasbourg, France. 3. University of Strasbourg, France. 4. Research Institute Against Cancer of the Digestive System, Strasbourg, France. 5. Institute for Minimally Invasive Image-Guided Surgery, Strasbourg, France Research Institute Against Cancer of the Digestive System, Strasbourg, France.
Abstract
INTRODUCTION: Image fusion between ultrasound (US) and computed tomography (CT) scan or magnetic resonance can increase operator accuracy in targeting liver lesions, particularly when those are undetectable with US alone. We have developed a modular gel to simulate hepatic solid lesions for educational purposes in imaging and minimally invasive ablation techniques. We aimed to assess the impact of image fusion in targeting artificial hepatic lesions during the hands-on part of 2 courses (basic and advanced) in hepatobiliary surgery. MATERIALS AND METHODS: Under US guidance, 10 fake tumors of various sizes were created in the livers of 2 pigs, by percutaneous injection of a biocompatible gel engineered to be hyperdense on CT scanning and barely detectable on US. A CT scan was obtained and a CT-US image fusion was performed using the ACUSON S3000 US system (Siemens Healthcare, Germany). A total of 12 blinded course attendants, were asked in turn to perform a 10-minute liver scan with US alone followed by a 10-minute scan using image fusion. RESULTS: Using US alone, the expert managed to identify all lesions successfully. The true positive rate for course attendants with US alone was 14/36 and 2/24 in the advanced and basic courses, respectively. The total number of false positives identified was 26. With image fusion, the rate of true positives significantly increased to 31/36 (P < .001) in the advanced group and 16/24 in the basic group (P < .001). The total number of false positives, considering all participants, decreased to 4 (P < .001). CONCLUSIONS: Image fusion significantly increases accuracy in targeting hepatic lesions and might improve echo-guided procedures.
INTRODUCTION: Image fusion between ultrasound (US) and computed tomography (CT) scan or magnetic resonance can increase operator accuracy in targeting liver lesions, particularly when those are undetectable with US alone. We have developed a modular gel to simulate hepatic solid lesions for educational purposes in imaging and minimally invasive ablation techniques. We aimed to assess the impact of image fusion in targeting artificial hepatic lesions during the hands-on part of 2 courses (basic and advanced) in hepatobiliary surgery. MATERIALS AND METHODS: Under US guidance, 10 fake tumors of various sizes were created in the livers of 2 pigs, by percutaneous injection of a biocompatible gel engineered to be hyperdense on CT scanning and barely detectable on US. A CT scan was obtained and a CT-US image fusion was performed using the ACUSON S3000 US system (Siemens Healthcare, Germany). A total of 12 blinded course attendants, were asked in turn to perform a 10-minute liver scan with US alone followed by a 10-minute scan using image fusion. RESULTS: Using US alone, the expert managed to identify all lesions successfully. The true positive rate for course attendants with US alone was 14/36 and 2/24 in the advanced and basic courses, respectively. The total number of false positives identified was 26. With image fusion, the rate of true positives significantly increased to 31/36 (P < .001) in the advanced group and 16/24 in the basic group (P < .001). The total number of false positives, considering all participants, decreased to 4 (P < .001). CONCLUSIONS: Image fusion significantly increases accuracy in targeting hepatic lesions and might improve echo-guided procedures.
Authors: Huaijun Wang; Stephen A Felt; Ismayil Guracar; Valentina Taviani; Jianhua Zhou; Rosa Maria Silveira Sigrist; Huiping Zhang; Joy Liau; José G Vilches-Moure; Lu Tian; Yamil Saenz; Thierry Bettinger; Brian A Hargreaves; Amelie M Lutz; Jürgen K Willmann Journal: Eur Radiol Date: 2017-11-23 Impact factor: 5.315