Seong-Ho Kong1,2, Nazim Haouchine3, Renato Soares1, Andrey Klymchenko4, Bohdan Andreiuk4, Bruno Marques3, Galyna Shabat5, Thierry Piechaud6, Michele Diana7,8, Stéphane Cotin3, Jacques Marescaux1,5. 1. IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France. 2. Department of Surgery, Seoul National University Hospital, Seoul, Korea. 3. Institut national de recherche en informatique et en automatique (INRIA) Mimesis, Strasbourg, France. 4. Biophotonic and Pharmacology Lab, UMR 7213 CNRS, Pharmacological Faculty, University of Strasbourg, Strasbourg, France. 5. IRCAD, Research Institute against Cancer of the Digestive System, 1, Place de l'Hôpital, 67091, Strasbourg, France. 6. Division of Urology, Clinique Saint-Augustin, Bordeaux, France. 7. IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France. michele.diana@ircad.fr. 8. IRCAD, Research Institute against Cancer of the Digestive System, 1, Place de l'Hôpital, 67091, Strasbourg, France. michele.diana@ircad.fr.
Abstract
BACKGROUND: Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials. METHODS: Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials. RESULTS: Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images. CONCLUSIONS: Our preliminary experiments showed the potential of a biomechanical model with fluorescent fiducials to propagate the deformation of solid organs' surface to their inner structures including tumors with good accuracy and automatized robust tracking.
BACKGROUND: Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials. METHODS: Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials. RESULTS: Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images. CONCLUSIONS: Our preliminary experiments showed the potential of a biomechanical model with fluorescent fiducials to propagate the deformation of solid organs' surface to their inner structures including tumors with good accuracy and automatized robust tracking.
Entities:
Keywords:
Augmented reality; Automatic registration; Fiducials; Finite element modeling; Fluorescence-guided surgery; Optical imaging; Solid organ tumor
Authors: Nishita Kothary; Jeremy J Heit; John D Louie; William T Kuo; Billy W Loo; Albert Koong; Daniel T Chang; David Hovsepian; Daniel Y Sze; Lawrence V Hofmann Journal: J Vasc Interv Radiol Date: 2008-11-18 Impact factor: 3.464
Authors: R Santambrogio; E Opocher; A Pisani Ceretti; M Barabino; M Costa; S Leone; M Montorsi Journal: Surg Endosc Date: 2006-11-21 Impact factor: 4.584
Authors: R Mårvik; T Langø; G A Tangen; J O Andersen; J H Kaspersen; B Ystgaard; E Sjølie; R Fougner; H E Fjøsne; T A Nagelhus Hernes Journal: Surg Endosc Date: 2004-06-23 Impact factor: 4.584
Authors: Iulia Andras; Elio Mazzone; Fijs W B van Leeuwen; Geert De Naeyer; Matthias N van Oosterom; Sergi Beato; Tessa Buckle; Shane O'Sullivan; Pim J van Leeuwen; Alexander Beulens; Nicolae Crisan; Frederiek D'Hondt; Peter Schatteman; Henk van Der Poel; Paolo Dell'Oglio; Alexandre Mottrie Journal: World J Urol Date: 2019-11-27 Impact factor: 4.226
Authors: Philip C Müller; Caroline Haslebacher; Daniel C Steinemann; Beat P Müller-Stich; Thilo Hackert; Matthias Peterhans; Benjamin Eigl Journal: Surg Endosc Date: 2020-04-06 Impact factor: 4.584
Authors: Gerd Reis; Mehmet Yilmaz; Jason Rambach; Alain Pagani; Rodrigo Suarez-Ibarrola; Arkadiusz Miernik; Paul Lesur; Nareg Minaskan Journal: Ann Med Surg (Lond) Date: 2021-05-13