Hossein Sadjadi1,2, Keyvan Hashtrudi-Zaad3, Gabor Fichtinger4. 1. Laboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, K7L 3N6, Canada. h.sadjadi@queensu.ca. 2. BioRobotics Research Laboratory, Department of Electrical and Computer Engineering, Queen's University, Kingston, ON, K7L 3N6, Canada. h.sadjadi@queensu.ca. 3. BioRobotics Research Laboratory, Department of Electrical and Computer Engineering, Queen's University, Kingston, ON, K7L 3N6, Canada. 4. Laboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, K7L 3N6, Canada.
Abstract
PURPOSE: The performance of a fusion-based needle deflection estimation method was experimentally evaluated using prostate brachytherapy phantoms. The accuracy of the needle deflection estimation was determined. The robustness of the approach with variations in needle insertion speed and soft tissue biomechanical properties was investigated. METHODS: A needle deflection estimation method was developed to determine the amount of needle bending during insertion into deformable tissue by combining a kinematic deflection model with measurements taken from two electromagnetic trackers placed at the tip and the base of the needle. Experimental verification of this method for use in prostate brachytherapy needle insertion procedures was performed. A total of 21 beveled tip, 18 ga, 200 mm needles were manually inserted at various speeds through a template and toward different targets distributed within 3 soft tissue mimicking polyvinyl chloride prostate phantoms of varying stiffness. The tracked positions of both the needle tip and base were recorded, and Kalman filters were applied to fuse the sensory information. The estimation results were validated using ground truth obtained from fluoroscopy images. RESULTS: The manual insertion speed ranged from 8 to 34 mm/s, needle deflection ranged from 5 to 8 mm at an insertion depth of 76 mm, and the elastic modulus of the soft tissue ranged from 50 to 150 kPa. The accuracy and robustness of the estimation method were verified within these ranges. When compared to purely model-based estimation, we observed a reduction in needle tip position estimation error by [Formula: see text] % (mean [Formula: see text] SD) and the cumulative deflection error by [Formula: see text] %. CONCLUSIONS: Fusion of electromagnetic sensors demonstrated significant improvement in estimating needle deflection compared to model-based methods. The method has potential clinical applicability in the guidance of needle placement medical interventions, particularly prostate brachytherapy.
PURPOSE: The performance of a fusion-based needle deflection estimation method was experimentally evaluated using prostate brachytherapy phantoms. The accuracy of the needle deflection estimation was determined. The robustness of the approach with variations in needle insertion speed and soft tissue biomechanical properties was investigated. METHODS: A needle deflection estimation method was developed to determine the amount of needle bending during insertion into deformable tissue by combining a kinematic deflection model with measurements taken from two electromagnetic trackers placed at the tip and the base of the needle. Experimental verification of this method for use in prostate brachytherapy needle insertion procedures was performed. A total of 21 beveled tip, 18 ga, 200 mm needles were manually inserted at various speeds through a template and toward different targets distributed within 3 soft tissue mimicking polyvinyl chloride prostate phantoms of varying stiffness. The tracked positions of both the needle tip and base were recorded, and Kalman filters were applied to fuse the sensory information. The estimation results were validated using ground truth obtained from fluoroscopy images. RESULTS: The manual insertion speed ranged from 8 to 34 mm/s, needle deflection ranged from 5 to 8 mm at an insertion depth of 76 mm, and the elastic modulus of the soft tissue ranged from 50 to 150 kPa. The accuracy and robustness of the estimation method were verified within these ranges. When compared to purely model-based estimation, we observed a reduction in needle tip position estimation error by [Formula: see text] % (mean [Formula: see text] SD) and the cumulative deflection error by [Formula: see text] %. CONCLUSIONS: Fusion of electromagnetic sensors demonstrated significant improvement in estimating needle deflection compared to model-based methods. The method has potential clinical applicability in the guidance of needle placement medical interventions, particularly prostate brachytherapy.
Authors: V Lagerburg; M A Moerland; M K Konings; R E van de Vosse; J J W Lagendijk; J J Battermann Journal: Phys Med Biol Date: 2006-01-25 Impact factor: 3.609
Authors: Ann Majewicz; Steven P Marra; Mark G van Vledder; MingDe Lin; Michael A Choti; Danny Y Song; Allison M Okamura Journal: IEEE Trans Biomed Eng Date: 2012-06-13 Impact factor: 4.538
Authors: Elodie Lugez; Hossein Sadjadi; David R Pichora; Randy E Ellis; Selim G Akl; Gabor Fichtinger Journal: Int J Comput Assist Radiol Surg Date: 2014-09-06 Impact factor: 2.924