Carlos Rossa1, Ron Sloboda2, Nawaid Usmani2, Mahdi Tavakoli3. 1. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. rossa@ualberta.ca. 2. Department of Oncology, University of Alberta, Edmonton, Canada. 3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.
Abstract
PURPOSE: This paper proposes a method to predict the deflection of a flexible needle inserted into soft tissue based on the observation of deflection at a single point along the needle shaft. METHODS: We model the needle-tissue as a discretized structure composed of several virtual, weightless, rigid links connected by virtual helical springs whose stiffness coefficient is found using a pattern search algorithm that only requires the force applied at the needle tip during insertion and the needle deflection measured at an arbitrary insertion depth. Needle tip deflections can then be predicted for different insertion depths. RESULTS: Verification of the proposed method in synthetic and biological tissue shows a deflection estimation error of [Formula: see text]2 mm for images acquired at 35 % or more of the maximum insertion depth, and decreases to 1 mm for images acquired closer to the final insertion depth. We also demonstrate the utility of the model for prostate brachytherapy, where in vivo needle deflection measurements obtained during early stages of insertion are used to predict the needle deflection further along the insertion process. CONCLUSION: The method can predict needle deflection based on the observation of deflection at a single point. The ultrasound probe can be maintained at the same position during insertion of the needle, which avoids complications of tissue deformation caused by the motion of the ultrasound probe.
PURPOSE: This paper proposes a method to predict the deflection of a flexible needle inserted into soft tissue based on the observation of deflection at a single point along the needle shaft. METHODS: We model the needle-tissue as a discretized structure composed of several virtual, weightless, rigid links connected by virtual helical springs whose stiffness coefficient is found using a pattern search algorithm that only requires the force applied at the needle tip during insertion and the needle deflection measured at an arbitrary insertion depth. Needle tip deflections can then be predicted for different insertion depths. RESULTS: Verification of the proposed method in synthetic and biological tissue shows a deflection estimation error of [Formula: see text]2 mm for images acquired at 35 % or more of the maximum insertion depth, and decreases to 1 mm for images acquired closer to the final insertion depth. We also demonstrate the utility of the model for prostate brachytherapy, where in vivo needle deflection measurements obtained during early stages of insertion are used to predict the needle deflection further along the insertion process. CONCLUSION: The method can predict needle deflection based on the observation of deflection at a single point. The ultrasound probe can be maintained at the same position during insertion of the needle, which avoids complications of tissue deformation caused by the motion of the ultrasound probe.
Authors: Carlos Rossa; Thomas Lehmann; Ronald Sloboda; Nawaid Usmani; Mahdi Tavakoli Journal: Med Biol Eng Comput Date: 2016-12-10 Impact factor: 2.602
Authors: Pedro Moreira; Niravkumar Patel; Marek Wartenberg; Gang Li; Kemal Tuncali; Tamas Heffter; Everette C Burdette; Iulian Iordachita; Gregory S Fischer; Nobuhiko Hata; Clare M Tempany; Junichi Tokuda Journal: Phys Med Biol Date: 2018-10-16 Impact factor: 3.609
Authors: Emanuele Perra; Eetu Lampsijärvi; Gonçalo Barreto; Muhammad Arif; Tuomas Puranen; Edward Hæggström; Kenneth P H Pritzker; Heikki J Nieminen Journal: Sci Rep Date: 2021-04-15 Impact factor: 4.379