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Published in: International Journal of Computer Assisted Radiology and Surgery 7/2016

01-07-2016 | Original Article

Estimating needle tip deflection in biological tissue from a single transverse ultrasound image: application to brachytherapy

Authors: Carlos Rossa, Ron Sloboda, Nawaid Usmani, Mahdi Tavakoli

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 7/2016

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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 \(<\)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.
Literature
1.
go back to reference Abayazid M, Roesthuis R, Reilink R, Misra S (2013) Integrating deflection models and image feedback for real-time flexible needle steering. Robot IEEE Trans 29(2):542–553CrossRef Abayazid M, Roesthuis R, Reilink R, Misra S (2013) Integrating deflection models and image feedback for real-time flexible needle steering. Robot IEEE Trans 29(2):542–553CrossRef
2.
go back to reference Abolhassani N, Patel R, Ayazi F (2007) Needle control along desired tracks in robotic prostate brachytherapy. In: IEEE international conference on systems, man and cybernetics, 2007, ISIC, pp 3361–3366. IEEE Abolhassani N, Patel R, Ayazi F (2007) Needle control along desired tracks in robotic prostate brachytherapy. In: IEEE international conference on systems, man and cybernetics, 2007, ISIC, pp 3361–3366. IEEE
3.
go back to reference Beer FP, Sanghi S (2012) Mechanics of materials, 6th edn. McGraw-Hill, New York (global ed./adapted by Sanjeev Sanghi edn., includes index) Beer FP, Sanghi S (2012) Mechanics of materials, 6th edn. McGraw-Hill, New York (global ed./adapted by Sanjeev Sanghi edn., includes index)
4.
go back to reference Bogdanich W (2009) At VA hospital, a rogue cancer unit. The New York Times, New York Bogdanich W (2009) At VA hospital, a rogue cancer unit. The New York Times, New York
6.
go back to reference Chin KJ, Perlas A, Chan VW, Brull R (2008) Needle visualization in ultrasound-guided regional anesthesia: challenges and solutions. Reg Anesth Pain Med 33(6):532–544PubMed Chin KJ, Perlas A, Chan VW, Brull R (2008) Needle visualization in ultrasound-guided regional anesthesia: challenges and solutions. Reg Anesth Pain Med 33(6):532–544PubMed
7.
go back to reference Dehghan E, Goksel O, Salcudean SE (2006) A comparison of needle bending models. In: Medical image computing and computer-assisted intervention–MICCAI 2006, pp 305–312. Springer Dehghan E, Goksel O, Salcudean SE (2006) A comparison of needle bending models. In: Medical image computing and computer-assisted intervention–MICCAI 2006, pp 305–312. Springer
8.
go back to reference Fischler MA, Bolles RC (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24(6):381–395CrossRef Fischler MA, Bolles RC (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24(6):381–395CrossRef
10.
go back to reference Goksel O, Dehghan E, Salcudean SE (2009) Modeling and simulation of flexible needles. Med Eng Phys 31(9):1069–1078CrossRefPubMed Goksel O, Dehghan E, Salcudean SE (2009) Modeling and simulation of flexible needles. Med Eng Phys 31(9):1069–1078CrossRefPubMed
11.
go back to reference Gonzales RC, Woods RE (2002) Digital image processing, 2nd edn. Prentice Hall, Upper Saddle River Gonzales RC, Woods RE (2002) Digital image processing, 2nd edn. Prentice Hall, Upper Saddle River
12.
go back to reference Haddadi A, Hashtrudi-Zaad K (2011) Development of a dynamic model for bevel-tip flexible needle insertion into soft tissues. In: 2011 annual international conference of the IEEE, engineering in medicine and biology society, EMBC, pp 7478–7482. IEEE Haddadi A, Hashtrudi-Zaad K (2011) Development of a dynamic model for bevel-tip flexible needle insertion into soft tissues. In: 2011 annual international conference of the IEEE, engineering in medicine and biology society, EMBC, pp 7478–7482. IEEE
13.
go back to reference Hong J, Dohi T, Hashizume M, Konishi K, Hata N (2004) An ultrasound-driven needle-insertion robot for percutaneous cholecystostomy. Phys Med Biol 49(3):441CrossRefPubMed Hong J, Dohi T, Hashizume M, Konishi K, Hata N (2004) An ultrasound-driven needle-insertion robot for percutaneous cholecystostomy. Phys Med Biol 49(3):441CrossRefPubMed
14.
go back to reference Khadem M, Fallahi B, Rossa C, Sloboda R, Usmani N, Tavakoli M (2015) A mechanics-based model for simulation and control of flexible needle insertion in soft tissue. In: 2015 IEEE international conference on, robotics and automation (ICRA), pp 2264–2269 Khadem M, Fallahi B, Rossa C, Sloboda R, Usmani N, Tavakoli M (2015) A mechanics-based model for simulation and control of flexible needle insertion in soft tissue. In: 2015 IEEE international conference on, robotics and automation (ICRA), pp 2264–2269
15.
go back to reference Krouskop TA, Wheeler TM, Kallel F, Garra BS, Hall T (1998) Elastic moduli of breast and prostate tissues under compression. Ultrason Imaging 20(4):260–274CrossRefPubMed Krouskop TA, Wheeler TM, Kallel F, Garra BS, Hall T (1998) Elastic moduli of breast and prostate tissues under compression. Ultrason Imaging 20(4):260–274CrossRefPubMed
16.
go back to reference Lachaine M, Falco T (2013) Intrafractional prostate motion management with the clarity autoscan system. Med Phys Int 1(1):72–80 Lachaine M, Falco T (2013) Intrafractional prostate motion management with the clarity autoscan system. Med Phys Int 1(1):72–80
17.
go back to reference Lehmann T, Rossa C, Usmani N, Sloboda R, Tavakoli M (2015) A virtual sensor for needle deflection estimation during soft-tissue needle insertion. In: 2015 IEEE international conference on, robotics and automation (ICRA), pp 1217–1222 Lehmann T, Rossa C, Usmani N, Sloboda R, Tavakoli M (2015) A virtual sensor for needle deflection estimation during soft-tissue needle insertion. In: 2015 IEEE international conference on, robotics and automation (ICRA), pp 1217–1222
18.
go back to reference Mathiassen K, Dall’Alba D, Muradore R, Fiorini P, Elle OJ (2013) Real-time biopsy needle tip estimation in 2d ultrasound images. In: 2013 IEEE international conference on, robotics and automation (ICRA), pp 4363–4369. IEEE Mathiassen K, Dall’Alba D, Muradore R, Fiorini P, Elle OJ (2013) Real-time biopsy needle tip estimation in 2d ultrasound images. In: 2013 IEEE international conference on, robotics and automation (ICRA), pp 4363–4369. IEEE
20.
go back to reference Moreira P, Misra S (2014) Biomechanics-based curvature estimation for ultrasound-guided flexible needle steering in biological tissues. Ann Biomed Eng. doi:10.1007/s10439-014-1203-5 Moreira P, Misra S (2014) Biomechanics-based curvature estimation for ultrasound-guided flexible needle steering in biological tissues. Ann Biomed Eng. doi:10.​1007/​s10439-014-1203-5
21.
go back to reference Nag S, Bice W, DeWyngaert K, Prestidge B, Stock R, Yu Y (2000) The american brachytherapy society recommendations for permanent prostate brachytherapy postimplant dosimetric analysis. Int J Radiat Oncol Biol Phys 46(1):221–230CrossRefPubMed Nag S, Bice W, DeWyngaert K, Prestidge B, Stock R, Yu Y (2000) The american brachytherapy society recommendations for permanent prostate brachytherapy postimplant dosimetric analysis. Int J Radiat Oncol Biol Phys 46(1):221–230CrossRefPubMed
22.
go back to reference Neubach Z, Shoham M (2010) Ultrasound-guided robot for flexible needle steering. Biomed Eng IEEE Trans 57(4):799–805 Neubach Z, Shoham M (2010) Ultrasound-guided robot for flexible needle steering. Biomed Eng IEEE Trans 57(4):799–805
24.
go back to reference Okazawa SH, Ebrahimi R, Chuang J, Rohling RN, Salcudean SE (2006) Methods for segmenting curved needles in ultrasound images. Med Image Anal 10(3):330–342CrossRefPubMed Okazawa SH, Ebrahimi R, Chuang J, Rohling RN, Salcudean SE (2006) Methods for segmenting curved needles in ultrasound images. Med Image Anal 10(3):330–342CrossRefPubMed
25.
go back to reference Schlosser J, Salisbury K, Hristov D (2011) We-d-220-01: tissue displacement monitoring for prostate and liver igrt using a robotically-controlled ultrasound system. Med Phys 38(6):3812–3812CrossRef Schlosser J, Salisbury K, Hristov D (2011) We-d-220-01: tissue displacement monitoring for prostate and liver igrt using a robotically-controlled ultrasound system. Med Phys 38(6):3812–3812CrossRef
26.
go back to reference Spong MW, Vidyasagar M (2008) Robot dynamics and control. Wiley, Hoboken Spong MW, Vidyasagar M (2008) Robot dynamics and control. Wiley, Hoboken
27.
go back to reference Vrooijink GJ, Abayazid M, Patil S, Alterovitz R, Misra S (2014) Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images. Int J Robot Res 33(10): 0278364914526627 Vrooijink GJ, Abayazid M, Patil S, Alterovitz R, Misra S (2014) Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images. Int J Robot Res 33(10): 0278364914526627
28.
go back to reference Waine M, Rossa C, Sloboda R, Usmani N, Tavakoli M (2015) 3D shape visualization of curved needles in tissue from 2D ultrasound images using ransac. In: 2015 IEEE international conference on, robotics and automation, pp 4723–4728. IEEE Waine M, Rossa C, Sloboda R, Usmani N, Tavakoli M (2015) 3D shape visualization of curved needles in tissue from 2D ultrasound images using ransac. In: 2015 IEEE international conference on, robotics and automation, pp 4723–4728. IEEE
29.
go back to reference Yan P, Cheeseborough JC, Chao KC (2012) Automatic shape-based level set segmentation for needle tracking in 3-d trus-guided prostate brachytherapy. Ultrasound Med Biol 38(9):1626–1636CrossRefPubMed Yan P, Cheeseborough JC, Chao KC (2012) Automatic shape-based level set segmentation for needle tracking in 3-d trus-guided prostate brachytherapy. Ultrasound Med Biol 38(9):1626–1636CrossRefPubMed
Metadata
Title
Estimating needle tip deflection in biological tissue from a single transverse ultrasound image: application to brachytherapy
Authors
Carlos Rossa
Ron Sloboda
Nawaid Usmani
Mahdi Tavakoli
Publication date
01-07-2016
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Computer Assisted Radiology and Surgery / Issue 7/2016
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-015-1329-4

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