Needle Placement for Robot-assisted 3D-guided Ultrasound Breast Biopsy: A Preliminary Study

Authors

Keywords:

Breast biopsy, Modeling, Needle placement, Robot-assisted, 3D ultrasound

Abstract

This work describes a new robot-assisted three-dimensional ultrasound-guided needle placement for breast biopsy to improve cancer diagnosis by automating needle trajectory, simplifying manual insertion and alleviating radiologist fatigue. In this way, basic robot requirements were first determined based on linking a free-hand ultrasound-guided breast biopsy with a whole-breast volumetric reconstruction system as part of a clinical workflow for breast cancer diagnosis. For modeling, a five-degree-of-freedom open-chain robot was proposed by considering the woman’s breast volume and a radial ultrasound scanning approach as workspace. The forward and inverse kinematics were calculated using the screw axis-based theory and a geometric-algebraic formulation, respectively. For trajectories, a collision-free path algorithm was computed to assess target reachability. For simulating, a dedicated biopsy environment was implemented in MATLAB-Simulink to perform multiple simulations by modifying some radiologist manipulability variables in accordance with a factorial-method research design. The results showed a numerical and graphical verification of the equations and even a visual one of the needle placement during two stages: before a biopsy and after it. In conclusion, it was computationally explored the use of a novel robot-assisted needle placement in breast biopsy for women in a prone position.

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Author Biographies

Sergio Jácobo-Zavaleta, Universidad Nacional de Trujillo

He received his bachelor’s degree in Mechatronics Engineering (2019) from the Universidad Nacional de Trujillo, Peru. His research interests include design of clinical robots and biomedical applications based on Artificial Intelligence using Machine Learning.ng.

Jorge Zavaleta, State University of Rio de Janeiro

He received the Ph. D in Systems and Computer Engineering in the Federal University of Rio de Janeiro (UFRJ) in 2017. He received the title of master’s in computer science from the Federal University of Rio Grande do Sul (UFRGS) in 1997. He received the title of Licenciate in Mathematics from the Universidad Nacional de Trujillo (UNT) in 1998 and received a bachelor’s degree in Physical and Mathematical Sciences from the UNT in 1992. Professor of Computing and currently a researcher of postdoctoral at the State University of Rio de Janeiro (UERJ) in the project CAPES-Telemedicine and Medical Data Analysis. He is interested in topics research related to Data Science, Artificial Intelligence and Machine Learning.

References

N. Azamjah, Y. Soltan-Zadeh, and F. Zayeri, “Global Trend of Breast Cancer Mortality Rate: A 25-date Study,” Asian Pacific Journal of Cancer Prevention, vol. 20, no. 7, pp. 43–46, 2019.

H. Sung, J. Ferlay, R. L. Siegel, M. Laversanne, I. Soerjomataram, A. Jemal, and F. Bray, “Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries,” CA: A Cancer Journal for Clinicians, vol. 71, pp. 209–249, May 2021.

Instituto Nacional de Estadística e Informática, “Peru: Enfermedades No Transmisibles y Transmisibles,” tech. rep., Ministerio de Salud, 2020.

Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, “Boletin epidemiológico del Perú, 2021,” Tech. Rep. 05, Ministerio de Salud, Perú, Jan. 2021.

A. Adam, R. F. Dondelinger, and P. R. Mueller, “Interventional Radiology in Breast Cancer,” in Interventional Radiology in Cancer, vol. 10.1007/978-3-642-18668-4 of Medical Radiology, p. 282, SpringerVerlag, first ed., 2004.

L. F. Smith, I. T. Rubio, R. Henry-Tillman, S. Korourian, and V. Klimberg, “Intraoperative ultrasound-guided breast biopsy,” The American Journal of Surgery, vol. 180, pp. 419–423, Dec. 2000.

M. Raghu and R. Hooley, “Breast Ultrasound for the Interventionalist,” Techniques in Vascular and Interventional Radiology, vol. 17, pp. 16–22, Mar. 2014.

H. Zhao, T. Liu, M. Chen, Q. Tian, Z. Li, S. Cao, and C. Ai, “A needle insertion concept and robot system for breast tumor,” in IEEE 2016 International Conference on Mechatronics and Automation - Harbin, Heilongjiang, China, pp. 896–901, 2016.

M. Z. Mahmoud, M. Aslam, M. Alsaadi, M. A. Fagiri, and B. Alonazi, “Evolution of Robot-assisted ultrasound-guided breast biopsy systems,” Journal of Radiation Research and Applied Sciences, vol. 11, no. 1, pp. 89–97, 2017.

J. C. M. van Zelst and R. M. Mann, “Automated Threedimensional Breast US for Screening: Technique, Artifacts, and Lesion Characterization,” Radiographics, p. 170162, 2018.

M. Chen, H. Zhao, Z. Li, Y. Zhao, Q. Tian, and T. Liu, “Development of a new needle insertion medical robot for breast tumor surgery,” in IEEE 2017 International Conference on Real-time Computing and Robotics (RCAR), Okinawa, Japón, pp. 28–33, 2017.

N. Tanaiutchawoot, B. Treepong, C. Wiratkapan, and J. Suthakorn,

“A path generation algorithm for biopsy needle insertion in a robotic breast biopsy navigation system,” in IEEE International Conference on Robotics and Biomimetics (ROBIO) - Bali, Indonesia, pp. 398–403, 2014.

S. O. Orhan, M. C. Yildirim, and O. Bebek, “Design and modeling of a parallel robot for ultrasound guided percutaneous needle interventions,” in 41st Annual Conference of the IEEE Industrial Electronics Society IECON - Yokohama, Japón, pp. 1–12, 2015.

M. Abayazid, P. Moreira, N. Shahriari, A. Zompas, and S. Misra, “ThreeDimensional Needle Steering Using Automated Breast Volume Scanner (ABVS),” Journal of Medical Robotics Research, vol. 1, no. 1, pp. 1–9, 2016.

M. K. Welleweerd, F. J. Siepel, V. Groenhuis, J. Veltman, and S. Stramigioli, “Design of an end-effector for robot-assisted ultrasoundguided breast biopsies,” International Journal of Computer Assisted Radiology and Surgery, vol. 15, pp. 681–690, 2020.

A. Priester, S. Natarajan, and M. Culjat, “Robotic ultrasound systems in medicine,” IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 60, pp. 507–523, Mar. 2013.

G. Megali, O. Tonet, C. Stefanini, M. Boccadoro, V. Papaspyropoulos, L. Angelini, and P. Dario, “A computer-assisted robotic ultrasoundguided biopsy system for video-assisted surgery,” in International Conference on Medical Image Computing and Computer-Assisted Intervention – MICCAI (W. Niessen and M. Viergever, eds.), vol. 2208, pp. 343–350, Springer-Verlag, 2001.

L. Bartella, C. S. Smith, D. D. Dershaw, and L. Liberman, “Imaging Breast Cancer,” Radiologic Clinics of North America, vol. 45, no. 1, pp. 45–67, 2007.

A. Farrokh, H. Erdönmez, F. Schäfer, and N. Maass, “SOFIA: A Novel Automated Breast Ultrasound System Used on Patients in the Prone Position: A Pilot Study on Lesion Detection in Comparison to Handheld Grayscale Ultrasound,” Geburtshilfe und Frauenheilkunde, vol. 78, no. 5, pp. 499–505, 2018.

S. Y. Huang, J. M. Boone, K. Yang, N. J. Packard, S. E. McKenney, N. D. Prionas, K. K. Lindfors, and M. J. Yaffe, “The characterization of breast anatomical metrics using dedicated breast CT,” Medical Physics, vol. 38, no. 4, pp. 2180–2191, 2011.

L.-H. Chen, S.-P. Ng, W. Yu, J. Zhou, and K. W. Frances Wan, “A study of breast motion using non-linear dynamic fe analysis,” Ergonomics, vol. 56, no. 5, pp. 868–878, 2013. PMID: 23514244.

S. N. Bhatti and M. Sridhar-Keralapura, “A novel breast software phantom for biomechanical modeling of elastography: A novel breast software phantom for elastography biomechanics,” Medical Physics, vol. 39, pp. 1748–1768, Mar. 2012.

J. Cheng, K. Brandt, R. Grimm, K. Glaser, and J. Kugel, “Noncompressive MR Elastography of Breasts,” in Proceedings of the International Society for Magnetic Resonance in Medicine, (Salt Lake City, USA), p. 25, 2013.

ICRP, Adult Reference Computational Phantoms, vol. 39 of ICRP Publication 110. SAGE Publications, first ed., 2009.

T. Ohno, R. W. Sweet, D. Dejak, and S. Spiegelman, “Purification and characterization of the DNA polymerase of human breast cancer particles.,” Proceedings of the National Academy of Sciences, vol. 74, pp. 764–768, Feb. 1977.

W. Liu, Z. Yang, S. Jiang, D. Feng, and D. Zhang, “Design and implementation of a new cable-driven robot for MRI-guided breast biopsy,” The International Journal of Medical Robotics and Computer Assisted Surgery, vol. 16, Apr. 2019.

Noras MRI products, “Breast Biopsy 7-Channel Coil BI 7 for Immobilization and MR-supported Mammography,” tech. rep., NORAS MRI products, 2020.

M. Pramanik, G. Ku, C. Li, and L. V. Wang, “Design and evaluation of a novel breast cancer detection system combining both thermoacoustic (TA) and photoacoustic (PA) tomography,” Medical Physics, vol. 35, no. 6, p. 2218, 2008.

S. Manohar and M. Dantuma, “Current and Future Trends in Photoacoustic Breast Imaging,” Photoacoustics, vol. 16, p. 26, 2019.

A. Nikolaev, H. H. Hansen, L. De Jong, R. Mann, E. Tagliabue, B. Maris, V. Groenhuis, F. Siepel, M. Caballo, I. Sechopoulos, and C. L. De Korte, “Ultrasound-guided breast biopsy of ultrasound occult lesions using multimodality image co-registration and tissue displacement tracking,” in Medical Imaging 2019, vol. 10955 of Progress in Biomedical Optics and Imaging - Proceedings of SPIE, pp. 1–8, SPIE, 2019.

R. D. Rocha, R. R. Pinto, D. P. B. A. Tavares, and C. S. A. Gonçalves, “Step-by-step of ultrasound-guided core-needle biopsy of the breast: Review and technique,” Radiologia Brasileira, vol. 46, no. 4, pp. 234– 241, 2013.

Hologic Inc., “The Affirm® Prone Biopsy System.” [Online]. Available at https://www.affirmpronebiopsy.com, 2022. (accessed 05 June 2022).

K. M. Lynch and F. C. Park, Modern Robotics: Mechanics, Planning, and Control. Cambridge, UK: Cambridge University Press, 2017.

F. C. Park, “Computational aspects of the product-of-exponentials formula for robot kinematics,” IEEE Transactions on Automatic Control, vol. 39, pp. 643–647, Mar. 1994.

A. Dominique, “Automatic Breast Ultrasound Scanning,” in Lobar Approach to Breast Ultrasound, ch. 26, pp. 325–336, Springer-Verlag, first ed., 2018.

L. Apesteguía and L. J. Pina, “Ultrasound-guided core-needle biopsy of breast lesions,” Insights into Imaging, vol. 2, no. 4, pp. 493–500, 2011.

K. S. Mahesh, “Screening for Breast Cancer,” in Breast Cancer Screening and Diagnosis: A Synopsis, vol. 23, pp. 23–36, SpringerVerlag, first ed., 2015.

N. Bluvol, A. Shaikh, A. Kornecki, D. Del Rey Fernandez, D. Downey, and A. Fenster, “A needle guidance system for biopsy and therapy using two-dimensional ultrasound: A needle guidance system for biopsy and therapy,” Medical Physics, vol. 35, pp. 617–628, Jan. 2008.

W. G. Zikmund, B. J. Babin, J. C. Carr, and M. Griffin, Business Research Methods, 8th Edition. South-Western College Pub, eighth ed., 2009.

A. C. Tamhane and D. D. Dunlop, Statistics and Data Analysis : From Elementary to Intermediate. Prentice Hall, 2000.

M. D. Mckay, R. J. Beckman, and W. J. Conover, “A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code,” Technometrics, vol. 42, pp. 55–61, Feb. 2000.

K. B. Reed, A. M. Okamura, and N. J. Cowan, “Modeling and control of needles with torsional friction,” IEEE transactions on bio-medical engineering, vol. 56, no. 12, pp. 2905–2916, 2009.

J. Suthakorn, N. Tanaiutchawoot, C. Wiratkapan, and S. Ongwattanakul, “Breast biopsy navigation system with an assisted needle holder tool and 2D graphical user interface,” European Journal of Radiology Open, vol. 5, pp. 93–101, 2018.

Published

2023-01-17

How to Cite

Jácobo-Zavaleta, S. ., & Zavaleta, J. (2023). Needle Placement for Robot-assisted 3D-guided Ultrasound Breast Biopsy: A Preliminary Study. IEEE Latin America Transactions, 21(3), 450–456. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/7442