Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core Vs. Multicore Approaches

Overview

Journal ArXiv

Date 2023 Sep 21

PMID 37731661

Authors

Dimitri A Lezcano

Yernar Zhetpissov

Alexandra Cheng

Jin Seob Kim

Iulian I Iordachita

Affiliations

Soon will be listed here.

Abstract

Flexible needle insertion procedures are common for minimally-invasive surgeries for diagnosing and treating prostate cancer. Bevel-tip needles provide physicians the capability to steer the needle during long insertions to avoid vital anatomical structures in the patient and reduce post-operative patient discomfort. To provide needle placement feedback to the physician, sensors are embedded into needles for determining the real-time 3D shape of the needle during operation without needing to visualize the needle intra-operatively. Through expansive research in fiber optics, a plethora of bio-compatible, MRI-compatible, optical shape-sensors have been developed to provide real-time shape feedback, such as single-core and multicore fiber Bragg gratings. In this paper, we directly compare single-core fiber-based and multicore fiber-based needle shape-sensing through identically constructed, four-active area sensorized bevel-tip needles inserted into phantom and tissue on the same experimental platform. In this work, we found that for shape-sensing in phantom tissue, the two needles performed identically with a -value of 0.164 > 0.05, but in real tissue, the single-core fiber sensorized needle significantly outperformed the multicore fiber configuration with a -value of 0.0005 < 0.05. This paper also presents the experimental platform and method for directly comparing these optical shape sensors for the needle shape-sensing task, as well as provides direction, insight and required considerations for future work in constructively optimizing sensorized needles.

References

Song K, Lezcano D, Sun G, Kim J, Iordachita I . Towards Automatic Robotic Calibration System for Flexible Needles with FBG Sensors. Int Symp Med Robot. 2022; 2021. PMC: 8855976. DOI: 10.1109/ismr48346.2021.9661542. View

Cheng A, Lezcano D, Kim J, Iordachita I . Optical Fiber -Based Needle Shape Sensing: Three-channel Single Core vs. Multicore Approaches. Int Symp Med Robot. 2023; 2023. PMC: 10249955. DOI: 10.1109/ismr57123.2023.10130249. View

Chen S, Wang F, Lin Y, Shi Q, Wang Y . Ultrasound-guided needle insertion robotic system for percutaneous puncture. Int J Comput Assist Radiol Surg. 2021; 16(3):475-484. DOI: 10.1007/s11548-020-02300-1. View

Li X, Young A, Raman S, Lu D, Lee Y, Tsao T . Automatic needle tracking using Mask R-CNN for MRI-guided percutaneous interventions. Int J Comput Assist Radiol Surg. 2020; 15(10):1673-1684. DOI: 10.1007/s11548-020-02226-8. View

Reisenauer J, Simoff M, Pritchett M, Ost D, Majid A, Keyes C . Ion: Technology and Techniques for Shape-sensing Robotic-assisted Bronchoscopy. Ann Thorac Surg. 2021; 113(1):308-315. DOI: 10.1016/j.athoracsur.2021.06.086. View

Deaton N, Brumfiel T, Sarma A, Desai J . Simultaneous Shape and Tip Force Sensing for the COAST Guidewire Robot. IEEE Robot Autom Lett. 2024; 8(6):3725-3731. PMC: 10805467. DOI: 10.1109/lra.2023.3267008. View

Francoeur J, Roberge A, Lorre P, Monet F, Wright C, Kadoury S . Optical frequency domain reflectometry shape sensing using an extruded optical fiber triplet for intra-arterial guidance. Opt Express. 2023; 31(1):396-410. DOI: 10.1364/OE.475715. View

Adebar T, Fletcher A, Okamura A . 3-D ultrasound-guided robotic needle steering in biological tissue. IEEE Trans Biomed Eng. 2014; 61(12):2899-910. PMC: 5545809. DOI: 10.1109/TBME.2014.2334309. View

Li M, Li G, Gonenc B, Duan X, Iordachita I . Towards human-controlled, real-time shape sensing based flexible needle steering for MRI-guided percutaneous therapies. Int J Med Robot. 2016; 13(2). PMC: 9596148. DOI: 10.1002/rcs.1762. View

10.

Lehocky C, Shi Y, Riviere C . Hyper- and viscoelastic modeling of needle and brain tissue interaction. Annu Int Conf IEEE Eng Med Biol Soc. 2015; 2014:6530-3. PMC: 4359917. DOI: 10.1109/EMBC.2014.6945124. View

11.

Zhao Z, Soto M, Tang M, Thevenaz L . Distributed shape sensing using Brillouin scattering in multi-core fibers. Opt Express. 2016; 24(22):25211-25223. DOI: 10.1364/OE.24.025211. View

12.

Medan G, Joskowicz L . Flexible needle and patient tracking using fractional scanning in interventional CT procedures. Int J Comput Assist Radiol Surg. 2019; 14(6):1039-1047. DOI: 10.1007/s11548-019-01945-x. View

13.

Lezcano D, Iordachita I, Kim J . Lie-Group Theoretic Approach to Shape-Sensing Using FBG-Sensorized Needles Including Double-Layer Tissue and S-Shape Insertions. IEEE Sens J. 2023; 22(22):22232-22243. PMC: 10193911. DOI: 10.1109/jsen.2022.3212209. View

14.

Amantayeva A, Adilzhanova N, Issatayeva A, Blanc W, Molardi C, Tosi D . Fiber Optic Distributed Sensing Network for Shape Sensing-Assisted Epidural Needle Guidance. Biosensors (Basel). 2021; 11(11). PMC: 8615863. DOI: 10.3390/bios11110446. View

15.

van de Berg N, Dankelman J, van den Dobbelsteen J . Design of an actively controlled steerable needle with tendon actuation and FBG-based shape sensing. Med Eng Phys. 2015; 37(6):617-22. DOI: 10.1016/j.medengphy.2015.03.016. View

16.

Donder A, Rodriguez Y Baena F . 3-D Path-Following Control for Steerable Needles With Fiber Bragg Gratings in Multi-Core Fibers. IEEE Trans Biomed Eng. 2022; 70(3):1072-1085. DOI: 10.1109/TBME.2022.3209149. View

17.

Beisenova A, Issatayeva A, Iordachita I, Blanc W, Molardi C, Tosi D . Distributed fiber optics 3D shape sensing by means of high scattering NP-doped fibers simultaneous spatial multiplexing. Opt Express. 2019; 27(16):22074-22087. DOI: 10.1364/OE.27.022074. View

18.

Mathews S, Shakir D, Mosse C, Xia W, Zhang E, Beard P . Ultrasonic Needle Tracking with Dynamic Electronic Focusing. Ultrasound Med Biol. 2022; 48(3):520-529. DOI: 10.1016/j.ultrasmedbio.2021.11.008. View

19.

Kim J, Chirikjian G . Conformational Analysis of Stiff Chiral Polymers with End-Constraints. Mol Simul. 2010; 32(14):1139-1154. PMC: 2829781. DOI: 10.1080/08927020601024137. View

20.

Park Y, Elayaperumal S, Daniel B, Ryu S, Shin M, Savall J . Real-Time Estimation of 3-D Needle Shape and Deflection for MRI-Guided Interventions. IEEE ASME Trans Mechatron. 2015; 15(6):906-915. PMC: 4577522. DOI: 10.1109/TMECH.2010.2080360. View