2024
Bernardes, Mariana C.; Moreira, Pedro; Lezcano, Dimitri; Foley, Lori; Tuncali, Kemal; Tempany, Clare; Kim, Jin Seob; Hata, Nobuhiko; Iordachita, Iulian; Tokuda, Junichi
In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures Journal Article
In: IEEE ROBOTICS AND AUTOMATION LETTERS, vol. 9, no. 10, pp. 8975–8982, 2024, ISSN: 2377-3766, (Num Pages: 8 Place: Piscataway Publisher: Ieee-Inst Electrical Electronics Engineers Inc Web of Science ID: WOS:001316210300001).
Abstract | Links | BibTeX | Tags: Accuracy, Fiber Bragg gratings, Force, In vivo, Magnetic Resonance Imaging, Medical robots and systems, needles, prostate biopsy, Robot sensing systems, robots, surgical robotics: steerable catheters/needles, TISSUE, Trajectory
@article{bernardes_vivo_2024,
title = {In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures},
author = {Mariana C. Bernardes and Pedro Moreira and Dimitri Lezcano and Lori Foley and Kemal Tuncali and Clare Tempany and Jin Seob Kim and Nobuhiko Hata and Iulian Iordachita and Junichi Tokuda},
doi = {10.1109/LRA.2024.3455940},
issn = {2377-3766},
year = {2024},
date = {2024-10-01},
journal = {IEEE ROBOTICS AND AUTOMATION LETTERS},
volume = {9},
number = {10},
pages = {8975–8982},
abstract = {This letter addresses the targeting challenges in MRI-guided transperineal needle placement for prostate cancer (PCa) diagnosis and treatment, a procedure where accuracy is crucial for effective outcomes. We introduce a parameter-agnostic trajectory correction approach incorporating a data-driven closed-loop strategy by radial displacement and an FBG-based shape sensing to enable autonomous needle steering. In an animal study designed to emulate clinical complexity and assess MRI compatibility through a PCa mock biopsy procedure, our approach demonstrated a significant improvement in targeting accuracy (p < 0.05), with mean target error of only 2.2 +/- 1.9 mm on first insertion attempts, without needle reinsertions. To the best of our knowledge, this work represents the first in vivo evaluation of robotic needle steering with FBG-sensor feedback, marking a significant step towards its clinical translation.},
note = {Num Pages: 8
Place: Piscataway
Publisher: Ieee-Inst Electrical Electronics Engineers Inc
Web of Science ID: WOS:001316210300001},
keywords = {Accuracy, Fiber Bragg gratings, Force, In vivo, Magnetic Resonance Imaging, Medical robots and systems, needles, prostate biopsy, Robot sensing systems, robots, surgical robotics: steerable catheters/needles, TISSUE, Trajectory},
pubstate = {published},
tppubtype = {article}
}
This letter addresses the targeting challenges in MRI-guided transperineal needle placement for prostate cancer (PCa) diagnosis and treatment, a procedure where accuracy is crucial for effective outcomes. We introduce a parameter-agnostic trajectory correction approach incorporating a data-driven closed-loop strategy by radial displacement and an FBG-based shape sensing to enable autonomous needle steering. In an animal study designed to emulate clinical complexity and assess MRI compatibility through a PCa mock biopsy procedure, our approach demonstrated a significant improvement in targeting accuracy (p < 0.05), with mean target error of only 2.2 +/- 1.9 mm on first insertion attempts, without needle reinsertions. To the best of our knowledge, this work represents the first in vivo evaluation of robotic needle steering with FBG-sensor feedback, marking a significant step towards its clinical translation.
2023
Bernardes, Mariana C.; Moreira, Pedro; Mareschal, Lisa; Tempany, Clare; Tuncali, Kemal; Hata, Nobuhiko; Tokuda, Junichi
Data-driven adaptive needle insertion assist for transperineal prostate interventions Journal Article
In: PHYSICS IN MEDICINE AND BIOLOGY, vol. 68, no. 10, pp. 105016, 2023, ISSN: 0031-9155, 1361-6560, (Num Pages: 14 Place: Bristol Publisher: IoP Publishing Ltd Web of Science ID: WOS:000987076600001).
Abstract | Links | BibTeX | Tags: biopsy, Brachytherapy, CANCER, Cryoablation, data-driven model, FEASIBILITY, Force, medical robotics, MOTION, needle insertion assist, Robot, TISSUE, transperineal prostate intervention, Ultrasound
@article{bernardes_data-driven_2023,
title = {Data-driven adaptive needle insertion assist for transperineal prostate interventions},
author = {Mariana C. Bernardes and Pedro Moreira and Lisa Mareschal and Clare Tempany and Kemal Tuncali and Nobuhiko Hata and Junichi Tokuda},
doi = {10.1088/1361-6560/accefa},
issn = {0031-9155, 1361-6560},
year = {2023},
date = {2023-05-01},
journal = {PHYSICS IN MEDICINE AND BIOLOGY},
volume = {68},
number = {10},
pages = {105016},
abstract = {Objective. Clinical outcomes of transperineal prostate interventions, such as biopsy, thermal ablations, and brachytherapy, depend on accurate needle placement for effectiveness. However, the accurate placement of a long needle, typically 150-200 mm in length, is challenging due to needle deviation induced by needle-tissue interaction. While several approaches for needle trajectory correction have been studied, many of them do not translate well to practical applications due to the use of specialized needles not yet approved for clinical use, or to relying on needle-tissue models that need to be tailored to individual patients. Approach. In this paper, we present a robot-assisted collaborative needle insertion method that only requires an actuated passive needle guide and a conventional needle. The method is designed to assist a physician inserting a needle manually through a needle guide. If the needle is deviated from the intended path, actuators shifts the needle radially in order to steer the needle trajectory and compensate for needle deviation adaptively. The needle guide is controlled by a new data-driven algorithm which does not require a priori information about needle or tissue properties. The method was evaluated in experiments with both in vitro and ex vivo phantoms. Main results. The experiments in ex vivo tissue reported a mean final placement error of 0.36 mm with a reduction of 96.25% of placement error when compared to insertions without the use of assistive correction. Significance. Presented results show that the proposed closed-loop formulation can be successfully used to correct needle deflection during collaborative manual insertion with potential to be easily translated into clinical application.},
note = {Num Pages: 14
Place: Bristol
Publisher: IoP Publishing Ltd
Web of Science ID: WOS:000987076600001},
keywords = {biopsy, Brachytherapy, CANCER, Cryoablation, data-driven model, FEASIBILITY, Force, medical robotics, MOTION, needle insertion assist, Robot, TISSUE, transperineal prostate intervention, Ultrasound},
pubstate = {published},
tppubtype = {article}
}
Objective. Clinical outcomes of transperineal prostate interventions, such as biopsy, thermal ablations, and brachytherapy, depend on accurate needle placement for effectiveness. However, the accurate placement of a long needle, typically 150-200 mm in length, is challenging due to needle deviation induced by needle-tissue interaction. While several approaches for needle trajectory correction have been studied, many of them do not translate well to practical applications due to the use of specialized needles not yet approved for clinical use, or to relying on needle-tissue models that need to be tailored to individual patients. Approach. In this paper, we present a robot-assisted collaborative needle insertion method that only requires an actuated passive needle guide and a conventional needle. The method is designed to assist a physician inserting a needle manually through a needle guide. If the needle is deviated from the intended path, actuators shifts the needle radially in order to steer the needle trajectory and compensate for needle deviation adaptively. The needle guide is controlled by a new data-driven algorithm which does not require a priori information about needle or tissue properties. The method was evaluated in experiments with both in vitro and ex vivo phantoms. Main results. The experiments in ex vivo tissue reported a mean final placement error of 0.36 mm with a reduction of 96.25% of placement error when compared to insertions without the use of assistive correction. Significance. Presented results show that the proposed closed-loop formulation can be successfully used to correct needle deflection during collaborative manual insertion with potential to be easily translated into clinical application.