Our paper entitled “In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures” has been published in IEEE Robotics and Automation Letters.
This is the most recent result from our decade-long collaboration with Johns Hopkins University (JHU) initiated by Dr. Clare Tempany, M.D. (Brigham and Women’s Hospital). This part of an NIH-funded project (NIH R01CA235134; MPI: Tokuda, Nobuhiko Hata (BWH), Iulian Iordachita, (JHU)) that brings the Tokuda Lab’s expertise in MR-conditional device, needle insertion control, and systems integration, Dr. Iordachita’s expertise in fiber-Bragg-grating (FBG) shape sensing, and Dr. Hata’s exertise in clinical translation together to develop a novel closed-loop precision needle placement system.
This paper 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.
Reference
- Bernardes MC, Moreira P, Lezcano D, Foley L, Tuncali K, Tempany C, Kim JS, Hata N, Iordachita I, Tokuda J. In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures. IEEE Robotics and Automation Letters. 2024;9(10):8975–8982. doi:10.1109/LRA.2024.3455940 PMID: 39371576. PMCID: PMC11448709.
Grant Support
This study is supported in part by the National Institutes of health (R01CA235134, R01EB020667, P41EB028741).
