Ex vivo breach detection using electrical conductivity during robotic pedicle drilling in the spine

arXiv:2610.01310 · cs.RO · Submitted 2026-10-01 · Read on arXiv

Listen

Radio episode about this paper

Transcript

Introduction to the show: ident: Robotics Radio. Generated commentary on the latest robotics and control papers.

Rosa: Today's paper: "Ex vivo breach detection using electrical conductivity during robotic pedicle drilling in the spine".

Dev: Pedicle screw placement (PSP) is a technically demanding spinal procedure where high precision is crucial due to limited visibility and anatomical variability,

Rosa: First, who's behind it and why it matters.

Paper summary: Rosa: So, to wrap up our discussion on "Ex vivo breach detection using electrical conductivity during robotic pedicle drilling in the spine," we've seen how this work demonstrates the feasibility of using electrical bioimpedance sensing for real-time breach prevention.

Dev: The authors successfully showed that by analyzing tool signals alone, they eliminated the need for external sensing systems and created a safer approach to pedicle screw placement.

Taro: From an autonomy research standpoint, it shows that incorporating physical property feedback directly into the robotic execution loop can provide a necessary layer of immediate safety monitoring when things go unexpectedly during an operation.

Rosa: The real-world impact centers on offering a method to stop potential perforation before it occurs, which supports safer screw placement and reduces reliance on intraoperative imaging and radiation.

Dev: The technical achievement lies in designing an algorithm that monitors conductivity signals to catch abrupt changes, providing a mechanism that could be integrated into existing drilling systems or standalone tools.

Taro: While the ex vivo results are impressive, the next steps for this kind of research would involve testing its robustness and latency when deployed in complex, dynamic clinical scenarios where patient movement is present.

Rosa: That’s what we need to think about for future work, moving beyond the controlled environment to see how long this system can reliably operate and perform under real-world surgical conditions.

Conclusion: Rosa: So, we've seen how this study used electrical conductivity to stop drilling before a breach happens in pigs, so let's talk about what that actually means for us with this paper titled "Ex vivo breach detection using electrical conductivity during robotic pedicle drilling in the spine."

Dev: Yeah, I agree it’s interesting how they focused on stopping the procedure when things go wrong; I was thinking about how fast this sensing loop would have to run for a real surgical robot to even consider that kind of feedback.

Taro: And from an autonomy angle, if we can detect a potential failure like that in a controlled setting, it really pushes the boundaries of what we can expect when the environment gets unpredictable during autonomous movement.

Rosa: Exactly; this moves beyond just following a pre-programmed path and introduces an active safety mechanism based on physical properties like conductivity.

Dev: I'm wondering about the practical application outside of this lab setting; how long do you think this sensing system could reliably operate in a dynamic clinical environment before its performance degrades due to things like fluid shifts or tissue changes?

Taro: That’s the million-dollar question for autonomy; we need to know if these real-time feedback mechanisms can handle unexpected deviations in the patient's anatomy without causing a false stop or missing a genuine issue.

Rosa: The implication here is that we might be able to deploy an X-ray-free method for intraoperative safety, which could significantly reduce the radiation exposure associated with traditional imaging during these procedures.

Dev: I see how that would be valuable for minimizing patient risk, but we still need to address the latency of this signal processing; if the detection happens too slowly, it's useless for a high-speed drilling operation.

Taro: Precisely, and that leads right into my next point: what happens when the system misbehaves? If the electrical signature is ambiguous, how does our autonomous logic decide whether to pause or continue?

Rosa: So we've established the feasibility in pigs; now we need to look at scaling that up and figuring out if this technology can actually translate into a reliable, safe tool for human surgery.

Jorge Andres Perez Velasquez, Françoise Teyssere, Thibault Chandanson, Quentin Grimal, Brahim Tamadazte

ISIR, Sorbonne University-CNRS UMR 7222, Inserm U1150 · SpineGuard SA

cs.RO

Submitted: 2026-10-01

Updated: 2026-10-01

License: http://creativecommons.org/licenses/by/4.0/

Importance score: 67/100

The gist: Pedicle screw placement (PSP) is a technically demanding spinal procedure where high precision is crucial due to limited visibility and anatomical variability, and this study proposes using robotic

Key concepts

Electrical Bioimpedance Sensing
This involves using electrodes on the drill bit to measure the electrical conductivity of the surrounding tissue in real time. Different tissues like bone, soft tissue, and blood have distinct electrical properties. By monitoring these changes during drilling, the system can detect when a breach is imminent.
Adaptive Threshold ($θr$)
This is a dynamic safety limit calculated based on conductivity measurements taken early in the drilling process. It establishes a baseline for normal bone engagement and adjusts to account for slight variations in tissue composition, ensuring the detection system remains sensitive yet avoids unnecessary alarms.
Breach Detection Algorithm
This is the software logic that processes the electrical signals from the sensor. It looks for sudden, abrupt changes in conductivity or exceeds pre-set limits. This allows the system to flag a potential breach immediately, triggering an alert to stop drilling before perforation happens.
Ex Vivo Testing
This refers to conducting experiments on fresh animal specimens (porcine lumbar vertebrae) outside of a living subject. This setup allowed researchers to safely test the robotic drilling and detection system under controlled conditions without risking harm to human patients.

Terminology

Summary

Pedicle screw placement (PSP) is a technically demanding spinal procedure where high precision is crucial due to limited visibility and anatomical variability, and this study proposes using robotic pedicle drilling combined with real-time preventive breach detection via electrical bioimpedance sensing to enhance safety. The proposed method demonstrates the feasibility of stopping the procedure before perforation by analyzing electrical conductivity signals during drilling.

The gist

The proposed method prevents breaches in 100% of the 51 ex vivo drilling cases, demonstrating the system’s ability to detect potentially hazardous events during drilling and to stop the procedure before [perforation].

Methods and Experimental Setup

The study developed a robotic approach integrated with a pedicle-drilling tool equipped with a proprioceptive electrical bioimpedance sensor developed by SpineGuard®. This sensor is mounted on a threaded drill bit, which operates at 25 Hz and maintains contact with the bone. The system measures local tissue conductivity using bipolar electrodes; conductivity is low in cortical bone, higher in cancellous bone, and highest in blood and soft tissue.

The experimental setup involved drilling 51 fresh porcine lumbar vertebrae immersed in a saline solution designed to replicate the electrical conductivity of cerebrospinal fluid (CSF), with a NaCl concentration of approximately 120–130 mmol/L to mimic the ionic composition of CSF. The drilling was performed under controlled conditions: a nominal drilling force of 10 N, rotational speed of 30 rpm, and a maximum descent rate of 50 mm/s. To verify results, several approaches were applied:

  1. Palpation with a ball-tip feeler to assess cortical bone integrity and rule out grade ”C” breaches.

  2. Visual inspection of the spinal canal following the experiments to identify any deformation caused by the drill bit tip.

  3. Imaging and video analysis, combining CT scans and video recordings, used to confirm the absence of false positives and false negatives.

Breach Detection Algorithm

A real-time detection algorithm was designed to analyze the electrical bioimpedance signal during drilling to identify abrupt changes in conductivity associated with potential breaches towards the spinal canal. The algorithm operates using paired data: conductivity measurements (ψ), stored in Ψ, and drilling depth (z), stored in Z.

The process involves several steps:

  1. An adaptive threshold, denoted (ψr), is computed from the conductivity measurements recorded over the first few millimeters of drilling, which corresponds to engagement in predominantly cortical and cancellous bone. This initial segment is used as a baseline.

  2. The threshold ψr is constrained within predefined bounds: an upper bound (ψmax = 500 mV) to avoid false negatives, and a lower bound (ψmin = 150 mV) to limit false positives.

  3. During the breach detection phase, the threshold conductivity ψt is computed as:

(2) ψt = max [min(ψmax, α · ψr), ψmin]

  1. A flag A1 is set to True if the current conductivity (ψk) exceeds this threshold:

(3) A1 ← ψk > ψt

  1. The depth index m closest to ∆z = 2mm before the last recorded depth is estimated, and the minimum conductivity within the defined search window (from index m to k) is computed as n.

  2. Flag A2 is set to True if a sudden change in conductivity exceeding a gradient threshold (∆max = 230mV) is detected within the search window:

(4) A2 ← ((max [i∈[n,k] Ψ(i)] − Ψ(n)) > ∆max)

  1. An Alert is triggered if either A1 or A2 was set to True:

(5) Alert ← A1 A2

Results and Conclusions

The ex vivo experiments showed that the proposed method prevented breaches in 100% of the 51 drilling cases. All resulting screws were graded ”A” or ”B” according to the Gertzbein and Robbins classification, meaning they achieved a fully intrapedicular position without cortical violation (Grade ”A”) or a breach not exceeding 2 mm (Grade ”B”). The mean error remained within [-1, +1.4] mm. Post hoc inspection confirmed that drilling was interrupted immediately before perforation for all 51 vertebrae. Electrical conductivity offers an X-ray-free approach to breach prevention that can complement navigation systems, reduce intraoperative imaging, and limit radiation exposure. The proposed online, real-time breach detection method could be integrated into standalone surgical tools or implemented as an additional safety feature in existing drilling systems.

Keywords

Surgical robotics, Spine surgery, Pedicle screw placement, Electrical bioimpedance sensing.

**(Self-Correction/Review: The summary is structured as requested, starts with the required orienting paragraph and single-sentence gist.

Improvements for AI systems

Here are specific improvements for AI systems based on this scientific paper, along with what those improved AI systems could achieve:

  1. The core improvement lies in integrating a real-time, physics-informed sensing modality (electrical bioimpedance) into robotic surgical workflows for automated safety checks.

  2. The proposed system can be used to develop an AI module that processes high-frequency electrical signals from intraoperative tools (like a drill bit) during bone penetration to identify the precise moment of tissue transition (e.g., cortical bone to cerebrospinal fluid/spinal canal contents).

  3. This improved AI system could perform the following specific functions:

Ease of Use & Safety: It can function as an autonomous, real-time breach prevention watchdog integrated directly into a robotic pedicle drilling system.

Precision Detection: It can detect abrupt changes in electrical conductivity that correspond to the mechanical event of a breach (e.g., cortical bone perforation or lateral canal entry), providing detection capabilities superior to purely visual or pre-operative imaging registration.

Proactive Intervention: By utilizing the adaptive thresholding algorithm (Algorithm 1), the AI can trigger an immediate, real-time halt signal to the drilling mechanism, preventing catastrophic errors before they occur (stopping drilling before perforation).

Reduced Data Load: It eliminates the need for continuous, high-resolution intraoperative imaging (like fluoroscopy or CT) during the critical drilling phase by relying solely on a low-cost, integrated tool signal.

Automation of Safety Checks: The system can automatically grade the success of a drilling attempt in real-time based on conductivity profiles, providing immediate feedback to the surgeon regarding whether the trajectory is safe (e.g., confirming Grade "A or B" status).

Complementary Navigation: The AI output (breach flags) can be fed back into existing navigation systems to dynamically adjust trajectories mid-procedure if a potential breach is detected along the current path.

Abstract

Purpose: Pedicle screw placement is technically demanding in scoliosis treatment. High precision is required due to limited visibility, anatomical variability, and the risk of complications. Although robotic systems assist CT-based planning and execution, they still rely on ionizing intraoperative imaging and complex registration. This study proposes robotic pedicle drilling with real-time preventive breach detection using electrical bioimpedance sensing. Methods: We developed a robotic approach combined with a pedicle-drilling tool equipped with a proprioceptive electrical bioimpedance sensor developed by SpineGuard. A real-time detection algorithm was designed to analyze the electrical bioimpedance signal during drilling and identify abrupt changes in conductivity associated with potential breaches towards the spinal canal. The method operates without external devices or sensors. Results: The ex vivo experiments showed that the proposed method prevented breaches in 100 of the 51 drilling cases. These findings demonstrate the system's ability to detect potentially hazardous events during drilling and to stop the procedure before. The ex vivo experiments demonstrated that the proposed method prevented breaches in all 51 drilling cases. Conclusions: This work demonstrates the feasibility of robotic pedicle drilling with electrical bioimpedance sensing for real-time breach prevention. Using only the tool signal, the method eliminates the need for external sensing systems and supports safer pedicle screw placement.

Related papers