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Three-Dimensional Ultrasonic Needle Tip Tracking with a Fiber-Optic Ultrasound Receiver
Published on: August 21, 2018
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Evaluation of Fiber Optic Shape Sensing Models for Minimally Invasive Prostate Needle Procedures Using OFDR Data
Jacynthe Francoeur1, Raman Kashyap2, Samuel Kadoury3
1Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218 USA.
IEEE Sensors Journal
|November 7, 2025
Summary
Linear Interpolation Models (LIM) offer faster, real-time shape sensing for prostate interventions compared to the Lie-Group Theoretic Model (LGTM), especially in ex vivo tissue, guiding clinical strategy.
Area of Science:
- Biomedical Engineering
- Medical Robotics
- Optical Sensing
Background:
- Accurate needle shape sensing is critical for precise prostate interventions.
- Fiber optic shape sensing offers a promising solution for real-time tracking.
Purpose of the Study:
- To systematically evaluate and compare two fiber optic shape sensing models: Linear Interpolation Models (LIM) and Lie-Group Theoretic Model (LGTM).
- To assess model performance across various phantoms and tissue types for prostate needle interventions.
Main Methods:
- Utilized a single needle with a three-fiber optical frequency domain reflectometry (OFDR) sensor.
- Emulated sparse and quasi-distributed sensing configurations using software-defined strain-point selection.
- Evaluated models in gel phantoms, ex vivo tissue, and a cadaveric pig model.
Main Results:
- Friedman test showed significant differences in Root Mean Square Errors (RMSEs) between LIM and LGTM (p < 0.05).
- LIM outperformed LGTM in ex vivo tissue.
- LIM demonstrated over 50-fold faster computation (< 1 ms vs. > 40 ms per shape), enabling real-time application.
Conclusions:
- LIM provides a computationally efficient and accurate shape sensing solution for prostate needle interventions.
- Model selection involves trade-offs between complexity, sensing density, computational load, and tissue variability.
- Findings offer guidance for choosing shape-sensing strategies in clinical and robotic needle-based procedures.
