Bilinear Model Predictive Control Framework of the OncoReach, a Tendon-Driven Steerable Stylet for Brachytherapy
Pejman Kheradmand, Behnam Moradkhani, Mir Masoud Ale Ali, Keith Sowards, Scott R. Silva, Yash Chitalia

TL;DR
This paper introduces a bilinear model predictive control framework for a tendon-driven steerable stylet used in brachytherapy, enabling precise control of needle trajectory within tissue-mimicking phantoms.
Contribution
The paper develops and validates a bilinear MPC approach for a clinically compatible steerable stylet, advancing control methods for standard brachytherapy needles.
Findings
Open-loop validation errors below 2 mm (3% of needle length)
Closed-loop fixed-target tracking error as low as 1.45 mm (1.7%)
Maximum observed error of 8.3 mm (7.8%) in certain bending directions
Abstract
Steerable needles have the potential to improve interstitial brachytherapy by enabling curved trajectories that avoid sensitive anatomical structures. However, existing modeling and control approaches are primarily developed for custom needle designs and are not directly applicable to stylets compatible with commercially available clinical needles. This paper presents a bilinear model predictive control (MPC) framework for a tendon-driven steerable stylet integrated with a standard brachytherapy needle. \textcolor{black}{A geometric bilinear model is formulated with three virtual inputs (an insertion speed and two bending rates) which are mapped to physically realizable inputs consisting of the insertion speed and the associated tendon tensions.} The approach is validated through simulations and physical insertion experiments in tissue-mimicking phantom material using image-based tip…
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