A Continuum Robotic Cannula with Tip Following Capability and Distal Dexterity for Intracerebral Hemorrhage Evacuation

Evolving Therapeutic Landscape of Intracerebral Hemorrhage: Emerging Cutting-Edge Advancements in Surgical Robots, Regenerative Medicine, and Neurorehabilitation Techniques

Intracerebral hemorrhage (ICH) is the most serious form of stroke and has limited available therapeutic options. As knowledge on ICH rapidly develops, cutting-edge techniques in the fields of surgical robots, regenerative medicine, and neurorehabilitation may revolutionize ICH treatment. However, these new advances still must be translated into clinical practice. In this review, we examined several emerging therapeutic strategies and their major challenges in managing ICH, with a particular focus on innovative therapies involving robot-assisted minimally invasive surgery, stem cell transplantation, in situ neuronal reprogramming, and brain-computer interfaces. Despite the limited expansion of the drug armamentarium for ICH over the past few decades, the judicious selection of more efficacious therapeutic modalities and the exploration of multimodal combination therapies represent opportunities to improve patient prognoses after ICH.

A Novel Extensible Continuum Robot with Growing Motion Capability Inspired by Plant Growth for Path-Following in Transoral Laryngeal Surgery

This article presents a novel extensible continuum robot (ECR) with growing motion capability for improved flexible access in transoral laryngeal procedures. The robot uses an extensible continuum joint with a staggered V-shaped notched structure as the backbone, driven by the pushing and pulling of superelastic Nitinol rods. The notched structure is optimized to achieve a wide range of extension/contraction and bending motion for the continuum joint. The successive and uniform deflection of the notches provides the continuum joint with excellent constant curvature bending characteristics. The bidirectional rod-driven approach expands the robot's extension capabilities with both pushing and pulling operations, and the superelasticity of the driving rods preserves the robot's bending performance. The ECR significantly increases motion dexterity and reachability through its variable length, which facilitates collision-free access to deep lesions by following the anatomy. To further exploit the advantages of the ECR in path-following for flexible access, a growing motion approach inspired by the plant growth process has been proposed to minimize the path deviation error. Characterization experiments are conducted to verify the performances of the proposed ECR. The extension ratio achieves up to 225.92%, and the average distal positioning error and hysteresis error values are 2.87% and 0.51% within the ±120° bending range. Compared with the typical continuum robot with a fixed length, the path-following deviation of this robot is reduced by more than 58.30%, effectively reducing the risk of collision during access. Phantom experiments validate the feasibility of the proposed concept in flexible access procedures.

The Role of ICP Monitoring in Minimally Invasive Surgery for the Management of Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is the second major stroke type, with high incidence, high disability rate, and high mortality. At present, there is no effective and reliable treatment for ICH. As a result, most patients have a poor prognosis. Minimally invasive surgery (MIS) is the fastest treatment method to remove hematoma, which is characterized by less trauma and easy operation. Some studies have confirmed the safety of MIS, but there are still no reports showing that it can significantly improve the functional outcome of ICH patients. Intracranial pressure (ICP) monitoring is considered to be an important part of successful treatment in traumatic brain diseases. By monitoring ICP in real time, keeping stable ICP could help patients with craniocerebral injury get a good prognosis. In the course of MIS treatment of ICH patients, keeping ICP stable may also promote patient recovery. In this review, we will take ICP monitoring as the starting point for an in-depth discussion.

Non-Metallic MR-Guided Concentric Tube Robot for Intracerebral Hemorrhage Evacuation

OBJECTIVE

We aim to develop and evaluate an MR-conditional concentric tube robot for intracerebral hemorrhage (ICH) evacuation.

METHODS

We fabricated the concentric tube robot hardware with plastic tubes and customized pneumatic motors. The robot kinematic model was developed using a discretized piece-wise constant curvature (D-PCC) approach to account for variable curvature along the tube shape, and tube mechanics model was used to compensate torsional deflection of the inner tube. The MR-safe pneumatic motors were controlled using a variable gain PID algorithm. The robot hardware was validated in a series of bench-top and MRI experiments, and the robot's evacuation efficacy was tested in MR-guided phantom trials.

RESULTS

The pneumatic motor was able to achieve a rotational accuracy of 0.32°±0.30° with the proposed variable gain PID control algorithm. The kinematic model provided a positional accuracy of the tube tip of 1.39 ± 0.54 mm. The robot was able to evacuate an initial 38.36 mL clot, leaving a residual hematoma of 8.14 mL after 5 minutes, well below the 15 mL guideline suggesting good post-ICH evacuation clinical outcomes.

CONCLUSION

This robotic platform provides an effective method for MR-guided ICH evacuation.

SIGNIFICANCE

ICH evacuation is feasible under MRI guidance using a plastic concentric tube, indicating potential feasibility in future live animal studies.

Design and Experimental Validation of a 3D-Printed Embedded-Sensing Continuum Robot for Neurosurgery

A minimally-invasive manipulator characterized by hyper-redundant kinematics and embedded sensing modules is presented in this work. The bending angles (tilt and pan) of the robot tip are controlled through tendon-driven actuation; the transmission of the actuation forces to the tip is based on a Bowden-cable solution integrating some channels for optical fibers. The viability of the real-time measurement of the feedback control variables, through optoelectronic acquisition, is evaluated for automated bending of the flexible endoscope and trajectory tracking of the tip angles. Indeed, unlike conventional catheters and cannulae adopted in neurosurgery, the proposed robot can extend the actuation and control of snake-like kinematic chains with embedded sensing solutions, enabling real-time measurement, robust and accurate control of curvature, and tip bending of continuum robots for the manipulation of cannulae and microsurgical instruments in neurosurgical procedures. A prototype of the manipulator with a length of 43 mm and a diameter of 5.5 mm has been realized via 3D printing. Moreover, a multiple regression model has been estimated through a novel experimental setup to predict the tip angles from measured outputs of the optoelectronic modules. The sensing and control performance has also been evaluated during tasks involving tip rotations.

Surgical Robotics for Intracerebral Hemorrhage Treatment: State of the Art and Future Directions

Intracerebral hemorrhage (ICH) is a stroke subtype with high mortality and disability, and there are no proven medical treatments that can improve the functional outcome of ICH patients. Robot-assisted neurosurgery is a significant advancement in the development of minimally invasive surgery for ICH. This review encompasses the latest advances and future directions of surgical robots for ICH. First, three robotic systems for neurosurgery applied to ICH are illustrated. Second, the key technologies of robot-assisted surgery for ICH are introduced in aspects of stereotactic technique and navigation, the puncture instrument, and hematoma evacuation. Finally, the limitations of current surgical robots are summarized, and the possible development direction is discussed, which is named "multisensor fusion and intelligent aspiration control of minimally invasive surgical robot for ICH". It is expected that the new generation of surgical robots for ICH will facilitate quantitative, precise, individualized, standardized treatment strategies for ICH.

Superelastic NiTi Functional Components by High-Precision Laser Powder Bed Fusion Process: The Critical Roles of Energy Density and Minimal Feature Size

Additive manufacturing (AM) was recently developed for building intricate devices in many fields. Especially for laser powder bed fusion (LPBF), its high-precision manufacturing capability and adjustable process parameters are involved in tailoring the performance of functional components. NiTi is well-known as smart material utilized widely in biomedical fields thanks to its unique superelastic and shape-memory performance. However, the properties of NiTi are extremely sensitive to material microstructure, which is mainly determined by process parameters in LPBF. In this work, we choose a unique NiTi intricate component: a robotic cannula tip, in which material superelasticity is a crucial requirement as the optimal object. First, the process window was confirmed by printing thin walls and bulk structures. Then, for optimizing parameters precisely, a Gyroid-type sheet triply periodic minimal-surface (G-TPMS) structure was proposed as the standard test sample. Finally, we verified that when the wall thickness of the G-TPMS structure is smaller than 130 μm, the optimal energy density changes from 167 J/m³ to 140 J/m³ owing to the lower cooling rate of thinner walls. To sum up, this work puts forward a novel process optimization methodology and provides the processing guidelines for intricate NiTi components by LPBF.

Surgical Continuum Manipulator Control Using Multiagent Team Deep Q Learning

Continuum manipulator has shown great potential in surgical applications. The flexibility of the continuum manipulator helps it achieve many complicated surgeries, such as neurosurgery, vascular surgery, abdominal surgery, etc. In this paper, we propose a Team Deep Q learning framework (TDQN) to control a 2-DoF surgical continuum manipulator with four cables, where two cables in a pair form one agent. During the learning process, each agent shares state and reward information with the other one, which namely is centralized learning. Using the shared information, TDQN shows better targeting accuracy than multiagent deep Q learning (MADQN) by verifying on a 2-DoF cable-driven surgical continuum manipulator. The root mean square error during tracking with and without disturbance are 0.82mm and 0.16mm respectively using TDQN, whereas 1.52mm and 0.98mm using MADQN respectively.Clinical Relevance-The proposed TDQN shows a promising future in improving control accuracy under disturbance and maneuverability in robotic-assisted endoscopic surgery.