Image-guided system with miniature robot for precise positioning and targeting in keyhole neurosurgery

NeuroPlan: A Surgical Planning Toolkit for an MRI-Compatible Stereotactic Neurosurgery Robot

The adoption of robotic image-guided surgeries has enabled physicians to perform therapeutic and diagnostic procedures with less invasiveness and higher accuracy. One example is the MRI-guided stereotactic robotic-assisted surgery for conformal brain tumor ablation, where the robot is used to position and orient a thin probe to target a desired region within the brain. Requirements such as the remote center of motion and precise manipulation, impose the use of complex kinematic structures, which result in non-trivial workspaces in these robots. The lack of workspace visualization poses a challenge in selecting valid entry and target points during the surgical planning and navigation stage. In this paper, we present a surgical planning toolkit called the "NeuroPlan" for our MRI-compatible stereotactic neurosurgery robot developed as a module for 3D Slicer software. This toolkit streamlines the current surgical workflow by rendering and overlaying the robot's reachable workspace on the MRI image. It also assists with identifying the optimal entry point by segmenting the cranial burr hole volume and locating its center. We demonstrate the accuracy of the workspace rendering and burr hole parameter detection through both phantom and MR-images acquired from previously conducted animal studies.

Concept description and accuracy evaluation of a moldable surgical targeting system

Purpose: We explain our concept for customization of a guidance instrument, present a prototype, and describe a set of experiments to evaluate its positioning and drilling accuracy.

Methods: Our concept is characterized by the use of bone cement, which enables fixation of a specific configuration for each individual surgical template. This well-established medical product was selected to ensure future intraoperative fabrication of the template under sterile conditions. For customization, a manually operated alignment device is proposed that temporary defines the planned trajectory until the bone cement is hardened. Experiments (n=10) with half-skull phantoms were performed. Analysis of accuracy comprises targeting validations and experiments including drilling in bone substitutes.

Results: The resulting mean positioning error was found to be 0.41±0.30  mm at the level of the target point whereas drilling was possible with a mean accuracy of 0.35±0.30  mm.

Conclusion: We proposed a cost-effective, easy-to-use approach for accurate instrument guidance that enables template fabrication under sterile conditions. The utilization of bone cement was proven to fulfill the demands of an easy, quick, and prospectively intraoperatively doable customization. We could demonstrate sufficient accuracy for many surgical applications, e.g., in neurosurgery. The system in this early development stage already outperforms conventional stereotactic frames and image-guided surgery systems in terms of targeting accuracy.

Electrode Placement Accuracy in Robot-Assisted Asleep Deep Brain Stimulation

Deep brain stimulation (DBS) involves the implantation of electrodes into specific central brain structures for the treatment of Parkinson's disease. Image guidance and robot-assisted techniques have been developed to assist in the accuracy of electrode placement. Traditional DBS is performed with the patient awake and utilizes microelectrode recording for feedback, which yields lengthy operating room times. Asleep DBS procedures use imaging techniques to verify electrode placement. The objective of this study is to demonstrate the validity of an asleep robot-assisted DBS procedure that utilizes intraoperative imaging techniques for precise electrode placement in a large, inclusive cohort. Preoperative magnetic resonance imaging (MRI) was used to plan the surgical procedure for the 128 patients that underwent asleep DBS. During the surgery, robot assistance was used during the implantation of the electrodes. To verify electrode placement, intraoperative CT scans were fused with the preoperative MRIs. The mean radial error of all final electrode placements is 0.85 ± 0.38 mm. MRI-CT fusion error is 0.64 ± 0.40 mm. The average operating room time for bilateral and unilateral implantations are 139.3 ± 34.7 and 115.4 ± 42.1 min, respectively. This study shows the validity of the presented asleep DBS procedure using robot assistance and intraoperative CT verification for accurate electrode placement with shorter operating room times.

A clinically applicable laser-based image-guided system for laparoscopic liver procedures

PURPOSE

Laser range scanners (LRS) allow performing a surface scan without physical contact with the organ, yielding higher registration accuracy for image-guided surgery (IGS) systems. However, the use of LRS-based registration in laparoscopic liver surgery is still limited because current solutions are composed of expensive and bulky equipment which can hardly be integrated in a surgical scenario.

METHODS

In this work, we present a novel LRS-based IGS system for laparoscopic liver procedures. A triangulation process is formulated to compute the 3D coordinates of laser points by using the existing IGS system tracking devices. This allows the use of a compact and cost-effective LRS and therefore facilitates the integration into the laparoscopic setup. The 3D laser points are then reconstructed into a surface to register to the preoperative liver model using a multi-level registration process.

RESULTS

Experimental results show that the proposed system provides submillimeter scanning precision and accuracy comparable to those reported in the literature. Further quantitative analysis shows that the proposed system is able to achieve a patient-to-image registration accuracy, described as target registration error, of [Formula: see text].

CONCLUSIONS

We believe that the presented approach will lead to a faster integration of LRS-based registration techniques in the surgical environment. Further studies will focus on optimizing scanning time and on the respiratory motion compensation.

Robotics in keyhole transcranial endoscope-assisted microsurgery: a critical review of existing systems and proposed specifications for new robotic platforms

BACKGROUND

Over the past decade, advances in image guidance, endoscopy, and tube-shaft instruments have allowed for the further development of keyhole transcranial endoscope-assisted microsurgery, utilizing smaller craniotomies and minimizing exposure and manipulation of unaffected brain tissue. Although such approaches offer the possibility of shorter operating times, reduced morbidity and mortality, and improved long-term outcomes, the technical skills required to perform such surgery are inevitably greater than for traditional open surgical techniques, and they have not been widely adopted by neurosurgeons. Surgical robotics, which has the ability to improve visualization and increase dexterity, therefore has the potential to enhance surgical performance.

OBJECTIVE

To evaluate the role of surgical robots in keyhole transcranial endoscope-assisted microsurgery.

METHODS

The technical challenges faced by surgeons utilizing keyhole craniotomies were reviewed, and a thorough appraisal of presently available robotic systems was performed.

RESULTS

Surgical robotic systems have the potential to incorporate advances in augmented reality, stereoendoscopy, and jointed-wrist instruments, and therefore to significantly impact the field of keyhole neurosurgery. To date, over 30 robotic systems have been applied to neurosurgical procedures. The vast majority of these robots are best described as supervisory controlled, and are designed for stereotactic or image-guided surgery. Few telesurgical robots are suitable for keyhole neurosurgical approaches, and none are in widespread clinical use in the field.

CONCLUSION

New robotic platforms in minimally invasive neurosurgery must possess clear and unambiguous advantages over conventional approaches if they are to achieve significant clinical penetration.

From passive tool holders to microsurgeons: safer, smaller, smarter surgical robots

Within only a few decades from its initial introduction, the field of surgical robotics has evolved into a dynamic and rapidly growing research area with increasing clinical uptake worldwide. Initially introduced for stereotaxic neurosurgery, surgical robots are now involved in an increasing number of procedures, demonstrating their practical clinical potential while propelling further advances in surgical innovations. Emerging platforms are also able to perform complex interventions through only a single-entry incision, and navigate through natural anatomical pathways in a tethered or wireless fashion. New devices facilitate superhuman dexterity and enable the performance of surgical steps that are otherwise impossible. They also allow seamless integration of microimaging techniques at the cellular level, significantly expanding the capabilities of surgeons. This paper provides an overview of the significant achievements in surgical robotics and identifies the current trends and future research directions of the field in making surgical robots safer, smaller, and smarter.

Portable robot for autonomous venipuncture using 3D near infrared image guidance

Venipuncture is pivotal to a wide range of clinical interventions and is consequently the leading cause of medical injury in the U.S. Complications associated with venipuncture are exacerbated in difficult settings, where the rate of success depends heavily on the patient's physiology and the practitioner's experience. In this paper, we describe a device that improves the accuracy and safety of the procedure by autonomously establishing a peripheral line for blood draws and IV's. The device combines a near-infrared imaging system, computer vision software, and a robotically driven needle within a portable shell. The device operates by imaging and mapping in real-time the 3D spatial coordinates of subcutaneous veins in order to direct the needle into a designated vein. We demonstrate proof of concept by assessing imaging performance in humans and cannulation accuracy on an advanced phlebotomy training model.

Accurate multi-robot targeting for keyhole neurosurgery based on external sensor monitoring

Robotics has recently been introduced in surgery to improve intervention accuracy, to reduce invasiveness and to allow new surgical procedures. In this framework, the ROBOCAST system is an optically surveyed multi-robot chain aimed at enhancing the accuracy of surgical probe insertion during keyhole neurosurgery procedures. The system encompasses three robots, connected as a multiple kinematic chain (serial and parallel), totalling 13 degrees of freedom, and it is used to automatically align the probe onto a desired planned trajectory. The probe is then inserted in the brain, towards the planned target, by means of a haptic interface. This paper presents a new iterative targeting approach to be used in surgical robotic navigation, where the multi-robot chain is used to align the surgical probe to the planned pose, and an external sensor is used to decrease the alignment errors. The iterative targeting was tested in an operating room environment using a skull phantom, and the targets were selected on magnetic resonance images. The proposed targeting procedure allows about 0.3 mm to be obtained as the residual median Euclidean distance between the planned and the desired targets, thus satisfying the surgical accuracy requirements (1 mm), due to the resolution of the diffused medical images. The performances proved to be independent of the robot optical sensor calibration accuracy.

Design of a bone-attached parallel robot for percutaneous cochlear implantation

Access to the cochlea requires drilling in close proximity to bone-embedded nerves, blood vessels, and other structures, the violation of which can result in complications for the patient. It has recently been shown that microstereotactic frames can enable an image-guided percutaneous approach, removing reliance on human experience and hand-eye coordination, and reducing trauma. However, constructing current microstereotactic frames disrupts the clinical workflow, requiring multiday intrasurgical manufacturing delays, or an on-call machine shop in or near the hospital. In this paper, we describe a new kind of microsterotactic frame that obviates these delay and infrastructure issues by being repositionable. Inspired by the prior success of bone-attached parallel robots in knee and spinal procedures, we present an automated image-guided microstereotactic frame. Experiments demonstrate a mean accuracy at the cochlea of 0.20 ± 0.07 mm in phantom testing with trajectories taken from a human clinical dataset. We also describe a cadaver experiment evaluating the entire image-guided surgery pipeline, where we achieved an accuracy of 0.38 mm at the cochlea.

Target and Trajectory Clinical Application Accuracy in Neuronavigation

BACKGROUND:

Catheter, needle, and electrode misplacement in navigated neurosurgery can result in ineffective treatment and severe complications.

OBJECTIVE:

To assess the Ommaya ventricular catheter localization accuracy both along the planned trajectory and at the target.

METHODS:

We measured the localization error along the ventricular catheter and on its tip for 15 consecutive patients who underwent insertion of the Ommaya catheter surgery with a commercial neuronavigation system. The preoperative computed tomography/magnetic resonance images and the planned trajectory were aligned with the postoperative computed tomography images showing the Ommaya catheter. The localization errors along the trajectory and at the target were then computed by comparing the preoperative planned trajectory with the actual postoperative catheter position. The measured localization errors were also compared with the error reported by the navigation system.

RESULTS:

The mean localization errors at the target and entry point locations were 5.9 ± 4.3 and 3.3 ± 1.9 mm, respectively. The mean shift and angle between planned and actual trajectories were 1.6 ± 1.9 mm and 3.9 ± 4.7°, respectively. The mean difference between the localization error at the target and entry point was 3.9 ± 3.7 mm. The mean difference between the target localization error and the reported navigation system error was 4.9 ± 4.8 mm.

CONCLUSION:

The catheter localization errors have significant variations at the target and along the insertion trajectory. Trajectory errors may differ significantly from the errors at the target. Moreover, the single registration error number reported by the navigation system does not appropriately reflect the trajectory and target errors and thus should be used with caution to assess the procedure risk.

Robotic and artificial intelligence for keyhole neurosurgery: the ROBOCAST project, a multi-modal autonomous path planner

The robot and sensors integration for computer-assisted surgery and therapy (ROBOCAST) project (FP7-ICT-2007-215190) is co-funded by the European Union within the Seventh Framework Programme in the field of information and communication technologies. The ROBOCAST project focuses on robot- and artificial-intelligence-assisted keyhole neurosurgery (tumour biopsy and local drug delivery along straight or turning paths). The goal of this project is to assist surgeons with a robotic system controlled by an intelligent high-level controller (HLC) able to gather and integrate information from the surgeon, from diagnostic images, and from an array of on-field sensors. The HLC integrates pre-operative and intra-operative diagnostics data and measurements, intelligence augmentation, multiple-robot dexterity, and multiple sensory inputs in a closed-loop cooperating scheme including a smart interface for improved haptic immersion and integration. This paper, after the overall architecture description, focuses on the intelligent trajectory planner based on risk estimation and human criticism. The current status of development is reported, and first tests on the planner are shown by using a real image stack and risk descriptor phantom. The advantages of using a fuzzy risk description are given by the possibility of upgrading the knowledge on-field without the intervention of a knowledge engineer.

Surface-based facial scan registration in neuronavigation procedures: a clinical study

OBJECT

Surface-based registration (SBR) with facial surface scans has been proposed as an alternative for the commonly used fiducial-based registration in image-guided neurosurgery. Recent studies comparing the accuracy of SBR and fiducial-based registration have been based on a few targets located on the head surface rather than inside the brain and have yielded contradictory conclusions. Moreover, no visual feedback is provided with either method to inform the surgeon about the estimated target registration error (TRE) at various target locations. The goals in the present study were: 1) to quantify the SBR error in a clinical setup, 2) to estimate the targeting error for many target locations inside the brain, and 3) to create a map of the estimated TRE values superimposed on a patient's head image.

METHODS

The authors randomly selected 12 patients (8 supine and 4 in a lateral position) who underwent neurosurgery with a commercial navigation system. Intraoperatively, scans of the patients' faces were acquired using a fast 3D surface scanner and aligned with their preoperative MR or CT head image. In the laboratory, the SBR accuracy was measured on the facial zone and estimated at various intracranial target locations. Contours related to different TREs were superimposed on the patient's head image and informed the surgeon about the expected anisotropic error distribution.

RESULTS

The mean surface registration error in the face zone was 0.9 +/- 0.35 mm. The mean estimated TREs for targets located 60, 105, and 150 mm from the facial surface were 2.0, 3.2, and 4.5 mm, respectively. There was no difference in the estimated TRE between the lateral and supine positions. The entire registration procedure, including positioning of the scanner, surface data acquisition, and the registration computation usually required < 5 minutes.

CONCLUSIONS

Surface-based registration accuracy is better in the face and frontal zones, and error increases as the target location lies further from the face. Visualization of the anisotropic TRE distribution may help the surgeon to make clinical decisions. The observed and estimated accuracies and the intraoperative registration time show that SBR using the fast surface scanner is practical and feasible in a clinical setup.

Joystick interfaces are not suitable for robotized endoscope applied to NOTES

BACKGROUND

NOTES has changed the working environment of endoscopy, leading to new difficulties. The limitations of conventional endoscopes call for the development of new platforms. Robotics may be the answer.

MATERIALS AND METHODS

The authors compared human to robotized manipulation of a flexible endoscope into the abdominal cavity, in an animal model. Thirty-two participants were enrolled. Results were analyzed according to the clinical background of the participants: experienced endoscopists, experienced laparoscopists, and medical students. Two single-channel gastroscopes were used. Whereas one was not modified, the other had the handling wheels replaced by motors controlled through a computer and a joystick. A NOTES transgastric approach was used to access the peritoneal cavity. The time to touch previously positioned intra-abdominal numbered plastic targets was recorded 3 times with each endoscope.

RESULTS

Mean time to complete the tasks was significantly shorter using the conventional endoscope (2.71 vs 6.96 minutes, P < .001). When the robotized endoscope was used, the mean times of endoscopists (7.42 minutes), laparoscopists (6.84 minutes), and students (6.77 minutes) were statistically identical. No differences were found between laparoscopists and students in both techniques.

DISCUSSION

Applying robotics to a flexible endoscope fails to enhance ability to move into the abdominal cavity, partly because of the interface. To overcome the limitations of endoscope when performing complex NOTES tasks, robotics may be useful, especially to control the instruments and to stabilize the endoscope itself.

CONCLUSION

Robotized endoscope with joystick interface is not sufficient to enhance immediate intuitiveness of flexible endoscopy applied to NOTES.

MRI-guided laparoscopic and robotic surgery for malignancies

Endoscopic surgery has some clear benefits, but it also has some disadvantages in reducing surgeons' normal dexterity and limiting their ability to deal with difficult situations. Computer-aided surgery has been proposed to overcome some of the drawbacks of traditional minimally invasive surgery. The proposed systems make possible a secure, precise procedure with no limitations on the operator's freedom of movement. Image-guided surgery is a new technical tool in surgical oncology. Interventional magnetic resonance imaging (MRI) has entered a new stage in which computer-based techniques play an expanding role in planning, monitoring, and controlling procedures. MRI-guided surgery not only represents a technical challenge but is a transformation from conventional hand-eye coordination to interactive navigational operations. We have recently developed an MRI-guided robot-assisted interventional surgical system as well as an MRI-compatible endoscope. They allow the performance of precise image-guided interventional therapy and endoscopic surgery. MRI-guided laparoscopic surgery is now feasible for malignancies and will play an important part in the development of minimally invasive therapy.