Integrated navigation and visualisation for skull base surgery

Skull base surgery involves the management of tumours located on the underside of the brain and the base of the skull. Skull base tumours are intricately associated with several critical neurovascular structures making surgery challenging and high risk. Vestibular schwannoma (VS) is a benign nerve sheath tumour arising from one of the vestibular nerves and is the commonest pathology encountered in skull base surgery. The goal of modern VS surgery is maximal tumour removal whilst preserving neurological function and maintaining quality of life but despite advanced neurosurgical techniques, facial nerve paralysis remains a potentially devastating complication of this surgery. This thesis describes the development and integration of various advanced navigation and visualisation techniques to increase the precision and accuracy of skull base surgery. A novel Diffusion Magnetic Resonance Imaging (dMRI) acquisition and processing protocol for imaging the facial nerve in patients with VS was developed to improve delineation of facial nerve preoperatively. An automated Artificial Intelligence (AI)-based framework was developed to segment VS from MRI scans. A user-friendly navigation system capable of integrating dMRI and tractography of the facial nerve, 3D tumour segmentation and intraoperative 3D ultrasound was developed and validated using an anatomically-realistic acoustic phantom model of a head including the skull, brain and VS. The optical properties of five types of human brain tumour (meningioma, pituitary adenoma, schwannoma, low- and high-grade glioma) and nine different types of healthy brain tissue were examined across a wavelength spectrum of 400 nm to 800 nm in order to inform the development of an Intraoperative Hypserpectral Imaging (iHSI) system. Finally, functional and technical requirements of an iHSI were established and a prototype system was developed and tested in a first-in-patient study

Cable-driven parallel robot for transoral laser phonosurgery

Transoral laser phonosurgery (TLP) is a common surgical procedure in otolaryngology. Currently, two techniques are commonly used: free beam and fibre delivery. For free beam delivery, in combination with laser scanning techniques, accurate laser pattern scanning can be achieved. However, a line-of-sight to the target is required. A suspension laryngoscope is adopted to create a straight working channel for the scanning laser beam, which could introduce lesions to the patient, and the manipulability and ergonomics are poor. For the fibre delivery approach, a flexible fibre is used to transmit the laser beam, and the distal tip of the laser fibre can be manipulated by a flexible robotic tool. The issues related to the limitation of the line-of-sight can be avoided. However, the laser scanning function is currently lost in this approach, and the performance is inferior to that of the laser scanning technique in the free beam approach. A novel cable-driven parallel robot (CDPR), LaryngoTORS, has been developed for TLP. By using a curved laryngeal blade, a straight suspension laryngoscope will not be necessary to use, which is expected to be less traumatic to the patient. Semi-autonomous free path scanning can be executed, and high precision and high repeatability of the free path can be achieved. The performance has been verified in various bench and ex vivo tests. The technical feasibility of the LaryngoTORS robot for TLP was considered and evaluated in this thesis. The LaryngoTORS robot has demonstrated the potential to offer an acceptable and feasible solution to be used in real-world clinical applications of TLP. Furthermore, the LaryngoTORS robot can combine with fibre-based optical biopsy techniques. Experiments of probe-based confocal laser endomicroscopy (pCLE) and hyperspectral fibre-optic sensing were performed. The LaryngoTORS robot demonstrates the potential to be utilised to apply the fibre-based optical biopsy of the larynx.Open Acces

Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

Objective: Surgical data science is evolving into a research field that aims to observe everything occurring within and around the treatment process to provide situation-aware data-driven assistance. In the context of endoscopic video analysis, the accurate classification of organs in the field of view of the camera proffers a technical challenge. Herein, we propose a new approach to anatomical structure classification and image tagging that features an intrinsic measure of confidence to estimate its own performance with high reliability and which can be applied to both RGB and multispectral imaging (MI) data. Methods: Organ recognition is performed using a superpixel classification strategy based on textural and reflectance information. Classification confidence is estimated by analyzing the dispersion of class probabilities. Assessment of the proposed technology is performed through a comprehensive in vivo study with seven pigs. Results: When applied to image tagging, mean accuracy in our experiments increased from 65% (RGB) and 80% (MI) to 90% (RGB) and 96% (MI) with the confidence measure. Conclusion: Results showed that the confidence measure had a significant influence on the classification accuracy, and MI data are better suited for anatomical structure labeling than RGB data. Significance: This work significantly enhances the state of art in automatic labeling of endoscopic videos by introducing the use of the confidence metric, and by being the first study to use MI data for in vivo laparoscopic tissue classification. The data of our experiments will be released as the first in vivo MI dataset upon publication of this paper.Comment: 7 pages, 6 images, 2 table

OPTICAL NAVIGATION TECHNIQUES FOR MINIMALLY INVASIVE ROBOTIC SURGERIES

Minimally invasive surgery (MIS) involves small incisions in a patient's body, leading to reduced medical risk and shorter hospital stays compared to open surgeries. For these reasons, MIS has experienced increased demand across different types of surgery. MIS sometimes utilizes robotic instruments to complement human surgical manipulation to achieve higher precision than can be obtained with traditional surgeries. Modern surgical robots perform within a master-slave paradigm, in which a robotic slave replicates the control gestures emanating from a master tool manipulated by a human surgeon. Presently, certain human errors due to hand tremors or unintended acts are moderately compensated at the tool manipulation console. However, errors due to robotic vision and display to the surgeon are not equivalently addressed. Current vision capabilities within the master-slave robotic paradigm are supported by perceptual vision through a limited binocular view, which considerably impacts the hand-eye coordination of the surgeon and provides no quantitative geometric localization for robot targeting. These limitations lead to unexpected surgical outcomes, and longer operating times compared to open surgery. To improve vision capabilities within an endoscopic setting, we designed and built several image guided robotic systems, which obtained sub-millimeter accuracy. With this improved accuracy, we developed a corresponding surgical planning method for robotic automation. As a demonstration, we prototyped an autonomous electro-surgical robot that employed quantitative 3D structural reconstruction with near infrared registering and tissue classification methods to localize optimal targeting and suturing points for minimally invasive surgery. Results from validation of the cooperative control and registration between the vision system in a series of in vivo and in vitro experiments are presented and the potential enhancement to autonomous robotic minimally invasive surgery by utilizing our technique will be discussed

Advanced cranial navigation

Neurosurgery is performed with extremely low margins of error. Surgical inaccuracy may have disastrous consequences. The overall aim of this thesis was to improve accuracy in cranial neurosurgical procedures by the application of new technical aids. Two technical methods were evaluated: augmented reality (AR) for surgical navigation (Papers I-II) and the optical technique of diffuse reflectance spectroscopy (DRS) for real-time tissue identification (Papers III-V). Minimally invasive skull-base endoscopy has several potential benefits compared to traditional craniotomy, but approaching the skull base through this route implies that at-risk organs and surgical targets are covered by bone and out of the surgeon’s direct line of sight. In Paper I, a new application for AR-navigated endoscopic skull-base surgery, based on an augmented-reality surgical navigation (ARSN) system, was developed. The accuracy of the system, defined by mean target registration error (TRE), was evaluated and found to be 0.55±0.24 mm, the lowest value reported error in the literature. As a first step toward the development of a cranial application for AR navigation, in Paper II this ARSN system was used to enable insertions of biopsy needles and external ventricular drainages (EVDs). The technical accuracy (i.e., deviation from the target or intended path) and efficacy (i.e., insertion time) were assessed on a 3D-printed realistic, anthropomorphic skull and brain phantom; Thirty cranial biopsies and 10 EVD insertions were performed. Accuracy for biopsy was 0.8±0.43 mm with a median insertion time of 149 (87-233) seconds, and for EVD accuracy was 2.9±0.8 mm at the tip with a median angular deviation of 0.7±0.5° and a median insertion time of 188 (135-400) seconds. Glial tumors grow diffusely in the brain, and patient survival is correlated with the extent of tumor removal. Tumor borders are often invisible. Resection beyond borders as defined by conventional methods may further improve a patient’s prognosis. In Paper III, DRS was evaluated for discrimination between glioma and normal brain tissue ex vivo. DRS spectra and histology were acquired from 22 tumor samples and 9 brain tissue samples retrieved from 30 patients. Sensitivity and specificity for the detection of low-grade gliomas were 82.0% and 82.7%, respectively, with an AUC of 0.91. Acute ischemic stroke caused by large vessel occlusion is treated with endovascular thrombectomy, but treatment failure can occur when clot composition and thrombectomy technique are mismatched. Intra-procedural knowledge of clot composition could guide the choice of treatment modality. In Paper IV, DRS, in vivo, was evaluated for intravascular clot characterization. Three types of clot analogs, red blood cell (RBC)-rich, fibrin-rich and mixed clots, were injected into the external carotids of a domestic pig. An intravascular DRS probe was used for in-situ measurements of clots, blood, and vessel walls, and the spectral data were analyzed. DRS could differentiate clot types, vessel walls, and blood in vivo (p<0,001). The sensitivity and specificity for detection were 73.8% and 98.8% for RBC clots, 100% and 100% for mixed clots, and 80.6% and 97.8% for fibrin clots, respectively. Paper V evaluated DRS for characterization of human clot composition ex vivo: 45 clot units were retrieved from 29 stroke patients and examined with DRS and histopathological evaluation. DRS parameters correlated with clot RBC fraction (R=81, p<0.001) and could be used for the classification of clot type with sensitivity and specificity rates for the detection of RBC-rich clots of 0.722 and 0.846, respectively. Applied in an intravascular probe, DRS may provide intra-procedural information on clot composition to improve endovascular thrombectomy efficiency

A Magnetic Laser Scanner for Endoscopic Microsurgery

Laser scanners increase the quality of the laser microsurgery enabling fast tissue ablation with less thermal damage. Such technology is part of state-of-the-art freebeam surgical laser systems. However, laser scanning has not been incorporated to fiber-based lasers yet. This is a combination that has potential to greatly improve the quality of laser microsurgeries on difficult-to-reach surgical sites. Current fiberbased tissue ablations are performed in contact with the tissue, resulting in excessive thermal damage to healthy tissue in the vicinity of the ablated tissue. This is far from ideal for delicate microsurgeries, which require high-quality tissue incisions without any thermal damage or char formation. However, the possibility to perform scanning laser microsurgery in confined workspaces is restricted by the large size of currently available actuators, which are typically located outside the patient and require direct line-of-sight to the microsurgical area. Thus, it is desired to have the laser scanning feature in an endoscopic system to provide high incision quality in hard-to-reach surgical sites. This thesis aims to introduce a new endoscopic laser scanner to perform 2D position control and high-speed scanning of a fiber-based laser for operation in narrow workspaces. It also presents a technology concept aimed at assisting in incision depth control during soft-tissue microsurgery. The main objective of the work presented in this thesis is to bring the benefits of free-beam lasers to laser-based endoscopic surgery by designing an end-effector module to be placed at the distal tip of a flexible robot arm. To this end, the design and control of a magnetic laser scanner for endoscopic microsurgeries is presented. The system involves an optical fiber, electromagnetic coils, a permanent magnet and optical lenses in a compact system for laser beam deflection. The actuation mechanism is based on the interaction between the electromagnetic field and the permanent magnets. A cantilevered optical fiber is bended with the magnetic field induced by the electromagnetic coils by creating magnetic torque on the permanent magnet. The magnetic laser scanner provides 2D position control and high-speed scanning of the laser beam. The device includes laser focusing optics to allow non-contact incisions. A proof-of-concept device was manufactured and evaluated. It includes four electromagnetic coils and two plano-convex lenses, and has an external diameter of 13 mm. A 4 74 mm2 scanning range was achieved at a 30 mm distance from the scanner tip. Computer-controlled trajectory executions demonstrated repeatable results with 75 m precision for challenging trajectories. Frequency analysis demonstrated stable response up to 33 Hz for 3 dB limit. The system is able to ablate tissue substitutes with a 1940 nm wavelength surgical diode laser. Tablet-based control interface has been developed for intuitive teleoperation. The performance of the proof-of-concept device is analysed through control accuracy and usability studies. Teleoperation user trials consisting in trajectory-following tasks involved 12 subjects. Results demonstrated users could achieve an accuracy of 39 m with the magnetic laser scanner system. For minimally invasive surgeries, it is essential to perform accurate laser position control. Therefore, a model based feed-forward position control of magnetic laser scanner was developed for automated trajectory executions. First, the dynamical model of the system was identified using the electromagnets current (input) and the laser position (output). Then, the identified model was used to perform feedforward control. Validation experiments were performed with different trajectory types, frequencies and amplitudes. Results showed that desired trajectories can be executed in high-speed scanning mode with less than 90 m (1.4 mrad bending angle) accuracy for frequencies up to 15 Hz. State-of-the-art systems do not provide incision depth control, thus the quality of such control relies entirely on the experience and visual perception of the surgeons. In order to provide intuitive incision depth control in endoscopic microsurgeries, the concept of a technology was presented for the automated laser incisions given a desired depth based on a commercial laser scanner. The technology aims at automatically controlling laser incisions based on high-level commands from the surgeon, i.e. desired incision shape, length and depth. A feed-forward controller provides (i) commands to the robotic laser system and (ii) regulates the parameters of the laser source to achieve the desired results. The controller for the incision depth is extracted from experimental data. The required energy density and the number of passes are calculated to reach the targeted depth. Experimental results demonstrate that targeted depths can be achieved with \ub1100 m accuracy, which proves the feasibility of this approach. The proposed technology has the potential to facilitate the surgeon\u2019s control over laser incisions. The magnetic laser scanner enables high-speed laser positioning in narrow and difficult-to-reach workspaces, promising to bring the benefits of scanning laser microsurgery to flexible endoscopic procedures. In addition, the same technology can be potentially used for optical fiber based imaging, enabling for example the creation of new family of scanning endoscopic OCT or hyperspectral probes