Targeting Accuracy of Image-Guided Radiosurgery for Intracranial Lesions: A Comparison Across Multiple Linear Accelerator Platforms

PURPOSE: To evaluate the overall positioning accuracy of image-guided intracranial radiosurgery across multiple linear accelerator platforms. METHODS: A computed tomography scan with a slice thickness of 1.0 mm was acquired of an anthropomorphic head phantom in a BrainLAB U-frame mask. The phantom was embedded with three 5-mm diameter tungsten ball bearings, simulating a central, a left, and an anterior cranial lesion. The ball bearings were positioned to radiation isocenter under ExacTrac X-ray or cone-beam computed tomography image guidance on 3 Linacs: (1) ExacTrac X-ray localization on a Novalis Tx; (2) cone-beam computed tomography localization on the Novalis Tx; (3) cone-beam computed tomography localization on a TrueBeam; and (4) cone-beam computed tomography localization on an Edge. Each ball bearing was positioned 5 times to the radiation isocenter with different initial setup error following the 4 image guidance procedures on the 3 Linacs, and the mean (µ) and one standard deviation (σ) of the residual error were compared. RESULTS: Averaged overall 3 ball bearing locations, the vector length of the residual setup error in mm (µ ± σ) was 0.6 ± 0.2, 1.0 ± 0.5, 0.2 ± 0.1, and 0.3 ± 0.1 on ExacTrac X-ray localization on a Novalis Tx, cone-beam computed tomography localization on the Novalis Tx, cone-beam computed tomography localization on a TrueBeam, and cone-beam computed tomography localization on an Edge, with their range in mm being 0.4 to 1.1, 0.4 to 1.9, 0.1 to 0.5, and 0.2 to 0.6, respectively. The congruence between imaging and radiation isocenters in mm was 0.6 ± 0.1, 0.7 ± 0.1, 0.3 ± 0.1, and 0.2 ± 0.1, for the 4 systems, respectively. CONCLUSIONS: Targeting accuracy comparable to frame-based stereotactic radiosurgery can be achieved with image-guided intracranial stereotactic radiosurgery treatment

Accuracy of SRS dose delivery using the TomoTherapy Hi-Art System

Purpose: To quantify the accuracy and precision of both target positioning and dose delivery for intracranial radiosurgery delivered with the TomoTherapy Hi-Art System using a non-invasive immobilization device. Methods: Techniques developed by Vinci et al (2007) were refined for the measurement of dose distributions in each principal plane using a CIRS head phantom. Pieces of Gafchromic EBT2 film were cut and digitized using a template developed by Vinci et al (2007). A plan was created for a 2 cm diameter x 2 cm long cylindrical target in the TomoTherapy treatment planning system (TPS) version 3.2.1. Intentional misalignments of 5 mm in each of the principal directions were applied to the phantom prior to treatment delivery. The MVCT feature of the TomoTherapy Hi-Art system was used to correct for these misalignments, and then the treatment was delivered. Measured dose distributions (film) were registered to the calculated dose distributions (TPS planar dose) and compared. Results: Alignment errors (displacement between the midpoints of the measured and calculated 70% dose points; mean ± standard deviation) were -0.15 ± 0.47 mm (range: -1.97 to 0.8 mm), -0.36 ± 0.56 mm (range: -1.25 to 0.63 mm), and -0.67 ± 0.93 mm (range: -3.04 to 0.90 mm) in the superior-inferior, anterior-posterior, and lateral directions, respectively. Positional errors of the 80% dose points in millimeters were 1.28 ± 0.91 (range: -0.09 to 3.62), -0.02 ± 0.96 (range: -2.24 to 1.72), -0.04 ± 0.62 (range: -1.24 to 1.25), 0.64 ± 0.52 (range: -0.35 to 1.55), 0.30 ± 0.52 (range: -1.57 to 1.28), and 0.60 ± 0.46 (range: -0.26 to 2.39) for the right, left, posterior, anterior, inferior, and superior directions, respectively. Conclusions: Using a non-invasive immobilization device, 1.98 mm dose voxel size, and manual lateral couch positioning, the spatial accuracy of dose delivery with the TomoTherapy Hi•Art System was not within 1 mm as hypothesized

Clinical Validation of an Optical Surface Detection System for Stereotactic Radiosurgery with Frameless Immobilization Device in CNS Tumors

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Radiações em Diagnóstico e Terapia), 2022Stereotactic Radiosurgery (SRS) has been consolidated in recent years as the treatment of choice in selected central nervous system (CNS) tumors. With the introduction of stereotactic approach in clinical practice, accurate immobilization and motion control during treatment becomes fundamental. During SRS treatments, the common practice is to immobilize CNS patients in a cushion molded head support, with specific open-face thermoplastic masks. To verify and correct internal isocenter uncertainties before and during treatment, X-Ray volumetric imaging (XVI) is performed - image guided radiation therapy (IGRT). An alternative to mid‐treatment imaging is optical surface detection (OSD) imaging – a non‐invasive, non‐radiographic form of image guidance – to monitor patient intra-fraction motion. This imaging technique has shown to properly position, accurately monitor, and quantify patient movements throughout the entirety of the treatment – surface guided radiation therapy (SGRT). The aim of this investigation is to test the viability of the implementation of a maskless immobilization approach, using only a vacuum mouthpiece suction system for head fixation in patients with CNS tumors who will undergo SRS treatment under the guidance of an OSD system coupled with 6-Degree of Freedom (6-DOF) robotic couch for submillimeter position correction. This master thesis addresses the five technical performance tests conducted on the Linear Accelerator components – XVI, HexaPOD couch and OSD system in the Radiotherapy Department of Hospital CUF Descobertas. The results obtained lecture the best acquisition orientation to perform image verification; if the HexaPOD couch is correctly calibrated to the XVI radiation isocenter to assure submillimeter corrections; OSD system performance regarding phantom surface detection since some immobilization components can block the signal reading; which coplanar and non-coplanar angles occur most signal inconsistencies due to camera pod occlusion; what is the overall OSD system accuracy and what is the best non-coplanar angle arrangement to perform an SRS treatment with OSD system monitoring

Accuracy of cranial coplanar beam therapy with BrainLAB ExacTrac image guidance

Purpose: To develop a system for measuring 2D dose distributions in the cranium and to use this system to evaluate the accuracy of coplanar conformal therapy using ExacTrac image guidance. Methods: Techniques were developed to measure dose distributions in each principal plane using a CIRS anthropomorphic head phantom with a custom internal film cassette. Sections of EDR2 film were cut, processed, and digitized using custom templates. Spatial and dosimetric accuracy and precision of the film system was assessed. BrainScan was used to plan a coplanar-beam treatment conforming to irradiate a 2-cm diameter x 2-cm cylindrical target. Prior to delivery phantom misalignments were imposed in combinations of ±8-mm offsets in each of the principal directions. ExacTrac X-ray correction was applied until the phantom was within an acceptance criteria of 1mm-1° (first two measurement sessions) or 0.4mm-0.4º (last two measurement sessions). Measured dose distributions on film were registered to the treatment plan and compared. Results: Alignment errors(displacement between midpoints of planned and measured 70% isodose contours), were 0.48±0.40, -0.20±0.44 and 0.45±0.43mm along the Posterior-Anterior, Right-Left and Superior-Inferior directions, respectively, using acceptance criteria of 1mm-1°, and 0.72±0.18, 0.12±0.18 and -0.14±0.34mm, respectively, using acceptance criteria, 0.4mm-0.4°. Positional errors of the 80% isodose line were -0.36±0.43, 0.38±0.38, and 0.03±0.44mm, on the Posterior, Right, and Inferior edges of each profile, respectively, and 0.68 ±0.40, -0.14 ±0.38, and 0.88±0.40mm for the Anterior, Left, and Superior edges, respectively for the 1mm-1° criteria. Using the 0.4mm-0.4° criteria, errors were -0.35±0.23, 0.31± 0.18, and 0.72±0.27mm on the Posterior, Left and Inferior portion of each profile respectively and 1.12±0.18, 0.22±0.23, and 0.35±0.33mm for the Anterior, Left and Superior portions, respectively. Data ranged approximately two standard deviations about the mean. Winston-Lutz tests with errors of approximately 0.5mm correlated with increased Anterior error in three measurement sessions. Conclusions: The ExacTrac system is capable of achieving sub-mm(2σ) accuracy given the alignment errors were small(\u3c0.3mm) when Winston-Lutz results were small(\u3c0.2mm), indicating pre-treatment corrections could be made

Augmented reality (AR) for surgical robotic and autonomous systems: State of the art, challenges, and solutions

Despite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human-robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future

Implementation of safe human robot collaboration for ultrasound guided radiation therapy

This thesis shows that safe human-robot-interaction and Human Robot Collaboration is possible for Ultrasound (US) guided radiotherapy. Via the chosen methodology, all components (US, optical room monitoring and robot) could be linked and integrated and realized in a realistic clinical workflow. US guided radiotherapy offers a complement and alternative to existing image-guided therapy approaches. The real-time capability of US and high soft tissue contrast allow target structures to be tracked and radiation delivery to be modulated. However, Ultrasound guided radiation therapy (USgRT) is not yet clinically established but is still under development, as reliable and safe methods of image acquisition are not yet available. In particular, the loss of contact of the US probe to the patient surface poses a problem for patient movements such as breathing. For this purpose, a Breathing and motion compensation (BaMC) was developed in this work, which together with the safe control of a lightweight robot represents a new development for USgRT. The developed BaMC can be used to control the US probe with contact to the patient. The conducted experiments have confirmed that a steady contact with the patient surface and thus a continuous image acquisition can be ensured by the developed methodology. In addition, the image position in space can be accurately maintained in the submillimeter range. The BaMC seamlessly integrates into a developed clinical workflow. The graphical user interfaces developed for this purpose, as well as direct haptic control with the robot, provide an easy interaction option for the clinical user. The developed autonomous positioning of the transducer represents a good example of the feasibility of the approach. With the help of the user interface, an acoustic plane can be defined and autonomously approached via the robot in a time-efficient and precise manner. The tests carried out show that this methodology is suitable for a wide range of transducer positions. Safety in a human-robot interaction task is essential and requires individually customized concepts. In this work, adequate monitoring mechanisms could be found to ensure both patient and staff safety. In collision tests it could be shown that the implemented detection measures work and that the robot moves into a safe parking position. The forces acting on the patient could thus be pushed well below the limits required by the standard. This work has demonstrated the first important steps towards safe robot-assisted ultrasound imaging, which is not only applicable to USgRT. The developed interfaces provide the basis for further investigations in this field, especially in the area of image recognition, for example to determine the position of the target structure. With the proof of safety of the developed system, first study in human can now follow

Convergence Analysis of an Iterative Targeting Method for Keyhole Robotic Surgery

In surgical procedures, robots can accurately position and orient surgical instruments. Intraoperatively, external sensors can localize the instrument and compute the targeting movement of the robot, based on the transformation between the coordinate frame of the robot and the sensor. This paper addresses the assessment of the robustness of an iterative targeting algorithm in perturbed conditions. Numerical simulations and experiments (with a robot with seven degrees of freedom and an optical tracking system) were performed for computing the maximum error of the rotational part of the calibration matrix, which allows for convergence, as well as the number of required iterations. The algorithm converges up to 50 degrees of error within a large working space. The study confirms the clinical relevance of the method because it can be applied on commercially available robots without modifying the internal controller, thus improving the targeting accuracy and meeting surgical accuracy requirements

Augmented Reality (AR) for Surgical Robotic and Autonomous Systems: State of the Art, Challenges, and Solutions

Despite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human–robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future

Patient Specific Systems for Computer Assisted Robotic Surgery Simulation, Planning, and Navigation

The evolving scenario of surgery: starting from modern surgery, to the birth of medical imaging and the introduction of minimally invasive techniques, has seen in these last years the advent of surgical robotics. These systems, making possible to get through the difficulties of endoscopic surgery, allow an improved surgical performance and a better quality of the intervention. Information technology contributed to this evolution since the beginning of the digital revolution: providing innovative medical imaging devices and computer assisted surgical systems. Afterwards, the progresses in computer graphics brought innovative visualization modalities for medical datasets, and later the birth virtual reality has paved the way for virtual surgery. Although many surgical simulators already exist, there are no patient specific solutions. This thesis presents the development of patient specific software systems for preoperative planning, simulation and intraoperative assistance, designed for robotic surgery: in particular for bimanual robots that are becoming the future of single port interventions. The first software application is a virtual reality simulator for this kind of surgical robots. The system has been designed to validate the initial port placement and the operative workspace for the potential application of this surgical device. Given a bimanual robot with its own geometry and kinematics, and a patient specific 3D virtual anatomy, the surgical simulator allows the surgeon to choose the optimal positioning of the robot and the access port in the abdominal wall. Additionally, it makes possible to evaluate in a virtual environment if a dexterous movability of the robot is achievable, avoiding unwanted collisions with the surrounding anatomy to prevent potential damages in the real surgical procedure. Even if the software has been designed for a specific bimanual surgical robot, it supports any open kinematic chain structure: as far as it can be described in our custom format. The robot capabilities to accomplish specific tasks can be virtually tested using the deformable models: interacting directly with the target virtual organs, trying to avoid unwanted collisions with the surrounding anatomy not involved in the intervention. Moreover, the surgical simulator has been enhanced with algorithms and data structures to integrate biomechanical parameters into virtual deformable models (based on mass-spring-damper network) of target solid organs, in order to properly reproduce the physical behaviour of the patient anatomy during the interactions. The main biomechanical parameters (Young's modulus and density) have been integrated, allowing the automatic tuning of some model network elements, such as: the node mass and the spring stiffness. The spring damping coefficient has been modeled using the Rayleigh approach. Furthermore, the developed method automatically detect the external layer, allowing the usage of both the surface and internal Young's moduli, in order to model the main parts of dense organs: the stroma and the parenchyma. Finally the model can be manually tuned to represent lesion with specific biomechanical properties. Additionally, some software modules of the simulator have been properly extended to be integrated in a patient specific computer guidance system for intraoperative navigation and assistance in robotic single port interventions. This application provides guidance functionalities working in three different modalities: passive as a surgical navigator, assistive as a guide for the single port placement and active as a tutor preventing unwanted collision during the intervention. The simulation system has beed tested by five surgeons: simulating the robot access port placemen, and evaluating the robot movability and workspace inside the patient abdomen. The tested functionalities, rated by expert surgeons, have shown good quality and performance of the simulation. Moreover, the integration of biomechanical parameters into deformable models has beed tested with various material samples. The results have shown a good visual realism ensuring the performance required by an interactive simulation. Finally, the intraoperative navigator has been tested performing a cholecystectomy on a synthetic patient mannequin, in order to evaluate: the intraoperative navigation accuracy, the network communications latency and the overall usability of the system. The tests performed demonstrated the effectiveness and the usability of the software systems developed: encouraging the introduction of the proposed solution in the clinical practice, and the implementation of further improvements. Surgical robotics will be enhanced by an advanced integration of medical images into software systems: allowing the detailed planning of surgical interventions by means of virtual surgery simulation based on patient specific biomechanical parameters. Furthermore, the advanced functionalities offered by these systems, enable surgical robots to improve the intraoperative surgical assistance: benefitting of the knowledge of the virtual patient anatomy