A method for the assessment of time-varying brain shift during navigated epilepsy surgery.

PURPOSE: Image guidance is widely used in neurosurgery. Tracking systems (neuronavigators) allow registering the preoperative image space to the surgical space. The localization accuracy is influenced by technical and clinical factors, such as brain shift. This paper aims at providing quantitative measure of the time-varying brain shift during open epilepsy surgery, and at measuring the pattern of brain deformation with respect to three potentially meaningful parameters: craniotomy area, craniotomy orientation and gravity vector direction in the images reference frame. METHODS: We integrated an image-guided surgery system with 3D Slicer, an open-source package freely available in the Internet. We identified the preoperative position of several cortical features in the image space of 12 patients, inspecting both the multiplanar and the 3D reconstructions. We subsequently repeatedly tracked their position in the surgical space. Therefore, we measured the cortical shift, following its time-related changes and estimating its correlation with gravity and craniotomy normal directions. RESULTS: The mean of the median brain shift amount is 9.64 mm ([Formula: see text] mm). The brain shift amount resulted not correlated with respect to the gravity direction, the craniotomy normal, the angle between the gravity and the craniotomy normal and the craniotomy area. CONCLUSIONS: Our method, which relies on cortex surface 3D measurements, gave results, which are consistent with literature. Our measurements are useful for the neurosurgeon, since they provide a continuous monitoring of the intra-operative sinking or bulking of the brain, giving an estimate of the preoperative images validity versus time.

Enhanced torque-based impedance control to assist brain targeting during open-skull neurosurgery: a feasibility study.

BACKGROUND: Cooperatively-controlled robotic assistance could provide increased positional accuracy and stable and safe tissue targeting tasks during open-skull neurosurgical procedures, which are currently performed free-hand. METHODS: Two enhanced torque-based impedance control approaches, i.e. a variable damping criterion and a force-feedback enhancement control, were proposed in combination with an image-based navigation system. Control systems were evaluated on brain-mimicking phantoms by 13 naive users and 8 neurosurgeons (4 novices and 4 experts). RESULTS: In addition to a 60% reduction of user effort, the combination of the proposed strategies showed comparable performances with respect to state-of-the-art admittance controller, thus satisfying the clinical accuracy requirements (below 1 mm), reducing the hand tremor (by a factor of 10) and the tissue's indentation overshooting (by 80%). CONCLUSION: Although the perceived reliability of the system should be improved, the proposed control was suitable to assist targeting procedures, such as brain cortex stimulation, allowing for accurate, stable and safe contact with soft tissues. Copyright © 2015 John Wiley & Sons, Ltd.

Multi-trajectories automatic planner for StereoElectroEncephaloGraphy (SEEG).

PURPOSE: StereoElectroEncephaloGraphy (SEEG) is done to identify the epileptogenic zone of the brain using several multi-lead electrodes whose positions in the brain are pre-operatively defined. Intracranial hemorrhages due to disruption of blood vessels can cause major complications of this procedure ([Formula: see text]1%). In order to increase the intervention safety, we developed and tested planning tools to assist neurosurgeons in choosing the best trajectory configuration. METHODS: An automated planning method was developed that maximizes the distance of the electrode from the vessels and avoids the sulci as entry points. The angle of the guiding screws is optimized to reduce positioning error. The planner was quantitatively and qualitatively compared with manually computed trajectories on 26 electrodes planned for three patients undergoing SEEG by four neurosurgeons. Quantitative comparison was performed computing for each trajectory using (a) the Euclidean distance from the closest vessel and (b) the incidence angle. RESULTS: Quantitative evaluation shows that automatic planned trajectories are safer in terms of distance from the closest vessel with respect to manually planned trajectories. Qualitative evaluation performed by four neurosurgeons showed that the automatically computed trajectories would have been preferred to manually computed ones in 30% of the cases and were judged good or acceptable in about 86% of the cases. A significant reduction in time required for planning was observed with the automated system (approximately 1/10). CONCLUSION: The automatic SEEG electrode planner satisfied the essential clinical requirements, by providing safe trajectories in an efficient timeframe.

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.

Method for the estimation of a double hinge kinematic model for the trapeziometacarpal joint using MR imaging.

In this paper, we propose a method to estimate the parameters of a double hinge model of the trapeziometacarpal joint (TMC) by MRI-based motion analysis. The model includes two non-orthogonal and non-intersecting rotation axes accounting for flexion-extension (F-E) and adduction-abduction (A-A). We evaluated the quality of the estimated model parameters in the prediction of the relative motion of the first metacarpal bone with respect to the trapezium. As a result, we obtained that: (a) the estimated location and orientation of the F-E and A-A axes were in agreement with previous in vitro studies, (b) the motion of the first metacarpal predicted by the 2 degrees of freedom (2DoF) model exhibits a maximum surface distance error in the range of about 2 mm and (c) four thumb postures at the boundary of the TMC range of motion are sufficient to provide a good estimation of the 2DoF TMC kinematic model and good reproducibility (~1.7 mm) of the real thumb motion at TMC level.

Bi-unicompartmental versus total knee arthroplasty: a matched paired study with early clinical results.

INTRODUCTION: The authors performed a matched paired study between two groups: bi-unicompartmental (Bi-UKR) versus total knee replacements (TKR) for the treatment of isolated bicompartmental tibio-femoral knee arthritis with an asymptomatic patello-femoral joint. The Authors believe that Bi-UKR could achieve comparable outcomes than TKR, but with a real less invasive surgery and maintaining a higher joint function. MATERIALS AND METHODS: A total of 22 patients with bicompartmental tibio-femoral knee arthritis, who underwent Bi-UKR between January 1999 and March 2003, were included in the study (group A). In all the knees the arthritic changes were graded according to the classification of Alback. All patients had an asymptomatic patello-femoral joint. All patients had a varus deformity lower than 8 degrees , a body-mass index lower than 34, no clinical evidence of ACL laxity or flexion deformity and a preoperative range of motion of a least 110 degrees . At a minimum follow-up of 48 months, every single patient in group A was matched with a patient who had undergone a computer assisted TKR between August 1999 and September 2002 (group B). In the Bi-UKR group, in two cases we registered intraoperatively the avulsion of the treated tibial spines, requiring intra-operative internal fixation and without adverse effects on the final outcome. Statistical analysis of the results was performed. RESULTS: At a minimum follow-up of 48 months there were no statistical significant differences in the surgical time while the hospital stay was statistically longer in TKR group. No statistically significant difference was seen for the Knee Society, Functional and GIUM scores between the two groups. Statistically significant better WOMAC Function and Stiffness indexes were registered for the Bi-UKR group. TKR implants were statistically better aligned with all the implants positioned within 4 degrees of an ideal hip-knee-ankle (HKA) angle of 180 degrees . CONCLUSIONS: The results of this 48 months follow-up study suggest that Bi-UKR is a viable option for bicompartmental tibio-femoral arthritis at least as well as TKR but maintaining a higher level of function.

In vivo validation of a realistic kinematic model for the trapezio-metacarpal joint using an optoelectronic system.

This article analyzes a realistic kinematic model of the trapezio-metacarpal (TM) joint in the human thumb that involves two non-orthogonal and non-intersecting rotation axes. The estimation of the model parameters, i.e. the position and orientation of the two axes with respect to an anatomical coordinate system, was carried out by processing the motion of nine retroreflective markers, externally attached to the hand surface, surveyed by a video motion capture system. In order to compute the model parameters, prototypical circumduction movements were processed within an evolutionary optimization approach. Quality and reproducibility in assessing the parameters were demonstrated across multiple testing sessions on 10 healthy subjects (both left and right thumbs), involving the complete removal of all markers and then retesting. Maximum errors of less than 5 mm in the axis position and less than 6 degrees in the orientation were found, respectively. The inter-subject mean distance between the two axes was 4.16 and 4.71 mm for right and left TM joints, respectively. The inter-subject mean relative orientation between the two axes was about 106 and 113 degrees for right and left TM joints, respectively. Generalization properties of the model were evaluated quantitatively on opposition movements in terms of distance between measured and predicted marker positions (maximum error less than 5 mm). The performance of the proposed model compared favorably with the one (maximum error in the range of 7-8 mm) obtained by applying a universal joint model (orthogonal and intersecting axes). The ability of in vivo estimating the parameters of the proposed kinematic model represents a significant improvement for the biomechanical analysis of the hand motion.

Finger kinematic modeling and real-time hand motion estimation.

This paper describes methods and experimental studies concerned with quantitative reconstruction of finger movements in real-time, by means of multi-camera system and 24 surface markers. The approach utilizes a kinematic model of the articulated hand which consists in a hierarchical chain of rigid body segments characterized by 22 functional degrees of freedom and the global roto-translation. This work is focused on the experimental evaluation of a kinematical hand model for biomechanical analysis purposes. From a static posture, a completely automatic calibration procedure, based on anthropometric measures and geometric constraints, computes axes, and centers of rotations which are then utilized as the base of an interactive real-time animation of the hand model. The motion tracking, based on automatic marker labeling and predictive filter, is empowered by introducing constraints from functional finger postures. The validation is performed on four normal subjects through different right-handed motor tasks involving voluntary flexion-extension of the thumb, voluntary abduction-adduction of the thumb, grasping, and finger pointing. Performances are tested in terms of repeatability of angular profiles, model-based ability to predict marker trajectories and tracking success during real-time motion estimation. Results show intra-subject repeatability of the model calibration both to different postures and to re-marking in the range of 0.5 and 2 mm, respectively. Kinematic estimation proves satisfactory in terms of prediction capability (index finger: maximum RMSE 2.02 mm; thumb: maximum RMSE 3.25 mm) and motion reproducibility (R (2) coefficients--index finger: 0.96, thumb: 0.94). During fast grasping sequence (60 Hz), the percentage of residual marker occlusions is less than 1% and processing and visualization frequency of 50 Hz confirms the real-time capability of the motion estimation system.

Automatic extraction of the mid-facial plane for cranio-maxillofacial surgery planning.

Recently developed computer applications provide tools for planning cranio-maxillofacial interventions based on 3-dimensional (3D) virtual models of the patient's skull obtained from computed-tomography (CT) scans. Precise knowledge of the location of the mid-facial plane is important for the assessment of deformities and for planning reconstructive procedures. In this work, a new method is presented to automatically compute the mid-facial plane on the basis of a surface model of the facial skeleton obtained from CT. The method matches homologous surface areas selected by the user on the left and right facial side using an iterative closest point optimization. The symmetry plane which best approximates this matching transformation is then computed. This new automatic method was evaluated in an experimental study. The study included experienced and inexperienced clinicians defining the symmetry plane by a selection of landmarks. This manual definition was systematically compared with the definition resulting from the new automatic method: Quality of the symmetry planes was evaluated by their ability to match homologous areas of the face. Results show that the new automatic method is reliable and leads to significantly higher accuracy than the manual method when performed by inexperienced clinicians. In addition, the method performs equally well in difficult trauma situations, where key landmarks are unreliable or absent.

A neural network based method for optical patient set-up registration in breast radiotherapy.

Patient set-up optimization is required in breast-cancer radiotherapy to fill the accuracy gap between personalized treatment planning and uncertainties in the irradiation set-up. Opto-electronic systems allow implementing automatic procedures to minimize the positional mismatches of light-reflecting markers located on the patient surface with respect to a corresponding reference configuration. The same systems are used to detect the position of the irradiated body surface by means of laser spots; patient set-up is then corrected by matching the control points onto a CT based reference model through surface registration algorithms. In this paper, a non-deterministic approach based on Artificial Neural Networks is proposed for the automatic, real-time verification of geometrical set-up of breast irradiation. Unlike iterative surface registration methods, no passive fiducials are used and true real-time performance is obtained. Moreover, the non-deterministic modeling performed by the neural algorithm minimizes sensitivity to intra-fractional and inter-fractional non-rigid motion of the breast. The technique was validated through simulated activities by using reference CT data acquired on four subjects. Results show that the procedure is able to detect and reduce simulated set-up errors and revealed high reliability in patient position correction, even when the surface deformation is included in testing conditions.