Proof-of-concept of a robotic-driven photogrammetric scanner for intra-operative knee cartilage repair.

This work presents a proof-of-concept of a robotic-driven intra-operative scanner designed for knee cartilage lesion repair, part of a system for direct in vivo bioprinting. The proposed system is based on a photogrammetric pipeline, which reconstructs the cartilage and lesion surfaces from sets of photographs acquired by a robotic-handled endoscope, and produces 3D grafts for further printing path planning. A validation on a synthetic phantom is presented, showing that, despite the cartilage smooth and featureless surface, the current prototype can accurately reconstruct osteochondral lesions and their surroundings with mean error values of 0.199 ± 0.096 mm but with noticeable concentration on areas with poor lighting or low photographic coverage. The system can also accurately generate grafts for bioprinting, although with a slight tendency to underestimate the actual lesion sizes, producing grafts with coverage errors of -12.2 ± 3.7, -7.9 ± 4.9, and -15.2 ± 3.4% for the medio-lateral, antero-posterior, and craneo-caudal directions, respectively. Improvements in lighting and acquisition for enhancing reconstruction accuracy are planned as future work, as well as integration into a complete bioprinting pipeline and validation with ex vivo phantoms.

Fast and versatile platform for pedicle screw insertion planning.

PURPOSE: Computer-assisted surgical planning methods help to reduce the risks and costs in transpedicular fixation surgeries. However, most methods do not consider the speed and versatility of the planning as factors that improve its overall performance. In this work, we propose a method able to generate surgical plans in minimal time, within the required safety margins and accounting for the surgeon's personal preferences. METHODS: The proposed planning module takes as input a CT image of the patient, initial-guess insertion trajectories provided by the surgeon and a reduced set of parameters, delivering optimal screw sizes and trajectories in a very reduced time frame. RESULTS: The planning results were validated with quantitative metrics and feedback from surgeons. The whole planning pipeline can be executed at an estimated time of less than 1 min per vertebra. The surgeons remarked that the proposed trajectories remained in the safe area of the vertebra, and a Gertzbein-Robbins ranking of A or B was obtained for 95 % of them. CONCLUSIONS: The planning algorithm is safe and fast enough to perform in both pre-operative and intra-operative scenarios. Future steps will include the improvement of the preprocessing efficiency, as well as consideration of the spine's biomechanics and intervertebral rod constraints to improve the performance of the optimisation algorithm.

Surgical planning assistance in keyhole and percutaneous surgery: A systematic review.

Surgical planning of percutaneous interventions has a crucial role to guarantee the success of minimally invasive surgeries. In the last decades, many methods have been proposed to reduce clinician work load related to the planning phase and to augment the information used in the definition of the optimal trajectory. In this survey, we include 113 articles related to computer assisted planning (CAP) methods and validations obtained from a systematic search on three databases. First, a general formulation of the problem is presented, independently from the surgical field involved, and the key steps involved in the development of a CAP solution are detailed. Secondly, we categorized the articles based on the main surgical applications, which have been object of study and we categorize them based on the type of assistance provided to the end-user.

Knowledge-based automated planning system for StereoElectroEncephaloGraphy: A center-based scenario.

Surgical planning for StereoElectroEncephaloGraphy (SEEG) is a complex and patient specific task, where the experience and medical workflow of each institution may influence the final planning choices. To account for this variability, we developed a data-based Computer Assisted Planning (CAP) solution able to exploit the knowledge extracted by past cases. By the analysis of retrospective patients' data sets, our system proposes a pool of trajectories commonly used by the institution, which can be selected to initialize a new patient plan. An optimization framework adapts those to the patient's anatomy by optimizing clinical requirements (e.g. distance from vessel, gray matter recording and insertion angle), and adapting its strategy based on the trajectory type selected.The system has been customized based on the data of a single institution. Two neurosurgeons, working in a high-volume hospital, have validated it by using 15 retrospective patient data sets, with more than 200 trajectories reviewed. Both surgeons considered ~81% of the optimized trajectories as clinically feasible (75% inter-rater reliability). Quantitative comparison of distance from vessels, insertion angle and gray matter recording index showed that the optimized trajectories reached superior or comparable values with respect to the original manual plans. The results suggest that a tailored center-based solution could increase the acceptance rate of the automated trajectories proposed.

White and grey matter development in utero assessed using motion-corrected diffusion tensor imaging and its comparison to ex utero measures.

OBJECTIVE: Fetal brain diffusion tensor imaging (DTI) offers quantitative analysis of the developing brain. The objective was to 1) quantify DTI measures across gestation in a cohort of fetuses without brain abnormalities using full retrospective correction for fetal head motion 2) compare results obtained in utero to those in preterm infants. MATERIALS AND METHODS: Motion-corrected DTI analysis was performed on data sets obtained at 1.5T from 32 fetuses scanned between 21.29 and 37.57 (median 31.86) weeks. Results were compared to 32 preterm infants scanned at 3T between 27.43 and 37.14 (median 33.07) weeks. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were quantified by region of interest measurements and tractography was performed. RESULTS: Fetal DTI was successful in 84% of fetuses for whom there was sufficient data for DTI estimation, and at least one tract could be obtained in 25 cases. Fetal FA values increased and ADC values decreased with age at scan (PLIC FA: p = 0.001; R2 = 0.469; slope = 0.011; splenium FA: p < 0.001; R2 = 0.597; slope = 0.019; thalamus ADC: p = 0.001; R2 = 0.420; slope = - 0.023); similar trends were found in preterm infants. CONCLUSION: This study demonstrates that stable DTI is feasible on fetuses and provides evidence for normative values of diffusion properties that are consistent with aged matched preterm infants.

Experience-based SEEG planning: from retrospective data to automated electrode trajectories suggestions.

StereoElectroEncephaloGraphy (SEEG) is a minimally invasive technique that consists of the insertion of multiple intracranial electrodes to precisely identify the epileptogenic focus. The planning of electrode trajectories is a cumbersome and time-consuming task. Current approaches to support the planning focus on electrode trajectory optimisation based on geometrical constraints but are not helpful to produce an initial electrode set to begin with the planning procedure. In this work, the authors propose a methodology that analyses retrospective planning data and builds a set of average trajectories, representing the practice of a clinical centre, which can be mapped to a new patient to initialise planning procedure. They collected and analysed the data from 75 anonymised patients, obtaining 30 exploratory patterns and 61 mean trajectories in an average brain space. A preliminary validation on a test set showed that they were able to correctly map 90% of those trajectories and, after optimisation, they have comparable or better values than manual trajectories in terms of distance from vessels and insertion angle. Finally, by detecting and analysing similar plans, they were able to identify eight planning strategies, which represent the main tailored sets of trajectories that neurosurgeons used to deal with the different patient cases.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait.

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton.

Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining.

Photogrammetry methods are being used more and more as a 3D technique for large scale metrology applications in industry. Optical targets are placed on an object and images are taken around it, where measuring traceability is provided by precise off-process pre-calibrated digital cameras and scale bars. According to the 2D target image coordinates, target 3D coordinates and camera views are jointly computed. One of the applications of photogrammetry is the measurement of raw part surfaces prior to its machining. For this application, post-process bundle adjustment has usually been adopted for computing the 3D scene. With that approach, a high computation time is observed, leading in practice to time consuming and user dependent iterative review and re-processing procedures until an adequate set of images is taken, limiting its potential for fast, easy-to-use, and precise measurements. In this paper, a new efficient procedure is presented for solving the bundle adjustment problem in portable photogrammetry. In-process bundle computing capability is demonstrated on a consumer grade desktop PC, enabling quasi real time 2D image and 3D scene computing. Additionally, a method for the self-calibration of camera and lens distortion has been integrated into the in-process approach due to its potential for highest precision when using low cost non-specialized digital cameras. Measurement traceability is set only by scale bars available in the measuring scene, avoiding the uncertainty contribution of off-process camera calibration procedures or the use of special purpose calibration artifacts. The developed self-calibrated in-process photogrammetry has been evaluated both in a pilot case scenario and in industrial scenarios for raw part measurement, showing a total in-process computing time typically below 1 s per image up to a maximum of 2 s during the last stages of the computed industrial scenes, along with a relative precision of 1/10,000 (e.g. 0.1 mm error in 1 m) with an error RMS below 0.2 pixels at image plane, ranging at the same performance reported for portable photogrammetry with precise off-process pre-calibrated cameras.

Inverse Kinematics for Upper Limb Compound Movement Estimation in Exoskeleton-Assisted Rehabilitation.

Robot-Assisted Rehabilitation (RAR) is relevant for treating patients affected by nervous system injuries (e.g., stroke and spinal cord injury). The accurate estimation of the joint angles of the patient limbs in RAR is critical to assess the patient improvement. The economical prevalent method to estimate the patient posture in Exoskeleton-based RAR is to approximate the limb joint angles with the ones of the Exoskeleton. This approximation is rough since their kinematic structures differ. Motion capture systems (MOCAPs) can improve the estimations, at the expenses of a considerable overload of the therapy setup. Alternatively, the Extended Inverse Kinematics Posture Estimation (EIKPE) computational method models the limb and Exoskeleton as differing parallel kinematic chains. EIKPE has been tested with single DOF movements of the wrist and elbow joints. This paper presents the assessment of EIKPE with elbow-shoulder compound movements (i.e., object prehension). Ground-truth for estimation assessment is obtained from an optical MOCAP (not intended for the treatment stage). The assessment shows EIKPE rendering a good numerical approximation of the actual posture during the compound movement execution, especially for the shoulder joint angles. This work opens the horizon for clinical studies with patient groups, Exoskeleton models, and movements types.

A review of surgical robots for spinal interventions.

BACKGROUND: This study aimed to describe the state of the art in surgical robotics for spinal interventions, a challenging problem for which robots can provide valuable assistance. METHODS: Multiple electronic databases were searched for articles published during the last 10 years (2002-2012). Results were refined by defined inclusion criteria. RESULTS: A total of 18 different robots were found. Among them, five are commercially available systems: one specifically designed for spinal surgery, one for percutaneous needle-based interventions, two are radiosurgical systems with reported applications on the spine and another is a commercial robot which has been experimentally tested on spinal surgery. The remaining projects are research prototypes which are still on validation stages. CONCLUSIONS: A comprehensive state of the art is presented, showing that spinal robotic surgery is still at an early stage of development but with great potential for improvement.

Volume visualization using a spatially aware mobile display device.

Volume visualization is a difficult three-dimensional task and a significant amount of research is devoted to the development of a suitable computer input device for it. Most of the proposed models use fixed displays, thus rendering extracted slices in orientations unrelated to their real locations within the volume. We present a new device which takes a different approach, as it leaves the volume in a fixed location and demands the user to change his or her posture to explore it from different angles. To implement this, we built a prototype based on a mobile display equipped with sensors that allows it to track its position, which is related to the location of the slice plane within the volume. Therefore, the user can manipulate this plane by displacing and rotating the display, which is a very intuitive method with minimum learning time. Furthermore, the postural changes required to use the device add a new channel of feedback, which effectively helps to reduce the cognitive load imposed on the user. We built a prototype device and tested it with two groups of volunteers who were asked to use it in a medical imaging application. Statistical analysis of the results shows that explorations made with the proposed device were considerably faster with no penalty in precision. We believe that, with further work, the proposed device can be developed into an useful tool for radiology and neurosurgery.