Path tracking control of a steerable catheter in transcatheter cardiology interventions.

PURPOSE: Intracardiac transcatheter interventions allow for reducing trauma and hospitalization stays as compared to standard surgery. In the treatment of mitral regurgitation, the most widely adopted transcatheter approach consists in deploying a clip on the mitral valve leaflets by means of a catheter that is run through veins from a peripheral access to the left atrium. However, precise manipulation of the catheter from outside the body while copying with the path constraints imposed by the vessels remains challenging. METHODS: We proposed a path tracking control framework that provides adequate motion commands to the robotic steerable catheter for autonomous navigation through vascular lumens. The proposed work implements a catheter kinematic model featuring nonholonomic constraints. Relying on the real-time measurements from an electromagnetic sensor and a fiber Bragg grating sensor, a two-level feedback controller was designed to control the catheter. RESULTS: The proposed method was tested in a patient-specific vessel phantom. A median position error between the center line of the vessel and the catheter tip trajectory was found to be below 2 mm, with a maximum error below 3 mm. Statistical testing confirmed that the performance of the proposed method exhibited no significant difference in both free space and the contact region. CONCLUSION: The preliminary in vitro studies presented in this paper showed promising accuracy in navigating the catheter within the vessel. The proposed approach enables autonomous control of a steerable catheter for transcatheter cardiology interventions without the request of calibrating the intuitive parameters or acquiring a training dataset.

Exteriorization of the uterus reduces fetoscopic cannula-induced stress and strain: A finite element model analysis.

OBJECTIVE: To estimate stresses and strains in the uterine wall and fetal membranes with single/multi-port fetoscopy, simulating either a percutaneous access or via exteriorized uterus. STUDY DESIGN: Finite element models based on anatomical dimensions, material properties and boundary conditions were created to simulate stresses, strains and displacements on the uterine wall and fetal membranes during simulated fetal surgery either via exteriorized uterus or percutaneous approach, and with one or three cannulas. Clinically, we measured the anatomical layer thickness and cannula entry point displacement in patients undergoing single port percutaneous fetoscopy. RESULTS: Simulations demonstrate that single port percutaneous fetoscopy increases stress on the fetal membranes (+105%, 128 to 262 kPa) and uterine wall (+115%, 0.89 to 1.9 kPa) compared to exteriorized uterine access. Using three ports increases stress by 110% (148 to 312 kPa) on membranes and 113% (1.08 to 2.3 kPa) on uterine wall. Finite Element Method showed 0.75 cm uterine entry point displacement from the cutaneous entry, while clinical measurements demonstrated displacement of more than double (1.69 ± 0.58 cm), suggesting modeled measurements may be underestimations. CONCLUSION: The stresses and strains on the fetal membranes and uterus are double as high when entering percutaneously than via an exteriorized uterus. Based on what can be clinically measured, this may be an underestimation.

High-fidelity, low-cost synthetic training model for fetoscopic spina bifida repair.

BACKGROUND: Fetoscopic spina bifida repair is increasingly being practiced, but limited skill acquisition poses a barrier to widespread adoption. Extensive training in relevant models, including both ex vivo and in vivo models may help. To address this, a synthetic training model that is affordable, realistic, and that allows skill analysis would be useful. OBJECTIVE: This study aimed to create a high-fidelity model for training in the essential neurosurgical steps of fetoscopic spina bifida repair using synthetic materials. In addition, we aimed to obtain a cheap and easily reproducible model. STUDY DESIGN: We developed a 3-layered, silicon-based model that resemble the anatomic layers of a typical myelomeningocele lesion. It allows for filling of the cyst with fluid and conducting a water tightness test after repair. A compliant silicon ball mimics the uterine cavity and is fixed to a solid 3-dimensional printed base. The fetal back with the lesion (single-use) is placed inside the uterine ball, which is reusable and repairable to allow for practicing port insertion and fixation multiple times. Following cannula insertion, the uterus is insufflated and a clinical fetoscopic or robotic or prototype instruments can be used. Three skilled endoscopic surgeons each did 6 simulated fetoscopic repairs using the surgical steps of an open repair. The primary outcome was surgical success, which was determined by water tightness of the repair, operation time <180 minutes and an Objective Structured Assessment of Technical Skills score of ≥18 of 25. Skill retention was measured using a competence cumulative sum analysis of a composite binary outcome of surgical success. Secondary outcomes were cost and fabrication time of the model. RESULTS: We made a model that can be used to simulate the neurosurgical steps of spina bifida repair, including anatomic details, port insertion, placode release and descent, undermining of skin and muscular layer, and endoscopic suturing. The model was made using reusable 3-dimensional printed molds and easily accessible materials. The 1-time startup cost was €211, and each single-use, simulated myelomeningocele lesion cost €9.5 in materials and 50 minutes of working time. Two skilled endoscopic surgeons performed 6 simulated, 3-port fetoscopic repairs, whereas a third used a Da Vinci surgical robot. Operation times decreased by more than 30% from the first to the last trial. Six experiments per surgeon did not show an obvious Objective Structured Assessment of Technical Skills score improvement. Competence cumulative sum analysis confirmed competency for each surgeon. CONCLUSION: This high-fidelity, low-cost spina bifida model allows simulated dissection and closure of a myelomeningocele lesion. VIDEO ABSTRACT.

3D vs. 2D simulated fetoscopy for spina bifida repair: a quantitative motion analysis.

3D imaging technology is becoming more prominent every day. However, more validation is needed to understand the actual benefit of 3D versus conventional 2D vision. This work quantitatively investigates whether experts benefit from 3D vision during minimally invasive fetoscopic spina bifida (fSB) repair. A superiority study was designed involving one expert team ([Formula: see text] procedures prior) who performed six 2D and six 3D fSB repair simulations in a high-fidelity animal training model, using 3-port access. The 6D motion of the instruments was recorded. Among the motion metrics are total path length, smoothness, maximum speed, the modified Spectral Arc Length (SPARC), and Log Dimensionless Jerk (LDLJ). The primary clinical outcome is operation time (power 90%, 5% significance) using Sealed Envelope Ltd. 2012. Secondary clinical outcomes are water tightness of the repair, CO[Formula: see text] insufflation volume, and OSATS score. Findings show that total path length and LDLJ are considerably different. Operation time during 3D vision was found to be significantly shorter compared to 2D vision ([Formula: see text] vs. [Formula: see text] min; p [Formula: see text] 0.026). These results suggest enhanced performance with 3D vision during interrupted suturing in fetoscopic SBA repair. To confirm these results, a larger-scale follow-up study involving multiple experts and novice surgeons is recommended.

Development and evaluation of robot-assisted ultrasound navigation system for pedicle screw placement: An ex-vivo animal validation.

PURPOSE: Spinal instrumentation with pedicle screw placement (PSP) is an important surgical technique for spinal diseases. Accurate screw trajectory is a prerequisite for PSP. Ultrasound (US) imaging with robot-assisted system forms a non-radiative alternative to provide precise screw trajectory. This study reports on the development and assessment of US navigation for this application. METHODS: A robot-assisted US reconstruction was proposed and an automatic CT-to-US registration algorithm was investigated, allowing the registration of screw trajectories. Experiments were conducted on ex-vivo lamb spines to evaluate system performance. RESULTS: In total, 72 screw trajectories are measured, displaying an average position accuracy of 2.80 ± 1.14 mm and orientation accuracy of 1.38 ± 0.61°. CONCLUSION: The experimental results demonstrate the feasibility of proposed US system. This work, although restricted to laboratory settings, encourages further exploration of the potential of this technology in clinical practice.

State-of-the-Art of Non-Radiative, Non-Visual Spine Sensing with a Focus on Sensing Forces, Vibrations and Bioelectrical Properties: A Systematic Review.

In the research field of robotic spine surgery, there is a big upcoming momentum for surgeon-like autonomous behaviour and surgical accuracy in robotics which goes beyond the standard engineering notions such as geometric precision. The objective of this review is to present an overview of the state of the art in non-visual, non-radiative spine sensing for the enhancement of surgical techniques in robotic automation. It provides a vantage point that facilitates experimentation and guides new research projects to what has not been investigated or integrated in surgical robotics. Studies were identified, selected and processed according to the PRISMA guidelines. Relevant study characteristics that were searched for include the sensor type and measured feature, the surgical action, the tested sample, the method for data analysis and the system's accuracy of state identification. The 6DOF f/t sensor, the microphone and the electromyography probe were the most commonly used sensors in each category, respectively. The performance of the electromyography probe is unsatisfactory in terms of preventing nerve damage as it can only signal after the nerve is disturbed. Feature thresholding and artificial neural networks were the most common decision algorithms for state identification. The fusion of different sensor data in the decision algorithm improved the accuracy of state identification.

Comparison of 2D and autostereoscopic 3D visualization during mixed reality simulation.

PURPOSE: In general minimally invasive surgical procedures, surgeons are tied to 2D visualization, leading to the loss of depth perception. This can lead to large mental load for the surgeons and may be responsible for the long learning curve. To restore the sense of depth, this study investigated the use and benefits of an autostereoscopic (3D) display during a simulated laparoscopic task. METHODS: A mixed reality simulator was developed for comparing the performance of participants while using 2D and autostereoscopic 3D visualization. An electromagnetic sensor was mounted on a physical instrument, and its pose was mapped to the virtual instrument. The virtual scene was developed using Simulation Open Framework Architecture (SOFA). Finite element modeling was used to calculate interaction forces, which were then mapped to visual soft tissue deformation. RESULTS: Ten non-expert participants completed a virtual laparoscopic task, where the subjects were asked to contact eighteen target areas distributed on the surface of the vagina, both in 2D and 3D. Results showed an improvement with 3D vision in task completion time (-16%), total traveled distance (-25%) and errors made (-14%). There was no difference in the average contact forces between the vagina and the instrument. Only the difference in time and forces were shown to be statistically significant. CONCLUSION: Overall, autostereoscopic 3D showed superiority over conventional 2D visualization. The traveled trajectory increased in 2D as the instrument was retracted more between the targets to avoid contact. The 2D and 3D deformation upon contact seems not to contribute differently to force perception. However, the participants only had visual feedback, but no haptic feedback. Therefore, it could be interesting to include haptic feedback in a future study.

Three-dimensional catheter tip force sensing using multi-core fiber Bragg gratings.

Awareness of catheter tip interaction forces is a crucial aspect during cardiac ablation procedures. The most important contact forces are the ones that originate between the catheter tip and the beating cardiac tissue. Clinical studies have shown that effective ablation occurs when contact forces are in the proximity of 0.2 N. Lower contact forces lead to ineffective ablation, while higher contact forces may result in complications such as cardiac perforation. Accurate and high resolution force sensing is therefore indispensable in such critical situations. Accordingly, this work presents the development of a unique and novel catheter tip force sensor utilizing a multi-core fiber with inscribed fiber Bragg gratings. A customizable helical compression spring is designed to serve as the flexural component relaying external forces to the multi-core fiber. The limited number of components, simple construction, and compact nature of the sensor makes it an appealing solution towards clinical translation. An elaborated approach is proposed for the design and dimensioning of the necessary sensor components. The approach also presents a unique method to decouple longitudinal and lateral force measurements. A force sensor prototype and a dedicated calibration setup are developed to experimentally validate the theoretical performance. Results show that the proposed force sensor exhibits 7.4 mN longitudinal resolution, 0.8 mN lateral resolution, 0.72 mN mean longitudinal error, 0.96 mN mean lateral error, a high repeatability, and excellent decoupling between longitudinal and lateral forces.

An Augmented Reality-Based Interaction Scheme for Robotic Pedicle Screw Placement.

Robot-assisted surgery is becoming popular in the operation room (OR) for, e.g., orthopedic surgery (among other surgeries). However, robotic executions related to surgical steps cannot simply rely on preoperative plans. Using pedicle screw placement as an example, extra adjustments are needed to adapt to the intraoperative changes when the preoperative planning is outdated. During surgery, adjusting a surgical plan is non-trivial and typically rather complex since the available interfaces used in current robotic systems are not always intuitive to use. Recently, thanks to technical advancements in head-mounted displays (HMD), augmented reality (AR)-based medical applications are emerging in the OR. The rendered virtual objects can be overlapped with real-world physical objects to offer intuitive displays of the surgical sites and anatomy. Moreover, the potential of combining AR with robotics is even more promising; however, it has not been fully exploited. In this paper, an innovative AR-based robotic approach is proposed and its technical feasibility in simulated pedicle screw placement is demonstrated. An approach for spatial calibration between the robot and HoloLens 2 without using an external 3D tracking system is proposed. The developed system offers an intuitive AR-robot interaction approach between the surgeon and the surgical robot by projecting the current surgical plan to the surgeon for fine-tuning and transferring the updated surgical plan immediately back to the robot side for execution. A series of bench-top experiments were conducted to evaluate system accuracy and human-related errors. A mean calibration error of 3.61 mm was found. The overall target pose error was 3.05 mm in translation and 1.12∘ in orientation. The average execution time for defining a target entry point intraoperatively was 26.56 s. This work offers an intuitive AR-based robotic approach, which could facilitate robotic technology in the OR and boost synergy between AR and robots for other medical applications.

Robotic Endoscope Control Via Autonomous Instrument Tracking.

Many keyhole interventions rely on bi-manual handling of surgical instruments, forcing the main surgeon to rely on a second surgeon to act as a camera assistant. In addition to the burden of excessively involving surgical staff, this may lead to reduced image stability, increased task completion time and sometimes errors due to the monotony of the task. Robotic endoscope holders, controlled by a set of basic instructions, have been proposed as an alternative, but their unnatural handling may increase the cognitive load of the (solo) surgeon, which hinders their clinical acceptance. More seamless integration in the surgical workflow would be achieved if robotic endoscope holders collaborated with the operating surgeon via semantically rich instructions that closely resemble instructions that would otherwise be issued to a human camera assistant, such as "focus on my right-hand instrument." As a proof of concept, this paper presents a novel system that paves the way towards a synergistic interaction between surgeons and robotic endoscope holders. The proposed platform allows the surgeon to perform a bimanual coordination and navigation task, while a robotic arm autonomously performs the endoscope positioning tasks. Within our system, we propose a novel tooltip localization method based on surgical tool segmentation and a novel visual servoing approach that ensures smooth and appropriate motion of the endoscope camera. We validate our vision pipeline and run a user study of this system. The clinical relevance of the study is ensured through the use of a laparoscopic exercise validated by the European Academy of Gynaecological Surgery which involves bi-manual coordination and navigation. Successful application of our proposed system provides a promising starting point towards broader clinical adoption of robotic endoscope holders.

A miniature robotic steerable endoscope for maxillary sinus surgery called PliENT.

In endoscopic maxillary sinus surgery, the maxillary sinus is accessed through the nasal cavity which constitutes a narrow and tortuous pathway. However, surgeons still use rigid endoscopes and rigid, straight or pre-bent instruments for this procedure. Resection of the uncinate process and creation of a medial antrostomy is warranted to access the pathology inside the maxillary sinus and depending on the location of the pathology (lateral, inferior or anterior wall), additional resection of healthy tissue and/or functional structures like the lacrimal duct and/or inferior turbinate is necessary to gain optimal access. In order to avoid this additional resection, a functional single-handed, steerable endoscope for endoscopic maxillary sinus surgery has been designed and built. This endoscope is, to our knowledge, the most slender active steerable endoscope ever reported for maxillary sinus surgery. The performance of the endoscope was validated by two surgeons on a cadaver. An increased field of view was found in comparison to currently used endoscopes. As a direct consequence, a reduced need for resection of healthy tissue was confirmed.

Preclinical implementation of a steerable, Da Vinci Xi® compatible CO2 -laser fibre carrier for transoral robotic surgery (TORS): A cadaveric feasibility study.

INTRODUCTION: Monopolar electrocautery is the most common dissection and coagulation tool during transoral robotic surgery (TORS) but causes significant collateral tissue damage as opposed to CO2 laser. We aimed at combining both modalities in one robotic instrument arm. METHODS: We developed a steerable CO2 -laser fibre carrier serving as an add-on to the existing Endowrist® monopolar spatula of the Da Vinci Xi. Feasibility and safety were assessed in a preclinical setting. RESULTS: One radical tonsillectomy with monopolar cautery and three with the instrument prototype were performed in two cadavers by two surgeons. No serious prototype-related intra-operative difficulties were observed. Safe and efficient switching between energy sources proved possible in all simulated intra-operative bleeding events. Prototype use allowed for the identification of the majority of key anatomical structures and was scored favourably on NASA-TLX questionnaires. DISCUSSION: The reported prototype successfully combines the advantages of CO2 -laser with the advantages of TORS.

FBG-Based Estimation of External Forces Along Flexible Instrument Bodies.

A variety of medical treatment and diagnostic procedures rely on flexible instruments such as catheters and endoscopes to navigate through tortuous and soft anatomies like the vasculature. Knowledge of the interaction forces between these flexible instruments and patient anatomy is extremely valuable. This can aid interventionalists in having improved awareness and decision-making abilities, efficient navigation, and increased procedural safety. In many applications, force interactions are inherently distributed. While knowledge of their locations and magnitudes is highly important, retrieving this information from instruments with conventional dimensions is far from trivial. Robust and reliable methods have not yet been found for this purpose. In this work, we present two new approaches to estimate the location, magnitude, and number of external point and distributed forces applied to flexible and elastic instrument bodies. Both methods employ the knowledge of the instrument's curvature profile. The former is based on piecewise polynomial-based curvature segmentation, whereas the latter on model-based parameter estimation. The proposed methods make use of Cosserat rod theory to model the instrument and provide force estimates at rates over 30 Hz. Experiments on a Nitinol rod embedded with a multi-core fiber, inscribed with fiber Bragg gratings, illustrate the feasibility of the proposed methods with mean force error reaching 7.3% of the maximum applied force, for the point load case. Furthermore, simulations of a rod subjected to two distributed loads with varying magnitudes and locations show a mean force estimation error of 1.6% of the maximum applied force.

Validation of a high-fidelity training model for fetoscopic spina bifida surgery.

Open fetal surgery for spina bifida (SB) is safe and effective yet invasive. The growing interest in fetoscopic SB repair (fSB-repair) prompts the need for appropriate training. We aimed to develop and validate a high-fidelity training model for fSB-repair. fSB-repair was simulated in the abdominal cavity and on the stomach of adult rabbits. Laparoscopic fetal surgeons served either as novices (n = 2) or experts (n = 3) based on their experience. Technical performance was evaluated using competency Cumulative Sum (CUSUM) analysis and the group splitting method. Main outcome measure for CUSUM competency was a composite binary outcome for surgical success, i.e. watertight repair, operation time ≤ 180 min and Objective-Structured-Assessment-of-Technical-Skills (OSATS) score ≥ 18/25. Construct validity was first confirmed since competency levels of novices and experts during their six first cases using both methods were significantly different. Criterion validity was also established as 33 consecutive procedures were needed for novices to reach competency using learning curve CUSUM, which is a number comparable to that of clinical fSB-repair. Finally, we surveyed expert fetal surgeons worldwide to assess face and content validity. Respondents (26/49; 53%) confirmed it with ≥ 71% of scores for overall realism ≥ 4/7 and usefulness ≥ 3/5. We propose to use our high-fidelity model to determine and shorten the learning curve of laparoscopic fetal surgeons and retain operative skills.

A Method Based on 3D Shape Analysis Towards the Design of Flexible Instruments for Endoscopic Maxillary Sinus Surgery.

The emergence of steerable flexible instruments has widened the uptake of minimally invasive surgical techniques. In sinus surgery, such flexible instruments could enable the access to difficult-to-reach anatomical areas. However, design-oriented metrics, essential for the development of steerable flexible instruments for maxillary sinus surgery, are still lacking. This paper proposes a method to process measurements and provides the instrument designer with essential information to develop adapted flexible instruments for limited access surgery. This method was applied to maxillary sinus surgery and showed that an instrument with a diameter smaller than 2.4 mm can be used on more than 72.5% of the subjects' set. Based on the statistical analysis and provided that this flexible instrument can bend up to [Formula: see text] it is estimated that all areas within the maxillary sinus could be reached through a regular antrostomy without resorting to extra incision or tissue removal in 94.9% of the population set. The presented method was partially validated by conducting cadaver experiments.

Deep learning-based fetoscopic mosaicking for field-of-view expansion.

PURPOSE: Fetoscopic laser photocoagulation is a minimally invasive surgical procedure used to treat twin-to-twin transfusion syndrome (TTTS), which involves localization and ablation of abnormal vascular connections on the placenta to regulate the blood flow in both fetuses. This procedure is particularly challenging due to the limited field of view, poor visibility, occasional bleeding, and poor image quality. Fetoscopic mosaicking can help in creating an image with the expanded field of view which could facilitate the clinicians during the TTTS procedure. METHODS: We propose a deep learning-based mosaicking framework for diverse fetoscopic videos captured from different settings such as simulation, phantoms, ex vivo, and in vivo environments. The proposed mosaicking framework extends an existing deep image homography model to handle video data by introducing the controlled data generation and consistent homography estimation modules. Training is performed on a small subset of fetoscopic images which are independent of the testing videos. RESULTS: We perform both quantitative and qualitative evaluations on 5 diverse fetoscopic videos (2400 frames) that captured different environments. To demonstrate the robustness of the proposed framework, a comparison is performed with the existing feature-based and deep image homography methods. CONCLUSION: The proposed mosaicking framework outperformed existing methods and generated meaningful mosaic, while reducing the accumulated drift, even in the presence of visual challenges such as specular highlights, reflection, texture paucity, and low video resolution.

FetNet: a recurrent convolutional network for occlusion identification in fetoscopic videos.

PURPOSE: Fetoscopic laser photocoagulation is a minimally invasive surgery for the treatment of twin-to-twin transfusion syndrome (TTTS). By using a lens/fibre-optic scope, inserted into the amniotic cavity, the abnormal placental vascular anastomoses are identified and ablated to regulate blood flow to both fetuses. Limited field-of-view, occlusions due to fetus presence and low visibility make it difficult to identify all vascular anastomoses. Automatic computer-assisted techniques may provide better understanding of the anatomical structure during surgery for risk-free laser photocoagulation and may facilitate in improving mosaics from fetoscopic videos. METHODS: We propose FetNet, a combined convolutional neural network (CNN) and long short-term memory (LSTM) recurrent neural network architecture for the spatio-temporal identification of fetoscopic events. We adapt an existing CNN architecture for spatial feature extraction and integrated it with the LSTM network for end-to-end spatio-temporal inference. We introduce differential learning rates during the model training to effectively utilising the pre-trained CNN weights. This may support computer-assisted interventions (CAI) during fetoscopic laser photocoagulation. RESULTS: We perform quantitative evaluation of our method using 7 in vivo fetoscopic videos captured from different human TTTS cases. The total duration of these videos was 5551 s (138,780 frames). To test the robustness of the proposed approach, we perform 7-fold cross-validation where each video is treated as a hold-out or test set and training is performed using the remaining videos. CONCLUSION: FetNet achieved superior performance compared to the existing CNN-based methods and provided improved inference because of the spatio-temporal information modelling. Online testing of FetNet, using a Tesla V100-DGXS-32GB GPU, achieved a frame rate of 114 fps. These results show that our method could potentially provide a real-time solution for CAI and automating occlusion and photocoagulation identification during fetoscopic procedures.

Deep learning-based monocular placental pose estimation: towards collaborative robotics in fetoscopy.

PURPOSE: Twin-to-twin transfusion syndrome (TTTS) is a placental defect occurring in monochorionic twin pregnancies. It is associated with high risks of fetal loss and perinatal death. Fetoscopic elective laser ablation (ELA) of placental anastomoses has been established as the most effective therapy for TTTS. Current tools and techniques face limitations in case of more complex ELA cases. Visualization of the entire placental surface and vascular equator; maintaining an adequate distance and a close to perpendicular angle between laser fiber and placental surface are central for the effectiveness of laser ablation and procedural success. Robot-assisted technology could address these challenges, offer enhanced dexterity and ultimately improve the safety and effectiveness of the therapeutic procedures. METHODS: This work proposes a 'minimal' robotic TTTS approach whereby rather than deploying a massive and expensive robotic system, a compact instrument is 'robotised' and endowed with 'robotic' skills so that operators can quickly and efficiently use it. The work reports on automatic placental pose estimation in fetoscopic images. This estimator forms a key building block of a proposed shared-control approach for semi-autonomous fetoscopy. A convolutional neural network (CNN) is trained to predict the relative orientation of the placental surface from a single monocular fetoscope camera image. To overcome the absence of real-life ground-truth placenta pose data, similar to other works in literature (Handa et al. in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2016; Gaidon et al. in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2016; Vercauteren et al. in: Proceedings of the IEEE, 2019) the network is trained with data generated in a simulated environment and an in-silico phantom model. A limited set of coarsely manually labeled samples from real interventions are added to the training dataset to improve domain adaptation. RESULTS: The trained network shows promising results on unseen samples from synthetic, phantom and in vivo patient data. The performance of the network for collaborative control purposes was evaluated in a virtual reality simulator in which the virtual flexible distal tip was autonomously controlled by the neural network. CONCLUSION: Improved alignment was established compared to manual operation for this setting, demonstrating the feasibility to incorporate a CNN-based estimator in a real-time shared control scheme for fetoscopic applications.

Handheld Active Add-On Control Unit for a Cable-Driven Flexible Endoscope.

The instruments currently used by surgeons for in utero treatment of the twin-to-twin transfusion syndrome (TTTS) are rigid or semi-rigid. Their poor dexterity makes this surgical intervention risky and the surgeon's work very complex. This paper proposes the design, assembly and quantitative evaluation of an add-on system intended to be placed on a commercialized cable-driven flexible endoscope. The add-on system is lightweight and easily exchangeable thanks to the McKibben muscle actuators embedded in its system. The combination of the flexible endoscope and the new add-on unit results in an easy controllable flexible instrument with great potential use in TTTS treatment, and especially for regions that are hard to reach with conventional instruments. The fetoscope has a precision of 7.4% over its entire bending range and allows to decrease the maximum planar force on the body wall of 6.15% compared to the original endoscope. The add-on control system also allows a more stable and precise actuation of the endoscope flexible tip.

Design and evaluation of a new bioelectrical impedance sensor for micro-surgery: application to retinal vein cannulation.

PURPOSE: Nowadays, millions of people suffer from retinal vein occlusion, a blind-making eye disease. No curative treatment currently exists for this vascular disorder. However, a promising treatment consists in injecting a thrombolytic drug directly inside the affected retinal vessel. Successfully puncturing miniature vessels with diameters between 50 and 400 [Formula: see text] remains a real challenge, amongst others due to human hand tremor, poor visualisation and depth perception. As a consequence, there is a significant risk of double-puncturing the targeted vessel. Sub-surfacic injection of thrombolytic agent could potentially lead to severe retinal damage. METHODS: A new bio-impedance sensor has been developed to visually display the instant of vessel puncture. The physical working principle of the sensor has been analysed, and a representative electrical model has been derived. Based on this model, the main design parameters were derived to maximise the sensor sensitivity. A detailed characterisation and experimental validation of this concept were conducted. RESULTS: Stable, repeatable and robust impedance measurements were obtained. In an experimental campaign, 35 puncture attempts on ex vivo pig eyes vessels were conducted. A confusion matrix shows a detection accuracy of 80% if there is a puncture, a double puncture or no puncture. The 20% of inaccuracy most probably comes from the limitations of the employed eye model and the experimental conditions. CONCLUSIONS: The developed bio-impedance sensor has shown great promise to help in avoiding double punctures when cannulating retinal veins. Compared to other puncture detection methods, the proposed sensor is simple and therefore potentially more affordable. Future research will include validation in an in vivo situation involving vitreoretinal surgeons.