Robot-assisted system for non-invasive wide-range flexible eye positioning and tracking in particle radiotherapy.

Particle (proton, carbon ion, or others) radiotherapy for ocular tumors is highly dependent on precise dose distribution, and any misalignment can result in severe complications. The proposed eye positioning and tracking system (EPTS) was designed to non-invasively position eyeballs and is reproducible enough to ensure accurate dose distribution by guiding gaze direction and tracking eye motion. Eye positioning was performed by guiding the gaze direction with separately controlled light sources. Eye tracking was performed by a robotic arm with cameras and a mirror. The cameras attached to its end received images through mirror reflection. To maintain a light weight, certain materials, such as carbon fiber, were utilized where possible. The robotic arm was controlled by a robot operating system. The robotic arm, turntables, and light source were actively and remotely controlled in real time. The videos captured by the cameras could be annotated, saved, and loaded into software. The available range of gaze guidance is 360° (azimuth). Weighing a total of 18.55 kg, the EPTS could be installed or uninstalled in 10 s. The structure, motion, and electromagnetic compatibility were verified via experiments. The EPTS shows some potential due to its non-invasive wide-range flexible eye positioning and tracking, light weight, non-collision with other equipment, and compatibility with CT imaging and dose delivery. The EPTS can also be remotely controlled in real time and offers sufficient reproducibility. This system is expected to have a positive impact on ocular particle radiotherapy.

A Novel Endovascular Robotic System for Treatment of Lower Extremity Peripheral Arterial Disease: First-in-Human Experience.

BACKGROUND: To assess the feasibility and first-in-human experience of a novel endovascular robotic system for treatment of lower extremity peripheral arterial disease (PAD). METHODS: Between November 2021 and January 2022, consecutive patients with obstructive lower extremity PAD and claudication (Rutherford 2-5) with >50% stenosis demonstrated on angiography were enrolled in this study. Lower extremity peripheral arterial intervention was performed using the endovascular robotic system, which consisted of a bedside unit and an interventional console. The primary endpoints were technical success, defined as the successful manipulation of the lower extremity peripheral arterial devices using the robotic system, and safety. The secondary endpoints were clinical success, defined as 50% residual stenosis at the completion of the robot-assisted procedure without major adverse cardiac events and radiation exposure. RESULTS: In total, 5 patients with PAD were enrolled in this study (69.2±6.0 years; 80% men). The novel endovascular robotic system successfully completed the entire procedure of endovascular treatment of lower extremity PAD. Conversion to manual operation, including advancement, retracement, rotation of the guidewires, catheters, sheaths, deployment, and release of the balloons and stent grafts, was not necessary. We achieved the criteria for clinical procedural and technical success in all patients. No deaths, myocardial infarctions, or ruptures occurred in the period up to 30 days after the procedure, and no device-related complications were observed. The robotic system operator had 97.6% less radiation exposure than that at the procedure table, with a mean of 1.40±0.49 µGy. CONCLUSIONS: This study demonstrated the safety and feasibility of the robotic system. The procedure reached technical and clinical performance metrics and resulted in significantly lower radiation exposure to the operators at the console compared with that at the procedure table. CLINICAL IMPACT: There were some reports about several robotic systems used in the peripheral arterial disease, but no robotic system was able to perform entire procedure of endovascular treatment of lower extremity peripheral arterial disease (PAD).To solve this problem, we designed a remote-control novel endovascular robotic system. It was the first robotic system that can perform entire procedure of endovascular treatment of PAD worldwide. A novelty retrieval report about this is provided in the supplementary materials.The robotic system is compatible with all commercial endovascular surgical devices currently available in the market, including guidewires, catheters and stent delivery systems. It can perform all types of motion, such as forward, backward, and rotation to meet the requirements of all types of endovascular procedures. During the operation, the robotic system can perform these operations in a fine-tuned manner, so it is easy to cross the lesions, which is the key factor influencing the success rate of the operation. In addition, the robotic system can effectively reduce the exposure time to radiation, thereby reducing the risk of occupational injury.

A novel endovascular robotic-assisted system for endovascular aortic repair: first-in-human evaluation of practicability and safety.

OBJECTIVES: To assess the practicability and safety of a novel endovascular robotic system for performing endovascular aortic repair in human. METHODS: A prospective observational study was conducted in 2021 with 6 months post-operative follow-up. Patients with aortic aneurysms and clinical indications for elective endovascular aortic repair were enrolled in the study. The novel developed robotic system is applicable for the majority of commercial devices and various types of endovascular surgeries. The primary endpoint was technical success without in-hospital major adverse events. Technical success was defined as the ability of the robotic system to complete all procedural steps based on procedural segments. RESULTS: The first-in-human evaluation of robot-assisted endovascular aortic repair was performed in five patients. The primary endpoint was achieved in all patients (100%). There were no device- or procedure-related complications or no in-hospital major adverse events. The operation time and total blood loss in these cases were equal to those in the manual procedures. The radiation exposure of the surgeon was 96.5% lower than that in the traditional position while the radiation exposure of the patients was not significantly increased. CONCLUSIONS: Early clinical evaluation of the novel endovascular aortic repair in endovascular aortic repair demonstrated practicability, safety, and procedural effectiveness comparable to manual operation. In addition, the total radiation exposure of the operator was significantly lower than that of traditional procedures. CLINICAL RELEVANCE STATEMENT: This study applies a novel approach to perform the endovascular aortic repair in a more accurate and minimal-invasive way and lays the foundation for the perspective automation of the endovascular robotic system, which reflects a new paradigm for endovascular surgery. KEY POINTS: • This study is a first-in-human evaluation of a novel endovascular robotic system for endovascular aortic repair (EVAR). • Our system might reduce the occupational risks associated with manual EVAR and contribute to achieving a higher degree of precision and control. • Early evaluation of the endovascular robotic system demonstrated practicability, safety, and procedural effectiveness comparable to that of manual operation.

Novel Endovascular Interventional Surgical Robotic System Based on Biomimetic Manipulation.

Endovascular therapy has emerged as a crucial therapeutic method for treating vascular diseases. Endovascular surgical robots have been used to enhance endovascular therapy. However, to date, there are no universal endovascular surgical robots that support molds of different types of devices for treating vascular diseases. We developed a novel endovascular surgical robotic system that can independently navigate the intravascular region, advance and retract devices, and deploy stents. This robot has four features: (1) The bionic design of the robot can fully simulate the entire grasping process; (2) the V-shaped relay gripper waived the need to redesign special guidewires and catheters for continuous rotation; (3) the handles designed based on the feedback mechanism can simulate push resistance and reduce iatrogenic damage; and (4) the detachable design of the grippers can reduce cross-infection risk and medical costs. We verified its performance by demonstrating six different types of endovascular surgeries. Early evaluation of the novel endovascular robotic system demonstrated its practicability and safety in endovascular surgeries.

Force feedback controls of multi-gripper robotic endovascular intervention: design, prototype, and experiments.

PURPOSE: Robotic endovascular intervention system (REIS) has the advantages of telemanipulation without radiation damage, precise location, and isolation of hand quiver. However, current REIS lacks a force feedback, which leads to high clinical risks. For the high operational safety of remote operations, this research proposes a force feedback control method for a novel manipulator with multi-grippers and develops a prototype to verify its expected telepresence. METHODS: A high-resolution force sensor is used to acquire and transmit the intervention resistance force to the control handle. When the handle is translated or rotated, a loading mechanism composed of a servomotor, a screw pair, a spring, and friction roller generates the resistance force transmitted to the doctor's hand through the handle. A force/displacement hybrid control and PID control algorithm are used for the smaller feedback force error and lower delay. RESULTS: This manipulator and its control handle are tested in the simulated catheter and vascular cases. The experiments show that force feedback precision can reach 0.05 N and the delay is not more than 50 ms, and the bandwidth is 9 Hz@-3 dB. CONCLUSION: The proposed force feedback method can recreate resistance force from the intervention devices. The control model is valid with higher precision and wide bands, which has laid foundations to the application of REIS in clinic.

A Novel Universal Endovascular Robot for Peripheral Arterial Stent-Assisted Angioplasty: Initial Experimental Results.

BACKGROUND: The bottleneck of the development of endovascular interventional robot is that it cannot fully adapt to commercialized endovascular devices, such as guidewires, catheters, and stents, and cannot complete the entire procedure of endovascular treatment, for instance, stent implantation. The purpose of this study is to evaluate whether the novel universal endovascular interventional robot can adapt to different commercialized endovascular devices and accomplish the entire procedure of endovascular treatment of peripheral vascular disease. METHODS AND MATERIAL: The novel universal endovascular interventional robot consists of 2 components: a master surgeon console and a robotic platform with 4 manipulators. An adult pig was served as the experimental animal. Bilateral iliac artery stent implantation was performed on the pig by the endovascular interventional robot using commercialized guidewires, catheters, and stent delivery systems. RESULTS: The novel universal endovascular interventional robot can adapt to commercialized endovascular devices, and most interventional procedures, such as insertion, withdrawal, and rotating, can be done through remote control. By coordinating multiple manipulators, complex actions such as superselection, crossing action, or implantation of self-expanding bare stent can be realized. The entire procedure took about 50 minutes, and the total exposure time of the surgeon was less than 1 minute. Postoperative angiography showed that the position of the stent grafts was accurate. The procedure was stable without any stent or surgical-related complications. CONCLUSION: The novel universal endovascular interventional robot can realize peripheral arterial stent-assisted angioplasty with commercialized devices. Through the design improvement, the problem related to stent implantation is solved, and the remote operation is realized throughout the endovascular procedure.

A novel SEA-based haptic force feedback master hand controller for robotic endovascular intervention system.

Robotic Endovascular Intervention System (REIS) has been a focused and interesting area in robot-assisted telesurgery. While, haptic feedback is the latest advancing study in interventional robots. Few systems with haptic feedback are commercialized due to accuracy, instantaneity, and the lack of surgeon previous experience on interventional surgery. In this article, a novel haptic force feedback master hand controller system is proposed to solve the problems. A SEA (Series Elastic Actuators)-based mechanism is designed to provide feedback force with high force/torque fidelity, low impedance, and inertia. Also, the handle of the mechanism is similar to the catheter, making the surgeon operate the telesurgery with his experience. The control model of the system is built, and PID algorithms are explored to realize the motion control. PID parameters are optimized for fast response time and stability. The experiments and results demonstrate that the master hand controller system has maximum feedback force relative error of 3%, instantaneity of 0.89 second and tracking performance of 9 Hz frequency 3 dB bandwidth.

A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild cognitive impairment (MCI) is a clinical precursor of AD. Although some treatments can delay its progression, no effective cures are available for AD. Accurate early-stage diagnosis of AD is vital for the prevention and intervention of the disease progression. Hippocampus is one of the first affected brain regions in AD. To help AD diagnosis, the shape and volume of the hippocampus are often measured using structural magnetic resonance imaging (MRI). However, these features encode limited information and may suffer from segmentation errors. Additionally, the extraction of these features is independent of the classification model, which could result in sub-optimal performance. In this study, we propose a multi-model deep learning framework based on convolutional neural network (CNN) for joint automatic hippocampal segmentation and AD classification using structural MRI data. Firstly, a multi-task deep CNN model is constructed for jointly learning hippocampal segmentation and disease classification. Then, we construct a 3D Densely Connected Convolutional Networks (3D DenseNet) to learn features of the 3D patches extracted based on the hippocampal segmentation results for the classification task. Finally, the learned features from the multi-task CNN and DenseNet models are combined to classify disease status. Our method is evaluated on the baseline T1-weighted structural MRI data collected from 97 AD, 233 MCI, 119 Normal Control (NC) subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The proposed method achieves a dice similarity coefficient of 87.0% for hippocampal segmentation. In addition, the proposed method achieves an accuracy of 88.9% and an AUC (area under the ROC curve) of 92.5% for classifying AD vs. NC subjects, and an accuracy of 76.2% and an AUC of 77.5% for classifying MCI vs. NC subjects. Our empirical study also demonstrates that the proposed multi-model method outperforms the single-model methods and several other competing methods.

Design and Performance Evaluation of Real-time Endovascular Interventional Surgical Robotic System with High Accuracy.

BACKGROUND: Endovascular interventional surgery (EIS) is performed under a high radiation environment at the sacrifice of surgeons' health. This paper introduces a novel endovascular interventional surgical robot that aims to reduce radiation to surgeons and physical stress imposed by lead aprons during fluoroscopic X-ray guided catheter intervention. METHODS: The unique mechanical structure allowed the surgeon to manipulate the axial and radial motion of the catheter and guide wire. Four catheter manipulators (to manipulate the catheter and guide wire), and a control console which consists of four joysticks, several buttons and two twist switches (to control the catheter manipulators) were presented. The entire robotic system was established on a master-slave control structure through CAN (Controller Area Network) bus communication, meanwhile, the slave side of this robotic system showed highly accurate control over velocity and displacement with PID controlling method. RESULTS: The robotic system was tested and passed in vitro and animal experiments. Through functionality evaluation, the manipulators were able to complete interventional surgical motion both independently and cooperatively. The robotic surgery was performed successfully in an adult female pig and demonstrated the feasibility of superior mesenteric and common iliac artery stent implantation. The entire robotic system met the clinical requirements of EIS. CONCLUSION: The results show that the system has the ability to imitate the movements of surgeons and to accomplish the axial and radial motions with consistency and high-accuracy.

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

Full-driving soft robotic colonoscope in compliant colon tissue.

Robotic colonoscopy is an efficient examination method for finding malignant tumour in its early stage. This research developed a novel robotic endoscope with 13 mm diameter, 105 mm length and 22.3 g weight. A contact biomechanical model is proposed to increase the locomotion safety and efficiency in the soft tissue. The model shows that the friction difference between the robot and the tissue is a key factor to locomotion capability. A soft, full bellow with excellent compatibility was designed to package the robot body. The bellow increased the static friction and decreased the kinetic friction given the change in the contact state. The bellow is divided into three segments. Each segment is composed of a linear locomotor with micromotor, turbine-worm and wire wrapping-sliding mechanism. The robot is tested in in vivo pig colon, which revealed an excellent locomotion capability and safety in soft tissues.

[Color features of fluorescent image for cervix cancer and its judgments].

Fluorescent image of human mucous can display a special color to demonstrate a cancer at its early stage. This will provide a novel method for early diagnose of the Pathological Changes. This research firstly extracted the color characteristics of the clinic images and then calculated all RGB components in different local areas. Finally, a stability analysis was performed. On the above basis we showed a conclusion that G/R can be used as a judge index for pathologic changes.

A robotic endoscope based on minimally invasive locomotion and wireless techniques for human colon.

BACKGROUND: Traditional endoscopy may cause tissue trauma and discomfort to patients because of the use of relatively long and semi-rigid scopes. METHODS: A wireless robotic endoscope has been designed based on minimally invasive locomotion and wireless techniques for energy, monitoring, and telecontrol. RESULTS: The robotic endoscope can move forward or backward effectively in a smooth synthetic glass tube. The increase of the tube dip angle reduces the relative speed. The robot moves with lower efficiency because of the viscoelasticity of intestinal tissue in in vitro pig colon. The wireless power system can continuously and stably provide a minimum 378 mW energy, which exceeds the maximum system consumption. The video system realizes wireless image transmission at 30 frames per second. Doctors control the robot remotely using a communication frequency of 433 MHz. CONCLUSIONS: The prototype robot shows the possibility of clinical application, but needs further improvement and testing.

A new type of medical micropump for an endoscopic robot.

Researchers have developed a new type of medical micropump for an endoscopic robot, which is driven by a linear actuator based on a direct current (DC) motor. This micropump consists of two active one-way valves and a cylindrical air drum. The overall size of the pump prototype is 12.5 mm in diameter and 56 mm in length. This paper describes the structure of the micropump and linear actuator and analyzes the inflation mechanism of the micropump. The experimental results show that the driving force of the linear actuator can reach up to 2.55 N, which fulfills the need of the micropump. The rated output flow of the micropump is 16 mL/min, which can rapidly supply the gas bag with enough air with minimal noise and vibration.

An earthworm-like robotic endoscope system for human intestine: design, analysis, and experiment.

The existing endoscope brings too much discomfort to patients because its slim and rigid rod is difficult to pass through alpha, gamma loop of the human intestine. A robotic endoscope, as a novel solution, is expected to replace the current endoscope in clinic. A microrobotic endoscope based on wireless power supply was developed in this paper. This robot is mainly composed of a locomotion mechanism, a wireless power supply subsystem, and a communication subsystem. The locomotion mechanism is composed of three liner-driving cells connected with each other through a two-freedom universal joint. The wireless power supply subsystem is composed of a resonance transmit coil to transmit an alternating magnetic field, and a secondary coil to receive the power. Wireless communication system could transmit the image to the monitor, or send the control commands to the robot. The whole robot was packaged in the waterproof bellows. Activating the three driving cells under some rhythm, the robot could creep forward or backward as a worm. A mathematic model is built to express the energy coupling efficiency. Some experiments are performed to test the efficiency and the capability of energy transferring. The results show the wireless energy supply has enough power capacity. The velocity and the navigation ability in a pig intestine were measured in in vitro experiments. The results demonstrated this robot can navigate the intestine easily. In general, the wireless power supply and the wireless communication remove the need of a connecting wire and improve the motion flexibility. Meanwhile, the presented locomotion mechanism and principle have a high reliability and a good adaptability to the in vitro intestine. This research has laid a good foundation for the real application of the robotic endoscope in the future.

Development of a micro-robot for endoscopes based on wireless power transfer.

This paper develops a new prototype of a wireless micro-robot system for endoscopes. The micro-robot we have fabricated and tested is able to propel itself in the intestine of pig. Its autonomous manner is earthworm-like and driven by linear actuators based on a DC motor. Unlike with conventional micro-robot endoscopes, that wireless module is used for communicating and power transfer. The experimental results show that the driving force of the linear actuator can reach up to 2.55 N and the stable supplying power is up to 480 mW DC power for the receiving coil in the proposed system, which all fulfill the need of the micro-robot system. The micro-robot can creep reliably in the small and large intestine of a pig. The video communication module embedded in the head of the micro-robot can capture the inner picture of the intestine and broadcast it to PC in real-time.

[Localization system for electrical capsule based on permanent magnetic field].

Localization system was designed based on analytic equation of permanent magnetic field to localize the swallowing electrical capsule in the gastrointestinal. Algorithm was presented and experiment was made. Two three-axis magnetism sensors were mounted in the capsule. The non linear equations set of sensor's output and capsule's position and attitude was created according to space position and attitude relationship model. The equations set was resolved with numerical method. Comparison between the calculation value and expected value showed that this method was feasible.