Validation of a novel robotic-assisted partial nephrectomy surgical training model

What's known on the subject? and What does the study add? One area of particular growth for robotic surgery has been partial nephrectomy. Despite a perceived notion that robotic-assisted partial nephrectomy is more easily adaptable compared to laparoscopic partial nephrectomy, there is nonetheless an associated learning curve. Validated training models with a corresponding assessment method for robotic-assisted partial nephrectomy were previously unavailable. We have designed and validated a RAPN surgical model appropriate for resident and fellow training.

Non-robotic thoracoscopic internal mammary artery preparation in the pig. A training model

Notwithstanding non-robotic, thoracoscopic preparation of the internal mammary artery (IMA) is a difficult surgical task, an appropriate experimental training model is lacking. We evaluated the young domestic pig for this purpose. Four domestic female pigs (30-40 kg body weight) were used for this study. Bilateral thoracoscopic preparation of the IMA was carried out under continuous, pressure controlled CO(2) insufflation. A 30 degrees rigid thoracoscope was inserted through a 10-mm port in the 5th/6th intercostal space (ICS) dorsally to the posterior axillary line. The dissection instrument (Ultracision Harmonic Scalpel) was inserted (5-mm port) in the 7th ICS at the posterior axillary line and the endo-forceps (5-mm port) in the 5th ICS at the posterior axillary line. Thoracoscopic IMA preparation in pig resulted more difficult than in man. A total of seven IMAs were prepared in their full intrathoracic length. A change in the preparation technique (lateral detachment of the endothoracic muscle) improved the safety of the procedure, allowing all four respective IMAs to be prepared safely, while the initial technique ensued an injury for 2 out of 3 vessels. The described young domestic pig model is suitable for experimental training of bilateral thoracoscopic IMA preparation.

Estimation of tool pose based on force-density correlation during robotic drilling

The application of image-guided systems with or without support by surgical robots relies on the accuracy of the navigation process, including patient-to-image registration. The surgeon must carry out the procedure based on the information provided by the navigation system, usually without being able to verify its correctness beyond visual inspection. Misleading surrogate parameters such as the fiducial registration error are often used to describe the success of the registration process, while a lack of methods describing the effects of navigation errors, such as those caused by tracking or calibration, may prevent the application of image guidance in certain accuracy-critical interventions. During minimally invasive mastoidectomy for cochlear implantation, a direct tunnel is drilled from the outside of the mastoid to a target on the cochlea based on registration using landmarks solely on the surface of the skull. Using this methodology, it is impossible to detect if the drill is advancing in the correct direction and that injury of the facial nerve will be avoided. To overcome this problem, a tool localization method based on drilling process information is proposed. The algorithm estimates the pose of a robot-guided surgical tool during a drilling task based on the correlation of the observed axial drilling force and the heterogeneous bone density in the mastoid extracted from 3-D image data. We present here one possible implementation of this method tested on ten tunnels drilled into three human cadaver specimens where an average tool localization accuracy of 0.29 mm was observed.

Feasibility of Using EMG for Early Detection of the Facial Nerve During Robotic Direct Cochlear Access

HYPOTHESIS Facial nerve monitoring can be used synchronous with a high-precision robotic tool as a functional warning to prevent of a collision of the drill bit with the facial nerve during direct cochlear access (DCA). BACKGROUND Minimally invasive direct cochlear access (DCA) aims to eliminate the need for a mastoidectomy by drilling a small tunnel through the facial recess to the cochlea with the aid of stereotactic tool guidance. Because the procedure is performed in a blind manner, structures such as the facial nerve are at risk. Neuromonitoring is a commonly used tool to help surgeons identify the facial nerve (FN) during routine surgical procedures in the mastoid. Recently, neuromonitoring technology was integrated into a commercially available drill system enabling real-time monitoring of the FN. The objective of this study was to determine if this drilling system could be used to warn of an impending collision with the FN during robot-assisted DCA. MATERIALS AND METHODS The sheep was chosen as a suitable model for this study because of its similarity to the human ear anatomy. The same surgical workflow applicable to human patients was performed in the animal model. Bone screws, serving as reference fiducials, were placed in the skull near the ear canal. The sheep head was imaged using a computed tomographic scanner and segmentation of FN, mastoid, and other relevant structures as well as planning of drilling trajectories was carried out using a dedicated software tool. During the actual procedure, a surgical drill system was connected to a nerve monitor and guided by a custom built robot system. As the planned trajectories were drilled, stimulation and EMG response signals were recorded. A postoperative analysis was achieved after each surgery to determine the actual drilled positions. RESULTS Using the calibrated pose synchronized with the EMG signals, the precise relationship between distance to FN and EMG with 3 different stimulation intensities could be determined for 11 different tunnels drilled in 3 different subjects. CONCLUSION From the results, it was determined that the current implementation of the neuromonitoring system lacks sensitivity and repeatability necessary to be used as a warning device in robotic DCA. We hypothesize that this is primarily because of the stimulation pattern achieved using a noninsulated drill as a stimulating probe. Further work is necessary to determine whether specific changes to the design can improve the sensitivity and specificity.

Investigation on the evolution of an indoor robotic localization system based on wireless networks

This work addresses the evolution of an artificial neural network (ANN) to assist in the problem of indoor robotic localization. We investigate the design and building of an autonomous localization system based on information gathered from wireless networks (WN). The article focuses on the evolved ANN, which provides the position of a robot in a space, as in a Cartesian coordinate system, corroborating with the evolutionary robotic research area and showing its practical viability. The proposed system was tested in several experiments, evaluating not only the impact of different evolutionary computation parameters but also the role of the transfer functions on the evolution of the ANN. Results show that slight variations in the parameters lead to significant differences on the evolution process and, therefore, in the accuracy of the robot position.

Augmented environments for the targeting of hepatic lesions during image-guided robotic liver surgery

BACKGROUND Stereotactic navigation technology can enhance guidance during surgery and enable the precise reproduction of planned surgical strategies. Currently, specific systems (such as the CAS-One system) are available for instrument guidance in open liver surgery. This study aims to evaluate the implementation of such a system for the targeting of hepatic tumors during robotic liver surgery. MATERIAL AND METHODS Optical tracking references were attached to one of the robotic instruments and to the robotic endoscopic camera. After instrument and video calibration and patient-to-image registration, a virtual model of the tracked instrument and the available three-dimensional images of the liver were displayed directly within the robotic console, superimposed onto the endoscopic video image. An additional superimposed targeting viewer allowed for the visualization of the target tumor, relative to the tip of the instrument, for an assessment of the distance between the tumor and the tool for the realization of safe resection margins. RESULTS Two cirrhotic patients underwent robotic navigated atypical hepatic resections for hepatocellular carcinoma. The augmented endoscopic view allowed for the definition of an accurate resection margin around the tumor. The overlay of reconstructed three-dimensional models was also used during parenchymal transection for the identification of vascular and biliary structures. Operative times were 240 min in the first case and 300 min in the second. There were no intraoperative complications. CONCLUSIONS The da Vinci Surgical System provided an excellent platform for image-guided liver surgery with a stable optic and instrumentation. Robotic image guidance might improve the surgeon's orientation during the operation and increase accuracy in tumor resection. Further developments of this technological combination are needed to deal with organ deformation during surgery.

Effects of arm training with the robotic device ARMin I in chronic stroke: three single cases

BACKGROUND: Several clinical studies on chronic stroke conducted with end-effector-based robots showed improvement of the motor function in the affected arm. Compared to end-effector-based robots, exoskeleton robots provide improved guidance of the human limb and are better suited to train task-oriented movements with a large range of motions. OBJECTIVE: To test whether intensive arm training with the arm exoskeleton ARMin I is feasible with chronic-stroke patients and whether it improves motor function in the paretic arm. METHODS: Three single cases with chronic hemiparesis resulting from unilateral stroke (at least 14 months after stroke). A-B design with 2 weeks of multiple baseline measurements (A), 8 weeks of training (B) with repetitive measurements and a follow-up measurement 8 weeks after training. The training included shoulder and elbow movements with the robotic rehabilitation device ARMin I. Two subjects had three 1-hour sessions per week and 1 subject received five 1-hour sessions per week. The main outcome measurement was the upper-limb part of the Fugl-Meyer Assessment (FMA). RESULTS: The ARMin training was well tolerated by the patients, and the FMA showed moderate, but significant improvements for all 3 subjects (p < 0.05). Most improvements were maintained 8 weeks after discharge. CONCLUSIONS: This study indicates that intensive training with an arm exoskeleton is feasible with chronic-stroke patients. Moderate improvements were found in all 3 subjects, thus further clinical investigations are justified.

Learning curve for robotic-assisted laparoscopic colorectal surgery.

BACKGROUND: Robotic-assisted laparoscopic surgery (RALS) is evolving as an important surgical approach in the field of colorectal surgery. We aimed to evaluate the learning curve for RALS procedures involving resections of the rectum and rectosigmoid. METHODS: A series of 50 consecutive RALS procedures were performed between August 2008 and September 2009. Data were entered into a retrospective database and later abstracted for analysis. The surgical procedures included abdominoperineal resection (APR), anterior rectosigmoidectomy (AR), low anterior resection (LAR), and rectopexy (RP). Demographic data and intraoperative parameters including docking time (DT), surgeon console time (SCT), and total operative time (OT) were analyzed. The learning curve was evaluated using the cumulative sum (CUSUM) method. RESULTS: The procedures performed for 50 patients (54% male) included 25 AR (50%), 15 LAR (30%), 6 APR (12%), and 4 RP (8%). The mean age of the patients was 54.4 years, the mean BMI was 27.8 kg/m(2), and the median American Society of Anesthesiologists (ASA) classification was 2. The series had a mean DT of 14 min, a mean SCT of 115.1 min, and a mean OT of 246.1 min. The DT and SCT accounted for 6.3% and 46.8% of the OT, respectively. The SCT learning curve was analyzed. The CUSUM(SCT) learning curve was best modeled as a parabola, with equation CUSUM(SCT) in minutes equal to 0.73 × case number(2) - 31.54 × case number - 107.72 (R = 0.93). The learning curve consisted of three unique phases: phase 1 (the initial 15 cases), phase 2 (the middle 10 cases), and phase 3 (the subsequent cases). Phase 1 represented the initial learning curve, which spanned 15 cases. The phase 2 plateau represented increased competence with the robotic technology. Phase 3 was achieved after 25 cases and represented the mastery phase in which more challenging cases were managed. CONCLUSIONS: The three phases identified with CUSUM analysis of surgeon console time represented characteristic stages of the learning curve for robotic colorectal procedures. The data suggest that the learning phase was achieved after 15 to 25 cases.

Robotic-assisted laparoscopic "salvage" rectopexy for recurrent ileoanal J-pouch prolapse.

Total restorative proctocolectomy with ileal pouch-anal anastomosis (RP/IPAA) has become the standard of care for the surgical treatment of ulcerative colitis. Despite its correlation with an excellent quality of life and favorable long-term outcomes, RP/IPAA has been associated with several complications. Prolapse of the ileoanal pouch is a rare and debilitating complication that should be considered in the differential diagnosis of pouch failure. Limited data exist regarding the prevalence and treatment of pouch prolapse. We present the case of a recurrent J-pouch prolapse treated with a novel minimally invasive "salvage" approach involving a robotic-assisted laparoscopic rectopexy with mesh.

Robotic lobectomy: tips, pitfalls and troubleshooting

The robotic approach in thoracic surgery has rapidly gained popularity in recent years. As with the introduction of any new technology, this warrants not only adaptation of the operative technique itself, but also the evolution of appropriate troubleshooting strategies. A selected number of helpful tips and technical procedural manoeuvres have been compiled to prevent intraoperative problems, as well as to overcome challenging situations that can arise during robotic lobectomies. In robotic surgery, as opposed to open surgery or video-assisted thoracic surgery, these tips serve an important purpose for the operating surgeon, as well as the entire surgical team involved in the procedure. All the assembled recommendations have proved their effectiveness and have been successfully used by the authors in many procedures. Furthermore, these manoeuvres have been found to be of great importance in the training and proctoring of thoracic surgeons, fellows and residents (bed-side assistants). This guide of clearly arranged tips and troubleshooting strategies offers surgeons a useful tool to overcome difficult situations in robotic lobectomy and preferably improve the reproducibility and safety of their procedures.