Lily Chang

Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete Markov model

Minimally invasive surgery (MIS) involves a multidimensional series of tasks requiring a synthesis between visual information and the kinematics and dynamics of the surgical tools. Analysis of these sources of information is a key step in defining objective criteria for characterizing surgical performance. The Blue DRAGON is a new system for acquiring the kinematics and the dynamics of two endoscopic tools synchronized with the endoscopic view of the surgical scene. Modeling the process of MIS using a finite state model [Markov model (MM)] reveals the internal structure of the surgical task and is utilized as one of the key steps in objectively assessing surgical performance. The experimental protocol includes tying an intracorporeal knot in a MIS setup performed on an animal model (pig) by 30 surgeons at different levels of training including expert surgeons. An objective learning curve was defined based on measuring quantitative statistical distance (similarity) between MM of experts and MM of residents at different levels of training. The objective learning curve was similar to that of the subjective performance analysis. The MM proved to be a powerful and compact mathematical model for decomposing a complex task such as laparoscopic suturing. Systems like surgical robots or virtual reality simulators in which the kinematics and the dynamics of the surgical tool are inherently measured may benefit from incorporation of the proposed methodology.

The use of small intestine submucosa in the repair of paraesophageal hernias: Initial observations of a new technique

BACKGROUND Recent reports suggest that when laparoscopy is used to repair paraesophageal hernias recurrence rates reach 20% to 40%. Tension-free hernia closure with synthetic mesh reduces recurrence but occasionally results in esophageal injury. We hypothesized that reinforcement of the hiatal closure with small intestine submucosa (SIS) mesh, in some unusually large hernias, might reduce recurrence rates without causing injury to the esophagus. METHODS From January 2001 to March 2002 we treated 18 large paraesophageal hernias via a laparoscopic approach. In 9 of the largest hernias (one type II and 8 type III, of which 1 was recurrent) the repair was reinforced with SIS mesh (Surgisis, Cook Surgical) and represent the subjects of this study. Nissen fundoplication with gastropexy was performed in all patients. Clinical follow-up ranged from 3 to 16 months (median 8). Every patient was evaluated with barium esophagram or endoscopy or both 1 to 8 months (median 2) postoperatively. RESULTS The presenting symptoms were postprandial pain/fullness (9 of 9), heartburn (4 of 9), anemia (4 of 9), dysphagia (3 of 9), regurgitation (3 of 9), and chest pain (3 of 9). One patient died of a hemorrhagic stroke within 30 days of the operation. Postoperatively, presenting symptoms resolved (83%) or improved (17%) in each of the remaining 8 patients. One patient required endoscopic dilation for mild dysphagia. Seven of 8 patients had a normal barium esophagram without evidence of hernia. One morbidly obese (body mass index = 47) patient had a small (2 cm) sliding hiatal hernia postoperatively. There were no other complications, and specifically no perforations or mesh erosions. CONCLUSIONS These observations suggest that the use of SIS in the repair of paraesophageal hernias is safe and may reduce recurrence. Longer follow-up and a randomized study are needed to validate these results.

The BlueDRAGON - a system for measuring the kinematics and dynamics of minimally invasive surgical tools in-vivo

Minimally invasive surgery involves a multidimensional series of tasks requiring a synthesis between visual information and the kinematics and dynamics of the surgical tools. Analysis of these sources of information is a key step in mastering MIS, but may also be used to define objective criteria for characterizing surgical performance. The BlueDRAGON is a new system for acquiring the kinematics and dynamics of two endoscopic tools synchronized with the visual view of the surgical scene. It includes two four-bar passive mechanisms equipped with position and force torque sensors for measuring the positions and orientations of the two endoscopic tools along with the forces and torques (F/T) applied by the surgeons hands. The methodology of decomposing the surgical task is based on a fully connected, 28 finite-states Markov model where each states corresponded to a fundamental tool/tissue interaction based on the tool kinematics and associated with unique F/T signatures. The experimental protocol includes seven MIS tasks performed on an animal model by 30 surgeons at different levels of their residency training including expert surgeons. From the preliminary analysis of these data, the major differences between residents at different skill levels are discussed. Systems like surgical robots or virtual reality simulators that inherently measure the kinematics and dynamics of the surgical tool may benefit from inclusion of the proposed methodology for the analysis of efficacy and objective evaluation of surgical skills during training.

The blue DRAGON - A system for monitoring the kinematics and the dynamics of endoscopic tools in minimally invasive surgery for objective laparoscopic skill assessment

Minimally invasive surgeiy (MIS) involves a multi-dimensional series of tasks requiring a synthesis between visual information and the kinematics and dynamics of the surgical tools. Analysis of these sources of information is a key step in mastering MIS surgery but may also be used to define objective criteria for characterizing surgical performance. The BIueDRAGON is a new system for acquiring the kinematics and the dynamics of two endoscopic tools along with the visual view of the surgical scene. It includes two four-bar mechanisms equipped with position and force torque sensors for measuring the positions and the orientations (P/O) of two endoscopic tools along with the forces and torques applied by the surgeons hands. The methodology of decomposing the surgical task is based on a fully connected, finite-states (28 states) Markov model where each states corresponded to a fundamental tool/tissue interaction based on the tool kinematics and associated with unique F/T signatures. The experimental protocol included seven MIS tasks performed on an animal model (pig) by 30 surgeons at different levels of their residency training. Preliminary analysis of these data showed that major differences between residents at different skill levels were: (i) the types of tool/tissue interactions being used, (ii) the transitions between tool/tissue interactions being applied by each hand, (iii) time spent while perfonning each tool/tissue interaction, (iv) the overall completion time, and (v) the variable F/T magnitudes being applied by the subjects through the endoscopic tools. Systems like surgical robots or virtual reality simulators that inherently measure the kinematics and the dynamics of the surgical tool may benefit from inclusion of the proposed methodology for analysis of efficacy and objective evaluation of surgical skills during training.

Percutaneous cholecystostomy for acute cholecystitis in veteran patients

BACKGROUND Surgical cholecystostomy has been shown to carry a significantly higher mortality rate at Veterans Administration (VA) hospitals than at non-federal hospitals in the past. METHODS A retrospective outcomes study was undertaken at a large VA medical center with a policy favoring radiologic over surgical cholecystostomy over the past 9 years. Records of 24 consecutive patients with acute cholecystitis were reviewed to evaluate the effectiveness of the procedure. RESULTS Cholecystostomy was performed radiologically in 22 patients and surgically in 2 patients. Most (78%) of patients improved within 48 hours. The periprocedural mortality was 25%. The majority of these patients died from unrelated illnesses. Four patients developed complications, none of which required operative intervention. CONCLUSIONS Comorbidities are the most important mortality factor for cholecystostomies in VA patients. Radiologic tube placement is effective and uncomplicated in most cases.

Quantifying Surgeon Grasping Mechanics in Laparoscopy Using the Blue DRAGON System

Mechanical testing of abdominal organs has a profound impact on surgical simulation and surgical robotics development. Due to the nonlinear and viscoelastic nature of soft tissue it is crucial to test them in surgically relevant ranges of applied force, deformation, and duration for incorporating haptic realism into surgical simulators and for safe operation of surgical robots. In order to determine these ranges, a system known as the Blue DRAGON was used to track the motions and the forces applied to surgical tools during live procedures for quantifying how surgeons typically perform a minimally invasive surgical procedure. Thirty-one surgeons of varying skill were recorded performing three different surgical tasks. Grasping force (as applied to the tool handles) and handle angle for each tool were the signals of interest among 26 channels total acquired by the system in real time. These data were analyzed for their magnitudes and frequency content. Using the tool contact state, an algorithm selected tissue grasps to analyze measures during grasps only, as well as obtain grasp durations. The mean force applied to the tool handles during tissue grasps was 8.52 N +/- 2.77 N; maximum force was 68.17 N. Ninety-five percent of the handle angle frequency content was below 1.98 Hz +/- 0.98 Hz. Average grasp time was 2.29 s +/- 1.65 s, and 95% of all grasps were held for 8.86 s +/- 7.06 s or less. The average maximum grasp time during these tasks was 13.37 s +/- 11.42 s. These results form the basis for determining how abdominal tissues are to be mechanically tested in ranges and durations of force and deformation that are surgically realistic. Additionally, this information may serve as design specifications for new surgical robots or haptic simulators.