Learning to use minimal access surgical instruments and 2-dimensional remote visual feedback: how difficult is the task for novices?
ABSTRACT Performing minimal access surgery requires the use of 2-dimensional information to produce 3-dimensional movements, as well as precise motor control for manipulating laparoscopic tools. The added visuomotor demands of this task make it more demanding and complex than traditional open surgery. The purpose of this study was to determine the relative task difficulty of performing laparoscopic tool movements with normal vision or 'laparoscopic vision' provided by a remote 2-D monitor. A second purpose of this study was to evaluate whether movement performance changes are induced by practice with normal vision (NV) and laparoscopic vision (LV). The study was also designed to determine whether order of visual condition (NV or LV) practice impacts the rate of performance acquisition when transferred to the opposing visual condition. Eleven individuals participated in this study. All subjects performed a bean grasping and a suturing task in two visual conditions: normal vision and laparoscopic vision. Results revealed that laparoscopic tools themselves do not appear to be problematic in performing minimal access surgery. Furthermore, performance ability in normal vision does not positively transfer to performance when switched to a laparoscopic vision condition. The 2-dimensional video does appear to be problematic for skill acquisition, as performance levels decreased as complexity of the task increased.
Article: Construct and face validity and task workload for laparoscopic camera navigation: virtual reality versus videotrainer systems at the SAGES Learning Center.[show abstract] [hide abstract]
ABSTRACT: Laparoscopic camera navigation (LCN) training on simulators has demonstrated transferability to actual operations, but no comparative data exist. The objective of this study was to compare the construct and face validity, as well as workload, of two previously validated virtual reality (VR) and videotrainer (VT) systems. Attendees (n = 90) of the SAGES 2005 Learning Center performed two repetitions on both VR (EndoTower) and VT (Tulane Trainer) LCN systems using 30 degrees laparoscopes and completed a questionnaire regarding demographics, simulator characteristics, and task workload. Construct validity was determined by comparing the performance scores of subjects with various levels of experience according to five parameters and face validity according to eight. The validated NASA-TLX questionnaire that rates the mental, physical, and temporal demand of a task as well as the performance, effort, and frustration of the subject was used for workload measurement. Construct validity was demonstrated for both simulators according to the number of basic laparoscopic cases (p = 0.005), number of advanced cases (p < 0.001), and frequency of angled scope use (p < 0.001), and only for VT according to training level (p < 0.001) and fellowship training (p = 0.008). Face validity ratings on a 1-20 scale averaged 15.4 +/- 3 for VR vs. 16 +/- 2.6 for VT (p = 0.04). Ninety-six percent of participants rated both simulators as valid educational tools. The NASA-TLX overall workload score was 69.5 +/- 24 for VR vs. 68.8 +/- 20.5 for VT (p = 0.31). This is the largest study to date that compares two validated LCN simulators. While subtle differences exist, both VR and VT simulators demonstrated excellent construct validity, good face validity, and acceptable workload parameters. These systems thus represent useful training devices and should be widely used to improve surgical performance.Surgical Endoscopy 07/2007; 21(7):1158-64. · 4.01 Impact Factor
Article: Feasibility of obtaining quantitative 3-dimensional information using conventional endoscope: a pilot study.[show abstract] [hide abstract]
ABSTRACT: Three-dimensional (3D) imaging is gaining popularity and has been partly adopted in laparoscopic surgery or robotic surgery but has not been applied to gastrointestinal endoscopy. As a first step, we conducted an experiment to evaluate whether images obtained by conventional gastrointestinal endoscopy could be used to acquire quantitative 3D information. Two endoscopes (GIF-H260) were used in a Borrmann type I tumor model made of clay. The endoscopes were calibrated by correcting the barrel distortion and perspective distortion. Obtained images were converted to gray-level image, and the characteristics of the images were obtained by edge detection. Finally, data on 3D parameters were measured by using epipolar geometry, two view geometry, and pinhole camera model. The focal length (f) of endoscope at 30 mm was 258.49 pixels. Two endoscopes were fixed at predetermined distance, 12 mm (d(12)). After matching and calculating disparity (v2-v1), which was 106 pixels, the calculated length between the camera and object (L) was 29.26 mm. The height of the object projected onto the image (h) was then applied to the pinhole camera model, and the result of H (height and width) was 38.21 mm and 41.72 mm, respectively. Measurements were conducted from 2 different locations. The measurement errors ranged from 2.98% to 7.00% with the current Borrmann type I tumor model. It was feasible to obtain parameters necessary for 3D analysis and to apply the data to epipolar geometry with conventional gastrointestinal endoscope to calculate the size of an object.Clinical endoscopy. 09/2012; 45(3):182-8.
Article: Psychomotor testing predicts rate of skill acquisition for proficiency-based laparoscopic skills training.[show abstract] [hide abstract]
ABSTRACT: Laparoscopic simulator training translates into improved operative performance. Proficiency-based curricula maximize efficiency by tailoring training to meet the needs of each individual; however, because rates of skill acquisition vary widely, such curricula may be difficult to implement. We hypothesized that psychomotor testing would predict baseline performance and training duration in a proficiency-based laparoscopic simulator curriculum. Residents (R1, n = 20) were enrolled in an IRB-approved prospective study at the beginning of the academic year. All completed the following: a background information survey, a battery of 12 innate ability measures (5 motor, and 7 visual-spatial), and baseline testing on 3 validated simulators (5 videotrainer [VT] tasks, 12 virtual reality [minimally invasive surgical trainer-virtual reality, MIST-VR] tasks, and 2 laparoscopic camera navigation [LCN] tasks). Participants trained to proficiency, and training duration and number of repetitions were recorded. Baseline test scores were correlated to skill acquisition rate. Cutoff scores for each predictive test were calculated based on a receiver operator curve, and their sensitivity and specificity were determined in identifying slow learners. Only the Cards Rotation test correlated with baseline simulator ability on VT and LCN. Curriculum implementation required 347 man-hours (6-person team) and 795,000 dollars of capital equipment. With an attendance rate of 75%, 19 of 20 residents (95%) completed the curriculum by the end of the academic year. To complete training, a median of 12 hours (range, 5.5-21), and 325 repetitions (range, 171-782) were required. Simulator score improvement was 50%. Training duration and repetitions correlated with prior video game and billiard exposure, grooved pegboard, finger tap, map planning, Rey Figure Immediate Recall score, and baseline performance on VT and LCN. The map planning cutoff score proved most specific in identifying slow learners. Proficiency-based laparoscopic simulator training provides improvement in performance and can be effectively implemented as a routine part of resident education, but may require significant resources. Although psychomotor testing may be of limited value in the prediction of baseline laparoscopic performance, its importance may lie in the prediction of the rapidity of skill acquisition. These tests may be useful in optimizing curricular design by allowing the tailoring of training to individual needs.Surgery 09/2006; 140(2):252-62. · 3.10 Impact Factor