Article

Orientation Strategies in Natural Orifice Translumenal Endoscopic Surgery

Authors:
  • Odin Vision
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Abstract

The aims of this study were to (1) describe the visual attention strategies employed by surgeons that are associated with high performance in reorientation and (2) identify key structures guiding attention deployment of the surgeon in the process of self-orientation in common clinical natural orifice translumenal endoscopic surgery (NOTES) scenarios. Disorientation has been identified as one of the major barriers to be overcome before widespread clinical NOTES uptake. Understanding disorientation requires description of key perceptual-motor factors leading to disorientation, assessment of their relative impact, and quantification of navigation performance. Twenty-one surgeons were shown a series of 8 images acquired during human NOTES operations from the flexible endoscope from different perspectives to induce disorientation. Gaze behavior was recorded using an eye tracker as the subjects were asked to establish the image orientation. Main outcome measures were times taken to establish orientation, eye-tracking parameters, and fixation sequences on organs and structures/regions of interest (ROI). High-performance subjects had a lower number of fixations and normalized dwell time per ROI compared with others, suggesting a more structured and focused approach to orientation. Orientation strategies associated with high performance were described using a validated algorithm for comparing visual reorientation behavior and amount of visual attention on individual ROIs in each scenario were quantified. Key areas of organs and structures during reorientation were illustrated using dwell time normalized visual maps. Targeted orientation strategies revealed in this study are expected to aid in decreasing the learning curve associated with NOTES and increase performance even for experienced surgeons and gastroenterologists. Crucially, these data can provide guidance for designing orientation friendly NOTES platforms.

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... Orientation training (15), control (15) Orientation-trained group gave more correct answers (75.6 versus 56.1, P ¼ 0.019) and took longer to give an answer (24.0 versus 19.8 s, P ¼ 0.010) than control group. Sodergren [39] Time taken to establish orientation and fixation sequences on organs and structures. ...
... The orientationtrained group gave more correct answers (75.6 versus 56.1, P ¼ 0.019) and took longer to give an answer (24.0 versus 19.8 s, P ¼ 0.010) than control group. In a further study by the same group [39], surgeons were given eight images of natural orifice transluminal endoscopic surgery and were asked to answer three questions on orientation. It was found that subjects who excelled had less fixations (P < 0.006) and lower normalized dwell time (P < 0.005) per area of interest. ...
... The studies presented here identify several assessment methods, which might be considered for future research, development, and validation. The overlap of gaze and fixation locations, as surrogate markers for the subject's perceived areas of importance, was assessed by several studies [11,14,15,17,30,33,34,39]. The knowledge and identification of key landmarks is critical for anatomical orientation and the avoidance of vital structures in surgery. ...
... We study the diagnostic arthroscopic shoulder surgery task since it involves navigating to various parts of the shoulder and inspecting them and thus allows us to focus purely on navigation skills. The existing studies on comparing eye movement patterns between experienced surgeons and novices have predominantly used VR training simulators [69], [150], [152], [155]- [157], still images of the surgery [99], [158] or physical box trainers [112]. We use so-called soft cadavers, which are specially prepared so as to retain the natural tissue properties. ...
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Digitization is penetrating more and more areas of life. Tasks are increasingly being completed digitally, and are therefore not only fulfilled faster, more efficiently but also more purposefully and successfully. The rapid developments in the field of artificial intelligence in recent years have played a major role in this, as they brought up many helpful approaches to build on. At the same time, the eyes, their movements, and the meaning of these movements are being progressively researched. The combination of these developments has led to exciting approaches. In this dissertation, I present some of these approaches which I worked on during my Ph.D. First, I provide insight into the development of models that use artificial intelligence to connect eye movements with visual expertise. This is demonstrated for two domains or rather groups of people: athletes in decision-making actions and surgeons in arthroscopic procedures. The resulting models can be considered as digital diagnostic models for automatic expertise recognition. Furthermore, I show approaches that investigate the transferability of eye movement patterns to different expertise domains and subsequently, important aspects of techniques for generalization. Finally, I address the temporal detection of confusion based on eye movement data. The results suggest the use of the resulting model as a clock signal for possible digital assistance options in the training of young professionals. An interesting aspect of my research is that I was able to draw on very valuable data from DFB youth elite athletes as well as on long-standing experts in arthroscopy. In particular, the work with the DFB data attracted the interest of radio and print media, namely DeutschlandFunk Nova and SWR DasDing. All resulting articles presented here have been published in internationally renowned journals or at conferences.
... 2011;Sodergren MH, Orihuela-Espina F, Froghi F, v.d. 2011;Sodergren MH, Orihuela-Espina F, Mountney P, et al., 2011;Chetwood v.d. 2012;Moore v.d. ...
... We study the diagnostic arthroscopic shoulder surgery task since it involves navigating to various parts of the shoulder and inspecting them and thus allows us to focus purely on navigation skills. The existing studies on comparing eye movement patterns between experienced surgeons and novices have predominantly used VR training simulators [1][2][3][4][5][6], still images of the surgery [7,8] or physical box trainers [9]. We use so-called soft cadavers, which are specially prepared so as to retain the natural tissue properties. ...
... They have been used in domains such as aviation, driving, medical and sports [13][14][15][16][17][18]. In medical domain, five successful training interventions were developed using eye tracking technology [8,[19][20][21][22]. In one study, a gaze-based training intervention was designed to train surgeons on experts' gaze behaviors. ...
Chapter
In this research, the application of K-means clustering analysis on pilots’ gaze points was studied in order to develop a quick evaluation approach for gazed-based training interventions. Detailed analysis of eye movements’ data takes a considerable amount of time which makes it difficult to use in some stages of training intervention. As a result, a more efficient indicator of trainees’ performance is needed to allow trainers the ability to provide timely feedback on trainees’ performance. In this research, the potential of using clustering analysis on pilots’ gaze points was assessed in order to classify bad and good gaze behaviors. One expert pilot and six novice pilots participated in the experiment. Pilots were equally divided into experimental and control groups.
... In addition, expert radiologists have exhibited lower fixation duration on AOIs for detection only tasks [12]. Similar results have been found in determining orientation of static images from endoscopic surgeries, where participants demonstrating the strongest performance exhibited lower number of fixations and dwell time per AOIs [11,15]. However, different medical tasks can have a reverse effect on these gaze metrics. ...
Article
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Background Eye-gaze metrics derived from areas of interest (AOIs) have been suggested to be effective for surgical skill assessment. However, prior research is mostly based on static images and simulated tasks that may not translate to complex and dynamic surgical scenes. Therefore, eye-gaze metrics must advance to account for changes in the location of important information during a surgical procedure. Methods We developed a dynamic AOI generation technique based on eye gaze collected from an expert viewing surgery videos. This AOI updated as the gaze of the expert moved with changes in the surgical scene. This technique was evaluated through an experiment recruiting a total of 20 attendings and residents to view 10 videos associated with and another 10 without adverse events. Results Dwell time percentage (i.e., gaze duration) inside the AOI differentiated video type (U = 13508.5, p < 0.001) between videos with the presence (Mdn = 16.75) versus absence (Mdn = 19.95) of adverse events. This metric also differentiated participant group (U = 14029.5, p < 0.001) between attendings (Mdn = 15.45) and residents (Mdn = 19.80). This indicates that our dynamic AOIs reflecting the expert eye gaze was able to differentiate expertise, and the presence of unexpected adverse events. Conclusion This dynamic AOI generation technique produced dynamic AOIs for deriving eye-gaze metrics that were sensitive to expertise level and event characteristics.
... The results further suggest that the problems encountered by the LE surgeons in the early phases were largely perceptual, thus agreeing with previous studies showing that errors leading to poor performance or injury are due more to errors in focus of attention, rather than deficits in the surgeons physical skills. [21][22][23][24] Future directions: quiet eye training in surgery ...
... Augmented reality has been proposed to overcome navigational challenges [3][4][5][6] . To this end, the authors have investigated an image registration system for NOTES procedures (IR-NOTES). ...
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Voluntarily paying attention to one object in a crowded scene enhances perception of that object and increases the activity of neurons representing it. Attention can also be drawn involuntarily by salient objects-for example, by the sudden onset of a bright stimulus. A study now shows how this involuntary type of attention may mediate competition between representations in human visual cortex.
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Optimal placement allows intuitive laparoscope positioning between two working trocars (0 degrees angle). However, this configuration may require the assistant to operate in an awkward position. We evaluated the effect of alteration of laparoscope position on surgeon performance and correlated this with surgical experience. Participants were stratified by laparoscopic experience. Group 1 (N = 10) was naïve (no surgical experience), group 2 (N = 7) had moderate laparoscopic experience (1-100 cases), and group 3 (N = 6) was laparoscopically experienced (>100 cases). Participants were timed performing a simple laparoscopic task three times in a trainer with camera angles randomized along the horizontal plane: 0 degrees , 45 degrees , 90 degrees , 135 degrees , and 180 degrees . All participants showed progressive deterioration in performance as the angle deviated from baseline. The mean time required to complete the tasks was significantly higher for group 1 v groups 2 and 3 at 135 degrees (158 v 77 and 73 seconds) and 180 degrees (153 v 89 and 86 seconds). Performance curves for each group revealed more pronounced deterioration of performance with alteration in the angle of vision in group 1 than in groups 2 and 3 (P < 0.01). There was no difference between groups 2 and 3 (P = 0.19). Even modest alteration in laparoscopic perspective results in deterioration of performance for all levels of surgical experience. Experienced laparoscopists adapt more quickly to complexities presented by alteration in camera angles. Novice surgeons should focus on trocar positioning to maintain intuitive surgical perspective and should refrain from working with alterations in camera angles until significant laparoscopic experience has been gained.
Soft tissue tracking for minimally invasive surgery: learning local deformation online. Medical image computing and computer-assisted interventionMICCAI. Pt Ii, Proc.
  • Mountney