The effect of intraoperative distractions on severe technical events in laparoscopic bariatric surgery

Neural insights on expert surgeons' mental workload during live robotic surgeries

Despite its adoption and benefits, robotic surgeries can impose additional mental workload on surgeons. Validated questionnaires mostly administered at the end of procedures may not accurately capture the dynamic nature of mental workload over an entire procedure. Hence, we sought to determine if electroencephalogram (EEG) based neural activities in different brain regions can measure variations in expert surgeons' mental workload intraoperatively. EEG data was collected from five different surgeons performing 13 robotic-assisted urological procedures. Data analysis focused on three surgery phases (before, critical, and after). After performing each phase, surgeons provided a rating of their perceived mental workload. A linear mixed effects model was applied to explore the impact of the study phases on the relative spectral band power of EEG signals. The relative theta band power in the frontal brain region was highest during the critical portions of the procedure (p < 0.05). As the subjective ratings increased, the relative frontal theta band power increased (p < 0.001) while the relative parietal alpha band power decreased across all phases. We show that EEG signals can distinguish intraoperative workload in robotic surgeries. This has several applications including predicting risk factors for increased case complexity and surgical education.

Evaluation of operating room inefficiencies and their impact on operating room duration using a surgical app

BACKGROUND

Efficient utilization of the operating room (OR) is essential. Inefficiencies are thought to cause preventable delays. Our goal was to identify OR incidents causing delays and estimate their impact on the duration of various general surgery procedures.

MATERIALS

Three trained observers prospectively collected intraoperative data using the ExplORer Surgical app, a tool that helped capture incidents causing delays. The impact of each incident on case duration was assessed using multivariable analysis.

RESULTS

151 general surgery procedures were observed. The mean number of incidents was 2.7 per each case that averaged 109min. On average, each incident caused a 2.8 ​min delay (p ​< ​0.001), however, some incidents were associated with longer delays. The procedural step of each procedure most susceptible to incidents was also defined.

CONCLUSION

The identification of the type of incidents and the procedural step during which they occur may allow targeted interventions to optimize OR efficiency and decrease operative time.

Defining digital surgery: a SAGES white paper

BACKGROUND

Digital surgery is a new paradigm within the surgical innovation space that is rapidly advancing and encompasses multiple areas.

METHODS

This white paper from the SAGES Digital Surgery Working Group outlines the scope of digital surgery, defines key terms, and analyzes the challenges and opportunities surrounding this disruptive technology.

RESULTS

In its simplest form, digital surgery inserts a computer interface between surgeon and patient. We divide the digital surgery space into the following elements: advanced visualization, enhanced instrumentation, data capture, data analytics with artificial intelligence/machine learning, connectivity via telepresence, and robotic surgical platforms. We will define each area, describe specific terminology, review current advances as well as discuss limitations and opportunities for future growth.

CONCLUSION

Digital Surgery will continue to evolve and has great potential to bring value to all levels of the healthcare system. The surgical community has an essential role in understanding, developing, and guiding this emerging field.

Evolution of the digital operating room: the place of video technology in surgery

PURPOSE

The aim of this review was to collate current evidence wherein digitalisation, through the incorporation of video technology and artificial intelligence (AI), is being applied to the practice of surgery. Applications are vast, and the literature investigating the utility of surgical video and its synergy with AI has steadily increased over the last 2 decades. This type of technology is widespread in other industries, such as autonomy in transportation and manufacturing.

METHODS

Articles were identified primarily using the PubMed and MEDLINE databases. The MeSH terms used were "surgical education", "surgical video", "video labelling", "surgery", "surgical workflow", "telementoring", "telemedicine", "machine learning", "deep learning" and "operating room". Given the breadth of the subject and the scarcity of high-level data in certain areas, a narrative synthesis was selected over a meta-analysis or systematic review to allow for a focussed discussion of the topic.

RESULTS

Three main themes were identified and analysed throughout this review, (1) the multifaceted utility of surgical video recording, (2) teleconferencing/telemedicine and (3) artificial intelligence in the operating room.

CONCLUSIONS

Evidence suggests the routine collection of intraoperative data will be beneficial in the advancement of surgery, by driving standardised, evidence-based surgical care and personalised training of future surgeons. However, many barriers stand in the way of widespread implementation, necessitating close collaboration between surgeons, data scientists, medicolegal personnel and hospital policy makers.

The Utility of Video Recording in Assessing Bariatric Surgery Complications

Introduction: Recording every procedure could diminish the postoperative complication rates in bariatric surgery. The aim of our study was to evaluate the correlation between recording every bariatric surgery and their postoperative analysis in relation to the early or late postoperative complications. Methods: Seven hundred fifteen patients who underwent a bariatric procedure between January 2018 and December 2019 were included in a retrospective analysis. There were: 589 laparoscopic sleeve gastrectomies (LSGs); 110 Roux-en-Y bypasses (RYGBs) and 16 gastric bands (LAGBs). The video recording was systematically used, and all patients were enrolled in the IFSO registry. Results: There were 15 patients (2.1%) with surgical postoperative complications: 5 leaks, 8 hemorrhages and 2 stenosis. Most complications were consequent to LSG, except for two, which occurred after RYGB. In four cases a site of active bleeding was identified. After reviewing the video, in three cases the site was correlated with an event which occurred during the initial procedure. Three out of five cases of leak following sleeve were treated purely endoscopically, and no potential correlated mechanism was identified. Two other possible benefits were observed: a better evaluation of the gastric pouch for the treatment of the ulcer post bypass and the review of one per operative incident. Two negative diagnostic laparoscopies were performed. The benefit of the systematic video recording was singled out in eight cases. All the other cases were completed by laparoscopy with no conversion. Conclusion: To record every bariatric procedure could help in understanding the mechanism of certain complications, especially when the analysis is performed within the team. Still, recording the procedure did not prevent the negative diagnostic laparoscopy, but it could play a significant role for the medico-legal aspect in the future.

Open surgery tool classification and hand utilization using a multi-camera system

PURPOSE

The goal of this work is to use multi-camera video to classify open surgery tools as well as identify which tool is held in each hand. Multi-camera systems help prevent occlusions in open surgery video data. Furthermore, combining multiple views such as a top-view camera covering the full operative field and a close-up camera focusing on hand motion and anatomy may provide a more comprehensive view of the surgical workflow. However, multi-camera data fusion poses a new challenge: A tool may be visible in one camera and not the other. Thus, we defined the global ground truth as the tools being used regardless their visibility. Therefore, tools that are out of the image should be remembered for extensive periods of time while the system responds quickly to changes visible in the video.

METHODS

Participants (n = 48) performed a simulated open bowel repair. A top-view and a close-up cameras were used. YOLOv5 was used for tool and hand detection. A high-frequency LSTM with a 1-second window at 30 frames per second (fps) and a low-frequency LSTM with a 40-second window at 3 fps were used for spatial, temporal, and multi-camera integration.

RESULTS

The accuracy and F1 of the six systems were: top-view (0.88/0.88), close-up (0.81,0.83), both cameras (0.9/0.9), high-fps LSTM (0.92/0.93), low-fps LSTM (0.9/0.91), and our final architecture the multi-camera classifier(0.93/0.94).

CONCLUSION

Since each camera in a multi-camera system may have a partial view of the procedure, we defined a 'global ground truth.' Defining this at the data labeling phase emphasized this requirement at the learning phase, eliminating the need for any heuristic decisions. By combining a system with a high fps and a low fps from the multiple camera array, we improved the classification abilities of the global ground truth.