The da vinci robot system eliminates multispecialty surgical trainees' hand dominance in open and robotic surgical settings

Mapping the Bibliometrics Landscape of AI in Medicine: Methodological Study

BACKGROUND

Artificial intelligence (AI), conceived in the 1950s, has permeated numerous industries, intensifying in tandem with advancements in computing power. Despite the widespread adoption of AI, its integration into medicine trails other sectors. However, medical AI research has experienced substantial growth, attracting considerable attention from researchers and practitioners.

OBJECTIVE

In the absence of an existing framework, this study aims to outline the current landscape of medical AI research and provide insights into its future developments by examining all AI-related studies within PubMed over the past 2 decades. We also propose potential data acquisition and analysis methods, developed using Python (version 3.11) and to be executed in Spyder IDE (version 5.4.3), for future analogous research.

METHODS

Our dual-pronged approach involved (1) retrieving publication metadata related to AI from PubMed (spanning 2000-2022) via Python, including titles, abstracts, authors, journals, country, and publishing years, followed by keyword frequency analysis and (2) classifying relevant topics using latent Dirichlet allocation, an unsupervised machine learning approach, and defining the research scope of AI in medicine. In the absence of a universal medical AI taxonomy, we used an AI dictionary based on the European Commission Joint Research Centre AI Watch report, which emphasizes 8 domains: reasoning, planning, learning, perception, communication, integration and interaction, service, and AI ethics and philosophy.

RESULTS

From 2000 to 2022, a comprehensive analysis of 307,701 AI-related publications from PubMed highlighted a 36-fold increase. The United States emerged as a clear frontrunner, producing 68,502 of these articles. Despite its substantial contribution in terms of volume, China lagged in terms of citation impact. Diving into specific AI domains, as the Joint Research Centre AI Watch report categorized, the learning domain emerged dominant. Our classification analysis meticulously traced the nuanced research trajectories across each domain, revealing the multifaceted and evolving nature of AI's application in the realm of medicine.

CONCLUSIONS

The research topics have evolved as the volume of AI studies increases annually. Machine learning remains central to medical AI research, with deep learning expected to maintain its fundamental role. Empowered by predictive algorithms, pattern recognition, and imaging analysis capabilities, the future of AI research in medicine is anticipated to concentrate on medical diagnosis, robotic intervention, and disease management. Our topic modeling outcomes provide a clear insight into the focus of AI research in medicine over the past decades and lay the groundwork for predicting future directions. The domains that have attracted considerable research attention, primarily the learning domain, will continue to shape the trajectory of AI in medicine. Given the observed growing interest, the domain of AI ethics and philosophy also stands out as a prospective area of increased focus.

Factors affecting upper limb ergonomics in robotic colorectal surgery

The aim of the study was to examine the factors which may influence suboptimal ergonomic surgeon hand positioning during robotic colorectal surgery (RCS). An observational study of 11 consecutive RCS cases from June 2022 to August 2022 was performed. Continuous video footage of RCS cases was analysed concurrently with video recordings of surgeon's hand positions at the console. The outcome studied was the frequency with which either hand remained in a suboptimal ergonomic position outside the predetermined double box outlines, as marked on the surgeon's video, for >1 min. Situations which resulted in poor upper limb ergonomics were dissection in the peripheral operating field location, left-hand use, use of the stapler, dissection of the main mesenteric blood vessels, and multi-quadrant surgery. Being aware of situations when suboptimal ergonomic positions occur can allow surgeons to consciously compensate by using the clutch or pausing to take a rest break.

What does this paper add to the literature?

The study is important because it is the first to look at factors which may influence poor upper limb ergonomics during non-simulated RCS. By recognizing these factors and compensating for them, it may improve surgeon ergonomics with resultant better performance.

Robotic Plastic Surgery Education: Developing a Robotic Surgery Training Program Specific to Plastic Surgery Trainees

Over the past two decades, the surgical community has increasingly embraced robotic-assisted surgery (RAS) due to its potential to enhance accuracy and decrease surgical morbidity. Plastic surgery as a field has been historically slow to incorporate RAS, with lack of adequate training posing as one of the most commonly cited barriers. To date, robot technology has been utilized for various reconstructive procedures including flap elevation and inset, pedicle dissection, and microvascular anastomosis. As RAS continues to integrate within plastic surgery procedures, the need for a structured RAS curriculum designed for plastic surgery trainees is rising. This article delineates the essential components of a plastic surgery-specific RAS curriculum and outlines current training models and assessment tools utilized across surgical subspecialties to date.

The Sinister Surgeon: Advanced Pediatric Minimally Invasive Surgery for Left-Handed Surgeons

Purpose: Left-handed (LH) surgeons face unique challenges in their training and practice. Contrary to the historical and unjust perception of technical inferiority, LH surgeons can thrive under appropriate mentorship and support. Here, we describe modifications to pediatric minimally invasive surgeries to benefit the LH surgeon. Methods: The surgical approaches to common and complex pediatric surgical operations were modified to facilitate training of an LH pediatric surgical fellow. Results: Preoperative preparation, including communication with the operating room team, patient positioning, and provision of appropriate equipment, allowed the procedures to be accomplished in a safe and efficient manner. Conclusions: Modifying complex minimally invasive surgery to allow for use of the dominant hand is feasible and safe.

The Atlantic divide: contrasting surgical robotics training in the USA, UK and Ireland

The uptake of robotic surgery is rapidly increasing worldwide across surgical specialties. However, there is currently a much higher use of robotic surgery in the United States of America (USA) compared to the United Kingdom (UK) and Ireland. Reduced exposure to robotic surgery in training may lead to longer learning curves and worse patient outcomes. We aimed to identify whether any difference exists in exposure to robotic surgery during general surgical training between trainees in the USA, UK and Ireland. Over a 15-week period from September 2021, a survey was distributed through the professional networks of the research team. Participants were USA, UK or Irish trainees who were part of a formal general surgical training curriculum. 116 survey responses were received. US trainees (n = 34) had all had robotic simulator experience, compared to only 37.93% of UK (n = 58) and 75.00% of Irish (n = 24) trainees (p <  0.00001). 91.18% of US trainees had performed 15 or more cases as the console surgeon, compared to only 3.44% of UK and 16.67% of Irish trainees (p <  0.00001). Fifty UK trainees (86.21%) and 22 Irish trainees (91.67%) compared to 12 US trainees (35.29%) do not think they have had adequate robotics training (p <  0.00001). Surgical trainees in the USA have had significantly more exposure to training in robotic surgery than their UK and Irish counterparts.

Surgical Hand Gesture Recognition Utilizing Electroencephalogram as Input to the Machine Learning and Network Neuroscience Algorithms

Surgical gestures detection can provide targeted, automated surgical skill assessment and feedback during surgical training for robot-assisted surgery (RAS). Several sources including surgical videos, robot tool kinematics, and an electromyogram (EMG) have been proposed to reach this goal. We aimed to extract features from electroencephalogram (EEG) data and use them in machine learning algorithms to classify robot-assisted surgical gestures. EEG was collected from five RAS surgeons with varying experience while performing 34 robot-assisted radical prostatectomies over the course of three years. Eight dominant hand and six non-dominant hand gesture types were extracted and synchronized with associated EEG data. Network neuroscience algorithms were utilized to extract functional brain network and power spectral density features. Sixty extracted features were used as input to machine learning algorithms to classify gesture types. The analysis of variance (ANOVA) F-value statistical method was used for feature selection and 10-fold cross-validation was used to validate the proposed method. The proposed feature set used in the extra trees (ET) algorithm classified eight gesture types performed by the dominant hand of five RAS surgeons with an accuracy of 90%, precision: 90%, sensitivity: 88%, and also classified six gesture types performed by the non-dominant hand with an accuracy of 93%, precision: 94%, sensitivity: 94%.

Is robot-assisted retroperitoneal adrenalectomy safe? An investigation of perioperative hypertensive crisis among hypertensive and normotensive patients

BACKGROUND

Objective: We examined the incidence of perioperative hypertensive crisis in robot-assisted retroperitoneal laparoscopic adrenalectomy.

METHODS

A consecutive series of 120 patients with adrenal tumours undergoing robot-assisted retroperitoneal laparoscopic adrenalectomy were included. Patients were divided into two groups: group A (hypertension group, 58 cases, mean age 43.59 years) and group B (normotension group, 62 cases, mean age 48.01 years). General anaesthesia was applied using endotracheal intubation and haemodynamic changes were closely monitored.

RESULTS

A total of nine (7.5%) hypertensive crisis cases were observed. After intravenous infusion of sodium nitroprusside, seven cases of them were quickly controlled and two cases experienced transient severe hypertension. The incidence of hypertensive crisis was 13.7% and 1.6% in groups A and B, respectively (p < 0.05).

CONCLUSION

These findings highlight the importance of strengthening the monitoring of anaesthesia and taking various measures to effectively control the blood pressure in robot-assisted retroperitoneal laparoscopic adrenalectomy, especially among hypertensive patients.

The Left-handed Plastic Surgery Trainee: Perspectives and Recommendations

Left-handed surgeons experience difficulty with tools designed for use in the right hand. The purpose of this study was to examine instrument laterality and to survey the experiences of left-handed plastic surgery trainees.

Impact of surgeon handedness in manual and robot-assisted total hip arthroplasty

BACKGROUND

The purpose of this study was to examine whether surgeon handedness could affect cup positioning in manual total hip arthroplasty (THA), and whether robot could diminish or eliminate the impact of surgeon handedness on cup positioning in robot-assisted THA.

METHODS

Fifty-three patients who underwent bilateral robot-assisted THA and sixty-two patients who underwent bilateral manual THA between August 2018 and July 2019 in our institute were respectively analyzed in this study. When the difference between the bilateral anteversion and inclination was greater than 5°, the patient was regarded as having different cup positioning between bilateral THA. Their demographics, orientation of acetabular cup, and postoperative 3 month Harris hip score (HHS) were recorded for analysis.

RESULTS

There were no significant differences in the gender, age, BMI, diagnosis's composition, and preoperative and postoperative HHS between the robotic and manual group. Two left hips dislocated in the manual group. The anteversion of left hip was significantly larger than that of right hip (24.77 ± 10.44 vs 22.44 ± 8.67, p = 0.043) in the manual group. There were no significant differences of cup positioning between bilateral robot-assisted THA. The patients in manual group were significantly more likely to have different cup positioning between bilateral hips than those in robotic group (77% vs 45%, p = 0.000). More manual THA were located out of the target zone than robot-assisted THA (70% vs 48%, p = 0.001).

CONCLUSIONS

Surgeon's handedness showed a trend towards an impact on cup positioning in manual THA and robot might help surgeon eliminate the adverse impact. However, the impact of handedness on the clinical outcomes still needs further observation.

The Right Way to Teach Left-Handed Residents: Strategies for Training by Right Handers

PURPOSE

Left-handed (LH) residents remain underrepresented among surgical trainees, and there are few available data on how best to train them. The challenge is amplified when pairing a LH resident with a right-handed (RH) mentor. This report provides recommendations on how to improve the training of LH surgeons in a safe and effective manner.

METHODS

A comprehensive literature review was performed using different databases and search engines to identify all articles relevant to the training of LH residents.

RESULTS

A total of 40 articles highlighted the challenges for LH surgical residents and RH mentors. Our recommendations are based on the following 4 themes: identifying inherent differences in left vs. RH residents, providing guidance to RH mentors training LH residents, adapting the RH environment to the LH surgeon, and maximizing safety during training.

CONCLUSION

An organized approach needs to be taken in training the LH resident. Changes should be instituted at program-wide and national levels to ensure that the training experience of the sinistral surgical resident is optimized.

The effect of handedness and laterality in a microlaryngeal surgery simulator

PURPOSE

There are no controlled prospective studies evaluating the effect of dominant handedness in left- and right-sided surgery in otolaryngology. Endoscopic microlaryngeal phonosurgery is an ideal procedure to assess technical aspects of handedness and laterality, due to anatomic symmetry. In this study, we analyzed (1) choice of surgical approach and (2) outcomes based on handedness and laterality in a microlaryngeal simulator.

METHODS

Using a validated high-fidelity phonosurgery model, a prospective cohort of 19 expert laryngologists undertook endoscopic resection of a simulated vocal fold lesion. These resections were video-recorded and scored by 2 blinded expert laryngologists using a validated global rating scale, procedure-specific rating scale, and a hand preference analysis.

RESULTS

There were 18 right-handed participants and 1 left-handed. 12 left and 7 right excisions were evaluated. Cronbach's alpha for inter-rater reliability was good (0.871, global scale; and 0.814, procedure-specific scale). Surgeons used their dominant hand 78.9% of the time for both incision and dissection. In cases where the non-dominant hand would have been preferred, surgeons used the non-dominant hand only 36.4% of the time for incision and dissection. Use of the non-dominant hand did not influence global or procedural rating (p=0.132 and p=0.459, respectively).

CONCLUSIONS

In this simulation of microlaryngeal surgery, there were measurable differences in surgical approaches based on hand dominance, with surgeons preferring to cut and perform resection with the dominant hand despite limitations in the instrumentation and exposure. Regardless of hand preference, overall outcomes based on global rating and technique specific rating scales were not significantly different.

Robotic liver resection including the posterosuperior segments: initial experience

BACKGROUND

Robot-assisted laparoscopy has been introduced to overcome the limitations of conventional laparoscopy. This technique has potential advantages over laparoscopy, such as increased dexterity, three-dimensional view, and a magnified view of the operative field. Therefore, improved dexterity may make a robotic system particularly suited for liver resections, which require nonlinear manipulation, such as curved parenchymal transection, hilar dissection, and resection of posterosuperior segments.

METHODS

Between August 2014 and March 2016, 16 patients underwent robot-assisted laparoscopic liver resection at University Medical Center Utrecht.

RESULTS

Fifteen robot-assisted laparoscopic liver resections were performed in a minimally invasive manner. One procedure was converted. In eight patients, we performed a resection of a posterosuperior segment (segment 7 or 8). Median operating time was 146 (60-265) min, and median blood loss was 150 (5-600) mL. Four patients had a Clavien-Dindo grade III complication. Median length of stay was 4 (1-8) days. There was no mortality.

CONCLUSIONS

This prospective study reporting on our initial experience with robot-assisted laparoscopic liver resection demonstrates that this technique is easily adopted, safe, and feasible for minor hepatectomies in selected patients. Moreover, it shows that the robotic platform also enables fully laparoscopic resections of the posterior segments.

Exploring hand coordination as a measure of surgical skill

BACKGROUND

The study aim was to identify residents' coordination between dominant and nondominant hands while grasping for sutures in a laparoscopic ventral hernia repair procedure simulation. We hypothesize residents will rely on their dominant and nondominant hands unequally while grasping for suture.

METHODS

Surgical residents had 15 min to complete the mesh securing and mesh tacking steps of a laparoscopic ventral hernia repair procedure. Procedure videos were coded for manual coordination events during the active suture grasping phase. Manual coordination events were defined as: active motion of dominant, nondominant, or both hands; and bimanual or unimanual manipulation of hands. A chi-square test was used to discriminate between coordination choices.

RESULTS

Thirty-six residents (postgraduate year, 1-5) participated in the study. Residents changed manual coordination types during active suture grasping 500 times, ranging between 5 and 24 events (M = 13.9 events, standard deviation [SD] = 4.4). Bimanual coordination was used most (40%) and required the most time on average (M = 20.6 s, SD = 27.2), while unimanual nondominant coordination was used least (2.2%; M = 7.9 s, SD = 6.9). Residents relied on their dominant and nondominant hands unequally (P < 0.001). During 24% of events, residents depended on their nondominant hand (n = 120), which was predominantly used to operate the suture passer device.

CONCLUSIONS

Residents appeared to actively coordinate both dominant and nondominant hands almost half of the time to complete suture grasping. Bimanual task durations took longer than other tasks on average suggesting these tasks were characteristically longer or switching hands required a greater degree of coordination. Future work is necessary to understand how task completion time and overall performance are affected by residents' hand utilization and switching between dominant and nondominant hands in surgical tasks.

Manual Ambidexterity Predicts Robotic Surgical Proficiency

BACKGROUND

The manual dexterity of a surgeon is known to be related with surgical proficiency. Recently, as an objective measurement of surgical skills, inanimate methods using several types of simulators have been introduced. Using these simulators, we aimed to investigate the impact of manual dexterity on laparoscopic and robotic surgical proficiency.

MATERIALS AND METHODS

Fellow surgeons, surgical residents, and medical students (n = 32) participated in this study. For the measurement of dexterity, the sums and differences of the right and left hand performance times for the Grooved Pegboard Test were used as an index of dexterity speed and ambidexterity, respectively. The performance times during three sessions of laparoscopic suturing using a D-box trainer and the performance scores during three sessions using two robotic suturing programs with different degrees of difficulty provided by the da Vinci® Skills Simulator™ (Intuitive Surgical Inc., Sunnyvale, CA) were analyzed according to the measured manual dexterity.

RESULTS

Manual dexterity was not a significant factor for performance time during laparoscopic suturing, which was more influenced by participants' surgical experiences. In robotic suturing, the performance score was impacted significantly by manual dexterity in terms of ambidexterity rather than dexterity speed. For an easy robotic suturing task, the gap of proficiency between the lower and higher ambidexterity groups was decreased successively with each of the three sessions. However, that gap in cases with a difficult task was maintained consistently throughout all three sessions.

CONCLUSIONS

The degree of ambidexterity was an initial predictor for proficiency with simulated robotic suture. However, this relation could be lessened through a few sessions of training, although for a more difficult task further repetitions would be needed.