Mechanical behavior of full-thickness burn human skin is rate-independent

Skin tissue is recognized to exhibit rate-dependent mechanical behavior under various loading conditions. Here, we report that the full-thickness burn human skin exhibits rate-independent behavior under uniaxial tensile loading conditions. Mechanical properties, namely, ultimate tensile stress, ultimate tensile strain, and toughness, and parameters of Veronda-Westmann hyperelastic material law were assessed via uniaxial tensile tests. Univariate hypothesis testing yielded no significant difference (p > 0.01) in the distributions of these properties for skin samples loaded at three different rates of 0.3 mm/s, 2 mm/s, and 8 mm/s. Multivariate multiclass classification, employing a logistic regression model, failed to effectively discriminate samples loaded at the aforementioned rates, with a classification accuracy of only 40%. The median values for ultimate tensile stress, ultimate tensile strain, and toughness are computed as 1.73 MPa, 1.69, and 1.38 MPa, respectively. The findings of this study hold considerable significance for the refinement of burn care training protocols and treatment planning, shedding new light on the unique, rate-independent behavior of burn skin.

One-shot skill assessment in high-stakes domains with limited data via meta learning

Deep Learning (DL) has achieved robust competency assessment in various high-stakes fields. However, the applicability of DL models is often hampered by their substantial data requirements and confinement to specific training domains. This prevents them from transitioning to new tasks where data is scarce. Therefore, domain adaptation emerges as a critical element for the practical implementation of DL in real-world scenarios. Herein, we introduce A-VBANet, a novel meta-learning model capable of delivering domain-agnostic skill assessment via one-shot learning. Our methodology has been tested by assessing surgical skills on five laparoscopic and robotic simulators and real-life laparoscopic cholecystectomy. Our model successfully adapted with accuracies up to 99.5 % in one-shot and 99.9 % in few-shot settings for simulated tasks and 89.7 % for laparoscopic cholecystectomy. This study marks the first instance of a domain-agnostic methodology for skill assessment in critical fields setting a precedent for the broad application of DL across diverse real-life domains with limited data.

Validation of a Virtual Simulator With Haptic Feedback for Endotracheal Intubation Training

INTRODUCTION

Endotracheal intubation (ETI) is a procedure that varies in difficulty because of patient characteristics and clinical conditions. Existing physical simulators do not encompass these variations. The Virtual Airway Skills Trainer for Endotracheal Intubation (VAST-ETI) was developed to provide different patient characteristics and high-fidelity haptic feedback to improve training.

METHODS

We demonstrate the effectiveness of VAST-ETI as a training and evaluation tool for ETI. Construct validation was evaluated by scoring the performance of experts ( N = 15) and novices ( N = 15) on the simulator to ensure its ability to distinguish technical proficiency. Convergent and predictive validity were evaluated by performing a learning curve study, in which a group of novices ( N = 7) were trained for 2 weeks using VAST-ETI and then compared with a control group ( N = 9).

RESULTS

The VAST-ETI was able to distinguish between expert and novice based on mean simulator scores ( t [88] = -6.61, P < 0.0005). When used during repeated practice, individuals demonstrated a significant increase in their score on VAST-ETI over the learning period ( F [11,220] = 7206, P < 0.001); however when compared with a control group, there was not a significant interaction effect on the simulator score. There was a significant difference between the simulator-trained and control groups ( t [12.85] = -2.258, P = 0.042) when tested in the operating room.

CONCLUSIONS

Our results demonstrate the effectiveness of virtual simulation with haptic feedback for assessing performance and training of ETI. The simulator was not able to differentiate performance between more experienced trainees and experts because of limits in simulator difficulty.

Fragmentation of water clusters formed in helium nanodroplets by charge transfer and Penning ionization

Helium nanodroplets ("HNDs") are widely used for forming tailor-made clusters and molecular complexes in a cold, transparent, and weakly interacting matrix. The characterization of embedded species by mass spectrometry is often complicated by the fragmentation and trapping of ions in the HNDs. Here, we systematically study fragment ion mass spectra of HND-aggregated water and oxygen clusters following their ionization by charge transfer ionization ("CTI") and Penning ionization ("PEI"). While the efficiency of PEI of embedded clusters is lower than for CTI by about factor 10, both the mean sizes of detected water clusters and the relative yields of unprotonated cluster ions are significantly larger, making PEI a "soft ionization" scheme. However, the tendency of ions to remain bound to HNDs leads to a reduced detection efficiency for large HNDs containing >104 helium atoms. These results are instrumental in determining optimal conditions for mass spectrometry and photoionization spectroscopy of molecular complexes and clusters aggregated in HNDs.

Endoscopic sleeve gastroplasty: stomach location and task classification for evaluation using artificial intelligence

PURPOSE

We have previously developed grading metrics to objectively measure endoscopist performance in endoscopic sleeve gastroplasty (ESG). One of our primary goals is to automate the process of measuring performance. To achieve this goal, the repeated task being performed (grasping or suturing) and the location of the endoscopic suturing device in the stomach (Incisura, Anterior Wall, Greater Curvature, or Posterior Wall) need to be accurately recorded.

METHODS

For this study, we populated our dataset using screenshots and video clips from experts carrying out the ESG procedure on ex vivo porcine specimens. Data augmentation was used to enlarge our dataset, and synthetic minority oversampling (SMOTE) to balance it. We performed stomach localization for parts of the stomach and task classification using deep learning for images and computer vision for videos.

RESULTS

Classifying the stomach's location from the endoscope without SMOTE for images resulted in 89% and 84% testing and validation accuracy, respectively. For classifying the location of the stomach from the endoscope with SMOTE, the accuracies were 97% and 90% for images, while for videos, the accuracies were 99% and 98% for testing and validation, respectively. For task classification, the accuracies were 97% and 89% for images, while for videos, the accuracies were 100% for both testing and validation, respectively.

CONCLUSION

We classified the four different stomach parts manipulated during the ESG procedure with 97% training accuracy and classified two repeated tasks with 99% training accuracy with images. We also classified the four parts of the stomach with a 99% training accuracy and two repeated tasks with a 100% training accuracy with video frames. This work will be essential in automating feedback mechanisms for learners in ESG.

Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Transcranial Direct Current Stimulation (tDCS) has demonstrated its potential in enhancing surgical training and performance compared to sham tDCS. However, optimizing its efficacy requires the selection of appropriate brain targets informed by neuroimaging and mechanistic understanding. Previous studies have established the feasibility of using portable brain imaging, combining functional near-infrared spectroscopy (fNIRS) with tDCS during Fundamentals of Laparoscopic Surgery (FLS) tasks. This allows concurrent monitoring of cortical activations. Building on these foundations, our study aimed to explore the multi-modal imaging of the brain response using fNIRS and electroencephalogram (EEG) to tDCS targeting the right cerebellar (CER) and left ventrolateral prefrontal cortex (PFC) during a challenging FLS suturing with intracorporeal knot tying task. Involving twelve novices with a medical/premedical background (age: 22-28 years, two males, 10 females with one female with left-hand dominance), our investigation sought mechanistic insights into tDCS effects on brain areas related to error-based learning, a fundamental skill acquisition mechanism. The results revealed that right CER tDCS applied to the posterior lobe elicited a statistically significant (q < 0.05) brain response in bilateral prefrontal areas at the onset of the FLS task, surpassing the response seen with sham tDCS. Additionally, right CER tDCS led to a significant (p < 0.05) improvement in FLS scores compared to sham tDCS. Conversely, the left PFC tDCS did not yield a statistically significant brain response or improvement in FLS performance. In conclusion, right CER tDCS demonstrated the activation of bilateral prefrontal brain areas, providing valuable mechanistic insights into the effects of CER tDCS on FLS peformance. These insights motivate future investigations into the effects of CER tDCS on error-related perception-action coupling through directed functional connectivity studies.

Distinguishing Laparoscopic Surgery Experts from Novices Using EEG Topographic Features

The study aimed to differentiate experts from novices in laparoscopic surgery tasks using electroencephalogram (EEG) topographic features. A microstate-based common spatial pattern (CSP) analysis with linear discriminant analysis (LDA) was compared to a topography-preserving convolutional neural network (CNN) approach. Expert surgeons (N = 10) and novice medical residents (N = 13) performed laparoscopic suturing tasks, and EEG data from 8 experts and 13 novices were analysed. Microstate-based CSP with LDA revealed distinct spatial patterns in the frontal and parietal cortices for experts, while novices showed frontal cortex involvement. The 3D CNN model (ESNet) demonstrated a superior classification performance (accuracy > 98%, sensitivity 99.30%, specificity 99.70%, F1 score 98.51%, MCC 97.56%) compared to the microstate based CSP analysis with LDA (accuracy ~90%). Combining spatial and temporal information in the 3D CNN model enhanced classifier accuracy and highlighted the importance of the parietal-temporal-occipital association region in differentiating experts and novices.

Cognitive Task Analysis of Escharotomy

INTRODUCTION

With the Army's emerging doctrine of prolonged field care, and with burns being a common injury among soldiers, non-expert providers must be trained to perform escharotomy when indicated. However, the existing physical simulators and training protocols are not sufficient for training non-experts for performing effective escharotomy. Hence, to provide guidance in developing realistic escharotomy simulators and effective training protocols suitable for prolonged field care, a cognitive task analysis (CTA) is needed. This work aims to obtain educative information from expert burn surgeons regarding escharotomy procedures via the CTA.

MATERIALS AND METHODS

The CTA was done by interviewing five subject matter experts with experience in performing escharotomy ranging from 20 to over 100 procedures and analyzing their responses. Interview questions were developed to obtain educative information from expert burn surgeons regarding the escharotomy procedure. A "gold standard protocol" was developed based on the CTA of each of the subject matter experts.

RESULTS

The CTA helped identify general themes, including objectives, conditions that mandate escharotomy, signs of successful escharotomy, precautions, challenges, decisions, and performance standards, and specific learning goals such as the use of equipment, vital signs, performing the procedure, and preoperative and postoperative care. A unique aspect of this CTA is that it identifies the background information and preparations that could be useful to the practitioners at various levels of expertise.

CONCLUSIONS

The CTA enabled us to compile a "gold standard protocol" for escharotomy that may serve as a guide for practitioners at various levels of expertise. This information will provide a framework for escharotomy training systems and simulators.

Split & Join: An Efficient Approach for Simulating Stapled Intestinal Anastomosis in Virtual Reality

Colorectal cancer is a life-threatening disease. It is the second leading cause of cancer-related deaths in the United States. Stapled anastomosis is a rapid treatment for colorectal cancer and other intestinal diseases and has become an integral part of routine surgical practice. However, to the best of our knowledge, there is no existing work simulating intestinal anastomosis that often involves sophisticated soft tissue manipulations such as cutting and stitching. In this paper, for the first time, we propose a novel split and join approach to simulate a side-to-side stapled intestinal anastomosis in virtual reality. We mimic the intestine model using a new hybrid representation - a grid-linked particles model for physics simulation and a surface mesh for rendering. The proposed split and join operations handle the updates of both the grid-linked particles model and the surface mesh during the anastomosis procedure. The simulation results demonstrate the feasibility of the proposed approach in simulating intestine models and the side-to-side anastomosis operation.

Assessment of Surgical Tasks Using Neuroimaging Dataset (ASTaUND)

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging tool for studying brain activity in mobile subjects. Open-access fNIRS datasets are limited to simple and/or motion-restricted tasks. Here, we report a fNIRS dataset acquired on mobile subjects performing Fundamentals of Laparoscopic Surgery (FLS) tasks in a laboratory environment. Demonstrating competency in the FLS tasks is a prerequisite for board certification in general surgery in the United States. The ASTaUND data set was acquired over four different studies. We provide the relevant information about the hardware, FLS task execution protocols, and subject demographics to facilitate the use of this open-access data set. We also provide the concurrent FLS scores, a quantitative metric for surgical skill assessment developed by the FLS committee. This data set is expected to support the growing field of assessing surgical skills via neuroimaging data and provide an example of data processing pipeline for use in realistic, non-restrictive environments.

Review of management practices of sinogenic intracranial abscesses in children

OBJECTIVE

This study aimed to evaluate the management practices and outcomes in children with sinogenic intracranial suppuration.

METHOD

This was a retrospective cohort study in a single paediatric tertiary unit that included patients younger than 18 years with radiologically confirmed intracranial abscess, including subdural empyema and epidural or intraparenchymal abscess secondary to sinusitis. Main outcomes studied were rate of return to the operating theatre, length of hospital stay, death in less than 90 days and neurological disability at 6 months.

RESULTS

A cohort of 39 consecutive patients presenting between 2000 and 2020 were eligible for inclusion. Subdural empyema was the most common intracranial complication followed by extradural abscess and intraparenchymal abscess. Mean length of hospital stay was 42 days. Sixteen patients were managed with combined ENT and neurosurgical interventions, 15 patients underwent ENT procedures alone and 4 patients had only neurosurgical drainage. Four patients initially underwent non-operative management. The rates of return to the operating theatre, neurological deficits and 90-day mortality were 19, 9 and 3, respectively, and were comparable across the 4 treatment arms. In the univariate logistic regression, only the size of an intracranial abscess was found be associated with an increased likelihood of return to the operating theatre, whereas combined ENT and neurosurgical intervention did not result in improved outcomes.

CONCLUSION

Sinogenic intracranial abscesses are associated with significant morbidity and mortality. The size of an intracranial abscess has a strong association with a need for a revision surgery.

What are essential laparoscopic skills these days? Results of the SAGES Fundamentals of Laparoscopic Surgery (FLS) Committee technical skills survey

INTRODUCTION

The Fundamentals of Laparoscopic Surgery (FLS) program tests basic knowledge and skills required to perform laparoscopic surgery. Educational experiences in laparoscopic training and development of associated competencies have evolved since FLS inception, making it important to review the definition of fundamental laparoscopic skills. The Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) assigned an FLS Technical Skills Working Group to characterize technical skills used in basic laparoscopic surgery in current practice contexts and their possible application to future FLS tests.

METHODS

A group of subject matter experts defined an inventory of 65 laparoscopic skills using a Nominal Group Technique. From these, a survey was developed rating these items for importance, frequency of use, and priority for testing for FLS certification. This survey was distributed to SAGES members, recent recipients of FLS certification, and members of the Association of Program Directors in Surgery (APDS). Results were collected using a secure web-based survey platform.

RESULTS

Complete data were available for 1742 surveys. Of these, 1143 comprised results for post-residency participants who performed advanced procedures. Seventeen competencies were identified for FLS testing prioritization by determining the proportion of respondents who identified them of highest priority, at median (50th percentile) of the maximum survey scale rating. These included basic peritoneal access, laparoscope and instrument use, tissue manipulation, and specific problem management skills. Sixteen could be used to show appropriateness of the domain construct by confirmatory factor analysis. Of these 8 could be characterized as manipulative tasks. Of these 5 mapped to current FLS tasks.

CONCLUSIONS

This survey-identified competencies, some of which are currently assessed in FLS, with a high level of priority for testing. Further work is needed to determine if this should prompt consideration of changes or additions to the FLS technical skills test component.

Efficient Indirect Interatomic Coulombic Decay Induced by Photoelectron Impact Excitation in Large Pure Helium Nanodroplets

Ionization of matter by energetic radiation generally causes complex secondary reactions that are hard to decipher. Using large helium nanodroplets irradiated by extreme ultraviolet (XUV) photons, we show that the full chain of processes ensuing primary photoionization can be tracked in detail by means of high-resolution electron spectroscopy. We find that elastic and inelastic scattering of photoelectrons efficiently induces interatomic Coulombic decay (ICD) in the droplets. This type of indirect ICD even becomes the dominant process of electron emission in nearly the entire XUV range in large droplets with radius ≳40  nm. Indirect ICD processes induced by electron scattering likely play an important role in other condensed-phase systems exposed to ionizing radiation as well, including biological matter.

Intelligent Virtual Operating Room for Enhancing Nontechnical Skills

This article discusses an intelligent immersive virtual operating room to enable teams to train in a distributed fashion wearing head-mounted displays.

Specular Reflection Removal for 3D Reconstruction of Tissues using Endoscopy Videos

Endoscopy is widely employed for diagnostic examination of the interior of organs and body cavities and numerous surgical interventions. Still, the inability to correlate individual 2D images with 3D organ morphology limits its applications, especially in intra-operative planning and navigation, disease physiology, cancer surveillance, etc. As a result, most endoscopy videos, which carry enormous data potential, are used only for real-time guidance and are discarded after collection. We present a complete method for the 3D reconstruction of inner organs that suggests image extraction techniques from endoscopic videos and a novel image pre-processing technique to reconstruct and visualize a 3D model of organs from an endoscopic video. We use advanced computer vision methods and do not require any modifications to the clinical-grade endoscopy hardware. We have also formalized an image acquisition protocol through experimentation with a calibrated test bed. We validate the accuracy and robustness of our reconstruction using a test bed with known ground truth. Our method can significantly contribute to endoscopy-based diagnostic and surgical procedures using comprehensive tissue and tumor 3D visualization.

Changes in functional neuroimaging measures as novices gain proficiency on the fundamentals of laparoscopic surgery suturing task

Significance

As trainees practice fundamental surgical skills, they typically rely on performance measures such as time and errors, which are limited in their sensitivity.

Aim

The goal of our study was to evaluate the use of portable neuroimaging measures to map the neural processes associated with learning basic surgical skills.

Approach

Twenty-one subjects completed 15 sessions of training on the fundamentals of laparoscopic surgery (FLS) suture with intracorporeal knot-tying task in a box trainer. Functional near infrared spectroscopy data were recorded using an optode montage that covered the prefrontal and sensorimotor brain areas throughout the task. Average oxy-hemoglobin (HbO) changes were determined for repetitions performed during the first week of training compared with the third week of training. Statistical differences between the time periods were evaluated using a general linear model of the HbO changes.

Results

Average performance scores across task repetitions increased significantly from the first day to the last day of training ( p < 0.01 ). During the first day of training, there was significant lateral prefrontal cortex (PFC) activation. On the final day, significant activation was observed in the PFC, as well as the sensorimotor areas. When comparing the two periods, significant differences in activation ( p < 0.05 ) were found for the right medial PFC and the right inferior parietal gyrus. While gaining proficiency, trainees activated the perception-action cycle to build a perceptual model and then apply the model to improve task execution.

Conclusions

Learners engaged the sensorimotor areas more substantially as they developed skill on the FLS suturing task. These findings are consistent with findings for the FLS pattern cutting task and contribute to the development of objective metrics for skill evaluation.

A statistical machine learning approach linking molecular conformational changes to altered mechanical characteristics of skin due to thermal injury

This article develops statistical machine learning models to predict the mechanical properties of skin tissue subjected to thermal injury based on the Raman spectra associated with conformational changes of the molecules in the burned tissue. Ex vivo porcine skin tissue samples were exposed to controlled burn conditions at 200 °F for five different durations: (i) 10s, (ii) 20s, (iii) 30s, (iv) 40s, and (v) 50s. For each burn condition, Raman spectra of wavenumbers 500-2000 cm^-1 were measured from the tissue samples, and tensile testing on the same samples yielded their material properties, including, ultimate tensile strain, ultimate tensile stress, and toughness. Partial least squares regression models were established such that the Raman spectra, describing conformational changes in the tissue, could accurately predict ultimate tensile stress, toughness, and ultimate tensile strain of the burned skin tissues with R² values of 0.8, 0.8, and 0.7, respectively, using leave-two-out cross validation scheme. An independent assessment of the resultant models showed that amino acids, proteins & lipids, and amide III components of skin tissue significantly influence the prediction of the properties of the burned skin tissue. In contrast, amide I has a lesser but still noticeable effect. These results are consistent with similar observations found in the literature on the mechanical characterization of burned skin tissue.

Skill-level classification and performance evaluation for endoscopic sleeve gastroplasty

BACKGROUND

We previously developed grading metrics for quantitative performance measurement for simulated endoscopic sleeve gastroplasty (ESG) to create a scalar reference to classify subjects into experts and novices. In this work, we used synthetic data generation and expanded our skill level analysis using machine learning techniques.

METHODS

We used the synthetic data generation algorithm SMOTE to expand and balance our dataset of seven actual simulated ESG procedures using synthetic data. We performed optimization to seek optimum metrics to classify experts and novices by identifying the most critical and distinctive sub-tasks. We used support vector machine (SVM), AdaBoost, K-nearest neighbors (KNN) Kernel Fisher discriminant analysis (KFDA), random forest, and decision tree classifiers to classify surgeons as experts or novices after grading. Furthermore, we used an optimization model to create weights for each task and separate the clusters by maximizing the distance between the expert and novice scores.

RESULTS

We split our dataset into a training set of 15 samples and a testing dataset of five samples. We put this dataset through six classifiers, SVM, KFDA, AdaBoost, KNN, random forest, and decision tree, resulting in 0.94, 0.94, 1.00, 1.00, 1.00, and 1.00 accuracy, respectively, for training and 1.00 accuracy for the testing results for SVM and AdaBoost. Our optimization model maximized the distance between the expert and novice groups from 2 to 53.72.

CONCLUSION

This paper shows that feature reduction, in combination with classification algorithms such as SVM and KNN, can be used in tandem to classify endoscopists as experts or novices based on their results recorded using our grading metrics. Furthermore, this work introduces a non-linear constraint optimization to separate the two clusters and find the most important tasks using weights.

Synthetic tissues lack the fidelity for the use in burn care simulators

This work compares the mechanical response of synthetic tissues used in burn care simulators from ten different manufacturers with that of ex vivo full thickness burned porcine skin as a surrogate for human skin tissues. This is of high practical importance since incorrect mechanical properties of synthetic tissues may introduce a negative bias during training due to the inaccurate haptic feedback from burn care simulator. A negative training may result in inadequately performed procedures, such as in escharotomy, which may lead to muscle necrosis endangering life and limb. Accurate haptic feedback in physical simulators is necessary to improve the practical training of non-expert providers for pre-deployment/pre-hospital burn care. With the U.S. Army's emerging doctrine of prolonged field care, non-expert providers must be trained to perform even invasive burn care surgical procedures when indicated. The comparison reported in this article is based on the ultimate tensile stress, ultimate tensile strain, and toughness that are measured at strain rates relevant to skin surgery. A multivariate analysis using logistic regression reveals significant differences in the mechanical properties of the synthetic and the porcine skin tissues. The synthetic and porcine skin tissues show a similar rate dependent behavior. The findings of this study are expected to guide the development of high-fidelity burn care simulators for the pre-deployment/pre-hospital burn care provider education.

Error-related brain state analysis using electroencephalography in conjunction with functional near-infrared spectroscopy during a complex surgical motor task

Error-based learning is one of the basic skill acquisition mechanisms that can be modeled as a perception-action system and investigated based on brain-behavior analysis during skill training. Here, the error-related chain of mental processes is postulated to depend on the skill level leading to a difference in the contextual switching of the brain states on error commission. Therefore, the objective of this paper was to compare error-related brain states, measured with multi-modal portable brain imaging, between experts and novices during the Fundamentals of Laparoscopic Surgery (FLS) "suturing and intracorporeal knot-tying" task (FLS complex task)-the most difficult among the five psychomotor FLS tasks. The multi-modal portable brain imaging combined functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) for brain-behavior analysis in thirteen right-handed novice medical students and nine expert surgeons. The brain state changes were defined by quasi-stable EEG scalp topography (called microstates) changes using 32-channel EEG data acquired at 250 Hz. Six microstate prototypes were identified from the combined EEG data from experts and novices during the FLS complex task that explained 77.14% of the global variance. Analysis of variance (ANOVA) found that the proportion of the total time spent in different microstates during the 10-s error epoch was significantly affected by the skill level (p < 0.01), the microstate type (p < 0.01), and the interaction between the skill level and the microstate type (p < 0.01). Brain activation based on the slower oxyhemoglobin (HbO) changes corresponding to the EEG band power (1-40 Hz) changes were found using the regularized temporally embedded Canonical Correlation Analysis of the simultaneously acquired fNIRS-EEG signals. The HbO signal from the overlying the left inferior frontal gyrus-opercular part, left superior frontal gyrus-medial orbital, left postcentral gyrus, left superior temporal gyrus, right superior frontal gyrus-medial orbital cortical areas showed significant (p < 0.05) difference between experts and novices in the 10-s error epoch. We conclude that the difference in the error-related chain of mental processes was the activation of cognitive top-down attention-related brain areas, including left dorsolateral prefrontal/frontal eye field and left frontopolar brain regions, along with a 'focusing' effect of global suppression of hemodynamic activation in the experts, while the novices had a widespread stimulus(error)-driven hemodynamic activation without the 'focusing' effect.

Development and Validation of Task-Specific Metrics for the Assessment of Linear Stapler-Based Small Bowel Anastomosis

INTRODUCTION

Task-specific metrics facilitate the assessment of surgeon performance. This 3-phased study was designed to (1) develop task-specific metrics for stapled small bowel anastomosis, (2) obtain expert consensus on the appropriateness of the developed metrics, and (3) establish its discriminant validity.

METHODS

In Phase I, a hierarchical task analysis was used to develop the metrics. In Phase II, a survey of expert colorectal surgeons established the importance of the developed metrics. In Phase III, to establish discriminant validity, surgical trainees and surgeons, divided into novice and experienced groups, constructed a side-to-side anastomosis on porcine small bowel using a linear cutting stapler. The participants' performances were videotaped and rated by 2 independent observers. Partial least squares regression was used to compute the weights for the task-specific metrics to obtain weighted total score.

RESULTS

In Phase II, a total of 45 colorectal surgeons were surveyed: 28 with more than 15 years, 13 with 5 to 15 years, and 4 with less than 5 years of experience. The consensus was obtained on all the task-specific metrics in the more experienced groups. In Phase III, 20 subjects participated equally in both groups. The experienced group performed better than the novice group regardless of the rating scale used: global rating scale (p = 0.009) and the task-specific metrics (p = 0.012). After partial least squares regression, the weighted task-specific metric score continued to show that the experienced group performed better (p < 0.001).

CONCLUSION

Task-specific metric items were developed based on expert consensus and showed good discriminant validity compared with a global rating scale between experienced and novice operators. These items can be used for evaluating technical skills in a stapled small bowel anastomosis model.

Deep learning-based motion artifact removal in functional near-infrared spectroscopy

Significance: Functional near-infrared spectroscopy (fNIRS), a well-established neuroimaging technique, enables monitoring cortical activation while subjects are unconstrained. However, motion artifact is a common type of noise that can hamper the interpretation of fNIRS data. Current methods that have been proposed to mitigate motion artifacts in fNIRS data are still dependent on expert-based knowledge and the post hoc tuning of parameters. Aim: Here, we report a deep learning method that aims at motion artifact removal from fNIRS data while being assumption free. To the best of our knowledge, this is the first investigation to report on the use of a denoising autoencoder (DAE) architecture for motion artifact removal. Approach: To facilitate the training of this deep learning architecture, we (i) designed a specific loss function and (ii) generated data to mimic the properties of recorded fNIRS sequences. Results: The DAE model outperformed conventional methods in lowering residual motion artifacts, decreasing mean squared error, and increasing computational efficiency. Conclusion: Overall, this work demonstrates the potential of deep learning models for accurate and fast motion artifact removal in fNIRS data.

Deep learning in fNIRS: a review

Significance: Optical neuroimaging has become a well-established clinical and research tool to monitor cortical activations in the human brain. It is notable that outcomes of functional near-infrared spectroscopy (fNIRS) studies depend heavily on the data processing pipeline and classification model employed. Recently, deep learning (DL) methodologies have demonstrated fast and accurate performances in data processing and classification tasks across many biomedical fields. Aim: We aim to review the emerging DL applications in fNIRS studies. Approach: We first introduce some of the commonly used DL techniques. Then, the review summarizes current DL work in some of the most active areas of this field, including brain-computer interface, neuro-impairment diagnosis, and neuroscience discovery. Results: Of the 63 papers considered in this review, 32 report a comparative study of DL techniques to traditional machine learning techniques where 26 have been shown outperforming the latter in terms of the classification accuracy. In addition, eight studies also utilize DL to reduce the amount of preprocessing typically done with fNIRS data or increase the amount of data via data augmentation. Conclusions: The application of DL techniques to fNIRS studies has shown to mitigate many of the hurdles present in fNIRS studies such as lengthy data preprocessing or small sample sizes while achieving comparable or improved classification accuracy.

Directed information flow during laparoscopic surgical skill acquisition dissociated skill level and medical simulation technology

Virtual reality (VR) simulator has emerged as a laparoscopic surgical skill training tool that needs validation using brain-behavior analysis. Therefore, brain network and skilled behavior relationship were evaluated using functional near-infrared spectroscopy (fNIRS) from seven experienced right-handed surgeons and six right-handed medical students during the performance of Fundamentals of Laparoscopic Surgery (FLS) pattern of cutting tasks in a physical and a VR simulator. Multiple regression and path analysis (MRPA) found that the FLS performance score was statistically significantly related to the interregional directed functional connectivity from the right prefrontal cortex to the supplementary motor area with F (2, 114) = 9, p < 0.001, and R² = 0.136. Additionally, a two-way multivariate analysis of variance (MANOVA) found a statistically significant effect of the simulator technology on the interregional directed functional connectivity from the right prefrontal cortex to the left primary motor cortex (F (1, 15) = 6.002, p = 0.027; partial η² = 0.286) that can be related to differential right-lateralized executive control of attention. Then, MRPA found that the coefficient of variation (CoV) of the FLS performance score was statistically significantly associated with the CoV of the interregionally directed functional connectivity from the right primary motor cortex to the left primary motor cortex and the left primary motor cortex to the left prefrontal cortex with F (2, 22) = 3.912, p = 0.035, and R² = 0.262. This highlighted the importance of the efference copy information from the motor cortices to the prefrontal cortex for postulated left-lateralized perceptual decision-making to reduce behavioral variability.

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.

Modeling Haptic Interactions in Endoscopic Submucosal Dissection (ESD)

The ability to provide realistic haptic feedback is indispensable for virtual-reality (VR) based endoscopic colorectal surgery simulators. Despite its importance, force feedback is commonly simulated by simplified approximations with parameters manually tuned in preliminary evaluations due to the complexity of the dynamics of haptic interaction in colonoscopy interventions. Endoscopic submucosal dissection (ESD) is a particularly challenging intervention that requires advanced manual skills for endoscopic control. This work proposes a mechanical impedance model for haptic interactions in ESD formulated via an experimental methodology applied to endoscopic colorectal interventions in general. The developed model is shown to capture the variations in the interaction force during two operations performed at distinct locations on a porcine sample. Salient cues in the recorded haptic interaction data are presented, and changes in the impedance characteristics of the tool-tissue interaction between the steps of the operation are analyzed.

Error related fNIRS-EEG microstate analysis during a complex surgical motor task

Fundamentals of Laparoscopic Surgery (FLS) is a standard education and training module with a set of basic surgical skills. During surgical skill acquisition, novices need to learn from errors due to perturbations in their performance which is one of the basic principles of motor skill acquisition. This study on thirteen healthy novice medical students and nine expert surgeons aimed to capture the brain state during error epochs using multimodal brain imaging by combining functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). We performed error-related microstate analysis in the latent space that was found using regularized temporally embedded Canonical Correlation Analysis from fNIRS-EEG recordings during the performance of FLS "suturing and intracorporeal knot-tying" task - the most difficult among the five psychomotor FLS tasks. We found from two-way analysis of variance (ANDVA) with factors, skill level (expert, novice), and microstate type (1-6) that the proportion of the total time spent in microstates in the error epochs was significantly affected by the skill level ( ), microstate type ( ), and the interaction between the skill level and the microstate type ( ). Therefore, our study highlighted the relevance of portable brain imaging to capture error behavior when comparing the skill level during a complex surgical task. Clinical Relevance-This establishes the brain-behavior relationship for monitoring complex surgical motor task errors that differentiated experts from novices.

Isoniazid preventive therapy among child contacts of TB patients, India

BACKGROUND: Isoniazid preventive therapy (IPT) for child contacts of TB patients, a globally accepted intervention, needs to be evaluated in diverse geographical regions.OBJECTIVES: To assess the extent of IPT coverage and adherence, to ascertain its sociodemographic and programmatic correlates and to explore existing constraints from service providers and beneficiaries´ perspectives.METHODS: A mixed-method study was conducted in January-June 2021 in Paschim Bardhaman District, West Bengal, India. Quantitative assessment was done among 280 child contacts of TB cases registered between January and December 2020 in all TB units in the district. Primary caregivers were interviewed using a pre-designed questionnaire. Two focus group discussions with all senior treatment supervisors of the district and in-depth interviews with 12 purposively selected caregivers of the children were undertaken. Qualitative data were analysed thematically.RESULTS: Only 48.9% (137/280) of child contacts were screened; 58.9% (165/280) were initiated on IPT and 40% (66/165) adhered to a full course. Coverage of the full 6-month IPT among total study participants was 23.6% (66/280). Household visits by health personnel and initial screening significantly predicted increased coverage. Programmatic inadequacies, poor understanding, social stigma and COVID situation were major constraints.CONCLUSION: Coverage of IPT remains unacceptably low and requires health system strengthening for effectively implementing current recommendations of TB preventive treatment.

Hypertriton Production in p-Pb Collisions at sqrt[s_{NN}]=5.02 TeV

The study of nuclei and antinuclei production has proven to be a powerful tool to investigate the formation mechanism of loosely bound states in high-energy hadronic collisions. The first measurement of the production of _{Λ}^{3}H in p-Pb collisions at sqrt[s_{NN}]=5.02  TeV is presented in this Letter. Its production yield measured in the rapidity interval -1<y<0 for the 40% highest-multiplicity p-Pb collisions is dN/dy=[6.3±1.8(stat)±1.2(syst)]×10^{-7}. The measurement is compared with the expectations of statistical hadronization and coalescence models, which describe the nucleosynthesis in hadronic collisions. These two models predict very different yields of the hypertriton in charged particle multiplicity environments relevant to small collision systems such as p-Pb, and therefore the measurement of dN/dy is crucial to distinguish between them. The precision of this measurement leads to the exclusion with a significance larger than 6.9σ of some configurations of the statistical hadronization model, thus constraining the theory behind the production of loosely bound states at hadron colliders.

Does your team know how to respond safely to an operating room fire? Outcomes of a virtual reality, AI-enhanced simulation training

BACKGROUND

Operating room (OR) fires are rare but devastating events requiring immediate and effective response. Virtual Reality (VR) simulation training can provide a safe environment for practice of skills in such highly stressful situation. This study assessed interprofessional participants' ability to respond to VR-simulated OR fire scenarios, attitudes, numbers of attempt of the VR simulation do participants need to successfully respond to OR fires and does prior experience, confidence level, or professional role predict the number of attempts needed to demonstrate safety and pass the simulation.

METHODS

180 surgical team members volunteered to participate in this study at Beth Israel Deaconess Medical Center, Boston, MA. Each participant completed five VR OR simulation trials; the final two trials incorporated AI assistance. Primary outcomes were performance scores, number of attempts needed to pass, and pre- and post-survey results describing participant confidence and experiences. Differences across professional or training role were assessed using chi-square tests and analyses of variance. Differences in pass rates over time were assessed using repeated measures logistic regression.

RESULTS

One hundred eighty participants completed simulation testing; 170 (94.4%) completed surveys. Participants included surgeons (17.2%), anesthesiologists (10.0%), allied health professionals (41.7%), and medical trainees (31.1%). Prior to training, 45.4% of participants reported feeling moderately or very confident in their ability to respond to an OR fire. Eight participants (4.4%) responded safely on the first simulation attempt. Forty-three participants (23.9%) passed by the third attempt (VR only); an additional 97 participants (53.9%) passed within the 4-5th attempt (VR with AI assistance).

CONCLUSIONS

Providers are unprepared to respond to OR fires. VR-based simulation training provides a practical platform for individuals to improve their knowledge and performance in the management of OR fires with a 79% pass rate in our study. A VR AI approach to teaching this essential skill is innovative, feasible, and effective.

Polarization of Λ and Λ[over ¯] Hyperons along the Beam Direction in Pb-Pb Collisions at sqrt[s]_{NN}=5.02 TeV

The polarization of the Λ and Λ[over ¯] hyperons along the beam (z) direction, P_{z}, has been measured in Pb-Pb collisions at sqrt[s_{NN}]=5.02  TeV recorded with ALICE at the Large Hadron Collider (LHC). The main contribution to P_{z} comes from elliptic flow-induced vorticity and can be characterized by the second Fourier sine coefficient P_{z,s2}=⟨P_{z}sin(2φ-2Ψ_{2})⟩, where φ is the hyperon azimuthal emission angle and Ψ_{2} is the elliptic flow plane angle. We report the measurement of P_{z,s2} for different collision centralities and in the 30%-50% centrality interval as a function of the hyperon transverse momentum and rapidity. The P_{z,s2} is positive similarly as measured by the STAR Collaboration in Au-Au collisions at sqrt[s_{NN}]=200  GeV, with somewhat smaller amplitude in the semicentral collisions. This is the first experimental evidence of a nonzero hyperon P_{z} in Pb-Pb collisions at the LHC. The comparison of the measured P_{z,s2} with the hydrodynamic model calculations shows sensitivity to the competing contributions from thermal and the recently found shear-induced vorticity, as well as to whether the polarization is acquired at the quark-gluon plasma or the hadronic phase.

Training on a virtual reality cricothyroidotomy simulator improves skills and transfers to a simulated procedure

Objective

The virtual airway skills trainer (VAST) is a virtual reality simulator for training in cricothyroidotomy (CCT). The goal of the study is to test the effectiveness of training and transfer of skills of the VAST-CCT.

Methods

Two groups, control (no training) and simulation (2 weeks of proficiency-based training), participated in this study. Subjects in the control condition did not receive any training on the task whereas those in the simulation received a proficiency-based training on the task during a period of 2 weeks. Two weeks post-training, both groups performed CCT on the TraumaMan to demonstrate the transfer of skills.

Results

A total of (n=20) subjects participated in the study. The simulation group performed better than the control group at both the post-test (p<0.001) and retention test (p<0.001) on the simulator. The cumulative sum analysis showed that all subjects in the simulation group reached proficiency with acceptable failure rate within the 2 weeks of training. On the transfer test, the simulation group performed better on skin cut (p<0.001), intubation (p<0.001) and total score (p<0.001) than the control group.

Conclusions

The VAST-CCT is effective in training and skills transfer for the CCT procedure.

Level of evidence

Not applicable. Simulator validation study.

Comparison of Antibiotic Use between the First Two Waves of COVID-19 in an Intensive Care Unit at a London Tertiary Centre: reducing broad-spectrum antimicrobial use did not adversely affect mortality

BACKGROUND

The COVID-19 pandemic increased the use of broad-spectrum antibiotics due to diagnostic uncertainty, particularly in critical care. Multiprofessional communication became more difficult, weakening stewardship activities.

AIM

To determine changes in bacterial co-/secondary infections and antibiotics used in COVID-19 patients in critical care, and mortality rates, between the first and second waves.

METHODS

Prospective audit comparing bacterial co-/secondary infections and their treatment during the first two waves of the pandemic in a single centre teaching hospital ICU. Data on demographics, daily antibiotic use, clinical outcomes, and culture results in patients diagnosed with COVID-19 infection were collected over 11 months.

FINDINGS

From 9/3/20 to 2/9/20 (Wave 1), there were 156 patients and between 3/9/20 and 1/2/21 (Wave 2) there were 235 patients with COVID-19 infection admitted to intensive care. No significant difference was seen in mortality or positive blood culture rates between the two waves. The proportion of patients receiving antimicrobial therapy (93.0% vs 81.7%; p<0.01), and the duration of meropenem use (median (interquartile range): 5 (2-7) vs 3 (2-5) days; p=0.01) was lower in Wave 2. However, the number of patients with respiratory isolates of Pseudomonas aeruginosa (4/156 vs 21/235; p<0.01) and bacteraemia from a respiratory source (3/156 vs 20/235 p<0.01) increased in Wave 2, associated with an outbreak of infection. There was no significant difference between waves with respect to isolation of other pathogens.

CONCLUSIONS

Reduced broad spectrum antimicrobial use in the second wave of COVID-19 compared with the first wave was not associated with significant change in mortality.

Thermally damaged porcine skin is not a surrogate mechanical model of human skin

Porcine skin is considered a de facto surrogate for human skin. However, this study shows that the mechanical characteristics of full thickness burned human skin are different from those of porcine skin. The study relies on five mechanical properties obtained from uniaxial tensile tests at loading rates relevant to surgery: two parameters of the Veronda-Westmann hyperelastic material model, ultimate tensile stress, ultimate tensile strain, and toughness of the skin samples. Univariate statistical analyses show that human and porcine skin properties are dissimilar (p < 0.01) for each loading rate. Multivariate classification involving the five mechanical properties using logistic regression can successfully separate the two skin types with a classification accuracy exceeding 95% for each loading rate individually as well as combined. The findings of this study are expected to guide the development of effective training protocols and high-fidelity simulators to train burn care providers.

Measurement of the Groomed Jet Radius and Momentum Splitting Fraction in pp and Pb-Pb Collisions at sqrt[s_{NN}]=5.02 TeV

This article presents groomed jet substructure measurements in pp and Pb-Pb collisions at sqrt[s_{NN}]=5.02  TeV with the ALICE detector. The soft drop grooming algorithm provides access to the hard parton splittings inside a jet by removing soft wide-angle radiation. We report the groomed jet momentum splitting fraction, z_{g}, and the (scaled) groomed jet radius, θ_{g}. Charged-particle jets are reconstructed at midrapidity using the anti-k_{T} algorithm with resolution parameters R=0.2 and R=0.4. In heavy-ion collisions, the large underlying event poses a challenge for the reconstruction of groomed jet observables, since fluctuations in the background can cause groomed parton splittings to be misidentified. By using strong grooming conditions to reduce this background, we report these observables fully corrected for detector effects and background fluctuations for the first time. A narrowing of the θ_{g} distribution in Pb-Pb collisions compared to pp collisions is seen, which provides direct evidence of the modification of the angular structure of jets in the quark-gluon plasma. No significant modification of the z_{g} distribution in Pb-Pb collisions compared to pp collisions is observed. These results are compared with a variety of theoretical models of jet quenching, and provide constraints on jet energy-loss mechanisms and coherence effects in the quark-gluon plasma.

Phosphonomethyl iminodiacetic acid functionalized metal organic framework supported PAN composite beads for selective removal of La(III) from wastewater: Adsorptive performance and column separation studies

The rare earth elements being toxic in nature are being accumulated in water bodies as their industrial usage is growing exponentially, thus their efficient separation holds an immense significance. Herein, ligand functionalized metal organic framework (MOF), Phosphonomethyl iminodiacetic acid coordinated at Fe-BTC, was synthesized post-synthetically and incorporated subsequently in polyacrylonitrile polymer to prepare the composite beads via nonsolvent induced-phase-inversion technique for selective adsorption of La(III) from the wastewater in batch and dynamic column mode. XPS NMR, and FTIR were used to establish the interaction between functionalized ligand and unsaturated metal nodes of MOF. The adsorption capacity was 232.5 mg/g and 77.51 mg/g at 298 K of the functionalized MOF and composite beads respectively. Adsorption kinetics followed a pseudo-second order rate equation, and isotherm indicated the best fitting with Langmuir model. The dynamic behavior of the adsorption column packed with MOF/Polymer beads was fairly described by the Thomas model. The breakthrough time of 23.2 h could be attained with 12 cm of bed height and 10 ml/min of flow rate. These MOF/Polymer beads shown the selectivity of La over transitional metals were recycled over 5 times with about 15% loss of adsorption capacity. The findings provide suggestive insights of the potential use of functionalized MOF towards the separation of the rare earth element.

Measurement of Prompt D^{0}, Λ_{c}^{+}, and Σ_{c}^{0,++}(2455) Production in Proton-Proton Collisions at sqrt[s]=13 TeV

The p_{T}-differential production cross sections of prompt D^{0}, Λ_{c}^{+}, and Σ_{c}^{0,++}(2455) charmed hadrons are measured at midrapidity (|y|<0.5) in pp collisions at sqrt[s]=13  TeV. This is the first measurement of Σ_{c}^{0,++} production in hadronic collisions. Assuming the same production yield for the three Σ_{c}^{0,+,++} isospin states, the baryon-to-meson cross section ratios Σ_{c}^{0,+,++}/D^{0} and Λ_{c}^{+}/D^{0} are calculated in the transverse momentum (p_{T}) intervals 2<p_{T}<12 and 1<p_{T}<24  GeV/c. Values significantly larger than in e^{+}e^{-} collisions are observed, indicating for the first time that baryon enhancement in hadronic collisions also extends to the Σ_{c}. The feed-down contribution to Λ_{c}^{+} production from Σ_{c}^{0,+,++} is also reported and is found to be larger than in e^{+}e^{-} collisions. The data are compared with predictions from event generators and other phenomenological models, providing a sensitive test of the different charm-hadronization mechanisms implemented in the models.

Measurement of the Cross Sections of Ξ_{c}^{0} and Ξ_{c}^{+} Baryons and of the Branching-Fraction Ratio BR(Ξ_{c}^{0}→Ξ^{-}e^{+}ν_{e})/BR(Ξ_{c}^{0}→Ξ^{-}π^{+}) in pp Collisions at sqrt[s]=13 TeV

The p_{T}-differential cross sections of prompt charm-strange baryons Ξ_{c}^{0} and Ξ_{c}^{+} were measured at midrapidity (|y|<0.5) in proton-proton (pp) collisions at a center-of-mass energy sqrt[s]=13  TeV with the ALICE detector at the LHC. The Ξ_{c}^{0} baryon was reconstructed via both the semileptonic decay (Ξ^{-}e^{+}ν_{e}) and the hadronic decay (Ξ^{-}π^{+}) channels. The Ξ_{c}^{+} baryon was reconstructed via the hadronic decay (Ξ^{-}π^{+}π^{+}) channel. The branching-fraction ratio BR(Ξ_{c}^{0}→Ξ^{-}e^{+}ν_{e})/BR(Ξ_{c}^{0}→Ξ^{-}π^{+})=1.38±0.14(stat)±0.22(syst) was measured with a total uncertainty reduced by a factor of about 3 with respect to the current world average reported by the Particle Data Group. The transverse momentum (p_{T}) dependence of the Ξ_{c}^{0}- and Ξ_{c}^{+}-baryon production relative to the D^{0} meson and to the Σ_{c}^{0,+,++}- and Λ_{c}^{+}-baryon production are reported. The baryon-to-meson ratio increases toward low p_{T} up to a value of approximately 0.3. The measurements are compared with various models that take different hadronization mechanisms into consideration. The results provide stringent constraints to these theoretical calculations and additional evidence that different processes are involved in charm hadronization in electron-positron (e^{+}e^{-}) and hadronic collisions.

Hierarchical task analysis of endoscopic sleeve gastroplasty

BACKGROUND

Endoscopic sleeve gastroplasty (ESG) is a minimally invasive endoscopic weight loss procedure used to treat obesity. The long-term goal of this project is to develop a Virtual Bariatric Endoscopy (ViBE) simulator for training and assessment of the ESG procedure. The objectives of this current work are to: (a) perform a task analysis of ESG and (b) create metrics to be validated in the created simulator.

METHODS

We performed a hierarchical task analysis (HTA) by identifying the significant tasks of the ESG procedure. We created the HTA to show the breakdown and connection of the tasks of the procedure. Utilizing the HTA and input from ESG experts, performance metrics were derived for objective measurement of the ESG procedure. Three blinded video raters analyzed seven recorded ESG procedures according to the proposed performance metrics.

RESULTS

Based on the seven videos, there was a positive correlation between total task times and total performance scores (R = 0.886, P = 0.008). Endoscopists expert were found to be more skilled in reducing the area of the stomach compared to endoscopists novice (34.6% reduction versus 9.4% reduction, P = 0.01). The mean novice performance score was significantly lower than the mean expert performance score (34.7 vs. 23.8, P = 0.047). The inter-rater reliability test showed a perfect agreement among three raters for all tasks except for the suturing task. The suturing task had a significant agreement (Inter-rater Correlation = 0.84, Cronbach's alpha = 0.88). Suturing was determined to be a critical task that is positively correlated with the total score (R = 0.962, P = 0.0005).

CONCLUSION

The task analysis and metrics development are critical for the development of the ViBE simulator. This preliminary assessment demonstrates that the performance metrics provide an accurate assessment of the endoscopist's performance. Further validation testing and refinement of the performance metrics are anticipated.

A deep learning model for burn depth classification using ultrasound imaging

Identification of burn depth with sufficient accuracy is a challenging problem. This paper presents a deep convolutional neural network to classify burn depth based on altered tissue morphology of burned skin manifested as texture patterns in the ultrasound images. The network first learns a low-dimensional manifold of the unburned skin images using an encoder-decoder architecture that reconstructs it from ultrasound images of burned skin. The encoder is then re-trained to classify burn depths. The encoder-decoder network is trained using a dataset comprised of B-mode ultrasound images of unburned and burned ex vivo porcine skin samples. The classifier is developed using B-mode images of burned in situ skin samples obtained from freshly euthanized postmortem pigs. The performance metrics obtained from 20-fold cross-validation show that the model can identify deep-partial thickness burns, which is the most difficult to diagnose clinically, with 99% accuracy, 98% sensitivity, and 100% specificity. The diagnostic accuracy of the classifier is further illustrated by the high area under the curve values of 0.99 and 0.95, respectively, for the receiver operating characteristic and precision-recall curves. A post hoc explanation indicates that the classifier activates the discriminative textural features in the B-mode images for burn classification. The proposed model has the potential for clinical utility in assisting the clinical assessment of burn depths using a widely available clinical imaging device.

Λ_{c}^{+} Production and Baryon-to-Meson Ratios in pp and p-Pb Collisions at sqrt[s_{NN}]=5.02 TeV at the LHC

The prompt production of the charm baryon Λ_{c}^{+} and the Λ_{c}^{+}/D^{0} production ratios were measured at midrapidity with the ALICE detector in pp and p-Pb collisions at sqrt[s_{NN}]=5.02  TeV. These new measurements show a clear decrease of the Λ_{c}^{+}/D^{0} ratio with increasing transverse momentum (p_{T}) in both collision systems in the range 2<p_{T}<12  GeV/c, exhibiting similarities with the light-flavor baryon-to-meson ratios p/π and Λ/K_{S}^{0}. At low p_{T}, predictions that include additional color-reconnection mechanisms beyond the leading-color approximation, assume the existence of additional higher-mass charm-baryon states, or include hadronization via coalescence can describe the data, while predictions driven by charm-quark fragmentation processes measured in e^{+}e^{-} and e^{-}p collisions significantly underestimate the data. The results presented in this Letter provide significant evidence that the established assumption of universality (colliding-system independence) of parton-to-hadron fragmentation is not sufficient to describe charm-baryon production in hadronic collisions at LHC energies.

Brain network effects related to physical and virtual surgical training revealed by Granger causality

this study investigates the difference in effective connectivity among novice medical students trained on physical and virtual simulators to perform the Fundamental laparoscopic surgery (FLS) pattern cutting task (PC). We propose using dynamic spectral Granger causality (GC) in the frequency band of [0.01-0.07]Hz to measure the effect of surgical training on effective brain connectivity. To obtain the dynamics relationship between the cortical regions, we propose to use the short-time Fourier transform (STFT) method. FLS pattern cutting is a complex bimanual task requiring fine motor skills and increased brain activity. With this in mind, we have used high resolution functional near-infrared spectroscopy to leverage its high temporal resolution for capturing the change in hemodynamics (HbO2) in 14 healthy subjects. Analysis of variance (ANOVA) found a statistically significant difference in "LPMC granger causes RPMC" (LPMC→ RPMC) in the subject trained on these two simulator in the first 40 sec of the task. We showed that the directed brain connectivity was affected by the type of surgical simulator used for training the medical students.

Neuroimaging guided tES to facilitate complex laparoscopic surgical tasks - insights from functional near-infrared spectroscopy

Fundamentals of Laparoscopic Surgery (FLS) is a prerequisite for board certification in general surgery in the USA. In FLS, the suturing task with intracorporeal knot tying is considered the most complex task. Transcranial direct current stimulation (tDCS) of the dorsolateral prefrontal cortex (PFC) has been shown to facilitate FLS surgical skill acquisition where 2mA tDCS for 15min with the anode over F3 (10/10 EEG montage) and cathode over F4 has improved performance score in an open knot-tying task. Since PFC has a functional organization related to the hierarchy of cognitive control, we performed functional near-infrared spectroscopy (fNIRS) to investigate PFC sub-domain activation during a more complex FLS suturing task with intracorporeal knot tying. We performed fNIRS-based analysis using AtlasViewer software on two expert surgeons and four novice medical students. We found an average cortical activation mainly at the left frontopolar PFC across the experts, while the average cortical activation across the novices was primarily at the left pars opercularis of the inferior frontal gyrus and ventral premotor cortex, inferior parietal lobule, and supramarginal gyrus. Here, the average cortical activation across the novices included not only the cognitive control related brain regions but also motor control complexity related brain regions. Therefore, we present a computational pipeline to identify a 4x1 high-definition (HD) tDCS montage of motor complexity related PFC sub-regions using ROAST software.Clinical Relevance-A computational pipeline for fNIRS-guided tES to individualize electrode montage that may facilitate FLS surgical training in our future studies.

Experimental Evidence for an Attractive p-ϕ Interaction

This Letter presents the first experimental evidence of the attractive strong interaction between a proton and a ϕ meson. The result is obtained from two-particle correlations of combined p-ϕ⊕ p[over ¯]-ϕ pairs measured in high-multiplicity pp collisions at sqrt[s]=13  TeV by the ALICE Collaboration. The spin-averaged scattering length and effective range of the p-ϕ interaction are extracted from the fully corrected correlation function employing the Lednický-Lyuboshits approach. In particular, the imaginary part of the scattering length vanishes within uncertainties, indicating that inelastic processes do not play a prominent role for the p-ϕ interaction. These data demonstrate that the interaction is dominated by elastic p-ϕ scattering. Furthermore, an analysis employing phenomenological Gaussian- and Yukawa-type potentials is conducted. Under the assumption of the latter, the N-ϕ coupling constant is found to be g_{N-ϕ}=0.14±0.03(stat)±0.02(syst). This work provides valuable experimental input to accomplish a self-consistent description of the N-ϕ interaction, which is particularly relevant for the more fundamental studies on partial restoration of chiral symmetry in nuclear medium.

Multiharmonic Correlations of Different Flow Amplitudes in Pb-Pb Collisions at sqrt[s_{NN}]=2.76 TeV

The event-by-event correlations between three flow amplitudes are measured for the first time in Pb-Pb collisions, using higher-order symmetric cumulants. We find that different three-harmonic correlations develop during the collective evolution of the medium when compared to correlations that exist in the initial state. These new results cannot be interpreted in terms of previous lower-order flow measurements since contributions from two-harmonic correlations are explicitly removed in the new observables. A comparison to Monte Carlo simulations provides new and independent constraints for the initial conditions and system properties of nuclear matter created in heavy-ion collisions.