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Malik Sallam,1– 3 Khaled Al-Salahat,1,3 Huda Eid,3 Jan Egger,4 Behrus Puladi5 1Department of Pathology, Microbiology and Forensic Medicine, School of Medicine, The University of Jordan, Amman, Jordan; 2Department of Clinical Laboratories and Forensic Medicine, Jordan University Hospital, Amman, Jordan; 3Scientific Approaches to Fight Epidemics of Infectious Diseases (SAFE-ID) Research Group, The University of Jordan, Amman, Jordan; 4Institute for AI in Medicine (IKIM), University Medicine Essen (AöR), Essen, Germany; 5Institute of Medical Informatics, University Hospital RWTH Aachen, Aachen, GermanyCorrespondence: Malik Sallam, Email malik.sallam@ju.edu.joIntroduction: Artificial intelligence (AI) chatbots excel in language understanding and generation. These models can transform healthcare education and practice. However, it is important to assess the performance of such AI models in various topics to highlight its strengths and possible limitations. This study aimed to evaluate the performance of ChatGPT (GPT-3.5 and GPT-4), Bing, and Bard compared to human students at a postgraduate master’s level in Medical Laboratory Sciences.Methods: The study design was based on the METRICS checklist for the design and reporting of AI-based studies in healthcare. The study utilized a dataset of 60 Clinical Chemistry multiple-choice questions (MCQs) initially conceived for assessing 20 MSc students. The revised Bloom’s taxonomy was used as the framework for classifying the MCQs into four cognitive categories: Remember, Understand, Analyze, and Apply. A modified version of the CLEAR tool was used for the assessment of the quality of AI-generated content, with Cohen’s κ for inter-rater agreement.Results: Compared to the mean students’ score which was 0.68± 0.23, GPT-4 scored 0.90 ± 0.30, followed by Bing (0.77 ± 0.43), GPT-3.5 (0.73 ± 0.45), and Bard (0.67 ± 0.48). Statistically significant better performance was noted in lower cognitive domains (Remember and Understand) in GPT-3.5 (P=0.041), GPT-4 (P=0.003), and Bard (P=0.017) compared to the higher cognitive domains (Apply and Analyze). The CLEAR scores indicated that ChatGPT-4 performance was “Excellent” compared to the “Above average” performance of ChatGPT-3.5, Bing, and Bard.Discussion: The findings indicated that ChatGPT-4 excelled in the Clinical Chemistry exam, while ChatGPT-3.5, Bing, and Bard were above average. Given that the MCQs were directed to postgraduate students with a high degree of specialization, the performance of these AI chatbots was remarkable. Due to the risk of academic dishonesty and possible dependence on these AI models, the appropriateness of MCQs as an assessment tool in higher education should be re-evaluated.Keywords: AI in healthcare education, higher education, large language models, evaluation

Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models). However, a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instruments is missing., Methods: We present MedShapeNet to translate data-driven vision algorithms to medical applications and to adapt state-of-the-art vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. We present use cases in classifying brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing., Results: By now, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing., Conclusions: MedShapeNet contains medical shapes from anatomy and surgical instruments and will continue to collect data for benchmarks and applications. The project page is: https://medshapenet.ikim.nrw/., (© 2024 Walter de Gruyter GmbH, Berlin/Boston.)

Nitric oxide-sensitive guanylyl cyclase (NO-GC) is a heterodimeric enzyme with an α- and a β-subunit. In its active form as an α 1 β 1 -heterodimer, NO-GC produces cyclic guanosine-3',5'-monophophate (cGMP) to regulate vasodilation and proliferation of vascular smooth muscle cells (VSMCs). In contrast to VSMCs, only a few studies reported on the expression of the NO-GC α 1 β 1 -heterodimer in human pericytes. Since NO-GC is a marker for platelet-derived growth factor-β (PDGFRβ)-positive pericytes, we investigated whether NO-GC is expressed in its active α 1 β 1 -heterodimer in pericytes of healthy human dental pulp. In our previous studies, we developed and validated an antibody against the α 1 -subunit of human NO-GC. Here, we developed a new antibody against the β 1 -subunit of human NO-GC and validated it by immunoblot, mass spectrometry, and immunohistochemistry on tissue samples from humans and NO-GC knockout (GCKO) mice. Using both antibodies, we detected α 1 - and β 1 -subunits of NO-GC in pericytes of pre-capillary arterioles, capillaries, and post-capillary venules in dental pulp of decalcified and non-decalcified human molars. We concluded that NO-GC as an active α 1 β 1 -heterodimer may be involved in the regulation of vascular permeability, vascular stability, organ homeostasis, and organ regeneration in healthy human dental pulp.

Conventional navigation systems (CNS) in surgery require strong spatial cognitive abilities and hand-eye coordination. Augmented Reality Navigation Systems (ARNS) provide 3D guidance and may overcome these challenges, but their accuracy and efficiency compared to CNS have not been systematically evaluated. In this randomized crossover study with 36 participants from different professional backgrounds (surgeons, students, engineers), drilling accuracy, time and perceived workload were evaluated using ARNS and CNS. For the first time, this study provides compelling evidence that ARNS and CNS have comparable accuracy in translational error. Differences in angle and depth error with ARNS were likely due to limited stereoscopic vision, hardware limitations, and design. Despite this, ARNS was preferred by most participants, including surgeons with prior navigation experience, and demonstrated a significantly better overall user experience. Depending on accuracy requirements, ARNS could serve as a viable alternative to CNS for guided drilling, with potential for future optimization., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Background Limited statistical knowledge can slow critical engagement with and adoption of artificial intelligence (AI) tools for radiologists. Large language models (LLMs) such as OpenAI's GPT-4, and notably its Advanced Data Analysis (ADA) extension, may improve the adoption of AI in radiology. Purpose To validate GPT-4 ADA outputs when autonomously conducting analyses of varying complexity on a multisource clinical dataset. Materials and Methods In this retrospective study, unique itemized radiologic reports of bedside chest radiographs, associated demographic data, and laboratory markers of inflammation from patients in intensive care from January 2009 to December 2019 were evaluated. GPT-4 ADA, accessed between December 2023 and January 2024, was tasked with autonomously analyzing this dataset by plotting radiography usage rates, providing descriptive statistics measures, quantifying factors of pulmonary opacities, and setting up machine learning (ML) models to predict their presence. Three scientists with 6-10 years of ML experience validated the outputs by verifying the methodology, assessing coding quality, re-executing the provided code, and comparing ML models head-to-head with their human-developed counterparts (based on the area under the receiver operating characteristic curve [AUC], accuracy, sensitivity, and specificity). Statistical significance was evaluated using bootstrapping. Results A total of 43 788 radiograph reports, with their laboratory values, from University Hospital RWTH Aachen were evaluated from 43 788 patients (mean age, 66 years ± 15 [SD]; 26 804 male). While GPT-4 ADA provided largely appropriate visualizations, descriptive statistical measures, quantitative statistical associations based on logistic regression, and gradient boosting machines for the predictive task (AUC, 0.75), some statistical errors and inaccuracies were encountered. ML strategies were valid and based on consistent coding routines, resulting in valid outputs on par with human specialist-developed reference models (AUC, 0.80 [95% CI: 0.80, 0.81] vs 0.80 [95% CI: 0.80, 0.81]; P = .51) (accuracy, 79% [6910 of 8758 patients] vs 78% [6875 of 8758 patients], respectively; P = .27). Conclusion LLMs may facilitate data analysis in radiology, from basic statistics to advanced ML-based predictive modeling. © RSNA, 2024 Supplemental material is available for this article.

Background: Early detection of oral cancer (OC) or its precursors is the most effective measure to improve outcome. The reasons for missing them on conventional oral examination (COE) or possible countermeasures are still unclear., Methods: In this randomized controlled trial, we investigated the effects of standardized oral examination (SOE) compared to COE. 49 dentists, specialists, and dental students wearing an eye tracker had to detect 10 simulated oral lesions drawn into a volunteer's oral cavity., Results: SOE had a higher detection rate at 85.4% sensitivity compared to 78.8% in the control (p = 0.017) due to higher completeness (p < 0.001). Detection rate correlated with examination duration (p = 0.002)., Conclusions: A standardized approach can improve systematics and thereby detection rates in oral examinations. It should take at least 5 min. Perceptual and cognitive errors and improper technique cause oral lesions to be missed. Its wide implementation could be an additional strategy to enhance early detection of OC., (© 2024 The Authors. Head & Neck published by Wiley Periodicals LLC.)

At the Worldwide Developers Conference in June 2023, Apple introduced the Vision Pro. The Apple Vision Pro (AVP) is a mixed reality headset; more specifically, it is a virtual reality device with an additional video see-through capability. The video see-through capability turns the AVP into an augmented reality (AR) device. The AR feature is enabled by streaming the real world via cameras on the (virtual reality) screens in front of the user's eyes. This is, of course, not unique and is similar to other devices, such as the Varjo XR-3 (Varjo Technologies Oy). Nevertheless, the AVP has some interesting features, such as an inside-out screen that can show the headset wearer's eyes to "outsiders," and a button on the top, called the "digital crown," that allows a seamless blend of digital content with the user's physical space by turning it. In addition, it is untethered, except for the cable to the battery, which makes the headset more agile, compared to the Varjo XR-3. This could actually come closer to "The Ultimate Display," which Ivan Sutherland had already sketched in 1965. After a great response from the media and social networks to the release, we were able to test and review the new AVP ourselves in March 2024. Including an expert survey with 13 of our colleagues after testing the AVP in our institute, this Viewpoint explores whether the AVP can overcome clinical challenges that AR especially still faces in the medical domain; we also go beyond this and discuss whether the AVP could support clinicians in essential tasks to allow them to spend more time with their patients., (©Jan Egger, Christina Gsaxner, Gijs Luijten, Jianxu Chen, Xiaojun Chen, Jiang Bian, Jens Kleesiek, Behrus Puladi. Originally published in JMIR Serious Games (https://games.jmir.org), 18.09.2024.)

Introduction: Process Mining (PM) has emerged as a transformative tool in healthcare, facilitating the enhancement of process models and predicting potential anomalies. However, the widespread application of PM in healthcare is hindered by the lack of structured event logs and specific data privacy regulations., Concept: This paper introduces a pipeline that converts routine healthcare data into PM-compatible event logs, leveraging the newly available permissions under the Health Data Utilization Act to use healthcare data., Implementation: Our system exploits the Core Data Sets (CDS) provided by Data Integration Centers (DICs). It involves converting routine data into Fast Healthcare Interoperable Resources (FHIR), storing it locally, and subsequently transforming it into standardized PM event logs through FHIR queries applicable on any DIC. This facilitates the extraction of detailed, actionable insights across various healthcare settings without altering existing DIC infrastructures., Lessons Learned: Challenges encountered include handling the variability and quality of data, and overcoming network and computational constraints. Our pipeline demonstrates how PM can be applied even in complex systems like healthcare, by allowing for a standardized yet flexible analysis pipeline which is widely applicable.The successful application emphasize the critical role of tailored event log generation and data querying capabilities in enabling effective PM applications, thus enabling evidence-based improvements in healthcare processes.

We developed and validated a statistical prediction model using 2.5 electronic health records from 24 German emergency departments (EDs) to estimate treatment timeliness at triage. The model's moderate fit and reliance on interoperable, routine data suggest its potential for implementation in ED crowding management.

Background and Objective: Cell segmentation in bright-field histological slides is a crucial topic in medical image analysis. Having access to accurate segmentation allows researchers to examine the relationship between cellular morphology and clinical observations. Unfortunately, most segmentation methods known today are limited to nuclei and cannot segment the cytoplasm., Methods: We present a new network architecture Cyto R-CNN that is able to accurately segment whole cells (with both the nucleus and the cytoplasm) in bright-field images. We also present a new dataset CytoNuke, consisting of multiple thousand manual annotations of head and neck squamous cell carcinoma cells. Utilizing this dataset, we compared the performance of Cyto R-CNN to other popular cell segmentation algorithms, including QuPath's built-in algorithm, StarDist, Cellpose and a multi-scale Attention Deeplabv3+. To evaluate segmentation performance, we calculated AP50, AP75 and measured 17 morphological and staining-related features for all detected cells. We compared these measurements to the gold standard of manual segmentation using the Kolmogorov-Smirnov test., Results: Cyto R-CNN achieved an AP50 of 58.65% and an AP75 of 11.56% in whole-cell segmentation, outperforming all other methods (QuPath 19.46/0.91%; StarDist 45.33/2.32%; Cellpose 31.85/5.61%, Deeplabv3+ 3.97/1.01%). Cell features derived from Cyto R-CNN showed the best agreement to the gold standard (D¯=0.15) outperforming QuPath (D¯=0.22), StarDist (D¯=0.25), Cellpose (D¯=0.23) and Deeplabv3+ (D¯=0.33)., Conclusion: Our newly proposed Cyto R-CNN architecture outperforms current algorithms in whole-cell segmentation while providing more reliable cell measurements than any other model. This could improve digital pathology workflows, potentially leading to improved diagnosis. Moreover, our published dataset can be used to develop further models in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objectives: Tooth extraction is one of the most frequently performed medical procedures. The indication is based on the combination of clinical and radiological examination and individual patient parameters and should be made with great care. However, determining whether a tooth should be extracted is not always a straightforward decision. Moreover, visual and cognitive pitfalls in the analysis of radiographs may lead to incorrect decisions. Artificial intelligence (AI) could be used as a decision support tool to provide a score of tooth extractability., Material and Methods: Using 26,956 single teeth images from 1,184 panoramic radiographs (PANs), we trained a ResNet50 network to classify teeth as either extraction-worthy or preservable. For this purpose, teeth were cropped with different margins from PANs and annotated. The usefulness of the AI-based classification as well that of dentists was evaluated on a test dataset. In addition, the explainability of the best AI model was visualized via a class activation mapping using CAMERAS., Results: The ROC-AUC for the best AI model to discriminate teeth worthy of preservation was 0.901 with 2% margin on dental images. In contrast, the average ROC-AUC for dentists was only 0.797. With a 19.1% tooth extractions prevalence, the AI model's PR-AUC was 0.749, while the dentist evaluation only reached 0.589., Conclusion: AI models outperform dentists/specialists in predicting tooth extraction based solely on X-ray images, while the AI performance improves with increasing contextual information., Clinical Relevance: AI could help monitor at-risk teeth and reduce errors in indications for extractions., (© 2024. The Author(s).)

Purpose: Efficient and precise surgical skills are essential in ensuring positive patient outcomes. By continuously providing real-time, data driven, and objective evaluation of surgical performance, automated skill assessment has the potential to greatly improve surgical skill training. Whereas machine learning-based surgical skill assessment is gaining traction for minimally invasive techniques, this cannot be said for open surgery skills. Open surgery generally has more degrees of freedom when compared to minimally invasive surgery, making it more difficult to interpret. In this paper, we present novel approaches for skill assessment for open surgery skills., Methods: We analyzed a novel video dataset for open suturing training. We provide a detailed analysis of the dataset and define evaluation guidelines, using state of the art deep learning models. Furthermore, we present novel benchmarking results for surgical skill assessment in open suturing. The models are trained to classify a video into three skill levels based on the global rating score. To obtain initial results for video-based surgical skill classification, we benchmarked a temporal segment network with both an I3D and a Video Swin backbone on this dataset., Results: The dataset is composed of 314 videos of approximately five minutes each. Model benchmarking results are an accuracy and F1 score of up to 75 and 72%, respectively. This is similar to the performance achieved by the individual raters, regarding inter-rater agreement and rater variability. We present the first end-to-end trained approach for skill assessment for open surgery training., Conclusion: We provide a thorough analysis of a new dataset as well as novel benchmarking results for surgical skill assessment. This opens the doors to new advances in skill assessment by enabling video-based skill assessment for classic surgical techniques with the potential to improve the surgical outcome of patients., (© 2024. The Author(s).)

Background: Liposarcomas are among the most common mesenchymal malignancies. However, the therapeutic options are still very limited and so far, targeted therapies had not yet been established. Immunotherapy, which has been a breakthrough in other oncological entities, seems to have no efficacy in liposarcoma. Complicating matters further, classification remains difficult due to the diversity of morphologies and nonspecific or absent markers in immunohistochemistry, leaving molecular pathology using FISH or sequencing as best options. Many liposarcomas harbor MDM2 gene amplifications. In close relation to the gene locus of MDM2, HER3 (ERBB3) gene is present and co-amplification could occur. Since the group of HER/EGFR receptor tyrosine kinases and its inhibitors/antibodies play a role in a broad spectrum of oncological diseases and treatments, and some HER3 inhibitors/antibodies are already under clinical investigation, we hypothesized that in case of HER3 co-amplifications a tumor might bear a further potential therapeutic target., Methods: We performed FISH analysis (MDM2, DDIT3, HER3) in 56 archived cases and subsequently performed reclassification to confirm the diagnosis of liposarcoma., Results: Next to 16 out of 56 cases needed to be re-classified, in 20 out of 54 cases, a cluster-amplification of HER3 could be detected, significantly correlating with MDM2 amplification. Our study shows that the entity of liposarcomas show specific molecular characteristics leading to reclassify archived cases by modern, established methodologies. Additionally, in 57.1% of these cases, HER3 was cluster-amplified profusely, presenting a putative therapeutic target for targeted therapy., Conclusion: Our study serves as the initial basis for further investigation of the HER3 gene as a putative therapeutic target in liposarcoma., (© 2024. The Author(s).)

Objective: The gold standard of oral cancer (OC) treatment is diagnostic confirmation by biopsy followed by surgical treatment. However, studies have shown that dentists have difficulty performing biopsies, dental students lack knowledge about OC, and surgeons do not always maintain a safe margin during tumor resection. To address this, biopsies and resections could be trained under realistic conditions outside the patient. The aim of this study was to develop and to validate a porcine pseudotumor model of the tongue., Methods: An interdisciplinary team reflecting various specialties involved in the oncological treatment of head and neck oncology developed a porcine pseudotumor model of the tongue in which biopsies and resections can be practiced. The refined model was validated in a final trial of 10 participants who each resected four pseudotumors on a tongue, resulting in a total of 40 resected pseudotumors. The participants (7 residents and 3 specialists) had an experience in OC treatment ranging from 0.5 to 27 years. Resection margins (minimum and maximum) were assessed macroscopically and compared beside self-assessed margins and resection time between residents and specialists. Furthermore, the model was evaluated using Likert-type questions on haptic and radiological fidelity, its usefulness as a training model, as well as its imageability using CT and ultrasound., Results: The model haptically resembles OC (3.0 ± 0.5; 4-point Likert scale), can be visualized with medical imaging and macroscopically evaluated immediately after resection providing feedback. Although, participants (3.2 ± 0.4) tended to agree that they had resected the pseudotumor with an ideal safety margin (10 mm), the mean minimum resection margin was insufficient at 4.2 ± 1.2 mm (mean ± SD), comparable to reported margins in literature. Simultaneously, a maximum resection margin of 18.4 ± 6.1 mm was measured, indicating partial over-resection. Although specialists were faster at resection (p < 0.001), this had no effect on margins (p = 0.114). Overall, the model was well received by the participants, and they could see it being implemented in training (3.7 ± 0.5)., Conclusion: The model, which is cost-effective, cryopreservable, and provides a risk-free training environment, is ideal for training in OC biopsy and resection and could be incorporated into dental, medical, or oncologic surgery curricula. Future studies should evaluate the long-term training effects using this model and its potential impact on improving patient outcomes., (© 2024. The Author(s).)

The recent release of ChatGPT, a chat bot research project/product of natural language processing (NLP) by OpenAI, stirs up a sensation among both the general public and medical professionals, amassing a phenomenally large user base in a short time. This is a typical example of the 'productization' of cutting-edge technologies, which allows the general public without a technical background to gain firsthand experience in artificial intelligence (AI), similar to the AI hype created by AlphaGo (DeepMind Technologies, UK) and self-driving cars (Google, Tesla, etc.). However, it is crucial, especially for healthcare researchers, to remain prudent amidst the hype. This work provides a systematic review of existing publications on the use of ChatGPT in healthcare, elucidating the 'status quo' of ChatGPT in medical applications, for general readers, healthcare professionals as well as NLP scientists. The large biomedical literature database PubMed is used to retrieve published works on this topic using the keyword 'ChatGPT'. An inclusion criterion and a taxonomy are further proposed to filter the search results and categorize the selected publications, respectively. It is found through the review that the current release of ChatGPT has achieved only moderate or 'passing' performance in a variety of tests, and is unreliable for actual clinical deployment, since it is not intended for clinical applications by design. We conclude that specialized NLP models trained on (bio)medical datasets still represent the right direction to pursue for critical clinical applications., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interests., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: The radial forearm free flap (RFFF) serves as a workhorse for a variety of reconstructions. Although there are a variety of surgical techniques for donor site closure after RFFF raising, the most common techniques are closure using a split-thickness skin graft (STSG) or a full-thickness skin graft (FTSG). The closure can result in wound complications and function and aesthetic compromise of the forearm and hand. The aim of the planned systematic review and meta-analysis is to compare the wound-related, function-related and aesthetics-related outcome associated with full-thickness skin grafts (FTSG) and split-thickness skin grafts (STSG) in radial forearm free flap (RFFF) donor site closure., Methods: A systematic review and meta-analysis will be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines will be followed. Electronic databases and platforms (PubMed, Embase, Scopus, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), China National Knowledge Infrastructure (CNKI)) and clinical trial registries (ClinicalTrials.gov, the German Clinical Trials Register, the ISRCTN registry, the International Clinical Trials Registry Platform) will be searched using predefined search terms until 15 January 2024. A rerun of the search will be carried out within 12 months before publication of the review. Eligible studies should report on the occurrence of donor site complications after raising an RFFF and closure of the defect. Included closure techniques are techniques that use full-thickness skin grafts and split-thickness skin grafts. Excluded techniques for closure are primary wound closure without the use of skin graft. Outcomes are considered wound-, functional-, and aesthetics-related. Studies that will be included are randomized controlled trials (RCTs) and prospective and retrospective comparative cohort studies. Case-control studies, studies without a control group, animal studies and cadaveric studies will be excluded. Screening will be performed in a blinded fashion by two reviewers per study. A third reviewer resolves discrepancies. The risk of bias in the original studies will be assessed using the ROBINS-I and RoB 2 tools. Data synthesis will be done using Review Manager (RevMan) 5.4.1. If appropriate, a meta-analysis will be conducted. Between-study variability will be assessed using the I 2 index. If necessary, R will be used. The quality of evidence for outcomes will eventually be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach., Discussion: This study's findings may help us understand both closure techniques' complication rates and may have important implications for developing future guidelines for RFFF donor site management. If available data is limited and several questions remain unanswered, additional comparative studies will be needed., Systematic Review Registration: The protocol was developed in line with the PRISMA-P extension for protocols and was registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 17 September 2023 (registration number CRD42023351903)., (© 2024. The Author(s).)

Objectives: Oral and maxillofacial surgery (OMFS) has to compete with other specialties for the best candidates. With the upcoming change of generations (Z and Alpha) and the movement toward gender parity of dentistry, understanding changing preferences and misconceptions is essential., Material and Methods: An online survey was conducted by the German-Association-of-Oral-and-Maxillofacial-Surgery (DGMKG) across German dental schools. The survey collected demographic data, academic background, and career aspirations, with a focus on OMFS. The dental student survey results were compared to a survey given to OMFS Specialists., Results: 637 dental students, mainly female (70%), from 30 German universities participated. 27% had defined career aspirations post-graduation, with self-employment and academia being popular choices. 67% were unsure. Specializations leaned towards restorative dentistry (41%), orthodontics (36%), and prosthodontics (31%). While 73% showed interest in surgical practices, 20% were attracted in specializing in OMFS. Of those averse to OMFS, 78% cited long training duration as the deterrent, 12% were put off by perceived unattractive working hours. Other reasons included negative undergraduate experiences, scarcity of part-time positions, and perceived inadequate earnings., Conclusion: Accurate data is crucial for career decisions. OMFS societies must proactively share accurate information and guide students. OMFS offers family-friendly hours, and while its training might be longer than dental specialties, it is on par with other surgical professions., Clinical Relevance: Dental students consistently regard OMFS as commendable career path. To guarantee sustained OMFS expertise, it is imperative to nurture this interest through dedicated academic mentorship and innovative education, thereby solidifying their professional direction., (© 2024. The Author(s).)

The availability of computational hardware and developments in (medical) machine learning (MML) increases medical mixed realities' (MMR) clinical usability. Medical instruments have played a vital role in surgery for ages. To further accelerate the implementation of MML and MMR, three-dimensional (3D) datasets of instruments should be publicly available. The proposed data collection consists of 103, 3D-scanned medical instruments from the clinical routine, scanned with structured light scanners. The collection consists, for example, of instruments, like retractors, forceps, and clamps. The collection can be augmented by generating likewise models using 3D software, resulting in an inflated dataset for analysis. The collection can be used for general instrument detection and tracking in operating room settings, or a freeform marker-less instrument registration for tool tracking in augmented reality. Furthermore, for medical simulation or training scenarios in virtual reality and medical diminishing reality in mixed reality. We hope to ease research in the field of MMR and MML, but also to motivate the release of a wider variety of needed surgical instrument datasets., (© 2023. The Author(s).)

Purpose: In bone surgery specialties, like orthopedics, neurosurgery, and oral and maxillofacial surgery patient safety and treatment success depends on the accurate implementation of computer-based surgical plans. Unintentional plan deviations can result in long-term functional damage to the patient. With on-site teleoperation, the surgeon operates a slave robot with a physically-decoupled master device, while being directly present at the operation site. This allows the surgeon to perform surgical tasks with robotic accuracy, while always remaining in the control loop., Methods: In this study the master- and slave-side accuracy of an on-site teleoperated miniature cooperative robot (minaroHD) is evaluated. Master-side accuracy is investigated in a user study regarding scale factor, target feed rate, movement direction and haptic guidance stiffness. Scale factors are chosen to correspond to primarily finger, hand, and arm movements. Slave-side accuracy is investigated in autonomous milling trials regarding stepover, feed rate, movement direction, and material density., Results: Master-side user input errors increase with increasing target feed rate and scale factor, and decrease with increasing haptic guidance stiffness. Resulting slave-side errors decrease with increasing scale factor and are < 0.07 mm for optimal guidance parameters. Slave-side robot position errors correlate with the feed rate but show little correlation with stepover distance. For optimal milling parameters, the 95th percentile of tracked slave-side position error is 0.086 mm with a maximal error of 0.16 mm., Conclusion: For optimal guidance and milling parameters, the combined error of 0.23 mm is in the range of the dura mater thickness (< 0.27 mm) or mandibular canal wall (~ 0.85 mm). This corresponds to safety margins in high-demand surgical procedures like craniotomies, laminectomies, or decortication of the jaw. However, for further clinical translation, the performance and usability of on-site teleoperated milling must be further evaluated for real-life clinical application examples with consideration of all error sources in a computer-assisted surgery workflow., (© 2023. The Author(s).)

Background: Although surgical suturing is one of the most important basic skills, many medical school graduates do not acquire sufficient knowledge of it due to its lack of integration into the curriculum or a shortage of tutors. E-learning approaches attempt to address this issue but still rely on the involvement of tutors. Furthermore, the learning experience and visual-spatial ability appear to play a critical role in surgical skill acquisition. Virtual reality head-mounted displays (HMDs) could address this, but the benefits of immersive and stereoscopic learning of surgical suturing techniques are still unclear., Material and Methods: In this multi-arm randomized controlled trial, 150 novices participated. Three teaching modalities were compared: an e-learning course (monoscopic), an HMD-based course (stereoscopic, immersive), both self-directed and a tutor-led course with feedback. Suturing performance was recorded by video camera both before and after course participation (>26 h of video material) and assessed in a blinded fashion using the Objective Structured Assessment of Technical Skills (OSATS) Global Rating Score (GRS). Furthermore, the optical flow of the videos was determined using an algorithm. The number of sutures performed was counted, the visual-spatial ability was measured with the Mental Rotation Test (MRT), and courses were assessed with questionnaires., Results: Students' self-assessment in the HMD-based course was comparable to that of the tutor-led course and significantly better than in the e-learning course ( P =0.003). Course suitability was rated best for the tutor-led course ( x̄ =4.8), followed by the HMD-based ( x̄ =3.6) and e-learning ( x̄ =2.5) courses. The median ΔGRS between courses was comparable ( P =0.15) at 12.4 (95% CI 10.0-12.7) for the e-learning course, 14.1 (95% CI 13.0-15.0) for the HMD-based course, and 12.7 (95% CI 10.3-14.2) for the tutor-led course. However, the ΔGRS was significantly correlated with the number of sutures performed during the training session ( P =0.002), but not with visual-spatial ability ( P =0.615). Optical flow ( R2 =0.15, P <0.001) and the number of sutures performed ( R2 =0.73, P <0.001) can be used as additional measures to GRS., Conclusion: The use of HMDs with stereoscopic and immersive video provides advantages in the learning experience and should be preferred over a traditional web application for e-learning. Contrary to expectations, feedback is not necessary for novices to achieve a sufficient level in suturing; only the number of surgical sutures performed during training is a good determinant of competence improvement. Nevertheless, feedback still enhances the learning experience. Therefore, automated assessment as an alternative feedback approach could further improve self-directed learning modalities. As a next step, the data from this study could be used to develop such automated AI-based assessments., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Although blood transfusions have adverse consequences for microvascular head and neck reconstruction, they are frequently administered. Pre-identifying patients would allow risk-stratified patient blood management., Methods: Development of machine learning (ML) and logistic regression (LR) models based on retrospective inclusion of 657 patients from 2011 to 2021. Internal validation and comparison with models from the literature by external validation. Development of a web application and a score chart., Results: Our models achieved an area under the receiver operating characteristic curve (ROC-AUC) of up to 0.825, significantly outperforming LR models from the literature. Preoperative hemoglobin, blood volume, duration of surgery and flap type/size were strong predictors., Conclusions: The use of additional variables improves the prediction for blood transfusion, while models seems to have good generalizability due to surgical standardization and underlying physiological mechanism. The ML models developed showed comparable predictive performance to an LR model. However, ML models face legal hurdles, whereas score charts based on LR could be used after further validation., (© 2023 The Authors. Head & Neck published by Wiley Periodicals LLC.)

The myocutaneous anterolateral thigh (ALT) and vastus lateralis (VL) flaps include a large muscle mass and a sufficient vascular pedicle, and they have been used for decades to reconstruct traumatic and acquired defects of the head and neck and extremities. In spite of these benefits, musculoskeletal dysfunction was reported in nearly 1 out of 20 patients at follow-up. It is unclear whether the recently proposed muscle-sparing flap-raising approach could preserve VL muscle function and whether patients at increased risk could benefit from such an approach. Therefore, we performed a predictive dynamic gait simulation based on a biological motion model with gradual weakening of the VL during a self-selected and fast walking speed to determine the compensable degree of VL muscle reduction. Muscle force, joint angle, and joint moment were measured. Our study showed that VL muscle reduction could be compensated up to a certain degree, which could explain the observed incidence of musculoskeletal dysfunction. In elderly or fragile patients, the VL muscle should not be reduced by 50% or more, which could be achieved by muscle-sparing flap-raising of the superficial partition only. In young or athletic patients, a VL muscle reduction of 10%, which corresponds to a muscle cuff, has no relevant effect. Yet, a reduction of more than 30% leads to relevant weakening of the quadriceps. Therefore, in this patient population with the need for a large portion of muscle, alternative flaps should be considered. This study can serve as the first basis for further investigations of human locomotion after flap-raising., Competing Interests: Declaration of Competing Interest Thomas Geijtenbeek is the creator and proprietor of the Hyfydy simulation software, which has been used in this study to speed up the optimizations. The other authors declare that they have no conflict of interest regarding the results and methods published in this article., (Copyright © 2022 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.)

Background: As an integral part of computer-assisted surgery, virtual surgical planning (VSP) leads to significantly better surgery results, such as for oral and maxillofacial reconstruction with microvascular grafts of the fibula or iliac crest. It is performed on a 2D computer desktop screen (DS) based on preoperative medical imaging. However, in this environment, VSP is associated with shortcomings, such as a time-consuming planning process and the requirement of a learning process. Therefore, a virtual reality (VR)-based VSP application has great potential to reduce or even overcome these shortcomings due to the benefits of visuospatial vision, bimanual interaction, and full immersion. However, the efficacy of such a VR environment has not yet been investigated., Objective: This study aimed to demonstrate the possible advantages of a VR environment through a substep of VSP, specifically the segmentation of the fibula (calf bone) and os coxae (hip bone), by conducting a training course in both DS and VR environments and comparing the results., Methods: During the training course, 6 novices were taught how to use a software application in a DS environment (3D Slicer) and in a VR environment (Elucis) for the segmentation of the fibula and os coxae, and they were asked to carry out the maneuvers as accurately and quickly as possible. Overall, 13 fibula and 13 os coxae were segmented for each participant in both methods (VR and DS), resulting in 156 different models (78 fibula and 78 os coxae) per method (VR and DS) and 312 models in total. The individual learning processes in both environments were compared using objective criteria (time and segmentation performance) and self-reported questionnaires. The models resulting from the segmentation were compared mathematically (Hausdorff distance and Dice coefficient) and evaluated by 2 experienced radiologists in a blinded manner., Results: A much faster learning curve was observed for the VR environment than the DS environment (β=.86 vs β=.25). This nearly doubled the segmentation speed (cm 3 /min) by the end of training, leading to a shorter time (P<.001) to reach a qualitative result. However, there was no qualitative difference between the models for VR and DS (P=.99). The VR environment was perceived by participants as more intuitive and less exhausting, and was favored over the DS environment., Conclusions: The more rapid learning process and the ability to work faster in the VR environment could save time and reduce the VSP workload, providing certain advantages over the DS environment., (©Max Ulbrich, Vincent Van den Bosch, Andrea Bönsch, Lennart Johannes Gruber, Mark Ooms, Claire Melchior, Ila Motmaen, Caroline Wilpert, Ashkan Rashad, Torsten Wolfgang Kuhlen, Frank Hölzle, Behrus Puladi. Originally published in JMIR Serious Games (https://games.jmir.org), 19.01.2023.)

The binding of nitric oxide (NO) to heme in the β 1 subunit of soluble guanylyl cyclase (sGC) activates both the heterodimeric α 1 β 1 and α 2 β 1 isoforms of the enzyme, leading to the increased production of cGMP from GTP. In cultured human mast cells, exogenous NO is able to inhibit mast cell degranulation via NO-cGMP signaling. However, under inflammatory oxidative or nitrosative stress, sGC becomes insensitive to NO. The occurrence of mast cells in healthy and inflamed human tissues and the in vivo expression of the α 1 and β 1 subunits of sGC in human mast cells during inflammation remain largely unresolved and were investigated here. Using peroxidase and double immunohistochemical incubations, no mast cells were found in healthy dental pulp, whereas the inflammation of dental pulp initiated the occurrence of several mast cells expressing the α 1 and β 1 subunits of sGC. Since inflammation-induced oxidative and nitrosative stress oxidizes Fe 2+ to Fe 3+ in the β 1 subunit of sGC, leading to the desensitization of sGC to NO, we hypothesize that the NO- and heme-independent pharmacological activation of sGC in mast cells may be considered as a regulatory strategy for mast cell functions in inflamed human dental pulp.

Objective: Aging is associated with structural and functional cardiovascular changes that may affect microvascular free flap perfusion, which is a prerequisite for flap viability and flap success. This study is aimed to investigate the impact of age on flap perfusion., Study Design: Intraoperative and postoperative flap perfusion of 348 patients who underwent successful reconstruction with a radial free forearm flap (RFFF), anterolateral thigh flap (ALTF), or fibular free flap (FFF) was retrospectively analyzed and compared between older (>70 years) and younger patients (≤70 years) using the Mann-Whitney test and linear regression models., Results: Intraoperative flap blood flow and hemoglobin concentration (55.5 arbitrary units [AU] vs 69.3 AU, P = .004; 42.5 AU vs 47.3 AU, P = .016, respectively) were reduced in ALTFs in older patients compared with younger patients. These 2 differences did not persist in multivariable testing (P = .097 and P = .323, respectively). No other differences were observed between the older and younger patients in terms of intraoperative and postoperative flap blood flow, hemoglobin concentration, and hemoglobin oxygen saturation in RFFFs, ALTFs, and FFFs (all P > .05)., Conclusions: Age has no impact on microvascular free flap perfusion in RFFFs, ALTFs, and FFFs. This could contribute to the observed equal success of free flaps in older patients., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Head and neck cancer has great regional anatomical complexity, as it can develop in different structures, exhibiting diverse tumour manifestations and high intratumoural heterogeneity, which is highly related to resistance to treatment, progression, the appearance of metastases, and tumour recurrences. Radiomics has the potential to address these obstacles by extracting quantitative, measurable, and extractable features from the region of interest in medical images. Medical imaging is a common source of information in clinical practice, presenting a potential alternative to biopsy, as it allows the extraction of a large number of features that, although not visible to the naked eye, may be relevant for tumour characterisation. Taking advantage of machine learning techniques, the set of features extracted when associated with biological parameters can be used for diagnosis, prognosis, and predictive accuracy valuable for clinical decision-making. Therefore, the main goal of this contribution was to determine to what extent the features extracted from Computed Tomography (CT) are related to cancer prognosis, namely Locoregional Recurrences (LRs), the development of Distant Metastases (DMs), and Overall Survival (OS). Through the set of tumour characteristics, predictive models were developed using machine learning techniques. The tumour was described by radiomic features, extracted from images, and by the clinical data of the patient. The performance of the models demonstrated that the most successful algorithm was XGBoost, and the inclusion of the patients' clinical data was an asset for cancer prognosis. Under these conditions, models were created that can reliably predict the LR, DM, and OS status, with the area under the ROC curve (AUC) values equal to 0.74, 0.84, and 0.91, respectively. In summary, the promising results obtained show the potential of radiomics, once the considered cancer prognosis can, in fact, be expressed through CT scans.

Head and neck reconstruction with microvascular free flaps is frequently performed in smokers. Smoking causes various alterations in the cardiovascular system. The aim of this study was to investigate the effects of smoking on flap perfusion as a critical factor for flap survival. A total of 370 patients reconstructed with a radial free forearm flap (RFFF) or anterolateral thigh flap (ALTF) in the head and neck region between 2011 and 2020 were retrospectively analyzed. Flap perfusion measurements with the O2C tissue oxygen analysis system were compared between nonsmokers, light smokers (< 20 pack-years), and heavy smokers (≥ 20 pack-years). The blood flow was intraoperatively equal in RFFFs (84.5 AU vs. 84.5 AU; p = 0.900) and increased in ALTFs (80.5 AU vs. 56.5 AU; p = 0.001) and postoperatively increased in RFFFs (114.0 AU vs. 86.0 AU; p = 0.035) and similar in ALTFs (70.5 AU vs. 71.0 AU; p = 0.856) in heavy smokers compared to nonsmokers. The flap survival rate was similar in nonsmokers, light smokers, and heavy smokers (97.3%, 98.4%, and 100.0%). Smoking partially increases rather than decreases microvascular free flap perfusion, which may contribute to similar flap survival rates in smokers and nonsmokers., (© 2022. The Author(s).)

Background: The impact of additional soft tissue resection on recurrence of oral squamous cell carcinoma (OSCC) remains controversial. The study aim was to compare recurrence between patients with secondary tumor-free resection margins after intraoperative additional resection (STF-RM) and patients with primary tumor-free resection margins without additional resection (PTF-RM)., Methods: Forty-five patients with STF-RM were matched with patients with PTF-RM according to Union for International Cancer Control stage, tumor location, and treatment modality and compared for local, regional, and distant recurrence., Results: Patients with STF-RM showed lower local and distant control rates compared to patients with PTF-RM (66.2% vs. 82.8%; p = 0.045 and 86.3% vs. 100.0%; p = 0.021). STF-RM was the only predictor of local recurrence accounting for tumor (T) status, nodal (N) status, tumor grade, margin distance, and extracapsular extension (hazard ratio 4.21 [95% confidence interval 1.26-14.04]; p = 0.019)., Conclusions: STF-RM have an adverse impact on local and distant recurrence of OSCC., (© 2022 The Authors. Head & Neck published by Wiley Periodicals LLC.)

Background: Although nearly one-third of the world's disease burden requires surgical care, only a small proportion of digital health applications are directly used in the surgical field. In the coming decades, the application of augmented reality (AR) with a new generation of optical-see-through head-mounted displays (OST-HMDs) like the HoloLens (Microsoft Corp) has the potential to bring digital health into the surgical field. However, for the application to be performed on a living person, proof of performance must first be provided due to regulatory requirements. In this regard, cadaver studies could provide initial evidence., Objective: The goal of the research was to develop an open-source system for AR-based surgery on human cadavers using freely available technologies., Methods: We tested our system using an easy-to-understand scenario in which fractured zygomatic arches of the face had to be repositioned with visual and auditory feedback to the investigators using a HoloLens. Results were verified with postoperative imaging and assessed in a blinded fashion by 2 investigators. The developed system and scenario were qualitatively evaluated by consensus interview and individual questionnaires., Results: The development and implementation of our system was feasible and could be realized in the course of a cadaver study. The AR system was found helpful by the investigators for spatial perception in addition to the combination of visual as well as auditory feedback. The surgical end point could be determined metrically as well as by assessment., Conclusions: The development and application of an AR-based surgical system using freely available technologies to perform OST-HMD-guided surgical procedures in cadavers is feasible. Cadaver studies are suitable for OST-HMD-guided interventions to measure a surgical end point and provide an initial data foundation for future clinical trials. The availability of free systems for researchers could be helpful for a possible translation process from digital health to AR-based surgery using OST-HMDs in the operating theater via cadaver studies., (©Behrus Puladi, Mark Ooms, Martin Bellgardt, Mark Cesov, Myriam Lipprandt, Stefan Raith, Florian Peters, Stephan Christian Möhlhenrich, Andreas Prescher, Frank Hölzle, Torsten Wolfgang Kuhlen, Ali Modabber. Originally published in JMIR Serious Games (https://games.jmir.org), 25.04.2022.)

Coronary artery systems of the inferior wall of the ventricles vary considerably. Schlesinger's concept distinguishes dominance of the right or left coronary artery (LCA) or balanced type. LCA dominance has been reported to be associated with increased mortality. Early angiography studies have shown that the anterior interventricular artery (AIVA), a branch of the LCA, often continues on the inferior surface of the heart and may replace the inferior interventricular artery. Others considered an AIVA on the inferior surface of the heart a rare variant. A long AIVA is a strong predictor of death in acute anterior wall myocardial infarction. We determined coronary artery variance at the inferior surface of the ventricles in 134 dissected human hearts and analyzed a possible association between coronary artery variance and age at death. The AIVA extended to the inferior side in 64.9% of the hearts, but rarely reached the basal half of the inferior interventricular groove. Most frequently (53%), it extended into the apical two-fifths of the length of the inferior ventricular walls. An AIVA extending to the apical 40% of the length of the inferior ventricular walls may therefore be considered a common variant. In 20.1% of the hearts, a right inferior diagonal artery was also found. Statistical analysis neither revealed an association between mean AIVA length at the inferior ventricular surface and type of coronary artery dominance nor an association between AIVA length at the inferior ventricular surface or coronary artery dominance type and age at death., (© 2022 The Authors. Clinical Anatomy published by Wiley Periodicals LLC on behalf of American Association for Clinical Anatomists and the British Association for Clinical Anatomists.)

Objective: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare and severe skin and mucosal reactions that are associated with high mortality. Despite the severity, an evidence-based treatment protocol for SJS/TEN is still lacking., Method: In this systematic review and meta-analysis, the PubMed database was searched using the following terms: [Stevens-Johnson syndrome] OR [toxic epidermal necrolysis] AND [therapy] OR [treatment] over a 20-year period (1999-2019) in the German and English language. All clinical studies reporting on the treatment of SJS/TEN were included, and epidemiological and diagnostic aspects of treatment were analysed. A meta-analysis was conducted on all comparative clinical studies that met the inclusion criteria., Results: A total of 88 studies met the inclusion criteria, reporting outcomes in 2647 patients. Treatment was either supportive or used systemic corticosteroid, intravenous immunoglobulin, plasmapheresis, cyclosporine, thalidomide or cyclophosphamide therapy. The meta-analysis included 16 (18%) studies, reporting outcomes in 976 (37%) patients. Systemic glucocorticoids showed a survival benefit for SJS/TEN patients in all analyses compared with other forms of treatment. Cyclosporine treatment also showed promising results, despite being used in a small cohort of patients. No beneficial effects on mortality could be demonstrated for intravenous immunoglobulins., Conclusion: Glucocorticoids and cyclosporine may be tentatively recommended as the most promising immunomodulatory therapies for SJS/TEN, but these results should be investigated in future prospective controlled trials.