Lagophthalmos is the incomplete closure of the eyelids posing the risk of corneal ulceration and blindness. Lagophthalmos is a common symptom of various pathologies. We aimed to program a ...convolutional neural network to automatize lagophthalmos diagnosis. From June 2019 to May 2021, prospective data acquisition was performed on 30 patients seen at the Department of Plastic, Hand, and Reconstructive Surgery at the University Hospital Regensburg, Germany (IRB reference number: 20-2081-101). In addition, comparative data were gathered from 10 healthy patients as the control group. The training set comprised 826 images, while the validation and testing sets consisted of 91 patient images each. Validation accuracy was 97.8% over the span of 64 epochs. The model was trained for 17.3 min. For training and validation, an average loss of 0.304 and 0.358 and a final loss of 0.276 and 0.157 were noted. The testing accuracy was observed to be 93.41% with a loss of 0.221. This study proposes a novel application for rapid and reliable lagophthalmos diagnosis. Our CNN-based approach combines effective anti-overfitting strategies, short training times, and high accuracy levels. Ultimately, this tool carries high translational potential to facilitate the physician's workflow and improve overall lagophthalmos patient care.
Facial palsy (FP) is a functional disorder of the facial nerve involving paralysis of the mimic muscles. According to the principle “time is muscle,” early surgical treatment is tremendously ...important for preserving the mimic musculature if there are no signs of nerve function recovery. In a 49-year-old female patient, even 19 months after onset of FP, successful neurotization was still possible by a V-to-VII nerve transfer and cross-face nerve grafting. Our patient suffered from complete FP after vestibular schwannoma surgery. With continuous application of electrostimulation (ES) therapy, the patient was able to bridge the period between the first onset of FP and neurotization surgery. The significance of ES for mimic musculature preservation in FP patients has not yet been fully clarified. More attention should be paid to this form of therapy in order to preserve the facial musculature, and its benefits should be evaluated in further prospective clinical studies.
Background: The Laboratory Risk Indicator for Necrotizing Fasciitis score (LRINEC) is a simple tool used to support early diagnosis of Necrotizing Fasciitis (NF). The aim of this study was to ...investigate whether the LRINEC is suitable as a progression and prognosis parameter in patients with NF. Methods: In this retrospective study, laboratory data of 70 patients with NF were analyzed. The LRINEC was calculated for every patient at the time of hospital admission and postoperatively after surgical interventions. Furthermore, the LRINEC was examined as a prognostic factor for survival. Results: The overall lethality of our series was 20 out of 70 (28.6%). A highly significant LRINEC decrease was found for serial debridements. The largest decrease was observed after the first debridement. There was a significant difference between the initial LRINEC of deceased and surviving patients. A cut off value of >6.5 (7 LRINEC points) resulted in an optimal constellation of sensitivity (70%) and specificity (60%) to predict lethality in patients with NF. Conclusions: The LRINEC significantly decreases after surgical debridement. An initial LRINEC equal or greater than seven is an independent prognostic marker for lethality and can help to identify high-risk patients.
Headache surgery has become a considerable therapeutic option in headache treatment and is of rising interest in the German medical sector. This viewpoint outlines the need for reimbursement of ...headache surgery in the German healthcare system and demonstrates its cost-effectiveness. Using state-of-the-art patient selection algorithms, the authors found headache surgery to be cost-effective within 7.2 to 6.3 years. Of note, the approach presented is not limited to the German healthcare system.
Background: Reliable, time- and cost-effective, and clinician-friendly diagnostic tools are cornerstones in facial palsy (FP) patient management. Different automated FP grading systems have been ...developed but revealed persisting downsides such as insufficient accuracy and cost-intensive hardware. We aimed to overcome these barriers and programmed an automated grading system for FP patients utilizing the House and Brackmann scale (HBS). Methods: Image datasets of 86 patients seen at the Department of Plastic, Hand, and Reconstructive Surgery at the University Hospital Regensburg, Germany, between June 2017 and May 2021, were used to train the neural network and evaluate its accuracy. Nine facial poses per patient were analyzed by the algorithm. Results: The algorithm showed an accuracy of 100%. Oversampling did not result in altered outcomes, while the direct form displayed superior accuracy levels when compared to the modular classification form (n = 86; 100% vs. 99%). The Early Fusion technique was linked to improved accuracy outcomes in comparison to the Late Fusion and sequential method (n = 86; 100% vs. 96% vs. 97%). Conclusions: Our automated FP grading system combines high-level accuracy with cost- and time-effectiveness. Our algorithm may accelerate the grading process in FP patients and facilitate the FP surgeon’s workflow.
Background: The grading process in facial palsy (FP) patients is crucial for time- and cost-effective therapy decision-making. The House-Brackmann scale (HBS) represents the most commonly used ...classification system in FP diagnostics. This study investigated the benefits of linking machine learning (ML) techniques with the HBS. Methods: Image datasets of 51 patients seen at the Department of Plastic, Hand, and Reconstructive Surgery at the University Hospital Regensburg, Germany, between June 2020 and May 2021, were used to build the neural network. A total of nine facial poses per patient were used to automatically determine the HBS. Results: The algorithm had an accuracy of 98%. The algorithm processed the real patient image series (i.e., nine images per patient) in 112 ms. For optimized accuracy, we found 30 training runs to be the most effective training length. Conclusion: We have developed an easy-to-use, time- and cost-efficient algorithm that provides highly accurate automated grading of FP patient images. In combination with our application, the algorithm may facilitate the FP surgeon’s clinical workflow.
Large Language Models (LLMs) like ChatGPT 4 (OpenAI), Claude 2 (Anthropic), and Llama 2 (Meta AI) have emerged as novel technologies to integrate artificial intelligence (AI) into everyday work. LLMs ...in particular, and AI in general, carry infinite potential to streamline clinical workflows, outsource resource-intensive tasks, and disburden the healthcare system. While a plethora of trials is elucidating the untapped capabilities of this technology, the sheer pace of scientific progress also takes its toll. Legal guidelines hold a key role in regulating upcoming technologies, safeguarding patients, and determining individual and institutional liabilities. To date, there is a paucity of research work delineating the legal regulations of Language Models and AI for clinical scenarios in plastic and reconstructive surgery. This knowledge gap poses the risk of lawsuits and penalties against plastic surgeons. Thus, we aim to provide the first overview of legal guidelines and pitfalls of LLMs and AI for plastic surgeons. Our analysis encompasses models like ChatGPT, Claude 2, and Llama 2, among others, regardless of their closed or open-source nature. Ultimately, this line of research may help clarify the legal responsibilities of plastic surgeons and seamlessly integrate such cutting-edge technologies into the field of PRS.
Background: Synkinesis of the facial musculature is a detrimental sequalae in post-paralytic facial palsy (PPFP) patients. Detailed knowledge on the technical requirements and device properties in a ...high-resolution ultrasound (HRUS) examination is mandatory for a reliable facial muscle assessment in PPFP patients. We therefore aimed to outline the key steps in a HRUS examination and extract an optimized workflow schema. Methods: From December 2020 to April 2021, 20 patients with unilateral synkinesis underwent HRUS. All HRUS examinations were performed by the first author using US devices with linear multifrequency transducers of 4–18 MHz, including a LOGIQ E9 and a LOGIQ S7 XDclear (GE Healthcare; Milwaukee, WI, USA), as well as Philips Affinity 50G (Philips Health Systems; Eindhoven, the Netherlands). Results: Higher-frequency and multifrequency linear probes ≥15 MHz provided superior imaging qualities. The selection of the preset program Small Parts, Breast or Thyroid was linked with a more detailed contrast of the imaging morphology of facial tissue layers. Frequency (Frq) = 15 MHz, Gain (Gn) = 25–35 db, Depth (D) = 1–1.5 cm, and Focus (F) = 0.5 cm enhanced the image quality and assessability. Conclusions: An optimized HRUS examination protocol for quantitative and qualitative facial muscle assessments was proposed.
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