The intraoperative assessment of tumor margins of head and neck cancer is crucial for complete tumor resection and patient outcome. The current standard is to take tumor biopsies during surgery for frozen section analysis by a pathologist after H&E staining. This evaluation is time-consuming, subjective, methodologically limited and underlies a selection bias. Optical methods such as hyperspectral imaging (HSI) are therefore of high interest to overcome these limitations. We aimed to analyze the feasibility and accuracy of an intraoperative HSI assessment on unstained tissue sections taken from seven patients with oral squamous cell carcinoma. Afterwards, the tissue sections were subjected to standard histopathological processing and evaluation. We trained different machine learning models on the HSI data, including a supervised 3D convolutional neural network to perform tumor detection. The results were congruent with the histopathological annotations. Therefore, this approach enables the delineation of tumor margins with artificial HSI-based histopathological information during surgery with high speed and accuracy on par with traditional intraoperative tumor margin assessment (Accuracy: 0.76, Specificity: 0.89, Sensitivity: 0.48). With this, we introduce HSI in combination with ML hyperspectral imaging as a potential new tool for intraoperative tumor margin assessment.

For the progress of point-of-care medicine, where individual health status can be easily and quickly monitored using a handheld sensor, saliva serves as one of the best-suited body fluids thanks to its availability and abundance of physiological indicators. Salivary biomarkers, combined with rapid and highly sensitive detection tools, may pave the way to new real-time health monitoring and personalized preventative therapy branches using saliva as a target matrix. Saliva is increasing in importance in liquid biopsy, a non-invasive approach that helps physicians diagnose and characterize specific diseases in patients. Here, we propose a proof-of-concept study combining the unique specificity in biomolecular recognition provided by surface-enhanced Raman spectroscopy (SERS) in combination with molecular dynamics (MD) simulations, which give leave to explore the biomolecular absorption mechanism on nanoparticle surfaces, in order to verify the traceability of two validated salivary indicators, i.e., interleukin-8 (IL-8) and lysozyme (LYZ), implicated in oropharyngeal squamous cell carcinoma (OSCC) and oral infection. This strategy simultaneously assures the detection and interpretation of protein biomarkers in saliva, ultimately opening a new route for the evolution of fast and accurate point-of-care SERS-based sensors of interest in precision medicine diagnostics.

The study demonstrates the potential of advanced vibrational spectroscopy to reveal the complex molecular composition of cerumen, suggesting its promising application as a non-invasive diagnostic tool for identifying disease-related biomarkers.

Background: In vivo visualization of malignant tumors remains the main challenge during head and neck cancer surgery. This can result in inadequate tumor margin assessment and incomplete tumor resection, adversely affecting patient outcomes. Hyperspectral imaging (HSI) is a promising approach to address this issue. However, its application in surgery has been limited by the lack of medically approved HSI devices compliant with MDR regulations, as well as challenges regarding the integration into the surgical workflow. Methods: In this feasibility study, we employed endoscopic HSI during surgery to visualize the tumor sites of 12 head and neck cancer patients. We optimized the HSI workflow to minimize time required during surgery and to reduce the adaptation period needed for surgeons to adjust to the new workflow. Additionally, we implemented data processing to enable real-time classification and visualization of HSI within the intraoperative setting. HSI evaluation was conducted using principal component analysis and k-means clustering, with this clustering validated through comparison with expert annotations. Results: Our complete HSI workflow requires two to three minutes, with each HSI measurement—including evaluation and visualization—taking less than 10 s, achieving an accuracy of 79%, sensitivity of 72%, and specificity of 84%. Medical personnel became proficient with the HSI system after two surgeries. Conclusions: This study presents an HSI workflow for in vivo tissue differentiation during head and neck cancer surgery, providing accurate and visually accessible results within minimal time. This approach enhances the in vivo evaluation of tumor margins, leading to more clear margins and, consequently, improved patient outcomes.

Biofeedback rehabilitation for facial palsy is not yet routinely available for patients. Methods: To improve evidence, the effect of an intensive two-week facial training combining electromyography (EMG) and visual biofeedback training of 30 patients (76.7% female; median age: 48.6 years) with post-paralytic facial synkinesis was objectively evaluated. At the beginning of each training day, EMG amplitudes of both halves of the face were recorded during relaxation using the EMG system that was synchronously used for the EMG biofeedback training. A single-factor analysis of variance was performed for the change over time, and a t-test was used to evaluate the side differences. Results: At the end of the training program, there was a significant decrease in the EMG amplitudes of both halves of the face (synkinetic side: p < 0.001; contralateral side p = 0.003), indicating an improved voluntary muscle relaxation. There was also a significant improvement in Sunnybrook Facial Grading System, Facial Disability Index and Facial Clinimetric Evaluation scores, which were assessed before the start of training and at the end (p < 0.001). Conclusion: Electrophysiological improvements can be objectively measured using surface EMG.

Functional Electrical Stimulation (FES) is an established intervention for a range of muscular and neurological disorders that has already been studied in numerous publications. However, its application to Peripheral Facial nerve Paralysis (PFP) still needs to be sufficiently investigated. As the first approach known to the authors, this study examines the effect of FES on the facial muscles in complete PFP using ultrasonography as a means of observation. In a prospective single-center observational pilot study, ten patients with complete PFP, confirmed by needle-electromyography (EMG), performed FES of the affected lateral mouth region at home twice daily for 20 minutes. The facial muscles’ Cross-Sectional Area (CSA) was regularly assessed using sonographic quantification. While the CSA of most non-stimulated muscles decreased considerably during ongoing paralysis, a significant CSA increase of the Zygomaticus Muscle (ZYG), which was regularly subjected to FES, could be demonstrated. FES can halt the atrophy of denervated ZYG and potentially other facial muscles. Further investigations with a more significant patient collective are recommended. From now on, FES could be established as an additive method in the non-invasive treatment of PFP.