We address the automatic differentiation of human tissue using multispectral imaging with promising potential for automatic visualization during surgery. Currently, tissue types have to be continuously differentiated based on the surgeon’s knowledge only. Further, automatic methods based on optical in vivo properties of human tissue do not yet exist, as these properties have not been sufficiently examined. To overcome this, we developed a hyperspectral camera setup to monitor the different optical behavior of tissue types in vivo. The aim of this work is to collect and analyze these behaviors to open up optical opportunities during surgery. Our setup uses a digital camera and several bandpass filters in front of the light source to illuminate different tissue types with 16 specific wavelength ranges. We analyzed the different intensities of eight healthy tissue types over the visible spectrum (400 to 700 nm). Using our setup and sophisticated postprocessing in order to handle motion during capturing, we are able to find tissue characteristics not visible for the human eye to differentiate tissue types in the 16-dimensional wavelength domain. Our analysis shows that this approach has the potential to support the surgeon’s decisions during treatment.

Objective: The preoperative diagnostical differentiation of parotid gland tumor (PGT) is not always simple due to several different entities. B-mode-ultrasound (US) remains the imaging modality of choice, while histopathology serves as the gold standard for finalizing the diagnosis. We aimed to evaluate the use of multiparametric US (mpUS) in the assessment of PGT. Methods: We included 97 PGTs from 96 patients. A standardized mpUS protocol using B-mode-US, shear-wave elastography (SWE), and standardized contrast-enhanced ultrasound (CEUS) was performed prior to surgical intervention. SWE was assessed by real-time measurement conducting a minimum of five measurements, while quantitative CEUS parameters were assessed with a post-processing perfusion software. Results: SWE allowed differentiation between benign PGT (Warthin’s Tumor (WT) paired with lymph nodes (LN) and pleomorphic adenoma (PA)), and WT and LN were softer compared to PA. WT showed lower velocities than squamous cell carcinoma (SCC): the most common malignant PGT. CEUS parameters showed significant group differences between WT and PA, WT and malignant lesions, WT and SCC, WT paired with LN versus PA, and WT paired with LN versus SCC. Conclusion: MpUS seems to be beneficial in the assessment of PGT characterization, with benign PGT appearing to be softer in SWE than tumors with malignant tendencies. The quantitative CEUS parameter shows higher perfusion in WT than in PA, and malignant PGTs are less vascularized than WTs.

The optical properties of human tissues have an effect on many diagnostic and therapeutic applications in laser medicine, but they are also important for routine medical diagnostics. Light can penetrate and then escape tissue, which increases the interest in understanding the scattering and absorption properties of human tissues, as it is the basis for medical diagnostics and therapy.¹ Specifying the optical properties of human tissue is the initial step in interpreting measurements correctly. These properties can then be used to predict the light distribution and deposition in tissue for many applications, e.g., intraoperative tissue analysis.

Existing challenges in surgical education (See one, do one, teach one) as well as the COVID-19 pandemic make it necessary to develop new ways for surgical training. Therefore, this work describes the implementation of a scalable remote solution called “TeleSTAR” using immersive, interactive and augmented reality elements which enhances surgical training in the operating room. The system uses a full digital surgical microscope in the context of Ear–Nose–Throat surgery. The microscope is equipped with a modular software augmented reality interface consisting an interactive annotation mode to mark anatomical landmarks using a touch device, an experimental intraoperative image-based stereo-spectral algorithm unit to measure anatomical details and highlight tissue characteristics. The new educational tool was evaluated and tested during the broadcast of three live XR-based three-dimensional cochlear implant surgeries. The system was able to scale to five different remote locations in parallel with low latency and offering a separate two-dimensional YouTube stream with a higher latency. In total more than 150 persons were trained including healthcare professionals, biomedical engineers and medical students.

Pathological structures, e.g., tumors, can develop between or in direct proximity to important structures, e.g., nerves. To reach the operating area, the surgeon has to expose the nerves without causing substantial damage.¹ This structure exposition process is of high risk and difficult, because damage to healthy structures, like nerves, can cause a temporary or permanent paralysis of the affected region. Furthermore, in normal light conditions, the different pathological tissue types are nearly undifferentiable from healthy neighboring tissue and the detailed anatomy differs widely between each patient. Therefore, it is very time-consuming to prepare important tissue without damaging the healthy anatomical structures,² but this slow and careful process is an important part of the operation. An automatic analysis, differentiation, and visualization of important tissue structures would allow the surgeon to perform operations faster and with lower risk.