570 Biowissenschaften, Biologie
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Purpose
Computerized medical imaging processing assists neurosurgeons to localize tumours precisely. It plays a key role in recent image-guided neurosurgery. Hence, we developed a new open-source toolkit, namely Slicer-DeepSeg, for efficient and automatic brain tumour segmentation based on deep learning methodologies for aiding clinical brain research.
Methods
Our developed toolkit consists of three main components. First, Slicer-DeepSeg extends the 3D Slicer application and thus provides support for multiple data input/ output data formats and 3D visualization libraries. Second, Slicer core modules offer powerful image processing and analysis utilities. Third, the Slicer-DeepSeg extension provides a customized GUI for brain tumour segmentation using deep learning-based methods.
Results
The developed Slicer-DeepSeg was validated using a public dataset of high-grade glioma patients. The results showed that our proposed platform’s performance considerably outperforms other 3D Slicer cloud-based approaches.
Conclusions
Developed Slicer-DeepSeg allows the development of novel AI-assisted medical applications in neurosurgery. Moreover, it can enhance the outcomes of computer-aided diagnosis of brain tumours. Open-source Slicer-DeepSeg is available at github.com/razeineldin/Slicer-DeepSeg.
Intraoperative imaging can assist neurosurgeons to define brain tumours and other surrounding brain structures. Interventional ultrasound (iUS) is a convenient modality with fast scan times. However, iUS data may suffer from noise and artefacts which limit their interpretation during brain surgery. In this work, we use two deep learning networks, namely UNet and TransUNet, to make automatic and accurate segmentation of the brain tumour in iUS data. Experiments were conducted on a dataset of 27 iUS volumes. The outcomes show that using a transformer with UNet is advantageous providing an efficient segmentation modelling long-range dependencies between each iUS image. In particular, the enhanced TransUNet was able to predict cavity segmentation in iUS data with an inference rate of more than 125 FPS. These promising results suggest that deep learning networks can be successfully deployed to assist neurosurgeons in the operating room.
In vitro, hydrogel-based ECMs for functionalizing surfaces of various material have played an essential role in mimicking native tissue matrix. Polydimethylsiloxane (PDMS) is widely used to build microfluidic or organ-on-chip devices compatible with cells due to its easy handling in cast replication. Despite such advantages, the limitation of PDMS is its hydrophobic surface property. To improve wettability of PDMS-based devices, alginate, a naturally derived polysaccharide, was covalently bound to the PDMS surface. This alginate then crosslinked further hydrogel onto the PDMS surface in desired layer thickness. Hydrogel-modified PDMS was used for coating a topography chip system and in vitro investigation of cell growth on the surfaces. Moreover, such hydrophilic hydrogel-coated PDMS is utilized in a microfluidic device to prevent unspecific absorption of organic solutions. Hence, in both exemplary studies, PDMS surface properties were modified leading to improved devices.
The paper describes how eye-tracking can be used to explore electronic patient records (EPR) in a sterile environment. As an information display, we used a system that we developed for the presentation of patient data and for supporting surgical hand disinfection. The eye-tracking was performed using the Tobii Eye Tracker 4C, and the connection between the eye-tracker and the HTML website was realized using the Tobii EyeX Chrome Extension. Interactions with the EPR are triggered by fixations of icons. The interaction was working as intended, but test persons reported a high mental load while using the system.
Analysis of multicellular patterns is required to understand tissue organizational processes. By using a multi-scale object oriented image processing method, the spatial information of cells can be extracted automatically. Instead of manual segmentation or indirect measurements, such as general distribution of contrast or flow, the orientation and distribution of individual cells is extracted for quantitative analysis. Relevant objects are identified by feature queries and no low-level knowledge of image processing is required.
Increasing number of studies are focused on how adherent cells respond, in vitro, to different properties of a material. Typical properties are the surface chemistry, topographical cues (at the nano- and micro-scale) of the surface, and the substrate stiffness. Cell Response studies are of importance for designing new biomaterials with applications in cell culture technologies, regenerative medicine, or for medical implants. However, only very few studies take the cell age factor, respectively the donor age, into account. In this work, we tested two types of human vascular cells (smooth muscle and endothelial cells) from old and young donors on (a) micro-structured surfaces made of pol (dimethylsiloxane) or on (b) flat polyacrylamide hydrogels with varying stiffnesses. These experiments reveal age-dependent and cell typedependent differences in the cell response to the topography and stiffness, and may establish the Basis for further studies focusing on cell age-dependent responses.
Polyelectrolyte multilayer coatings (PEM) are prepared by alternative layer-by-layer deposition of cationic and anionic polyelectrolyte monolayers on charged surfaces. The thickness of the coatings ranges from nm to few μm. Their properties such as roughness, stiffness, surface charge and surface energy can be precisely tuned to fulfil different technical or biological requirements. The coating process is based on self-assembly of polyelectrolytes. Advantages of these coatings are their easy handling, no harsh chemistry and the possibility for coatings on complex geometries. The PEM coatings can be prepared from a variety of suitable polyelectrolytes. Their stability varies from very durable PEM coatings that are only soluble in strong solvents to quickly degradable, which may be applied as drug release system. One example of such a degradable PEM system is the one based on the polyelectrolyte pair Hyaluronan (HA) and Chitosan (CHI). These biopolymers originate from natural sources and show low toxicity towards human cells. However, HA/CHI multilayers show only weak adhesiveness for human umbilical vein endothelial cells (HUVEC). In this article, we summarize our approaches to enhance the HA/CHI multilayer by incorporation of a non-polymer substance –graphene oxide– to improve the cell adhesion and keep such properties as low cytotoxicity and biodegradability. Different approaches for incorporation of graphene oxide were performed and the cellular adhesion was tested by metabolic assay.
Focal adhesion clusters (FAC) are dynamic and complex structures that help cells to sense physicochemical properties of their environment. Research in biomaterials, cell adhesion or cell migration often involves the visualization of FAC by fluorescence staining and microscopy, which necessitates quantitative analysis of FAC and other cell features in microscopy images using image processing. Fluorescence microscopy images of human umbilical vein endothelial cells (HUVEC) obtained at 63x magnification were quantitatively analysed using ImageJ software. A generalised algorithm for selective segmentation and morphological analysis of FAC, nucleus and cell morphology is implemented. Further, a method for discrimination of FACnear the nucleus and around the periphery is implemented using masks. Our algorithm is able to effectively quantify different morphological characteristics of cell components and shows a high sensitivity and specificity while providing a modular software implementation.
Natural extracellular matrix (ECM) represents an ideal biomaterial for tissue engineering and regenerative medicine approaches. For further functionalization, there is a need for specific addressable functional groups within this biomaterial. Metabolic glycoengineering (MGE) provides a technique to incorporate modified monosaccharide derivatives into the ECM during their assembly, which was shown by us earlier for the production of a modified fibroblast-derived dermal ECM.
Endogenous electrical fields play an important role in various physiological and pathological events. Yet the effects of electrical cues on processes such as wound healing, tumor development or metastasis are still rarely investigated, though it is known that direct current electrical fields can alter cell migration or proliferation in vitro. Several 2D experimental models for studying cell responses to direct current electrical fields have been presented and characterized but suitable experimental models for electrotaxis studies in 3D are rare. Here we present a novel, easy-to-produce, multi-well-based galvanotactic-chamber for the use in 2D and 3D cell experiments for investigations on the influence of electrical fields on tumor cell migration and tumor spheroid growth. Our presented system allows the simultaneous application of electrical field to cells in four chambers, either cultured on the bottom of the culture-plate (2D) or embedded in hydrogel filled channels(3D). The set-up is also suitable for, live-cell-imaging. Validation tests show stable electrical fields and high cell viabilities inside the channel. Tumor spheroids of various diameters can be exposed to direct current electrical fields up to one week.
Soft lithography, a tool widely applied in biology and life sciences with numerous applications, uses the soft molding of photolithography-generated master structures by polymers. The central part of a photolithography set-up is a mask-aligner mostly based on a high-pressure mercury lamp as an ultraviolet (UV) light source. This type of light source requires a high level of maintenance and shows a decreasing intensity over its lifetime, influencing the lithography outcome. In this paper, we present a low-cost, bench-top photolithography tool based on ninety-eight 375 nm light-emitting diodes (LEDs). With approx. 10 W, our presented lithography set-up requires only a fraction of the energy of a conventional lamp, the LEDs have a guaranteed lifetime of 1000 h, which becomes noticeable by at least 2.5 to 15 times more exposure cycles compared to a standard light source and with costs less than 850 C it is very affordable. Such a set-up is not only attractive to small academic and industrial fabrication facilities who want to enable work with the technology of photolithography and cannot afford a conventional set-up, but also microfluidic teaching laboratories and microfluidic research and development laboratories, in general, could benefit from this cost-effective alternative. With our self-built photolithography system, we were able to produce structures from 6 μm to 50 μm in height and 10 μm to 200 μm in width. As an optional feature, we present a scaled-down laminar flow hood to enable a dust-free working environment for the photolithography process.
Ultra wideband real-time locating system for tracking people and devices in the operating room
(2022)
Position tracking within the OR could be one possible input for intraoperative situation recognition. Our approach demonstrates a Real-time Locating System (RTLS) using the Ultra Wideband (UWB) technology to determine the position of people or objects. The UWB RTLS was integrated into the research OR at Reutlingen University and the system’s settings were optimized regarding the four factors accuracy, susceptibility to interference, range, and latency. Therefore, different parameters were adapted and the effects on the factors were compared. Goodtracking quality could be achieved under optimal settings. These results indicate that a UWB RTLS is well suited to determine the position of people and devices in our setting. The feasibility of the system needsto be evaluated under real OR conditions.
Vitamin E (VitE) additives are important in treating osteoarthritis inclusive cartilage regeneration due to their antioxidant and anti-inflammatory properties. The present research study focuses on the ability of biological antioxidant VitE (alpha-tocopherol isoform) to reduce or minimize oxidative degradation of soft implantable polyurethane (PU) elastomers after extended periods of time (5 months) in vitro. The effect of the oxidation storage media on the morphology of the segmented PUs was evaluated by mechanical softening, crystallization and melting behavior of both soft and hard segments (SS, HS) using dynamic mechanical analysis (DMA). Bulk mechanical properties of the potential implant materials during ageing were predicted from comprehensive mechanical testing of the biomaterials under tension and compression cyclic loads. 5-months in vitro data suggest that the prepared siloxane-poly(carbonate urethane) formulations have sufficient resistance against degradation to be suitable materials for chondral long term bio-stable implants. Most importantly, the positive effect of incorporating VitE (0.5 or 1.0% w/w) as bio-antioxidant and lubricant on the bio-stability was observed for all PU types. VitE-additives protected the surface layer from erosion and cracking during chemical oxidation in vitro as well as from thermal oxidation during extrusion re-processing.
A series of novel biomedical TPCUs with different percentages of hard segment and a silicone component in the soft segment were synthesized in a multi stage one-pot method. The kinetic profiles of the urethane formation in TPCU-based copolymer systems were monitored by rheological, in line FTIR spectroscopic (React IR) and real-time calorimetric (RC1) methods. This process-analytically monitored multi step synthesis was successfully used to optimize the production of medical-grade TPCU elastomers on preparative scale (in lots of several kg) with controlled molecular structure and mechanical properties. Various surface and bulk analytical methods as well as systematic studies of the mechanic response of the elastomer end-products towards compression and tensile loading were used to estimate the bio-stability of the prepared TPCUs in vitro after 3 months. The tests suggested that high bio-stability of all polyurethane formulations using accelerating in vitro test can be attributed to the synthetic design as well as to the specific techniques used for specimen preparation, namely: (1) the annealing for reducing residual polymer surface stress and preventing IES, (2) stabilization of the morphology by long time storage of the specimens after processing before being immersed in the test liquids, (3) purification by extraction to remove the shot chain oligomers which are the most susceptible to degradation. All mechanical tests were performed on cylindrical and circular disc specimens for modelling the thickness of the meniscus implants under application-relevant stress conditions.
Polyelectrolyte multi-layer (PEM) coatings are prepared by alternative deposition of single polyelectrolyte monolayers on charged surfaces using the Layer-by-Layer (LbL) dip coating procedure. These are nanometre scaled coatings which allow fulfilling of different technical or biological requirements. The build-up process is based on selfassembly and self organization of polycations and polyanions on different substrates including complex geometrical structures and even closed volumes, forming homogeneous layer without defects. Depending on the proper selection of the applied polyelectrolytes, coatings with different stabilities can be prepared. Some of the coatings are stable and cannot be removed from the surface. Others are degradable and can be used as systems for controlled local drug delivery. Here we summarise the results of our experience in preparation of PEM coatings with different functionalities. PEM coatings can be used as controllable delivery system for siRNA polyplexes. They can be used to control the adhesion of different cell types on the surfaces and support e.g. the endothelialisation process on cardio-vascular medical devices as e.g. stents or reduce the immunological response of the tissue after implantation. We summarise results from physical characterisation of the coatings (e.g. film thickness, roughness, electrical charge and hydrophilicity) combined with in-vitro biological studies on adhesion of HUVEC cells.
The extracellular matrix (ECM) naturally surrounds cells in humans, and therefore represents the ideal biomaterial for tissue engineering. ECM from different tissues exhibit different composition and physical characteristics. Thus, ECM provides not only physical support but also contains crucial biochemical signals that influence cell adhesion, morphology, proliferation and differentiation. Next to native ECM from mature tissue, ECM can also be obtained from the in vitro culture of cells. In this study, we aimed to highlight the supporting effect of cell-derived- ECM (cdECM) on adipogenic differentiation. ASCs were seeded on top of cdECM from ASCs (scdECM) or pre-adipocytes (acdECM). The impact of ECM on cellular activity was determined by LDH assay, WST I assay and BrdU assay. A supporting effect of cdECM substrates on adipogenic differentiation was determined by oil red O staining and subsequent quantification. Results revealed no effect of cdECM substrates on cellular activity. Regarding adipogenic differentiation a supporting effect of cdECM substrates was obtained compared to control. With these results, we confirm cdECM as a promising biomaterial for adipose tissue engineering.
In the current study the in vitro outcome of a degradable magnesium alloy (AZ91D) and standard titanium modified by nanostructured-hydroxyapatite (n-HA) coatings concerning cell adhesion and osteogenic differentiation was investigated by direct cell culture. The n-HA modification was prepared via radio-frequency magnetron sputtering deposition and proven by field emission scanning electron microscopy and X-ray powder diffraction patterns revealing a homogenous surface coating. Human mesenchymal stem cell (hMSCs) adhesion was examined after one and 14 days displaying an enhanced initial cell adhesion on the n-HA modified samples. The osteogenic lineage commitment of the cells was determined by alkaline phosphatase (ALP) quantification. On day one n-HA coated AZ91D exhibited a comparable ALP expression to standard tissue culture polystyrene samples. However, after 14 days solely little DNA and ALP amounts were measurable on n-HA coated AZ91D due to the lack of adherent cells. Titanium displayed excellent cell adhesion properties and ALP was detectable after 14 days. An increased pH of the culture was measured for AZ91D as well as for n-HA coated AZ91D. We conclude that n-HA modification improves initial cell attachment on AZ91D within the first 24 h. However, the effect does not ersist for 14 days in in vitro conditions.
Towards Automated Surgical Documentation using automatically generated checklists from BPMN models
(2021)
The documentation of surgeries is usually created from memory only after the operation, which is an additional effort for the surgeon and afflicted with the possibility of imprecisely, shortend reports. The display of process steps in the form of checklists and the automatic creation of surgical documentation from the completed process steps could serve as a reminder, standardize the surgical procedure and save time for the surgeon. Based on two works from Reutlingen University, which implemented the creation of dynamic checklists from Business Process Modelling Notation (BPMN) models and the storage of times at which a process step was completed, a prototype was developed for an android tablet, to expand the dynamic checklists by functions such as uploading photos and files, manual user entries, the interception of foreseeable deviations from the normal course of operations and the automatic creation of OR documentation.
We present an approach for segmenting individual cells and lamellipodia in epithelial cell clusters using fully convolutional neural networks. The method will set the basis for measuring cell cluster dynamics and expansion to improve the investigation of collective cell migration phenomena. The fully learning-based front-end avoids classical feature engineering, yet the network architecture needs to be designed carefully. Our network predicts how likely each pixel belongs to one of the classes and, thus, is able to segment the image. Besides characterizing segmentation performance, we discuss how the network will be further employed.
Digital light microscopy techniques are among the most widely used methods in cell biology and medical research. Despite that, the automated classification of objects such as cells or specific parts of tissues in images is difficult. We present an approach to classify confluent cell layers in microscopy images by learned deep correlation features using deep neural networks. These deep correlation features are generated through the use of gram-based correlation features and are input to a neural network for learning the correlation between them. In this work we wanted to prove if a representation of cell data based on this is suitable for its classification as has been done for artworks with respect to their artistic period. The method generates images that contain recognizable characteristics of a specific cell type, for example, the average size and the ordered pattern.