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This work presents a novel approach for detecting underlying pulsatile structures with laparoscopic tools by using proximal vibroacoustic sensing. This new method could detect pulsations at a depth of up to 1.5 cm. The outcome of this work indicates the potential of identifying deep-seated pulsatile structures during robot-assisted laparoscopy, where haptic feedback is highly limited, to help surgeons prevent vascular damage that may lead to injuries.

The interaction between the surgical instrument and tissue is a yet little-exploited source of information. Vibroacoustic signals resulting from an interaction can be analyzed to extract relevant information related to the tissue. This work presents a summary of feasibility studies with synthetic-, animal-, and ex-vivo tissue specimen. A standard palpation probe is equipped with a vibration measurement system. A manual and robot-assisted setup is used for data acquisition. Simple features derived from the signals are used in a subsequent classification step using kNN and SVM. The obtained results show the capability to differentiate various tissues, such as subchondral bone with an accuracy of 98.44%. This demonstrates the potential of the approach to provide tissue related information based on instrument interactions.

Image-guided and minimally invasive procedures still require confirmation on having reached a target. Intraoperative imaging is not always sufficient or conclusive as it comes with artifacts that can come with a certain amount of ambiguity and inaccurate location information. As an alternative to imaging, we want to explore sounds produced by the biopsy needle tip while advancing and interacting with tissue. In this paper, we show that by analyzing vibroacoustic signals acquired at the proximal end of the needle we are able to differentiate the tissue type. In total, 419 audio samples of 5 tissues were acquired and converted to spectrograms used as input to a convolutional neural network. Using this experimental setup we were able to differentiate the tissue types with an F1 score of 71.64%. Based on these results we were able to demonstrate the feasibility of our approach, as well as the importance of further experiments to ensure that vibroacoustic sounds produced by the needle tip can be a new navigation method.

The overall complication rate during laparoscopic access is estimated to be as high as 14 %. Surgeons have to rely heavily on their experience and haptic perception while inserting the Veress needle or a trocar into the peritoneal cavity. Surgical Audio Guidance (SURAG) is a promising alternative to current techniques. It acquires instrument-born vibroacoustic (VA) waves to track the insertion of the instrument and provide real-time feedback to surgeons. This article presents an initial evaluation of the SURAG technology through two sets of experiments to classify Veress needle events using different AI-models. The results demonstrate the feasibility of using AI for classifying Veress needle events and the potential of the SURAG technology to support surgeons during laparoscopic access and minimally invasive needle interventions in general.

In previous work, we demonstrated the potential of blood flow sounds for biometric authentication acquired by a custom-built auscultation device. For this purpose, we calculated the frequency spectrum for each cardiac cycle represented within the measurements based on continuous wavelet transform. The resulting spectral images were used to train a convolutional neural network based on measurements from seven users. In this work, we investigate which areas of those images are relevant for the network to correctly identify a user. Since they describe the frequencies’ energy within a cardiac cycle, this information can be used to gain knowledge on biometric properties within the signal. Therefore, we calculate the saliency maps for each input image and investigate their mean for each user, opening perspectives for further investigation of the spectral information that was found to be potentially relevant.

Cerebrovascular diseases like atherosclerosis pose a great threat to health and wellbeing of people worldwide. To enable early diagnosis and treatment of a gradually progressing occlusion of the carotid arteries, we propose the BODYTUNE system. Consisting of a custom-built auscultation device and a mobile application, it aims at enabling the monitoring of the blood flow within the carotid arteries on a regular basis at home. In this work, we present the results of a survey with 65 participants from the system target group to investigate aspects like technical affinity and experience with comparable systems. These results provide the basis on how the BODYTUNE system should be designed to be user-centered, concerns.

Ultrasound (US) imaging is used for the diagnosis and also evaluation of thyroid nodules. A Thyroid Imaging Reporting and Data System (TIRADS) is used for the risk stratification of thyroid nodules through US images. The composition of thyroid nodules plays an important role in the risk-stratification process. The percentages of cystic and solid components in a thyroid nodule are one of the features that are can be indicative of the risk of malignancy. In this work, we attempt to classify and estimate solid and cystic regions within nodules. 20x20 texture patches were extracted from solid and cystic regions and converted into signals. These signals are decomposed into low, mid, and high-frequency bands using Continuous Wavelet Transform (CWT). A total of 36 features were extracted from the decomposed signals using Auto- Regressive Modeling. The features were fed into three different Machine Learning (ML) algorithms (Artificial Neural Networks, K-Nearest Neighbors, and Random Forest Classifier) to provide us with a classification of solid versus cystic regions in thyroid nodule US images. The Random Forest Classifier obtained an Accuracy, Sensitivity, and Specificity of 90.41%, 99% and 91% respectively which was the highest among the three chosen ML algorithms. Additionally, the output from the classification phase was also be used to determine the percentage of cystic and solid regions with a given thyroid nodule US image.

This paper presents the proof-of-concept study of an adaptor allowing the combination of a gamma probe with ultrasound (US) imaging, intending to improve the detectability of sentinel lymph nodes (SLNs). The performance of the adaptor in US imaging, in terms of depth of penetration and distance accuracy, and gamma scanning, in terms of sensitivity and spatial resolution, was investigated. We observed that the quality of the US imaging through the adaptor was promising and close to that of normal US imaging. However, the performance of the gamma probe through the adaptor was fairly poor, necessitating the improvement in the design of the adaptor for better gamma scanning. This study shall provide a basis for the development of a handheld gamma-US scanner for interventional procedures and small field-of-view (FOV) imaging in the future.

Minimal-invasive procedures come with significant advantages for the patient. They also come with problems as the navigation/guidance of the devices to a target location is either based on pre-operatively acquired images and then performed free-hand or is accompanied by intraoperative imaging such as MRI or CT that is expensive, complicated and produces artifacts. Using robotic systems for moving and guiding these interventional and therapeutic devices adds additional issues like lack of palpation sensation and missing tissue feedback. While it is possible to add sensors to the distal tip, this creates other obstacles concerning reduced functionality, cables, sterility issues and added complexity and cost. We propose to use a proximally attached audio sensor to record the tissue tool interaction and provide real-time feedback to the clinician. This paper reports on initial attempts to use this technology with robotic arms for surface characterization and interventional vascular procedures that gain increased attention in combination with robotic devices. In summary, Proximal Audio Sensing could be a versatile, cost-effective and powerful tool to guide minimally invasive needle interventions and enable (semi-) autonomous robot-assisted surgery.

Today's healthcare challenges with unmet clinical needs, high regulation and certification standards, and increasing costs demand faster innovation and technical translation. To address this challenge, Stanford released a fellowship called Biodesign, where need-based healthcare innovation is taught with the approach identify, invent and implement. Since then, different European institutions have adopted the Biodesign innovation approach and organized within the Biomedical Engineering- Innovation, Design, and Entrepreneurship Alliance (BMEidea EU). The generation of successful healthcare innovation isn't only based on participating in an Innovation teaching program. It is much more a matter of having the right innovation ecosystem with an open creative mindset, experts, the respective stakeholders, and access to essential resources within reach (close to clinic). Through a qualitative survey, seven Biodesign based teaching programs in the EU were examined. The study from an academic perspective contains information covering Resources, Activities, Academic Performance, and Transfer Performance. The demand for new healthcare innovations, and especially innovation training programs that address challenges, developed collaboratively with the respective stakeholders, is increasing. Additionally, there is a growing expectation that innovation needs to reach the market quickly and be implemented accordingly. A Healthcare Innovation Ecosystem, where different entities function as a productive unit with a shared vision and committed to application-driven research and technology transfer, will increase innovation's success and adaptation.

Polyethylene (PE) inlays of knee endoprostheses are exposed to constant mechanical stress causing particle abrasion and volumetric wear. With the current inlay surveillance strategy, significant change often can be only detected when the implant has already failed. To reduce medical complications arising from implant malposition or failure, early and accurate assessment of the implant condition is of great value. We present a novel concept to monitor PE inlays based on an implanted sensor. Requirements of sensor integration into endoprostheses were discussed and specified for an inlay monitoring concept. A planar eddy current sensor for measuring the gradual descent of the femoral component was proposed where inductive and capacitive sensor elements form a resonant circuit. The potential sensitivity of the proposed measuring method was tested in an experimental setup using an RFID tag as a sensor substitute. A measurement concept, including the sensor and an extracorporal readout coil, was described and the validity was verified using finite element method (FEM) simulation of a simplified knee model. The experiments showed that a significant resonant frequency shift occurs in the sensor with decreasing distance to the femoral component. FEM simulation demonstrated that the sensor could be powered and readout extracorporeally through inductive coupling with an external readout coil. The proposed concept is a promising solution for feasible and accurate reading of the implant status designed to meet medical requirements. It can enable autonomous and routine monitoring as well as early detection of critical inlay deformation with a home-use device.

Auscultation methods allow a non-invasive diagnosis of cardiovascular diseases like atherosclerosis based on blood flow sounds of the carotid arteries. Since this process is highly dependent on the clinician’s experience, it is of great interest to develop automated data processing techniques for objective assessment. We have recently proposed a computerassisted auscultation system that we use to acquire carotid blood flow sounds. In this work, we present an approach for detecting artifacts within the blood flow sound caused by swallowing or coughing events. For this purpose, we first decompose the signal using a discrete wavelet transform (DTW). Then, we compute an energy ratio between the DWT scales associated with the signal information with and without artifacts using a sliding window of 1 s length. Evaluation based on Kruskal-Wallis and Wilcoxon rank-sum tests shows a statistically significant difference (p-value

Health longevity, cost reduction, prevention-based healthcare, personalized medicine, predictive diagnostic, transformed care delivery, de-aging, healthy lifestyle trends, and implementation of intelligent technologies should lead to a more democratized (availability for everyone on this planet) healthcare provision. Forecasting the future of healthcare and health policy certainly is imperfect but nevertheless a precious scientific approach that can lead to novel innovative approaches. In the last decade, the healthcare system faced several challenges, including the significant increase of care costs, demographic changes towards the older population, inability to prevent and overcome pandemics, increased chronic and non-communicable diseases, or resistance to adopting emerging technologies. The need to shift the focus from sickness to health becomes a critical mission. We developed a lecture titled "Healthtech Innovation Design" for graduate students from medicine, biomedical engineering, neuroscience and software engineering. The lecture's goal is to teach innovation methodologies, exponential technologies and methods to achieve healthcare democratization. A critical component is to promote initiatives with global teams focused on the future of health. The educational and initiative programs were impactful in growing interest toward innovation, focusing on disruption and healthcare democratization. Participants awareness towards the main issues and challenges was raised. Interdisciplinary participation was qualitatively processed to generate a holistic vision toward innovation. Through embracing digitalization to a patient-centric approach, affordable care services, and the expansion of precision medicine, the entire healthcare organization and management will likely undergo a worldwide change. Notably, digital technologies, the leverage of artificial intelligence and empathy would satisfy unmet clinical needs. With a future-oriented statement, the forecast of healthcare becomes more imaginable, in which democratization will allow the affordability of services in different countries and economic status.

About 50 % of complications during laparoscopy occur when surgical access is created. The Veress needle and proposed technical alternatives do not provide reliable information to support the surgeons in guiding the needle, or the feedback is not clearly perceivable. Based on acoustic emissions, Surgical Audio Guidance (SURAG) proposes a non-invasive and efficient way to enhance the perception of guidance information through acoustic and visual feedback displayed in real-time. This article demonstrates that the developed feedback matches the information about tissue layer crossings provided by force measurements. This indicates that SURAG can provide an effective means to make laparoscopic access more precise and safe, especially in pediatric surgery, where space for placing the needle is minimal.

Auscultation methods allow the non-invasive diagnosis of pathological conditions (e.g., of the lung, heart or blood vessels) based on sounds that the body produces (e.g., breathing, heartbeat, swallowing or the blood flow). Through regular homebased examinations and Big Data combined with Machine learning techniques like Deep Learning, these could help detect diseases in an early stage, thus preventing serious health conditions and subsequently ensuring optimal therapy through continuous monitoring. This paper presents BODYTUNE, a novel inexpensive multi-auscultation system that aims at providing a tool for establishing a baseline of audio signal derived classification parameters that could be used for the self-monitoring of personal health for everybody through the analysis of deviations from that baseline. In the future, Big Data analysis could additionally lead to prediction and early detection of disease events.

Irreversible Electroporation (IRE) is a non-thermal tumor ablation treatment applicable for prostate cancer. IRE uses ultra-short but strong electrical pulses to destroy cancer cells nonthermally [1]. Clinically available IRE therapy requires two or more needle electrodes placed around the target tissue to apply the electric fields. A pre-requirement to achieve successful and effective ablation is an accurate and parallel needle placement to cover the tumor zone. Differences in tissue density, organ surface curvature as well as organ and patient motion in combination with long and highly flexible needle electrodes causes’ difficulties to achieve the desired target accuracy during needle placement process. We propose a concept of a shooting mechanism in combination with a grid template support to improve the parallel needle placement process for prostate cancer treatment. Instead of conventionally inserting the needle in the body by hand, it can be placed with high speed using a shooting device setup, that works similar like a biopsy gun.

Ultrasound (US) imaging is used as a preliminary diagnostic tool for the detection, risk-stratification and classification of thyroid nodules. In order to perform the risk stratification of nodules in US images physicians first need to effectively detect the nodules. This process is affected due to the presence of inter-observer and intra-observer variability and subjectivity. Computer Aided Diagnostic tools prove to be a step in the right direction towards reducing the issue of subjectivity and observer variability. Several segmentation techniques have been proposed, from these Deep Learning techniques have yielded promising results. This work presents a comparison between four state of the art (SOTA) Deep Learning segmentation algorithms (UNet, SUMNet, ResUNet and Attention UNet). Each network was trained on the same dataset and the results are compared using performance metrics such as accuracy, dice coefficient and Intersection over Union (IoU) to determine the most effective in terms of thyroid nodule segmentation in US images. It was found that ResUNet performed the best with an accuracy, dice coefficient and IoU of 89.2%, 0.857, 0.767. The aim is to use the trained algorithm in the development of a Computer Aided Diagnostic system for the detection, riskstratification and classification of thyroid nodules using US images to reduce subjectivity and observer variability

The grade of reperfusion after endovascular treatment of ischemic stroke e.g. mechanical thrombectomy is determined based on the mTICI score. The mTICI score shows significant interrater variability; it is usually biased towards better reperfusion results if selfassessed by the operator. We therefore developed a semiautomated image processing technique for assessing and evaluating the degree of reperfusion independently, resulting in a more objective mTICI score. Methods: Fifty angiography datasets of patients who were treated with mechanical thrombectomy for middle cerebral artery (MCA) occlusion were selected from our database. Image datasets were standardized by adjustment of field of view and orientation. Based on pixel intensity features, the internal carotid artery (ICA) curve was detected automatically and used as a starting point for identifying the target downstream territory (TDT) of the MCA on the DSA series. Furthermore, a grid with predefined dimensions was used to divide the TDT into checkzones and be classified as perfused or unperfused. Results: The algorithm detected the TDT and classified each zone of the grid as perfused or unperfused. Lastly, the percentage of the perfused area in the TDT was calculated for each patient and compared to the grading of experienced clinical users. Conclusion: A semi-automatic image-processing workflow was developed to evaluate perfusion rate based on angiographic images. The approach can be used for the objective calculation of the mTICI score. The semi-automatic grading is currently feasible for MCA occlusion but can be extended for other brain territories. The work shows a starting point for a machine learning approach to achieve a fully automated system that can evaluate and give an accurate mTICI score to become a common AI-based grading standard in the coming near future.

Under-staffing of nurses is a significant problem in most countries. It is expected to rise in the coming years, making it challenging to perform crucial tasks like assessing a patient's condition, assisting the surgeon in medical procedures, catheterization and Blood Transfusion etc., Automation of some essential tasks would be a viable idea to overcome this shortage of nurses. One such task intended to automate is the role of a 'Scrub Nurse' by using a robotic arm to hand over the surgical instruments. In this project, we propose to use a Collaborative Robotic-arm as a Scrub nurse that can be controlled with voice commands. The robotic arm was programmed to reach the specified position of the instruments placed on the table equipped with a voice recognition module to recognize the requested surgical instrument. When the Surgeon says "Pick Instrument", the arm picks up the instrument from the table and moves it over to the prior defined handover position. The Surgeon can take over the instrument by saying the command "Drop". Safe pathways for automatic movement of arm and handover position will be predefined by the Surgeon manually. This concept was developed considering the convenience of the Surgeon and the patient's safety, tested for collision, noisy environments, positioning failures and accuracy in grasping the instruments. Limitations that need to be considered in future work are the recognition of voice commands which as well as the returning of the instruments by the surgeon in a practical and safe way.

We have witnessed impressive advances in preoperative imaging of cancer and the development of dualmodality scanners. However, there is a need for a scanner with functional and anatomical imaging capability suitable for surgical settings and radioguided surgery. The current paper introduces a handheld gamma-ultrasound scanner prototype and illustrates the initial result of testing its very first version. The result of the testing was promising and encouraging in continuing the further development of the prototype.

This work aims to demonstrate the feasibility that haptic information can be acquired from a da Vinci robotic tool using audio sensing according to sensor placement requirements in a real clinical scenario. For that, two potential audio sensor locations were studied using an experimental setup for performing, in a repeatable way, interactions of a da Vinci forceps with three different tissues. The obtained audio signals were assessed in terms of their resulting signal-to-noise-ratio (SNR) and their capability to distinguish between different tissues. A spectral energy distribution analysis using Discrete Wavelet Transformation was performed to extract signal signatures from the tested tissues. Results show that a high SNR was obtained in most of the audio recordings acquired from both studied positions. Additionally, evident spectral energy-related patterns could be extracted from the audio signals allowing us to distinguish between different palpated tissues.

During thermal ablation in a target tissue the information about temperature is crucial for decision making of successful therapy. An observable temporal and spatial temperature propagation would give a visual feedback of irreversible cell damage of the target tissue. Potential temperature features in ultrasound (US) B-Mode image sequences during radiofrequency (RF) ablation in ex-vivo porcine liver were found and analysed. These features could help to detect the transition between reversible and irreversible damage of the ablated target tissue. Experimental RF ablations of ex-vivo porcine liver were imaged with US B-Mode imaging and image sequences were recorded. Temperature was simultaneously measured within the liver tissue around a bipolar RF needle electrode. In the B-Mode images, regions of interest (ROIs) around the centre of the measurement spots were analysed in post-processing using average gray-level (AVGL) compared against temperature. The pole of maximum energy level in the time-frequency domain of the AVGL changes was investigated in relation to the measured temperatures. Frequency shifts of the pole were observed which could be related to transitions between the states of tissue damage.

For assessing clinically relevant structures in the neck area, especially the thyroid, it has been shown that 3D or tomographic ultrasound (3D US or tUS) is able to outperform standard 2D ultrasound [1] and computed tomography [2] for certain diagnostic procedures. However, when using a freehand and unassisted scanning method to acquire a 3D US volume data set in this area overlapping image slices, a variation of the probe angulation or differences in training might lead to unusable scanning results. Based on previous works [3] [4] we propose the design - with subsequent testing - of an assistive device that is able to aid physicians during the tUS scanning process on the neck. To validate the feasibility and efficacy we compared the image quality of both freehand and assisted scanning.

Vascular endoscopic imaging is known for a long time but has never made its way into clinical routine. Reasons for that are the complexity, lack of low-cost portable systems, and the lack of suitable endoscopes providing high image quality with small dimensions. In addition, an interruption of the blood flow caused by the device and the opacity of blood are difficult to manage. In the past we have already developed ideas to overcome these difficulties and now we present a feasibility test of a thin diameter ureteroscope for observation of vascular procedures. The imaging system was tested in a phantom where side branches were explored, a stent was placed and a simulated aneurysm coiled.

In robot-assisted procedures, the surgeon controls the surgical instruments from a remote console, while visually monitoring the procedure through the endoscope. There is no haptic feedback available to the surgeon, which impedes the assessment of diseased tissue and the detection of hidden structures beneath the tissue, such as vessels. Only visual clues are available to the surgeon to control the force applied to the tissue by the instruments, which poses a risk for iatrogenic injuries. Additional information on haptic interactions of the employed instruments and the treated tissue that is provided to the surgeon during robotic surgery could compensate for this deficit. Acoustic emissions (AE) from the instrument/tissue interactions, transmitted by the instrument are a potential source of this information. AE can be recorded by audio sensors that do not have to be integrated into the instruments, but that can be modularly attached to the outside of the instruments shaft or enclosure. The location of the sensor on a robotic system is essential for the applicability of the concept in real situations. While the signal strength of the acoustic emissions decreases with distance from the point of interaction, an installation close to the patient would require sterilization measures. The aim of this work is to investigate whether it is feasible to install the audio sensor in non-sterile areas far away from the patient and still be able to receive useful AE signals. To determine whether signals can be recorded at different potential mounting locations, instrument/tissue interactions with different textures were simulated in an experimental setup. The results showed that meaningful and valuable AE can be recorded in the non-sterile area of a robotic surgical system despite the expected signal losses.

Novel challenges and developments require adaptations on skill set, content, and associated education. A biomedical engineer will require a broad range of skills - which to a large extent are currently not taught - in the coming years to meet the development needs of future healthcare: intensive interdisciplinary team work, advanced communication skills, team management and coaching capabilities, advanced project management, learn how to learn, visionary and forward looking thinking, understanding of health economics, entrepreneurship and leadership. But above all empathy towards the clinical user and patients is needed as well as a basic understanding of the current and future clinical workflows that can globally vary. An innovation process for a healthcare related product or service will likely only create value through the consideration and implementation of several of these points. Even though techniques for the development of innovation and enhancing creativity in individuals are widely discussed, there are relatively few reports on the practice of mainstreaming creativity in an organizational setting. We report on the setup of our Graduate School “Technology Innovation in Therapy and Imaging (T²I²)” that has implemented a structured post graduate program and focuses on interdisciplinary and application-oriented innovation generation education. The educational process starts with the observation and identification of clinical needs and an in-depth understanding of the problem and subsequently covers all steps necessary to transfer prototypes into viable solutions and further into implementing valuable products.

Endoscopy is an important modality in medical imaging. Thin flexible endoscopes are for example used to examine the upper airways, for gastroscopy procedures or lung inspection. With standard flexible endoscopes one can change the direction of view by bending the tip with the disadvantage of large space required due to the bending radius. With first experiences of a concept of a moveable camera head on the tip of rigid endoscopes, we now propose a novel design employing a swiveling camera for flexible endoscopes. This concept is based on the use of a shape memory wire used to control the movement of the camera, a flexible plastic flap joint for tight rotation and flexible printed circuits for the electronic connection. The prototype was realized in a first low cost setup using a 5,5 mm HD chip on the tip camera with LED light. The motion and imaging performance of the prototype allowed swiveling of the camera on the endoscope tip from straight view to 100° side view. The space needed in fully rotation was limited to 9mm with an overall diameter of the endoscope in straight view of only 5,6mm, but could even be further reduced in a more professional setup. The image quality is good, but close-up views appear blurry due to the fixed focus point of the low-cost camera. The presented steering concept of the camera is promising, as it could potentially improve imaging of narrow cavities using flexible endoscopes. Especially for “in office” examinations this principle could add value to diagnosis and patient comfort.

Longitudinal and perpendicular changes in the blood vessels of the vocal fold have been related to the advancement from benign to malignant laryngeal cancer stages. The combination of Contact Endoscopy (CE) and Narrow Band Imaging (NBI) provides intraoperative realtime visualization of vascular pattern in Larynx. The evaluation of these vascular patterns in CE+NBI images is a subjective process leading to differentiation difficulty and subjectivity between benign and malignant lesions. The main objective of this work is to compare multi-observer classification versus automatic classification of laryngeal lesions. Six clinicians visually classified CE+NBI images into benign and malignant lesions. For the automatic classification of CE+NBI images, we used an algorithm based on characterizing the level of the vessel’s disorder. The results of the manual classification showed that there is no objective interpretation, leading to difficulties to visually distinguish between benign and malignant lesions. The results of the automatic classification of CE+NBI images on the other hand showed the capability of the algorithm to solve these issues. Based on the observed results we believe that, the automatic approach could be a valuable tool to assist clinicians to classifying laryngeal lesions.

The effectiveness, efficiency, availability, agility, and equality of global healthcare systems are in question. The COVID-19 pandemic have further highlighted some of these issues and also shown that healthcare provision is in many parts of the world paternalistic, nimble, and often governed too extensively by revenue and profit motivations. The 4th industrial revolution - the machine learning age - with data gathering, analysis, optimisation, and delivery changes has not yet reached Healthcare / Health provision. We are still treating patients when they are sick rather then to use advanced sensors, data analytics, machine learning, genetic information, and other exponential technologies to prevent people from becoming patients or to help and support a clinicians decision. We are trying to optimise and improve traditional medicine (incremental innovation) rather than to use technologies to find new medical and clinical approaches (disruptive innovation). Education of future stakeholders from the clinical and from the technology side has not been updated to Health 4.0 demands and the needed 21st century skills. This paper presents a novel proposal for a university and innovation lab based interdisciplinary Master education of HealthTEC innovation designers.

Arthroscopic surgery is a technically challenging but common minimally invasive procedure with a long learning curve and a high incidence of iatrogenic damage. These damages can occur due to the lack of feedback and supplementary information regarding tissue-instrumentcontact during surgery. Deliberately performed interactions can be used however to obtain clinically relevant information, e.g. when a surgeon uses the tactile feedback to assess the condition of articular cartilage. Yet, the perception of such events is highly subjective. We propose a novel proximally attached sensing concept applied to arthroscopic surgery to allow an objective characterization and utilization of interactions. It is based on acoustic emissions which originate from tissue-instrument-contact, that propagate naturally via the instrument shaft and that can be obtained by a transducer setup outside of the body. The setup was tested on its ability to differentiate various conditions of articular cartilage. A femoral head with varying grades of osteoarthritic cartilage was tapped multiple times ex-vivo with a conventional Veress needle with a sound transducer attached at the outpatient end. A wavelet-based processing of the obtained signals and subsequent analysis of distribution of spectral energy showed the potential of tool-tissue-interactions to characterize different cartilage conditions. The proposed concept needs further evaluation with a dedicated design of the palpation tool and should be tested in realistic arthroscopic scenarios.

The short-range and sharp dose fall-off of beta particles in tissue make them an interesting option for use in the radiation therapy of superficial skin tumors. This can be used to protect bony or other sensitive structures located right beneath the tumor. In a previous study, we studied the feasibility of using 3D printing technology to create 2D radioactive models for the treatment of skin tumors. In the current study, the Monte Carlo method was used to simulate the transverse dose profile form 3D printed extruded line containing yttrium-90 (Y-90) particles. The time and activity required for treating a superficial skin tumor using these extruded lines were also calculated.

Photodynamic therapy (PDT) is a potential option for treatment of cancer since it can be performed non- invasive for superficial cancers or minimal-invasive with low traumatization. But PDT is intrinsically inefficient due to the complex accumulation of the photosensitizing drug inside the tumor and the processes of heme syntheses to create the needed cell killing components. To optimize the outcome of PDT and increase acceptance as viable option it is necessary to predict the optimal time for the start of the treatment based on measurable precursors. A former cell study proposed a new filter fluorometer in a complex and sensitive setup. In this work we now designed and tested a simplified system that can be used in combination with standard endoscopic imaging systems. This system will be used as base to prove viability of this approach for a future clinical study.

The location of a puncture needle’s tip and the resistance of tissue against puncture are crucial information for clinicians during a percutaneous procedure. The tip location and needle alignment can be observed by image guidance. Tactile information caused by tissue resistance to rupture, allow clinicians the perception of structural changes during puncture. Nevertheless, this sense is individual and subjective. To improve percutaneous procedures, the implementation of transducers to enhance or complement the senses offer objective feedback to the user. Known approaches are e.g. based on integrated force sensors. However, this is connected to higher device costs, sterilization and certification issues. A recent publication shows the implementation of an audio transducer clipped at the proximal end of the needle. This sensor is capable of acquiring emitted sounds of the distal tiptissue interaction that are transmitted over the needle structure. The interpretation of the measured audio signals is highly depended on the transmission over the needle, the tissue and, the penetration depth. To evaluate the influence of these parameters, this work implements a simplified experimental setup in a controlled environment with a minimum of noise and without micro tremors induced by clinician’s hands. A steel rod simulating a needle is inserted into pork meat of different thickness. A controlled impact covering the needle’s tip mimics tissue contact. The resulting signals are recorded and analyzed for better understanding of the system.

For imaging of the vascular structure, angiography is state of the art. This can be done by contrast enhanced XRay, CT or MR imaging. But these modalities typically only show the blood flow and do not allow a depiction of the vasculature itself. To provide information about the vessel walls and plaques narrowing the blood flow, catheter based intra vascular ultrasound or vascular optical coherence tomography can be used. Optical endoscopic imaging is rarely used in vascular diagnosis. But endoscopic imaging can depict superficial inflammations or defects of the intima vessel layer and the real anatomical shape of the inner vasculature e.g. at bifurcations or aneurysms. Since OCT and endoscopic imaging both need a flushing to remove the blood for a short time, a combination of both modalities seems viable. For combining the two modalities, various background studies were performed including the selection of a feasible fibre endoscope, light source and camera system. A new pull-back and flushing device was designed and created for realizing the synchronous image acquisition using the two modalities. For calibration of the system and definition of the pullback and imaging parameters, first tests on artificial phantoms were performed. Then vascular and tissue models were imaged in a combined pullback mode after using the flush for complete blood removal. Endoscopic images were acquired in a video mode. The analysis of the images was done subjectively. As expected, the OCT provided structural information of the wall. The endoscopic images in combination with pullback appear blurry in video mode. The flushing liquid hinders the automatic focusing of the camera. Thus, smaller details could not be identified but bifurcations were visible. Even though the results were not good as expected, the study showed the potential of a bimodal system and addressed the issues faced in the initial implementation.

Cerebrovascular diseases such as stenosis, atherosclerosis or distention of the carotid artery are accountable for about 1 million death per year across Europe. Diagnostic tools like ultrasound imaging, angiography or magnetic resonance-based imaging require specific hardware and highly depend on the experience of the examining clinician. In contrast auscultation with a stethoscope can be used to screen for carotid bruits - audible vascular sounds associated with turbulent blood flow - a method called phonoangiography. A reliable auscultation setup is prerequisite to ensure high signal quality, adequate processing and the objective evaluation of this audible signal. We propose a computer assisted auscultation system for the acquisition of vascular sounds of the carotid. The system comprises of an auscultation device, a smartphone-based control application and cloud-based signal analysis and storage. It is designed to facilitate the objective assessment, screening and monitoring of long-term changes in the vessel condition based on auscultation of the carotid artery.

At present transoral laryngeal interventions are mainly observed and controlled by an external two dimensional direct microscopic view. This modality provides an overall view on the surgery situs in a straight line of sight. For treatment planning and appropriate documentation, an endoscopic inspection is mandatory prior to surgery. Nowadays a detailed endoscopic work-up of laryngeal lesions can be performed by contact endoscopy in combination with structure enhancement like Narrow Band Imaging. High resolution and magnification of up to 150 times provide detailed visualization of vascular structures and pathological changes of the tissue surface. In these procedures it is difficult however to localize the evaluated areas on large scale scenes like the microscopic view used for surgery. To provide a fast and easy image matching an automated vessel pattern recognition and allocation is presented. Endoscopic images depicting representative vessel structures of the vocal folds are selected out of contact endoscopy video scenes. These images are pre-processed for background homogenization. A Frangi Vessel Segmentation filter and morphological operations are used to extract the vessel structure and match it to the microscopic image. Using this method 4 detailed contact endoscopy images could be allocated in different scenes of the microscope video. This method can be used to simplify treatment planning and to prepare image data for documentation.

Robotic surgeries are still limited with respect to the surgeon’s natural senses. The tactile sense is exceptional important in conventional clinical procedures. To identify critical structures inside the tissue, palpation is a commonly used technique in conventional open surgeries. The underlying organ or pathological structures conditions (healthy, abnormally hard or soft) can for example be localized and assessed through this process. Palpation needs a tactile sense; however, that is commonly not available or limited in robotic surgeries. The palpation need was already addressed by several research groups that integrated complex sensor-feedback-systems into prototype surgical instruments for robotic systems. We propose a new technique to acquire data of the tissue tool interaction of the surgical instruments. The structure borne transmission path is used to measure acoustic emission (AE) at the outpatient (proximal) end of the instruments with the help of different sensors attached to the surface of the surgical tool. Initial tests were performed using a microphone in combination with a stethoscope. This setup showed promising results and a more integrated prototype was subsequently designed. A piezoelectric charge accelerometer was used as vibration sensor and compared to a MEMS microphone. A signal acquisition system was developed to acquire signals from both sensors in parallel. The sensors were then attached onto the shaft of a daVinci Prograsp Forceps instrument. According to the surgery observation, a series of simulated experiments was conducted. The tip of the grasper was swiped manually over a human subject’s dorsal and palmar hand side, lateral side of neck and over the carotid artery. Additionally, contact with soft tissue and other instruments were evaluated since these are events of interest during surgery. Advanced signal processing techniques allowed the identification and characterization of significant events such as palpation dynamics, contact and pulsation. Signals acquired by the MEMS microphone showed the most promising results. This approach will now be used to build a prototype for further evaluation in a clinical setup. The paper presents the first results that show that this novel technique can provide valuable information about the tool-tissue interaction in robotic surgery that typically can only be obtained through advanced distal sensor systems or actual human touch.

Radiation therapy is a valuable option for treatment of skin cancer. In order to deliver the radiation dose to the superficial skin tumor, an X-ray source, electron beam radiation therapy or a radioisotope is applied. The effectiveness of these procedures is well established in the literature. Findings of some recent studies have indicated that beta particles can be of particular interest in suppressing skin tumor growth. Betaemitting radioisotopes are favorable because of the short penetration depth of their emitted particles. Beta radiation can induce significant damage in superficial skin tumor, and at the same time, result in enhanced protection of the underlying healthy tissues. In this study, we propose the design of a patch that can be used in beta radiation therapy of skin cancer patients. For that, we describe the components of this radioactive patch, as well as a proposal for the subsequent clinical application procedure. A scaffold was used as a substrate for embedding the desired beta-emitting radioisotope, and two layers of hydrogel to provide protection and shielding for the radioactively labelled scaffold. The proposed design could provide a universal platform for all beta-emitting radioisotopes. Depending on the depth of the tumor spread, a suitable beta emitter for that specific tumor can be selected and used. This is of particular and critical importance in cases where the tumor is located directly on top of the bone and for which the depth of penetration of radiation should be limited to only the tumor volume. The proposed design has the mechanical flexibility to adapt to curved body regions so as to allow the use in anatomically challenging areas of the body.

In orthopedic hand surgeries C-arms are the standard imaging modalities for procedure and tool guidance. However, the currently used systems have a large footprint and high weight, which can lead to workspace restrictions and difficult positioning of the device at the desired imaging position. The aim of this paper is to present a prototype of a new, flexible, lightweight and small footprint X-ray system, which is capable to create 2D projection images from different orientations. The new design includes a miniaturized Xray tube covered in a custom-made case mounted on a flexible holding arm attached to the standard OR table rail. With that, fast positioning and fixation for the subsequent image acquisition is achieved. A flat panel detector is placed in an adjustable metal sheet construction below the table. For safety aspects an overlay of the X-ray cone beam with an integrated light source visualizes the irradiation area. The acquired images are visualized on a 2-in-1 netbook. A foot pedal initiates the imaging process. A prototype of the free movable miniaturized X-ray system FlexScan was build. Workspace restriction, usability and general imaging needs were simulated and tested. FlexScan has the potential to improve X-ray guided interventions on extremities especially for small private surgery centers. It fulfills the general imaging needs and is capable of producing 2D projection images from different orientations within a small and lightweight setup.

Optical tracking systems, such as the Moiré Phase Tracking system (MPT), can be used to correct motion prospectively especially during magnetic resonance imaging (MRI, MR) in neurologic application. For that an MRI safe camera is mounted in the MRI bore to detect motion by tracking a specific MPT marker, which is rigidly attached on the subject’s head. To enable prospective updates of the imaging volume´s position and orientation, and therefore to correct motion from the subject, the motion information captured from the camera need to be transformed from the camera into the MR coordinate system. The process of finding the transformation between both coordinate systems is called cross calibration and is essential for the overall motion correction performance. For the procedure of the cross calibration, an MR visible phantom with an attached MPT-marker is measured simultaneously with MRI and the MPT camera in multiple specific alignment positions. To reduce cross calibration errors, it is essential to move the phantom precisely into specified alignment positions. Due to the long and narrow bore design of ultra-high field systems (tunnel length > 3 m), the phantom can not be moved simply from a person leaning inside the scanner bore. Thus, to rotate it after each measurement step, either a technician must work inside the tunnel during the complete period of the cross calibration or the table must be moved in and out of the bore multiple times. To improve this currently established cross calibration procedure, we have developed an MRI safe phantom rotation system, which can be controlled remotely and precisely from outside the MRI bore. Even for ultra-high field imaging, the rotation system is fully MRI compatible. Initial tests were performed at a 7T whole-body MRI system and have proven the benefit of our rotation system.

Thermographic imaging is a known technology to detect temperature differences. For medical applications, the patterns of heat distribution are used for diagnosis. It is already tested to visualize blood supply, inflammatory processes, and superficial or more extensive tumors, e.g. in the breast tissue. This method was promoted for breast screening purposes and as a substitute for mammography for mid aged women, but the results were not convincing for younger women, where tissue density is higher, tumor growth is often connected to local temperature increase and radiation-based mammography is not an option. Infrared (IR) thermography can support tumor screening. The screening should allow the early detection of small lesions even in the depth. Therefor we evaluated the feasibility of dynamic cooling in combination with IR imaging in a phantom study. A temperature-controllable gel phantom including a heating plate, a depth-adjustable heat source mimicking a tumor, and three sensors for temperature monitoring was built up. A raspberry pi device serves as a control unit to create a stable temperature balance comparable to a human breast. For the experiments, the tumor was placed in various depth. After cooling, the thermal recovery phase of the phantom was imaged using an IR camera and a webcam. A pixel-wise analysis of the IR data detects a higher gradient of temperature change in the tumor region. The experiments demonstrated the feasibility of tumor detection based on dynamic cooling and IR imaging.

Ex vivo lung perfusion (EVLP) is a preservation method for donor lungs, which keep lungs viable in a physiological environment outside of a body for a short period of time. EVLP is established clinically for lung transplantation. Experimental applications for EVLP are e.g. lung cancer research or medical device development and testing. For preservation, a lung is ventilated artificially in an organ chamber and perfused antegrade through the pulmonary artery. Here we introduce a thermoregulation system for an experimental EVLP system to be used for translational research approaches as well as for training medical staff. To implement physiological culture conditions that are a prerequisite for lung preservation and tissue homeostasis, a thermoregulation is needed to rewarm the explanted lung tissue (storage temperature 4°C). Technically, the EVLP system must be thermally insulated, so loss of caloric is avoided. For monitoring, temperature sensors are integrated within the lung, in the organ chamber and in the afferent perfusate tube, whereby the measured values determine the thermoregulation. Initial tests using thermal packs (cooled to 4-6°C) placed on a heating mat, as a part of the perfusion circuit, showed that the perfusate temperature falls to 34°C, but restores after approximately 60 minutes (36.5°C), whereby the thermal pack is warmed. With this setup longer perfusion times should be obtained rather than without thermoregulation due to normothermic perfusion of the lung.

MRI-guided interventions (iMRI, e.g. prostate biopsy) are usually performed under a free-hand instrument targeting approach to guide and feed the instrument (e.g. biopsy needle) along the desired trajectory. However, this technique requires many iterative movements either from the interventionist or of the patient (with the MRI table) in and out of the MRI tunnel, which is cumbersome, time-consuming and expensive. To overcome these downsides, interventional MRI procedures can be facilitated with remotely controllable assistance systems for instrument alignment. Such systems require an accurate registration and tracking of the position and orientation of the instrument. Passive fiducial marker frames (e.g. additively manufactured Z-frame marker) are capable of providing full information about a device´s orientation within the image. In this paper, we present an automated alignment detection algorithm to track a Z-marker from system-independent screen-captured images. We evaluated the precision of the detection algorithm by analysing its computation results from schematic gold standard images in different marker orientations in comparison to MR-images with the same orientations. Our combined setup consists of a precise alignment system, an additively manufactured Z-frame marker and the related detection algorithm. It offers a fast, simple, independent and accurate automated instrument targeting for iMRI. For future work, we plan to conduct phantom targeting tests in combination with robotic alignment systems.

The automation of instruments and tools (e.g. bone drill) or robotic devices (e.g. needle positioning robot for prostate surgery) for use in interventional MRI (iMRI) is still challenging due to a lack of accurate, affordable and completely metal-free actuators and motors. Inspired by biological muscles, a bionic equivalent known as the fluid muscle actuator (which can be operated pneumatically or hydraulically) is well-known in the mechanical engineering industry. Fluid muscle actuators have multiple beneficial characteristics: they are simple, self-returning, low-friction and can produce relatively high actuation forces at low diameters and pressures. We present two novel designs for metal-free, pneumatic stepper motors for potential application in iMRI. Our stepper motors are powered by simple pneumatic muscles, which are assembled from low-cost off-the-shelf components. Besides, the components of the stepper motor demonstrators were 3Dprinted using a stereolithographic additive manufacturing process (SLA printing). We evaluate the effect of pneumatic muscle length on contractile force and length. Our results demonstrated the functional feasibility of the pneumatic muscle-powered and fully MRI-compatible stepper motor designs. In a next step, we will optimize the motor´s design, characterize their performance and reliability, and use the stepper motors to power a micropositioning device in iMRI-phantom tests.

Carbon nanotube (CNT) is a new technology used to generate gamma photons in X-ray tubes. CNTs, in comparison to other small X-ray sources, produce high X-ray intensities and as they are not based on a thermionic principle they considered cold electron sources with a very high conversion of electrical to photon energy. Their small size and other interesting properties could make them feasible for use in intraoperative radiation therapy applications. In this study, physical characteristics of the photon beam generated by the CNT-based X-ray source were assessed. A soft X-ray ionization chamber and a flat panel detector was used to measure dose and photon counts, respectively. The repetitively produced pulses had almost the same photon intensities with differences of less than 1% between them. For a typical selected pulse, the variation in the pulse amplitude was also insignificant, which shows a stable radiation exposure of the tube during the ON-mode. When moving from the center of the beam profile to the lateral distance of 25 mm, both intensity profile and dose profile showed a falling trend by a factor of almost 3 in the measured values.

Photodynamic diagnostic (PDD) is an optical enhancement option for the endoscope to support the detection of cancer, for example in the bladder. In real application PDD efficiency suffers due to the complex accumulation of the photosensitizing drug inside the tumor and the associated processes of heme syntheses to create the fluorescent components needed. To optimize the diagnostic outcome of PDD it would be helpful to predict the optimal time for diagnosis based on measurable precursors. In a previous cell study, we proposed a new filter fluorometer to image the accumulation of the precursors Coproporphyrin III (CP-III) and Uroporphyrin III (UP-III) that metabolize to Protoporphyrin IX (PP-IX) later. This accumulation process can be used to predict the optimal time slot for diagnostic imaging. Therefore, a new filter system was designed to distinguish between CP-III and PP-IX. In this work we tested this filter system in combination with a standard PDD endoscopic imaging system. Goal of this study was to prove the technical feasibility in a non-patient setup to prepare a later clinical study.

Susceptibility artefacts in magnetic resonance imaging (MRI) caused by medical devices can result in a severe degradation of the MR image quality. The quantification of susceptibility artefacts is regulated by the ASTM standard which defines a manual method to assess the size of an artefact. This means that the estimated artefact size can be user dependent. To cope with this problem, we propose an algorithm to automatically quantify the size of such susceptibility artefacts. The algorithm is based on the analysis of a 3D surface generated from the 2D MR images. The results obtained by the automatic algorithm were compared to the manual measurements performed by study participants. The results show that the automatic and manual measurements follow the same trend. The clear advantage of the automated algorithm is the absence of the inter- and intra-observer variability. In addition, the algorithm also detects the slice containing the largest artefact which was not the case for the manual measurements.

One of the oldest methods used in minimally invasive surgeries is the transurethral resection. This is an operation technique in which diseased tissue from the bladder or the prostate is removed using a resectoscope through the urethra [Schostak M, Blana A, Hrsg. Alternative operative Therapien in der Uroonkologie. Berlin, Heidelberg, Springer Berlin Heidelberg; 2016]. A resectoscope has a channel for the view of the surgeon, a liquid supply, a working channel and a hand piece which could rotate up to 360 degrees. A RF- electrode on the tip of the resectoscope is used to cut out pathological growths. For diseased tissue which is located in the bladder on the ventral side, a rotation of the resectoscope up to 180 degrees is necessary. This means on the one side tiring of the hands, wrist pain and a change of the position of the operating surgeon. On the other side a reorganization of the connected tubes and cables is necessary. To avoid these problems and integrate additional features a standard resectoscope was adapted with an easy to use twist mechanism. After discussion with experienced urological surgeons a complete new design of the resectoscope with a twist mechanism in combination with a gyro sensor and a reference display was realized.

In this paper, we propose a method to segment the thyroid from a set of 2D ultrasound images. We extended an active contour model in 2D to generate a 3D segmented thyroid volume. First, a preprocessing step is carried out to suppress the noise present in US data. Second, an active contour is used to segment the thyroid in each of the 2D images. Finally, all the segmented thyroid images are passed to a 3D reconstruction algorithm to obtain a 3D model of the thyroid. We obtained an average segmentation accuracy of 86.7% in six datasets with a total of 703 images.

Interventional MRI in closed bore high-field systems is a challenge due to limited space and the need of dedicated MRI compatible equipment and tools. A possible solution could be to perform an ultrasound procedure for guidance of the therapy tools outside the bore, but still on the MRI patient bed. That could track and subsequently combine the superior images of MRI with the real-time features of ultrasound. Conventional optical tracking systems suffer from line of sight issues and electromagnetic tracking does not perform well in the presence of magnetic fields. Hence, to overcome these issues a new optical tracking system called inside-out tracking is used. In this approach, the camera is directly attached to the US probe and the markers are placed onto the patient to achieve the location information of the US slice. The evaluation of our novel system of framed fusion markers can easily be adapted to various imaging modalities without losing image registration. To confirm this evaluation, phantom studies with MRI and US imaging were carried out using a point-registration algorithm along with a similarity measure for fusion. In the inside-out system approach, image registration was found to yield an accuracy of upto 4 mm, depending on the imaging modality and the employed marker arrangement and with that provides an accuracy that cannot be easily achieved by combining pre-operative MRI with live ultrasound.