Search

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.

Minimally Invasive Robotic Surgery (MIRS) has emerged as a transformative approach in surgical practice, offering reduced patient trauma and enhanced precision. However, challenges persist, including the loss of tactile feedback for surgeons. This study explores the application of machine learning algorithms, specifically variational autoencoders, in vibro-acoustic (VA) signal analysis to address this issue. Our comparative analysis evaluates the potential of supervised learning in surgical data analysis, contributing to advancements in surgical technology. Despite achieving an accuracy of 81%, our results indicate opportunities for further refinement, considering the superior accuracies reported in previous studies. This research underscores the importance of innovative approaches in medical data analysis for optimizing patient care in minimally invasive surgery.

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.

This paper presents the use of vibro-acoustic sensing to augment laparoscopic surgery procedures by analyzing the signals produced during cutting and palpation tasks on various tissue samples. Vibro-acoustic signals were acquired during an experiment on a dedicated phantom covered in dense foam, where three trocars were inserted into the phantom to place the endoscopic camera and two laparoscopic instruments. The results of the signals analysis demonstrate the potential of this approach for making laparoscopic interactions audible, differentiating between tissue types, and detecting variations in tissue properties. Vibro-acoustic sensing could be a valuable tool for integrating sound into the current clinical workflow for enhancing endoscope video images.

Vascular diseases like aneurysms or atherosclerosis belong to the leading causes of death. For diagnosis and treatment, medical imaging is essential. Standard imaging methods are Ultrasound, X-ray-based Angiography, Computed tomography or Magnet Resonant Imaging. Additionally, Intravascular Ultrasound or Optical Coherence Tomography are available for intravascular imaging. One imaging technique for direct investigation of the inner vessel is vascular endoscopy, also called angioscopy. It is based on the insertion of an optical endoscope into the blood vessel for direct imaging. Dependent on the vessel diameter, these endoscopes have to be very small. Angioscopy can provide valuable information about the condition of the vessel wall and serve for procedure observation or implant assessment. But angioscopy requires the absence of blood for a clear field of view. In prior research, we have already developed methods for the placement of a tiny optical fiber inside a catheter combination. As an essential step toward a clinical study, we now want to evaluate the flushing parameters needed to achieve a clear field of view for the endoscope. The parameters are affected by the blood flow and vessel diameter. We designed a test setup that allows angioscopic examination and the simulation of realistic conditions, such as blood flow and different vessel diameters and that includes a test pattern for image quality assessment.

According to [1]-[3], the healthcare systems are suffering from severe personnel shortages with a lack of medical care workers, operating room nurses, and surgical technicians. This deficiency will become worse in the upcoming decades. Automatization of highly standardized procedures could be a promising approach to address this issue. We designed a new concept for the automated handover and return of surgical instruments to the surgeon in an operating theater scenario to relieve operating room personnel from their workload. In this setup, the surgical instruments are delivered pre-sorted in an upright position by the sterilization unit in an instrument basket or drum. A single-use, doublelayered, brushy conveyor belt system mounted on a robot arm acts as the connector between pick-position (instrument basket) and individually pre-definable hand-over-position. The system is placed next to the table inside the operation room (OR). Based on voice commands, the conveyor intake moves over to the selected instrument and delivers it to the surgeon in a fast and short motion. After use, the surgeon can feed the instrument into the intake at the handover position and place it back in the instrument basket. The robot arm allows precise maneuvering of the intake and output position. The concept was realized as a minimal-viable product and will be evaluated for further improvement.

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.

For treatment decision of Eustachian tube (ET) dysfunction, a reliable diagnosis of the reason for this dysfunction is of interest. Imaging methods like CT or MRI do not show enough details today. Endoscopy is challenging but can show at least superficial structures at the pharyngeal orifice. To look into the deeper tissue layers vascular imaging methods like IVUS and OCT were evaluated already. But these procedures are not made and certified for this application and come with risks for the patient. To overcome this issue, we propose the use of an additional closed end guide catheter that can be advanced into the ET. An OCT catheter can be placed inside without touching the patient’s tissue. In this paper we evaluate this approach on a sheep cadaver head and a human cadaver head.

Knee arthroplasty follow-up involves only a limited number of X-ray-based implant condition assessments at extended intervals. Polyethylene (PE) wear of knee endoprosthesis often progresses unnoticed until symptomatic adverse effects become apparent or implant failure occurs. A PE wear measuring concept, consisting of an implanted passive sensor and an extracorporeal readout unit, was previously presented by our group. This system is intended to enable patients to regularly check their knee implants’ condition at home. In this context, an appropriate product design for the readout unit is essential to enable the user to record correct measurements. An experimental investigation of the optimized positioning of the system's readout unit was conducted and the measurement data were analyzed. The findings were then implemented in a prototype for readout unit attachment. A sleeve with Velcro and a sewn-in readout unit has been fabricated. A cutout for the patella ensures intuitive correct alignment of the measurement system according to the experimental results. A hardware housing incorporates the electronics.

Retractors are used in surgery for the displacement of tissue and organs and to keep the surgical area open. The retraction can lead to a tissue compression that can cause irritation on nerves, perfusion deficits, hematoma or late sequelae like wound healing disorders, pain and numbness. The retraction force and thus the load on the tissue can not be measured with retraction systems today. We present a new concept for a retractor with an integrated spring element and an indicator to visualize retraction force and allow an adjustment of the organ compression. The new retractor was designed considering organ compression limits, requirements on sterility and easy manufacturing. Two retractors were built up as a prototype by 3D printing and tested in a distinguished test setup. The first test of the retractors was performed on a force measurement test bench using a fixed retractor, and in a second test, a liver specimen in a bowl. Tests were repeated for both retractor variants. The tests showed how different spring characteristics could be realized with the new retractor design. Depending on the spring characteristics, the compression could be limited to a certain level and flexibility that can compensate for unwanted patient motion. An indicator is integrated into the design showing the applied load on the retraction system. The presented concept can help to increase patient safety and reduce tissue trauma and late sequelae. The indicator is an easy way to visualize applied forces and allow adaption of the setup to the surgeon's needs.

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.

Laparoscopic access, a critical yet challenging step in surgical procedures, often leads to complications. Existing systems, such as improved Veress needles and optical trocars, offer limited safety benefits but come with elevated costs. In this study, a prototype of a novel technology for guiding needle interventions based on vibroacoustic signals is evaluated in porcine cadavers. The prototype consistently detected successful abdominal cavity entry in 100% of cases during 193 insertions across eight porcine cadavers. The high signal quality allowed for the precise identification of all Veress needle insertion phases, including peritoneum puncture. The findings suggest that this vibroacoustic-based guidance technology could enhance surgeons' situational awareness and provide valuable support during laparoscopic access. Unlike existing solutions, this technology does not require sensing elements in the instrument's tip and remains compatible with medical instruments from various manufacturers. [ABSTRACT FROM AUTHOR]

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

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.

The use of catheters and guide-wires in minimally invasive therapeutic approaches is an important part of clinical practice. In the neurovascular field, the unique nature of cerebral blood vessels necessitates very thin-walled and flexible catheters. The blood vessels in question are highly branched and at the same time can be less than one millimetre in diameter. This results in high demands on micro-catheters and guide-wires for successful endovascular therapy. The interaction of these surgical tools and the vessel wall is of especial interest. Depending on the catheter stiffness, this interaction can be friction, punctual collision or straightening. The work aims to design and implement a test setup for evaluation of these interactions with the vessel wall. For this purpose, a standardized vessel course with representative characteristics is necessary. Furthermore, by implementing suitable measuring equipment, an endovascular intervention can be simulated.

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.

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.

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.