Carina Veil

All Publications

• Electrical impedance-based tissue classification for bladder tumor differentiation SCIENTIFIC REPORTS Veil, C., Krauss, F., Amend, B., Fend, F., Sawodny, O. 2025; 15 (1): 825

  Abstract

  Including sensor information in medical interventions aims to support surgeons to decide on subsequent action steps by characterizing tissue intraoperatively. With bladder cancer, an important issue is tumor recurrence because of failure to remove the entire tumor. Impedance measurements can help to classify bladder tissue and give the surgeons an indication on how much tissue to remove. Over the years of research, it became obvious that electrical impedance spectroscopy is a very promising tool for tissue differentiation, but also a very sensitive one. While differentiation in preliminary studies shows great potential, challenges arise when transferring this concept to real, intraoperative conditions, mainly due to the influence of preoperative radiotherapy, possibly different tumor types, and mechanical tissue deformations due to peristalsis or unsteady contact force of the sensor. This work proposes a patient-based classification approach that evaluates the distance of an unknown measurement to a healthy reference of the same patient, essentially a relative classification of the difference in impedance that is robust against inter-individual differences and systematic errors. A diversified dataset covering multiple disturbance scenarios is recorded. Two alternatives to define features from the impedance data are investigated, namely using measurement points and model-based parameters. Based on the distance of the feature vector of a unknown measurement to a healthy reference, a Gaussian process classifier is trained. The approach achieves a high classification accuracy of up to 100% on noise-free impedance data recorded under controlled conditions. Even when the differentiation is more ambiguous due to external disturbances, the presented approach still achieves a classification accuracy of 80%. These results are a starting point to tackle intraoperative bladder tissue characterization and decrease the recurrence rate.

  View details for DOI 10.1038/s41598-024-84844-9

  View details for Web of Science ID 001390173900012

  View details for PubMedID 39755796

  View details for PubMedCentralID PMC11700109

• Enhancing Tissue Impedance Measurements Through Modeling of Fluid Flow During Viscoelastic Relaxation IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING Veil, C., Mueller, D., Walz, S., Schule, J., Somers, P., Tarin, C., Stenzl, A., Sawodny, O. 2023; 70 (2): 650-658

  Abstract

  Bladder cancer recurrence is an important issue after endoscopic urological surgeries. Additional sensor information such as electrical impedance measurements aim to support surgeons to ensure that the entirety of the tumor is removed. The foundation for differentiating lies in the altered sodium contents and cell structures within tumors that change their conductivity and permittivity. Mechanical deformations in the tissue expel fluid from the compressed area and pose a great difficulty, as they also lead to impedance changes. It is crucial to determine if this effect outweighs the alterations due to the tumorous tissue properties.Impedance measurements under ongoing viscoelastic relaxation are taken on healthy and tumorous tissue samples from human bladders and breasts. A fluid model to account for extra- and intracellular fluid flow under compression is derived. It is based on the fluid content within the individual tissue compartments and their outflow via diffusion.After an initial deformation, the tissue relaxes and the impedance increases. The proposed model accurately represents these effects and validates the link between fluid flow under mechanical deformation and its impact on tissue impedance. A method to compensate for these undesired effects of fluid flow is proposed and the measurements are assessed in terms of differentiability between tumorous and healthy tissue samples.The electrical parameters are found to be promising for differentiation even under varying mechanical deformation, and the distinction is additionally improved by the proposed compensation approach.Electrical impedance measurements show great potential to support urologist during endoscopic surgeries.

  View details for DOI 10.1109/TBME.2022.3199468

  View details for Web of Science ID 000966933700001

  View details for PubMedID 35976818

• Cystoscopic depth estimation using gated adversarial domain adaptation BIOMEDICAL ENGINEERING LETTERS Somers, P., Holdenried-Krafft, S., Zahn, J., Schuele, J., Veil, C., Harland, N., Walz, S., Stenzl, A., Sawodny, O., Tarin, C., Lensch, H. A. 2023; 13 (2): 141-151

  Abstract

  Monocular depth estimation from camera images is very important for surrounding scene evaluation in many technical fields from automotive to medicine. However, traditional triangulation methods using stereo cameras or multiple views with the assumption of a rigid environment are not applicable for endoscopic domains. Particularly in cystoscopies it is not possible to produce ground truth depth information to directly train machine learning algorithms for using a monocular image directly for depth prediction. This work considers first creating a synthetic cystoscopic environment for initial encoding of depth information from synthetically rendered images. Next, the task of predicting pixel-wise depth values for real images is constrained to a domain adaption between the synthetic and real image domains. This adaptation is done through added gated residual blocks in order to simplify the network task and maintain training stability during adversarial training. Training is done on an internally collected cystoscopy dataset from human patients. The results after training demonstrate the ability to predict reasonable depth estimations from actual cystoscopic videos and added stability from using gated residual blocks is shown to prevent mode collapse during adversarial training.

  View details for DOI 10.1007/s13534-023-00261-3

  View details for Web of Science ID 000918310500001

  View details for PubMedID 37124116

  View details for PubMedCentralID PMC10130294

• Compensating the Influence of Tremors on Impedance Measurements Through Fourier Analysis Veil, C., Glaesle, M., Somers, P., Schuele, J., Tarin, C., Sawodny, O., IEEE IEEE. 2023: 1-4

  Abstract

  Electrical mpedance measurements are a promising method for detecting structural changes in tissue and can be used in oncology to differentiate between healthy and tumorous tissue areas. The impedance measurements are so sensitive that they are not only affected by changes in the tissue itself, but also by a fluctuating contact force between sensor and tissue. In this work, the correlation between impedance measurements and movements during the measuring process, such as physiological tremors, are analyzed. To do this, impedance measurements are taken on pig bladders and the sensor-tissue contact force is simultaneously recorded. The tremor frequencies are directly visible in the Fourier transform of the impedance measurement. To counteract these effects, a Butterworth filter is used to filter out tremor frequencies and remove unwanted artefacts. Additionally, placing an spring on top of the impedance sensor helped to achieve a steadier contact force between sensor and tissue to also remove low frequency disturbances in the impedance measurements.Clinical relevance- This approach can help to obtain more reliable impedance measurements on tissue both for ex vivo and in vivo applications.

  View details for DOI 10.1109/EMBC40787.2023.10340912

  View details for Web of Science ID 001133788304026

  View details for PubMedID 38082760

• An Enhanced Synthetic Cystoscopic Environment for Use in Monocular Depth Estimation Somers, P., Deutschmann, M., Holdenried-Krafft, S., Tovey, S., Schuele, J., Veil, C., Aslani, V., Sawodny, O., Lensch, H. A., Tarin, C., IEEE IEEE. 2023: 1-4

  Abstract

  As technology advances and sensing devices improve, it is becoming more and more pertinent to ensure accurate positioning of these devices, especially within the human body. This task remains particularly difficult during manual, minimally invasive surgeries such as cystoscopies where only a monocular, endoscopic camera image is available and driven by hand. Tracking relies on optical localization methods, however, existing classical options do not function well in such a dynamic, non-rigid environment. This work builds on recent works using neural networks to learn a supervised depth estimation from synthetically generated images and, in a second training step, use adversarial training to then apply the network on real images. The improvements made to a synthetic cystoscopic environment are done in such a way to reduce the domain gap between the synthetic images and the real ones. Training with the proposed enhanced environment shows distinct improvements over previously published work when applied to real test images.

  View details for DOI 10.1109/EMBC40787.2023.10340303

  View details for Web of Science ID 001133788301123

  View details for PubMedID 38083134

• In-plane Strain Analysis by Correlating Geometry and Visual Data Through a Gradient-Based Surface Reconstruction Schuele, J., Aslani, V., Staerk, C., Somers, P., Veil, C., Tarin, C., Herkommer, A., Sawodny, O., IEEE IEEE. 2023: 1-6

  Abstract

  Abnormalities in tissue can be detected and analyzed by evaluating mechanical properties, such as strain and stiffness. While current sensor systems are effective in measuring longitudinal properties perpendicular to the measurement sensor, identifying in-plane deformation remains a significant challenge. To address this issue, this paper presents a novel method for reconstructing in-plane deformation of observed tissue surfaces using a fringe projection sensor specifically designed for measuring tissue deformations. The method employs the latest techniques from computer vision, such as differentiable rendering, to formulate the in-plane reconstruction as a differentiable optimization problem. This enables the use of gradient-based solvers for an efficient and effective optimization of the problem optimum. Depth information and image information are combined using landmark correspondences between the respective image observations of the undeformed and deformed scenes. By comparing the reconstructed pre- and post-deformation geometry, the in-plane deformation can be revealed through the analysis of relative variations between the corresponding models' geometries. The proposed reconstruction pipeline is validated on an experimental setup, and the potential for intraoperative applications is discussed.

  View details for DOI 10.1109/EMBC40787.2023.10340777

  View details for Web of Science ID 001133788303125

  View details for PubMedID 38083300

• Mathematical modeling and simulation of thyroid homeostasis: Implications for the Allan-Herndon-Dudley syndrome FRONTIERS IN ENDOCRINOLOGY Wolff, T. M., Veil, C., Dietrich, J. W., Mueller, M. A. 2022; 13: 882788

  Abstract

  A mathematical model of the pituitary-thyroid feedback loop is extended to deepen the understanding of the Allan-Herndon-Dudley syndrome (AHDS). The AHDS is characterized by unusual thyroid hormone concentrations and a mutation in the SLC16A2 gene encoding for the monocarboxylate transporter 8 (MCT8). This mutation leads to a loss of thyroid hormone transport activity. One hypothesis to explain the unusual hormone concentrations of AHDS patients is that due to the loss of thyroid hormone transport activity, thyroxine (T 4) is partially retained in thyroid cells.This hypothesis is investigated by extending a mathematical model of the pituitary-thyroid feedback loop to include a model of the net effects of membrane transporters such that the thyroid hormone transport activity can be considered. A nonlinear modeling approach based on the Michaelis-Menten kinetics and its linear approximation are employed to consider the membrane transporters. The unknown parameters are estimated through a constrained parameter optimization.In dynamic simulations, damaged membrane transporters result in a retention of T 4 in thyroid cells and ultimately in the unusual hormone concentrations of AHDS patients. The Michaelis-Menten modeling approach and its linear approximation lead to similar results.The results support the hypothesis that a partial retention of T 4 in thyroid cells represents one mechanism responsible for the unusual hormone concentrations of AHDS patients. Moreover, our results suggest that the retention of T 4 in thyroid cells could be the main reason for the unusual hormone concentrations of AHDS patients.

  View details for DOI 10.3389/fendo.2022.882788

  View details for Web of Science ID 000899537900001

  View details for PubMedID 36568087

  View details for PubMedCentralID PMC9772020

• Growth of Simulated Tumors Under the Influence of Oxygen Supply Somers, P., Seibold, J., Lipke, N., Harland, N., Amend, B., Stenzl, A., Schuele, J., Veil, C., Sawodny, O., Tarin, C. ELSEVIER. 2022: 653-658

  View details for DOI 10.1016/j.ifacol.2022.09.170

  View details for Web of Science ID 000860842100110

• Electro-Mechanical Coupling in Impedance-Based Tissue Differentiation Under Compression Veil, C., Schoene, S., Harland, N., Schuele, J., Somers, P., Stenzl, A., Tarin, C., Sawodny, O. ELSEVIER. 2022: 564-569

  View details for DOI 10.1016/j.ifacol.2022.09.155

  View details for Web of Science ID 000860842100095

• Geometric Mapping Evaluation for Real-Time Local Sensor Simulation. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Somers, P., Schule, J., Veil, C., Sawodny, O., Tarin, C. 2022; 2022: 609-612

  Abstract

  Medical augmented reality and simulated test environments struggle in accurately simulating local sensor measurements across large spatial domains while maintaining the proper resolution of information required and real time capability. Here, a simple method for real-time simulation of intraoperative sensors is presented to aid with medical sensor development and professional training. During a surgical intervention, the interaction between medical sensor systems and tissue leads to mechanical deformation of the tissue. Through the inclusion of detailed finite element simulations in a real-time augmented reality system the method presented will allow for more accurate simulation of intraoperative sensor measurements that are independent of the mechanical state of the tissue. This concept uses a coarse, macro-level deformation mesh to maintain both computational speed and the illusion of reality and a simple geometric point mapping method to include detailed fine mesh information. The resulting system allows for flexible simulation of different types of localized sensor measurement techniques. Preliminary simulation results are provided using a real-time capable simulation environment and prove the feasibility of the method.

  View details for DOI 10.1109/EMBC48229.2022.9871932

  View details for PubMedID 36086634

• Detection Limits of Tetrapolar Impedance Sensors for Tissue Differentiation. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Veil, C., Makni, O., Somers, P., Schule, J., Tarin, C., Sawodny, O. 2022; 2022: 1-4

  Abstract

  Cancer recurrence is an important issue in bladder tumor resections, because tissue cannot generously be removed from the thin bladder wall without impacting its functionality. Electrical impedance measurements during an operation aim to support the surgeon in making the decision which tissue areas to preserve, because physiological changes in tissue due to cancerous mutations can be detected by their altered electrical characteristics. This work investigates the detection limits of tetrapolar sensors when the impedance of heterogeneous tissue is measured. To do this, a finite element analysis is carried out where the sensors are placed on a dielectric medium with inclusions of different sizes, conductivity, and locations relative to the sensor. It is shown that a sensor with four electrodes in a square performs poorly in comparison to a sensor where the electrodes are symmetrically shaped as rings around one center electrode. This is mainly due to its enlarged regions of negative sensitivity. Based on the results, a third, optimized sensor geometry is proposed that shows superior performance to the other sensors in terms of geometry factor, sensitivities, and tumor detection. In simulation, it can reliably detect tumors with only half the radius of the sensor surface. Smaller tumor fractions cannot be detected by either sensor.

  View details for DOI 10.1109/EMBC48229.2022.9871065

  View details for PubMedID 36085873

• A Model-based Simultaneous Localization and Mapping Approach for Deformable Bodies Schuele, J., Haag, J., Somers, P., Veil, C., Tarin, C., Sawodny, O., IEEE IEEE. 2022: 607-612

  View details for DOI 10.1109/AIM52237.2022.9863308

  View details for Web of Science ID 000860750800058

• Model-Based Feedforward Control of an Intra- and Interspecific Competitive Population System IEEE CONTROL SYSTEMS LETTERS Kurth, A., Veil, C., Sawodny, O. 2022; 6: 3397-3402

  View details for DOI 10.1109/LCSYS.2022.3183894

  View details for Web of Science ID 000819822000023

• Minimally Invasive Sensors for Transurethral Impedance Spectroscopy IEEE SENSORS JOURNAL Veil, C., Petillon, S., Hotz, J., Knoeller, A., Zimmermann, A., Sawodny, O. 2021; 21 (20): 22858-22867

  View details for DOI 10.1109/JSEN.2021.3108779

  View details for Web of Science ID 000709128900078

• Nonlinear disturbance observers for robotic continuum manipulators MECHATRONICS Veil, C., Mueller, D., Sawodny, O. 2021; 78

  View details for DOI 10.1016/j.mechatronics.2021.102518

  View details for Web of Science ID 000689316300002

• Geometry Factor Determination for Tetrapolar Impedance Sensor Probes Veil, C., Bach, R., Somers, P., Sawodny, O., Tarin, C., IEEE IEEE. 2021: 6800-6805

  View details for DOI 10.1109/EMBC46164.2021.9629757

  View details for Web of Science ID 000760910506097

• Multi-Physical Tissue Modeling of a Human Urinary Bladder Schuele, J., Krauss, F., Veil, C., Kunkel, S., Somers, P., Tarin, C., Sawodny, O., IEEE IEEE. 2021: 4297-4302

  Abstract

  A multi-physical model of a human urinary bladder is an essential element for the potential application of electrical impedance spectroscopy during transurethral resection surgery, where measurements are taken at different fill levels inside the bladder. This work derives a multi-physical bladder tissue model that incorporates the electrical impedance properties with dependence on mechanical deformation due to filling of the bladder. The volume and ratio of the intracellular to extracellular tissue fluid heavily influence the electrical impedance characteristics and thus provide the connection between the mechanical and electrical domains. Modeling the fluid within the tissue links both the physical and histological processes and enables useful inferences of the properties from empiric observations. This is demonstrated by taking impedance measurements at different fill volumes. The resulting model provides a tool to analyze impedance measurements during surgery at different stress levels. In addition, this model can be used to determine patient-specific tissue parameters.

  View details for DOI 10.1109/EMBC46164.2021.9629482

  View details for Web of Science ID 000760910504050

  View details for PubMedID 34892172

• One-Shot kinesthetic programming by demonstration for soft collaborative robots MECHATRONICS Mueller, D., Veil, C., Seidel, M., Sawodny, O. 2020; 70

  View details for DOI 10.1016/j.mechatronics.2020.102418

  View details for Web of Science ID 000576787000002

• Hybrid force/position control for quasi continuum manipulators AT-AUTOMATISIERUNGSTECHNIK Mueller, D., Veil, C., Sawodny, O. 2020; 68 (10): 854-862

  View details for DOI 10.1515/auto-2020-0053

  View details for Web of Science ID 000574539800004

• Disturbance Observer Based Control for Quasi Continuum Manipulators Muller, D., Veil, C., Sawodny, O. ELSEVIER. 2020: 9808-9813

  View details for DOI 10.1016/j.ifacol.2020.12.2681

  View details for Web of Science ID 000652593100165