Thomas Schmitz-Rode

Background: A major reason for the failure of bioprosthetic heart valves is calcification. Various pretreatment methods are developed to reduce the calcification behavior. The effectiveness of these methods has so far been investigated in expensive and time‐consuming large animal studies. To provide a cost‐effective, animal‐ and possibly also time‐saving method, we developed an accelerated dynamic in vitro calcification test method. Methods: We validated this method using a comparative study of two differently pretreated groups of porcine heart valve bioprostheses. Each group contained N = 4 identical aortic bioprostheses. Calcification onsets, progression, and extent were detected by high‐speed video (HSV) documentation and microscopy. Structural identification of the deposits was carried out by X‐ray powder diffraction (XRD). Semi‐destructive quantification of the calcifications was done by μ‐CT as well as destructive chemical quantification via colorimetry and complexometry. The histomorphologic localization of the calcifications was examined by von Kossa staining. Results: Structural analysis of the deposits indicated “biological apatite” for both test groups. Histological examination revealed localization of the calcifications in the spongiosa zone of the cusps. Quantification of the calcifications showed a distinctly stronger calcification tendency of the No‐T6 compared to the anti‐calcifying pretreated T6 bioprostheses. Conclusions: We developed and validated a novel and unique test method for in vitro calcification assessment. The quantitative calcification tendencies of the two test groups are comparable with the results of an in vivo study in sheep. The structural findings are in line with published in vivo observations. The histomorphological localization appears as known for porcine prostheses.

Background: Heart valve diseases remain a leading cause of death in industrialized nations. Polycarbonate urethane (PCU) is a promising material for heart valve prostheses due to its biocompatibility and low calcification tendency. However, the impact of processing methods on calcification remains unclear. Methods: PCU patches were fabricated via hot pressing or solution casting. Both groups ( n = 3 each), along with bovine pericardium patches as positive controls ( n = 3), were incubated for 10 weeks in a custom in vitro calcification fluid. Calcification, cytocompatibility, and material properties were assessed using light and electron microscopy, infrared spectroscopy, and gel permeation chromatography (GPC). Results: Calcification was observed in hot‐pressed PCU and control patches but not in solution‐cast PCU. Both PCU types showed comparable cytocompatibility. Spectroscopy and GPC revealed chemical and structural changes in hot‐pressed PCU, likely promoting calcification. Conclusion: Hot pressing alters the chemical structure of PCU and increases its calcification propensity without affecting cytocompatibility. These findings highlight the importance of process control and in vitro screening during heart valve material development.

Objective. Magnetic particle imaging (MPI) opens huge possibilities in image-guided therapy. Its effectiveness is strongly influenced by the quality of the magnetic nanoparticles (MNP) used as tracers. Besides MNP optimisation following different synthesis routes, MNP assembly into linear structures can significantly enhance their performance in MPI. The present study investigates the influence of linear MNP structures on MPI signal for different MNP types. With regard to theranostic applications the role of linear structures in hybrid stent imaging is explored. Approach. Three MNP types were used to create linear MNP structures. MNP respectively the MNP structures were immobilised in a hydrogel and positioned at various orientations relative to the coordinate system of the MPI. A multi-channel reconstruction approach was applied to assess the orientation-specific signal. The insights gained were used to reconstruct a fibre-based polymer stent with incorporated linear structures. Main results. Different linear structure orientations could be delineated and visualised in multi-colour images. Linear structures orientated parallel to the direction of a magnetic excitation field lead to the highest signal intensities and peak positions of MPI frequency spectra were located near multiples of the frequency of the excitation coil. Image reconstructions of the stent were very sensitive to the orientation of linear structures within the fibres. Significance. This study reveals that the assembly of MNP results in non-linear contributions to the MPI signal. Consequently, the MPI signal intensity is not as usual merely linearly correlated with MNP concentration increasing the complexity in image reconstruction. The findings demonstrate the necessity of accounting for MNP structure orientation in image reconstruction. They also reveal the high potential of MPI to detect different MNP types and structures. Linear structures cause either significant signal reduction or signal increase depending on the angular position of the linear structures relative to the direction of MPI magnetic fields.

Background: This study investigated fluorescent hemolysis detection as an optical method to detect local hemolysis in mechanical circulatory support systems, addressing the limitations of standard hemolysis tests and current simulation methods. Standard tests, per ASTM1841‐19, quantify general hemolysis but do not localize it. Methods: We employ a two‐phase blood analog fluid composed of calcium‐loaded ghost cells and phosphate‐buffered saline. Ghost cells are hemoglobin‐depleted red blood cells, allowing for optical measurements. A calcium‐sensitive fluorescent indicator (Cal590 potassium salt, AAT Bioquest, Pleasanton, USA), activated by calcium released upon ghost cell hemolysis, enables fluorescent hemolysis detection. Hemolysis tests were conducted using porcine whole blood and the blood analog fluid, confirming that both undergo mechanical hemolysis in the Food and Drug Administration pump model. Results: The results revealed increased fluorescence intensity in response to hemolysis, with a quantitative fluorescence increase of 8.85/min at 3500 rpm and 2.5 L/min, indicating hemolysis, particularly at the rotor tip. Through image processing of fluorescence images, local hemolysis was visualized. Conclusion: This study is the first to use fluorescent hemolysis detection for local detection of mechanical hemolysis. Further refinement may enhance the design of mechanical circulatory support systems and bridge simulation limitations with experimental, localized hemolysis detection.

Background: In vitro thrombosis tests for mechanical circulatory support systems lack standardized ISO guidelines. A major limitation of current approaches is the absence of continuous thrombus monitoring, as terminated experiments at a single time point fail to capture the dynamic nature of thrombus formation. However, spatially resolved thrombus formation and its underlying dynamics are crucial for the optimization of mechanical circulatory support systems. Methods: In this study, we present a high‐resolution thrombus monitoring approach using particle image velocimetry with a thrombogenic, two‐phase blood analog fluid, designated as “ghost blood”. Ghost blood consists of plasma and ghost cells, which are hemoglobin‐depleted erythrocytes. We validate and quantify the particle image velocimetry with ghost blood and use this combination to monitor thrombus growth. Results: The validation demonstrated velocity fields in the FDA‐pump are consistent with existing literature, confirming the usability of ghost blood in particle image velocimetry. The use range of ghost blood is quantified as a formula to determine the maximum possible optical penetration depth. Finally, thrombus growth was successfully monitored in the FDA‐pump. Conclusion: In this proof of principle study, we grew a thrombus in the FDA‐pump and were able to monitor its growth from a first thrombus thread to a complete obstruction of the flow. This approach enables both the localization and the temporal growth of the thrombus to be visualized and thereby provides a foundation for future advancements in thrombosis assessment and the optimization of mechanical circulatory support systems.

This study explores the size of magnetic nanoparticles (MNP) for applications in Magnetic Resonance Imaging (MRI) and Magnetic Particle Imaging (MPI). Emphasizing the critical role of MNP size on their response to alternating magnetic fields, the study unveils a regression model to optimize MNP synthesis towards tailored sizes of MNP. With a limited and broadly distributed data set at hand, the feasibility of building an accurate predictive model based on Support Vector Machines is shown. Integrating such a model into a continuous synthesis setup establishes a feedback loop, enabling real-time control and adaptation of synthesis parameters.

Background: Hemolysis in mechanical circulatory support systems is currently determined quantitatively. To also locally resolve hemolysis, we are developing a fluorescent hemolysis detection method. This requires a translucent two‐phase blood analog fluid combined with particle image velocimetry, an optical flow field measurement. The blood analog fluid is composed of red blood cell surrogates. However, producing surrogates in sufficient volume is a challenge. We therefore present a high‐volume and high‐concentration production for our surrogates: ghost cells, hemoglobin‐depleted erythrocytes. Methods: In the ghost cell production, the hemoglobin is removed by a repeated controlled osmolar lysis. We have varied the solution mixture, centrifugation time, and centrifugation force in order to increase production efficiency. The production is characterized by measurements of output volume, hematocrit, transparency, and rheology of the blood analog fluid. Results: The volume of produced ghost cells was significantly increased, and reproducibility was improved. An average production of 389 mL of ghost cells were achieved per day. Those ghost cells diluted in plasma have a rheology similar to blood while being permeable to light. Conclusion: The volume of ghost cells produced is sufficient for optical measurements as particle image velocimetry in mechanical circulatory support systems. This makes further work on experimental measurements for a locally resolved hemolysis detection possible.

Donor cell-specific tissue-engineered (TE) implants are a promising therapy for personalized treatment of cardiovascular diseases, but current development protocols lack a stable longitudinal assessment of tissue development at subcellular resolution. As a first step toward such an assessment approach, in this study we establish a generalized labeling and imaging protocol to obtain quantified maturation parameters of TE constructs in three dimensions (3D) without the need of histological slicing, thus leaving the tissue intact. Focusing on intracellular matrix (ICM) and extracellular matrix (ECM) networks, multiphoton laser scanning microscopy (MPLSM) was used to investigate TE patches of different conditioning durations of up to 21 days. We show here that with a straightforward labeling procedure of whole-mount samples (so without slicing into thin histological sections), followed by an easy-to-use multiphoton imaging process, we obtained high-quality images of the tissue in 3D at various time points during development. The stacks of images could then be further analyzed to visualize and quantify the volume of cell coverage as well as the volume fraction and network of structural proteins. We showed that collagen and alpha-smooth muscle actin (α-SMA) volume fractions increased as normalized to full tissue volume and proportional to the cell count, with a converging trend to the final density of (4.0% ± 0.6%) and (7.6% ± 0.7%), respectively. The image analysis of ICM and ECM revealed a developing and widely branched interconnected matrix. We are currently working on the second step, that is, to integrate MPLSM endoscopy into a dynamic bioreactor system to monitor the maturation of intact TE constructs over time, thus without the need to take them out.

For reliable in silico or in vitro investigations in, for example, biosensing and drug delivery applications, accurate models of tumor vascular networks down to the capillary size are essential. Compared to images acquired with conventional medical imaging techniques, digitalized histological tumor slices have a higher resolution, enabling the delineation of capillaries. Volume rendering procedures can then be used to generate a 3D model. However, the preparation of such slices leads to misalignments in relative slice orientation between consecutive slices. Thus, image registration algorithms are necessary to re-align the slices. Here, we present an algorithm for the registration and reconstruction of a vascular network from histologic slices applied to 169 tumor slices. The registration includes two steps. First, consecutive images are incrementally pre-aligned using feature- and area-based transformations. Second, using the previous transformations, parallel registration for all images is enabled. Combining intensity- and color-based thresholds along with heuristic analysis, vascular structures are segmented. A 3D interpolation technique is used for volume rendering. This results in a 3D vascular network with approximately 400–450 vessels with diameters down to 25–30 µm. A delineation of vessel structures with close distance was limited in areas of high structural density. Improvement can be achieved by using images with higher resolution and or machine learning techniques.

Semantic segmentation is an important imaging analysis method enabling the identification of tissue structures. Histological image segmentation is particularly challenging, having large structural information while providing only limited training data. Additionally, labeling these structures to generate training data is time consuming. Here, we demonstrate the feasibility of a semantic segmentation using U-Net with a novel sparse labeling technique. The basic U-Net architecture was extended by attention gates, residual and recurrent links, and dropout regularization. To overcome the high class imbalance, which is intrinsic to histological data, under- and oversampling and data augmentation were used. In an ablation study, various architectures were evaluated, and the best performing model was identified. This model contains attention gates, residual links, and a dropout regularization of 0.125. The segmented images show accurate delineations of the vascular structures (with a precision of 0.9088 and an AUC-ROC score of 0.9717), and the segmentation algorithm is robust to images containing staining variations and damaged tissue. These results demonstrate the feasibility of sparse labeling in combination with the modified U-Net architecture.