Search

This is an Accepted Manuscript of an article published by Taylor & Francis in Computer Methods in Biomechanics and Biomedical Engineering : Imaging & Visualization on 17.03.2020, available online: https://www.tandfonline.com/doi/full/10.1080/21681163.2020.1728579, The morphological assessment of anatomical structures is clinically relevant, but often falls short of quantitative or standardised criteria. Whilst human observers are able to assess morphological characteristics qualitatively, the development of robust shape features remains challenging. In this study, we employ psychometric and radiomic methods to develop quantitative models of the perceived irregularity of intracranial aneurysms (IAs). First, we collect morphological characteristics (e.g. irregularity, asymmetry) in imaging-derived data and aggregated the data using rank-based analysis. Second, we compute regression models relating quantitative shape features to the aggregated qualitative ratings (ordinal or binary). We apply our method for quantifying perceived shape irregularity to a dataset of 134 IAs using a pool of 179 different shape indices. Ratings given by 39 participants show good agreement with the aggregated ratings (Spearman rank correlation ρSp=0.84). The best-performing regression model based on quantitative shape features predicts the perceived irregularity with R2:0.84±0.05.

OBJECTIVE: Incidental aneurysms pose a challenge for physicians, who need to weigh the rupture risk against the risks associated with treatment and its complications. A statistical model could potentially support such treatment decisions. A recently developed aneurysm rupture probability model performed well in the US data used for model training and in data from two European cohorts for external validation. Because Japanese and Finnish patients are known to have a higher aneurysm rupture risk, the authors’ goals in the present study were to evaluate this model using data from Japanese and Finnish patients and to compare it with new models trained with Finnish and Japanese data. METHODS: Patient and image data on 2129 aneurysms in 1472 patients were used. Of these aneurysm cases, 1631 had been collected mainly from US hospitals, 249 from European (other than Finnish) hospitals, 147 from Japanese hospitals, and 102 from Finnish hospitals. Computational fluid dynamics simulations and shape analyses were conducted to quantitatively characterize each aneurysm’s shape and hemodynamics. Next, the previously developed model’s discrimination was evaluated using the Finnish and Japanese data in terms of the area under the receiver operating characteristic curve (AUC). Models with and without interaction terms between patient population and aneurysm characteristics were trained and evaluated including data from all four cohorts obtained by repeatedly randomly splitting the data into training and test data. RESULTS: The US model’s AUC was reduced to 0.70 and 0.72, respectively, in the Finnish and Japanese data compared to 0.82 and 0.86 in the European and US data. When training the model with Japanese and Finnish data, the average AUC increased only slightly for the Finnish sample (to 0.76 ± 0.16) and Finnish and Japanese cases combined (from 0.74 to 0.75 ± 0.14) and decreased for the Japanese data (to 0.66 ± 0.33). In models including interaction terms, the AUC in the Finnish

High-contrast, high-resolution imaging of biomedical specimens is indispensable for studying organ function and pathologies. Conventional histology, the gold standard for soft-tissue visualization, is limited by its anisotropic spatial resolution, elaborate sample preparation, and lack of quantitative image information. X-ray absorption or phase tomography have been identified as promising alternatives enabling non-destructive, distortion-free three-dimensional (3D) imaging. However, reaching sufficient contrast and resolution with a simple experimental procedure remains a major challenge. Here, we present a solution based on x-ray phase tomography through speckle-based imaging (SBI). We demonstrate on a mouse kidney that SBI delivers comprehensive 3D maps of hydrated, unstained soft tissue, revealing its microstructure and delivering quantitative tissue-density values at a density resolution of better than 2mg/cm3 and spatial resolution of better than 8 µm. We expect that SBI virtual histology will find widespread application in biomedicine and will open up new possibilities for research and histopathology.

BACKGROUND Morphological irregularity is linked to intracranial aneurysm wall instability and manifests in the lumen shape. Yet there is currently no consent on how to assess shape irregularity. The aims of this work are to quantify irregularity as perceived by clinicians, to break down irregularity into morphological attributes, and to relate these to clinically relevant factors such as rupture status, aneurysm location, and patient age or sex. METHODS Thirteen clinicians and 26 laypersons assessed 134 aneurysm lumen segmentations in terms of overall perceived irregularity and five different morphological attributes (presence/absence of a rough surface, blebs, lobules, asymmetry, complex geometry of the parent vasculature). We examined rater agreement and compared the ratings with clinical factors by means of regression analysis or binary classification. RESULTS Using rank-based aggregation, the irregularity ratings of clinicians and laypersons did not differ statistically. Perceived irregularity showed good agreement with curvature (coefficient of determination R$^{2}$ = 0.68 ± 0.08) and was modeled very accurately using the five morphological rating attributes plus shape elongation (R$^{2}$ = 0.95 ± 0.02). In agreement with previous studies, irregularity was associated with aneurysm rupture status (AUC = 0.81 ± 0.08); adding aneurysm location as an explanatory variable increased the AUC to 0.87 ± 0.09. Besides irregularity, perceived asymmetry, presence of blebs or lobules, aneurysm size, non-sphericity, and curvature were linked to rupture. No association was found between morphology and any of patient sex, age, and history of smoking or hypertension. Aneurysm size was linked to morphology. CONCLUSIONS Irregular lumen shape carries significant information on the aneurysm's disease status. Irregularity constitutes a continuous parameter that shows a strong association with the rupture status. To improve the objectivity of morphological assessment, we suggest exam

Ventricular assist devices (VADs), among which the HeartMate 3 (HM3) is the latest clinically approved representative, are often the therapy of choice for patients with end‐stage heart failure. Despite advances in the prevention of pump thrombosis, rates of stroke and bleeding remain high. These complications are attributed to the flow field within the VAD, among other factors. One of the HM3’s characteristic features is an artificial pulse that changes the rotor speed periodically by 4000 rpm, which is meant to reduce zones of recirculation and stasis. In this study, we investigated the effect of this speed modulation on the flow fields and stresses using high‐resolution computational fluid dynamics. To this end, we compared Eulerian and Lagrangian features of the flow fields during constant pump operation, during operation with the artificial pulse feature, and with the effect of the residual native cardiac cycle. We observed good washout in all investigated situations, which may explain the low incidence rates of pump thrombosis. The artificial pulse had no additional benefit on scalar washout performance, but it induced rapid variations in the flow velocity and its gradients. This may be relevant for the removal of deposits in the pump. Overall, we found that viscous stresses in the HM3 were lower than in other current VADs. However, the artificial pulse substantially increased turbulence, and thereby also total stresses, which may contribute to clinically observed issues related to hemocompatibility.

In vitro quantification of the effect of mechanical loads on cells by live microscopy requires precise control of load and culture environment. Corresponding systems are often bulky, their setup and maintenance are time consuming, or the cell yield is low. Here, we show the design and initial testing of a new cell culture system that fits on standard light microscope stages. Based on the parallel plate principle, the system allows for live microscopy of cells exposed to flow-induced shear stress, features short setup time and requires little user interaction. An integrated feedback-controlled heater and a bubble trap enable long observation times. The key design feature is the possibility for quick exchange of the cultured cells. We present first test results that focus on verifying the robustness, biocompatibility, and ease of use of the device.

We present a novel computational approach, based on a parametrized reduced-order model, for accelerating the calculation of pressure drop along blood vessels. Vessel lumina are defined by a geometric parametrization using the discrete empirical interpolation method on control points located on the surface of the vessel. Hemodynamics are then computed using a reduced-order representation of the parametrized three-dimensional unsteady Navier-Stokes and continuity equations. The reduced-order model is based on an offline-online splitting of the solution process, and on the projection of a finite volume full-order model on a low-dimensionality subspace generated by proper orthogonal decomposition of pressure and velocity fields. The algebraic operators of the hemodynamic equations are assembled efficiently during the online phase using the discrete empirical interpolation method. Our results show that with this approach calculations can be sped up by a factor of about 25 compared to the conventional full-order model, while maintaining prediction errors within the uncertainty limits of invasive clinical measurement of pressure drop. This is of importance for a clinically viable implementation of noninvasive, medical imaging-based computation of fractional flow reserve.

Phenylketonuria (PKU) is an inherited metabolic disease characterized by abnormally high concentrations of the essential amino acid L-phenylalanine (Phe) in blood plasma caused by reduced activity of phenylalanine hydroxylase (PAH). While numerous studies have shown association between high plasma Phe concentration and intellectual impairment, it is not clear whether increased Phe fluctuations also observed in PKU affect the brain as well. To investigate this, time-resolved data on Phe and competing large neutral amino acid (LNAA) concentrations in neurons are needed, but cannot be acquired readily with current methods. We have used modeling as an alternative approach to characterize the interactive dynamics of Phe and competing LNAAs (CL) in the neurovascular unit (NVU). Our results suggest that plasma Phe fluctuations can propagate into the NVU cells and change there the concentration of LNAAs, with the highest magnitude of this effect observed at low frequency and high amplitude-to-mean ratio of the plasma Phe concentration fluctuations. Our model further elucidates the effect of therapeutic LNAA supplementation in PKU, showing how abnormal concentrations of Phe and CL in the NVU move thereby toward normal physiologic levels.

Working towards a system to match intracranial aneurysms of similar morphology, we examine how a variety of established shape descriptors relate to expert assessments of aneurysm morphology. For this purpose, we extract 3D models of aneurysms from 3D angiographies and calculate numerical values (geometry indices and moment invariants) that describe the size and shape of the aneurysm and the surrounding arteries. We then compare these shape descriptors with human assessments of qualitative morphological characteristics like irregularity or the presence/absence of blebs. Here, we present preliminary results based on 137 aneurysm models.

Introduction: To date, it is difficult for clinicians to judge the associated risks of intracranial aneurysms reliably. Because the 3D-shape of an aneurysm is strongly linked to the underlying formation processes it is very likely that the presence or absence of certain shape features indicate the disease status of the aneurysm. Shape (extracted from medical imaging data) already plays a significant role in the qualitative assessment of the aneurysm by the clinician and has been associated with risk prediction. Still, no consensus exists about which shape features reliably predict instability or whether there exist any that qualify as biomarkers at all. In an effort to find support for the assumption that aneurysm shape carries information about the aneurysm status, we developed a flexible classification pipeline that extracts shape features and tests their applicability. Methods: 3D models of aneurysms are extracted from medical imaging data (mostly 3DRA) by a standardized vessel segmentation method. The aneurysm is cut from its parent vessels according to a simple and reproducible cut protocol. Different representations of the 3D shape that have been suggested by literature are calculated for the extracted aneurysm. So far we have looked at Zernike moments (ZM), their invariants (ZMI) and simple geometry indices such as undulation or non-sphericity. Different feature reduction techniques (for ZMI) and machine-learning methods are applied to find linking patterns between shape features and aneurysm stability. This processing pipeline is applied to a relatively large clinical dataset (ca. 400 cases), whereas the collection of new cases is an on-going effort. We will present the findings on the latest state of the database. Results: Initial results indicate that the ZMI alone are insufficient to classify aneurysms reliably in terms of rupture or stability status. Because of their global support, ZMI bare a strong dependency on the placement of the cuts. In a prelimin

Intracranial aneurysms are pathological deformations of brain arteries. Although remaining asymptomatic most of the time, aneurysms expose the patient to an increased risk of subarachnoid hemorrhage, which can cause severe brain damage and death. To this date, it is difficult for clinicians to judge the aneurysm risk status reliably, even though availability and quality of imaging modalities have much improved recently. The goal of this project is to investigate whether a quantitative description of 3D-shape can be used to judge the disease status of intracranial aneurysms, and, ultimately, to equip clinicians with a tool to assess the risks of treatment. In recent scientific literature, various candidates of 3D-shape descriptors are discussed, out of which Zernike Moment Invariants (ZMIs) belong to the most popular ones. In an attempt to understand their mode of operation, we applied them to classify the rupture-risk status of intracranial aneurysms. Based on the analysis of synthetic and real data we accumulated evidence and are presenting first results on the utility of ZMI and alternative representations.

It is exceedingly challenging to assess the clinical significance of intracranial aneurysms. Currently, clinicians associate aneurysm shape irregularity with wall instability. However, there is no consensus on which shape features reliably predict aneurysm rupture risk. Here we present a machine learning approach to tackle this problem: We implemented a classification pipeline to identify shape features with predictive power of aneurysm instability. 3D models of aneurysms are extracted from medical imaging data (mostly 3D rotational angiography) using a standardized vessel segmentation protocol. A variety of established representations of the 3D shape are calculated for the extracted aneurysm segment. These include the calculation of Zernike moment invariants (ZMI) and simpler geometry indices such as undulation, ellipticity and non-sphericity. Feature reduction techniques (for ZMI) and classification methods are applied to find patterns linking shape features to aneurysm stability in an exploratory way. This processing pipeline was applied to a clinical dataset of approximately 250 aneurysms registered in the AneurysmDataBase (SwissNeuroFoundation and AneuriskWeb database. Classification based on ZMI alone allowed us to distinguish between sidewall and bifurcation aneurysms, but failed to forecast an aneurysm’s rupture status reliably. Remarkably, simpler geometry indices performed similarly well in rupture status prediction. It remains to be investigated whether further stratification of the aneurysms in terms of location, size and clinical factors will increase the robustness of the applied classification methods. This study was performed within the scope of the AneuX project, funded by SystemsX.ch, and received support by SNSF NCCR Kidney.CH.

The rupture of intracranial aneurysms is a potentially deadly event. Aneurysm detection is based on imaging techniques, amongst which 3D angiograms deliver the highest quality. Currently, neuroradiologists assess such images only in a qualitative manner, even though it remains unclear how morphological properties relate to the disease status quantitatively. In an effort to identify suitable descriptors that capture the irregularity of aneurysms, we relate a range of shape descriptors to expert assessments of aneurysm morphology. In a first step, we extracted 3D models of aneurysms from 3D angiographies and calculated geometry indices and moment invariants describing size and shape of aneurysms and surrounding arteries. In a second step, we compared these descriptors to human assessments of irregularity of the aneurysm dome. Preliminary results are presented based on 134 aneurysm models and 15 raters (5 clinicians, 10 informed laymen). Univariate correlation revealed that curvature-based metrics predict most accurately the human assessment of irregularity (rank correlation: ?=0.86). This study was performed within the scope of the AneuX project, funded by SystemsX.ch, and received support by SNSF NCCR Kidney.CH.

OBJECTIVE: We aimed to test whether there is an association of slow vasogenic wave (SVW) occurrence with positive response to external lumbar drainage (ELD) and ventriculoperitoneal shunting and to design a method for the recognition and quantification of SVWs in the intracranial pressure (ICP) signal. MATERIALS AND METHODS: We constructed SVW templates using normalized sine waves. We calculated the cross-correlation between the respective SVW template and the ICP signal. This was followed by shifting the templates forward and performing the cross-correlation analysis again until the end of the recording. Cross-correlation values above a threshold were considered to be indicative of SVWs. This threshold was previously determined and validated on a sample of ICP records of six patients. We calculated the root mean square of the recognized SVW periods as a measure of signal strength. Time-averaged signal strength was calculated over the full recording time (ICP) and over the wave periods (ICP). RESULTS: We determined ICPand ICPin recordings of 2 groups of patients presenting with Hakim's triad: 26 normal pressure hydrocephalus (NPH) patients and 20 non-NPH patients. We then tested whether there was an association between ICPor ICPand the respective diagnosis using a Mann-Whitney test. We found significant association between ICP(p = 0.014) and ICP(p = 0.022) and the diagnoses. CONCLUSIONS: The described method based on pattern recognition in the time domain is suitable for the detection and quantification of SVWs in ICP signals. We found a significant association between the occurrence of SVWs and independent NPH diagnosis.

The homeostatic regulation of large neutral amino acid (LNAA) concentration in the brain interstitial fluid (ISF) is essential for proper brain function. LNAA passage into the brain is primarily mediated by the complex and dynamic interactions between various solute carrier (SLC) transporters expressed in the neurovascular unit (NVU), among which SLC7A5/LAT1 is considered to be the major contributor in microvascular brain endothelial cells (MBEC). The LAT1-mediated trans-endothelial transport of LNAAs, however, could not be characterized precisely by available and standard methods so far. To circumvent these limitations, we have incorporated published data of rat brain into a robust computational model of NVU-LNAA homeostasis, allowing us to evaluate hypotheses concerning LAT1-mediated trans-endothelial transport of LNAAs across the blood brain barrier (BBB). We show that accounting for functional polarity of MBECs with either asymmetric LAT1 distribution between membranes and/or intrinsic LAT1 asymmetry with low intraendothelial binding affinity is required to reproduce the experimentally measured brain ISF response to intraperitoneal (IP) L-tyrosine and L-phenylalanine injection. On the basis of these findings, we have also investigated the effect of IP administrated L-tyrosine and L-phenylalanine on the dynamics of LNAAs in MBECs, astrocytes and neurons. Finally, the computational model was shown to explain the trans-stimulation of LNAA uptake across the BBB observed upon ISF perfusion with a competitive LAT1 inhibitor.

Detailed knowledge of aortic root geometry is a prerequisite to anticipate complications of transcatheter aortic valve (TAV) implantation. We determined coronary ostial locations and aortic root dimensions in patients with aortic stenosis (AS) and compared these values with normal subjects using computed tomography (CT). One hundred consecutive patients with severe tricuspid AS and 100 consecutive patients without valvular pathology (referred to as the controls) undergoing cardiac dual-source CT were included. Distances from the aortic annulus (AA) to the left coronary ostium (LCO), right coronary ostium (RCO), the height of the left coronary sinus (HLS), right coronary sinus (HRS), and aortic root dimensions [diameters of AA, sinus of Valsalva (SV), and sino-tubular junction(STJ)] were measured. LCO and RCO were 14.9 ± 3.2mm (8.2-25.9) and 16.8 ± 3.6mm (12.0-25.7) in the controls, 15.5 ± 2.9mm (8.8-24.3) and 17.3 ± 3.6mm (7.3-26.0) in patients with AS. Controls and patients with AS had similar values for LCO (P = 0.18), RCO (P = 0.33) and HLS (P = 0.88), whereas HRS (P < 0.05) was significantly larger in patients with AS. AA (r = 0.55,P < 0.001), SV (r = 0.54,P < 0.001), and STJ (r = 0.52,P < 0.001) significantly correlated with the body surface area in the controls; whereas no correlation was found in patients with AS. Patients with AS had significantly larger AA (P < 0.01) and STJ (P < 0.01) diameters when compared with the controls. In patients with severe tricuspid AS, coronary ostial locations were similar to the controls, but a transverse remodelling of the aortic root was recognized. Owing to the large distribution of ostial locations and the dilatation of the aortic root, CT is recommended before TAV implantation in each patient

Purpose: Knowledge of the normal in vivo distribution and variation of coronary ostial locations is essential in the planning of various interventional and surgical procedures. However, all studies to date have reported the distribution of coronary ostia locations only in cadaver hearts. In this study, we sought to assess the distribution of coronary ostial locations in patients using cardiac dual-source computed tomography (CT) and compare these values to those of human cadaveric specimens. Methods: Measurements of the coronary ostia location were performed in 150 patients undergoing dual-source CT and in 75 cadavers using open measurement techniques. All 150 patients had a normal aortic valve function and no previous cardiac intervention or surgery. The location of the right and left coronary origin in relation to the aortic annulus and the height of the sinus of Valsalva were measured. Results: Mean ostial locations at CT were 17.0 (±3.6)mm and 15.3 (±3.1)mm for the right and left coronary ostia, with large variations of both sides (right: 10.4-28.5mm; left: 9.8-29.3mm). In cadavers, mean locations were 14.9 (±4.3)mm [5-24mm] for right and 16.0 (±3.6)mm [9-24mm] for left coronary ostia. Comparison of CT and cadaver data showed statistically significant differences for right (P<0.0001) but not left (P=0.1675) coronary ostia. Conclusions: This study provides data of normal coronary ostial origins and demonstrates significant differences between in vivo and ex vivo measurements regarding the right coronary ostium. The observed large variations of coronary ostia origins emphasize the importance of considering such anatomic variations in the development of treatments