Experimental and Computational Flow Evaluation of Coronary Stents

Local flow alterations created by a metallic stent in a simulated coronary artery were studied to compare the hemodynamic effects of two different stent geometries. Dye injection flow visualization and computational fluid dynamics were used. Resting and exercise conditions were studied. Flow visualization using the dye injection method provided a qualitative picture of stent hemodynamics while the computational approach provided detailed quantitative information on the flow next to the vessel wall near the intersections of stent wires. Dye injection visualization revealed that more dye became entrapped between the wires where the wire spacing was smallest. The dye washout times were shorter under exercise conditions for both wire spacings tested. The computational results showed that stagnation zones were continuous from one wire to the next when the wire spacing was small. Results from greater wire spacing (more than six wire diameters) showed that the stagnation zones were separate for at least part of the cardiac cycle. The sizes of the stagnation zones were larger under exercise conditions, and the largest stagnation zones were observed distal to the stent. These studies demonstrate that stent geometry has a significant effect on local hemodynamics. The observation that fluid stagnation is continuous in stents with wire spacings of less than six wire diameters may provide a criterion for future stent design. © 2000 Biomedical Engineering Society. PAC00: 8719Uv, 8719Hh, 8780-y     

BOOK REVIEW: Computational Biomechanics, edited by K. Hayashi and H. Ishikawa

PAC99: 8719-j, 8710+e, 0705Tp, 0130Ee     

Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond

Recent progress in machine learning (ML), together with advanced computational power, have provided new research opportunities in cardiovascular modeling. While classifying patient outcomes and medical image segmentation with ML have already shown significant promising results, ML for the prediction of biomechanics such as blood flow or tissue dynamics is in its infancy. This perspective article discusses some of the challenges in using ML for replacing well-established physics-based models in cardiovascular biomechanics. Specifically, we discuss the large landscape of input features in 3D patient-specific modeling as well as the high-dimensional output space of field variables that vary in space and time. We argue that the end purpose of such ML models needs to be clearly defined and the tradeoff between the loss in accuracy and the gained speedup carefully interpreted in the context of translational modeling. We also discuss several exciting venues where ML could be strategically used to augment traditional physics-based modeling in cardiovascular biomechanics. In these applications, ML is not replacing physics-based modeling, but providing opportunities to solve ill-defined problems, improve measurement data quality, enable a solution to computationally expensive problems, and interpret complex spatiotemporal data by extracting hidden patterns. In summary, we suggest a strategic integration of ML in cardiovascular biomechanics modeling where the ML model is not the end goal but rather a tool to facilitate enhanced modeling.

     

Biomechanics of Atherosclerotic Coronary Plaque: Site,Stability and In Vivo Elasticity Modeling

Coronary atheroma develop in local sites that are widely variable among patients and are considerably variable in their vulnerability for rupture. This article summarizes studies conducted by our collaborative laboratories on predictive biomechanical modeling of coronary plaques. It aims to give insights into the role of biomechanics in the development and localization of atherosclerosis, the morphologic features that determine vulnerable plaque stability, and emerging in vivo imaging techniques that may detect and characterize vulnerable plaque. Composite biomechanical and hemodynamic factors that influence the actual site of development of plaques have been studied. Plaque vulnerability, in vivo, is more challenging to assess. Important steps have been made in defining the biomechanical factors that are predictive of plaque rupture and the likelihood of this occurring if characteristic features are known. A critical key in defining plaque vulnerability is the accurate quantification of both the morphology and the mechanical properties of the diseased arteries. Recently, an early IVUS based palpography technique developed to assess local strain, elasticity and mechanical instabilities has been successfully revisited and improved to account for complex plaque geometries. This is based on an initial best estimation of the plaque components’ contours, allowing subsequent iteration for elastic modulus assessment as a basis for plaque stability determination. The improved method has also been preliminarily evaluated in patients with successful histologic correlation. Further clinical evaluation and refinement are on the horizon.     

Development and Validation of a Computational Model for Investigation of Wrist Biomechanics

In this study, a computational model of the wrist joint complex was developed and validated for investigating the biomechanical function of the joint in clinically representative scenarios. Joint behavior and kinematics were dictated only by osteoarticular contact, ligamentous constraints, and muscle loading. Three-dimensional articular surfaces of each bone were generated from CT images, while ligaments and muscles were modeled as linear springs and constant-magnitude force vectors, respectively. Commercially available rigid body dynamics software was to both build the model and simulate joint function. Range of motion model predictions were compared to a cadaveric study analyzing the effects of scaphoid distal pole excision and triquetral excision after radioscapholunate (RSL) fusion for validation. The computational model was able to accurately predict flexion, extension, radial deviation, and ulnar deviation motions in four states: normal (intact), RSL fusion, RSL fusion with the scaphoid distal pole excised, and RSL fusion with both the scaphoid distal pole and triquetrum excised. The model was also able to calculate other parameters of interest that are not easily obtainable experimentally, such as midcarpal forces. This model and modeling approach are anticipated to have value as a predictive clinical tool including effect of injuries or anatomical variations and initial outcome of surgical procedures for patient specific planning and custom implant design.     

Temporomandibular Joint: Disorders,Treatments, and Biomechanics

Temporomandibular joint (TMJ) is a complex, sensitive, and highly mobile joint. Millions of people suffer from temporomandibular disorders (TMD) in USA alone. The TMD treatment options need to be looked at more fully to assess possible improvement of the available options and introduction of novel techniques. As reconstruction with either partial or total joint prosthesis is the potential treatment option in certain TMD conditions, it is essential to study outcomes of the FDA approved TMJ implants in a controlled comparative manner. Evaluating the kinetics and kinematics of the TMJ enables the understanding of structure and function of normal and diseased TMJ to predict changes due to alterations, and to propose more efficient methods of treatment. Although many researchers have conducted biomechanical analysis of the TMJ, many of the methods have certain limitations. Therefore, a more comprehensive analysis is necessary for better understanding of different movements and resulting forces and stresses in the joint components. This article provides the results of a state-of-the-art investigation of the TMJ anatomy, TMD, treatment options, a review of the FDA approved TMJ prosthetic devices, and the TMJ biomechanics.     

Impact of Positive End-Expiratory Pressure During Heterogeneous Lung Injury: Insights from Computed Tomographic Image Functional Modeling

Image Functional Modeling (IFM) synthesizes three dimensional airway networks with imaging and mechanics data to relate structure to function. The goal of this study was to advance IFM to establish a method of exploring how heterogeneous alveolar flooding and collapse during lung injury would impact regional respiratory mechanics and flow distributions within the lung at distinct positive end-expiratory pressure (PEEP) levels. We estimated regional respiratory system elastance from computed tomography (CT) scans taken in 5 saline-lavaged sheep at PEEP levels from 7.5 to 20 cmH₂O. These data were anatomically mapped into a computational sheep lung model, which was used to predict the corresponding impact of PEEP on dynamic flow distribution. Under pre-injury conditions and during lung injury, respiratory system elastance was determined to be spatially heterogeneous and the values were distributed with a hyperbolic distribution in the range of measured values. Increases in PEEP appear to modulate the heterogeneity of the flow distribution throughout the injured lung. Moderate increases in PEEP decreased the heterogeneity of elastance and predicted flow distribution, although heterogeneity began to increase for PEEP levels above 12.5–15 cmH₂O. By combining regional respiratory system elastance estimated from CT with our computational lung model, we can potentially predict the dynamic distribution of the tidal volume during mechanical ventilation and thus identify specific areas of the lung at risk of being overdistended.     

Auditory hallucinations: Insights and questions from neuroimaging

Introduction. The human brain has the capacity to hallucinate but rarely, except in severe neuropsychiatric conditions such as schizophrenia, do they naturally predominate. The neural basis of auditory verbal hallucinations (AVHs) has been investigated using structural and functional neuroimaging techniques. So far, no studies have defined a model that explains why auditory hallucinations are perceived in the absence of an external stimulus. Methods. A selective literature review was undertaken specifically to focus on: (1) clinical phenomenology; (2) putative brain systems involved in the pathogenesis of auditory hallucinations as suggested by neuroimaging studies; (3) contributions and weaknesses of the neuroimaging findings in potentially bridging the gap between the neuroscience and phenomenology. Throughout, an attempt was made to ask questions as much as to answer them. Results. Functional domains implicated in the genesis of auditory verbal hallucinations include: (1) hearing and language; (2) “sense of reality”, including externality of voices; (3) attention and salience; (4) emotional response; (5) memory; (6) volition and self-monitoring; (7) impulse control. Each of these domains can be mapped onto neural “systems” that comprise components that overlap with brain regions known to activate during the experience of auditory hallucinations Conclusions. In the next phase of neuroimaging research into the pathogenesis of auditory hallucinations we need to examine component processes that lead to the patient's perception of them as real.     

Biomechanics of plaque rupture: progress,problems, and new frontiers

Plaque rupture has become identified as a critical step in the evolution of arterial plaques, especially as clinically significant events occur in critical arteries. It has become common in the past dozen years or so to consider which plaques are vulnerable, even though not yet ruptured. Thrombotic events have remained significant, but in a context where they are seen as being triggered often by plaque rupture. Weaving together considerations from structural mechanics, fluid mechanics, plaque morphology, epidemiological pathology, micromechanical measurements of arterial wall tissues, and emerging information on the complex roles of the matrix metalloproteinases, this critical review draws attention to the relative paucity of data (i) on the mechanical behavior of small test portions of arterial tissues and (ii) on the relation of plaque locations to local vessel curvature and curvature flexure. This is especially important in the epicardial arteries, where combination of biplane angiograms and intravascular ultrasound (both becoming increasingly available in digital recordings) offer opportunities for clinical investigation, allied to biomechanics, to an extent previously not possible. Improved imaging and local tissue property assessments provide related opportunities for the carotid bifurcation. The discussion includes a proposal for developing an assessment scale for plaque vulnerability. © 2002 Biomedical Engineering Society. PAC2002: 8719Rr, 8719Xx, 8763Df, 4380Vj, 4380Qf     

Glioma Pathophysiology: Insights Emerging from Proteomics

Proteomics is increasingly employed in both neurological and oncological research to provide insight into the molecular basis of disease but rarely has a coherent, novel pathophysiological insight emerged. Gliomas account for >50% of adult primary intracranial tumors, with malignant gliomas (anaplastic astrocytomas and glioblastoma multiforme) being the most common. In glioma, the application of proteomic technology has identified altered protein expression but without consistency of these alterations or their biological significance being established. A systematic review of multiple independent proteomic analyses of glioma has demonstrated alterations of 99 different proteins. Importantly 10 of the 99 proteins found differentially expressed in glioma [PHB, Hsp20, serum albumin, epidermal growth factor receptor (EGFR), EA-15, RhoGDI, APOA1, GFAP, HSP70, PDIA3] were identified in multiple publications. An assessment of protein–protein interactions between these proteins compiled using novel web-based technology, revealed a robust and cohesive network for glioblastoma. The protein network discovered (containing TP53 and RB1 at its core) compliments recent findings in genomic studies of malignant glioma. The novel perspective provided by network analysis indicates that the potential of this technology to explore crucial aspects of glioma pathophysiology can now be realized but only if the conceptual and technical limitations highlighted in this review are addressed.     

Autophagy and ageing: Insights from invertebrate model organisms

Ageing in diverse species ranging from yeast to humans is associated with the gradual, lifelong accumulation of molecular and cellular damage. Autophagy, a conserved lysosomal, self-destructive process involved in protein and organelle degradation, plays an essential role in both cellular and whole-animal homeostasis. Accumulating evidence now indicates that autophagic degradation declines with age and this gradual reduction of autophagy might have a causative role in the functional deterioration of biological systems during ageing. Indeed, loss of autophagy gene function significantly influences longevity. Moreover, genetic or pharmacological manipulations that extend lifespan in model organisms often activate autophagy. Interestingly, conserved signalling pathways and environmental factors that regulate ageing, such as the insulin/IGF-1 signalling pathway and oxidative stress response pathways converge on autophagy. In this article, we survey recent findings in invertebrates that contribute to advance our understanding of the molecular links between autophagy and the regulation of ageing. In addition, we consider related mechanisms in other organisms and discuss their similarities and idiosyncratic features in a comparative manner.     

Resource allocation and fluid intelligence: Insights from pupillometry

Thinking is biological work and involves the allocation of cognitive resources. The aim of this study was to investigate the impact of fluid intelligence on the allocation of cognitive resources while one is processing low-level and high-level cognitive tasks. Individuals with high versus average fluid intelligence performed low-level choice reaction time tasks and high-level geometric analogy tasks. We combined behavioral measures to examine speed and accuracy of processing with pupillary measures that indicate resource allocation. Individuals with high fluid intelligence processed the low-level choice reaction time tasks faster than normal controls. The task-evoked pupillary responses did not differ between groups. Furthermore, individuals with high fluid intelligence processed the high-level geometric analogies faster, more accurately, and showed greater pupil dilations than normal controls. This was only true, however, for the most difficult analogy tasks. In addition, individuals with high fluid intelligence showed greater preexperimental pupil baseline diameters than normal controls. These results indicate that individuals with high fluid intelligence have more resources available and thus can solve more demanding tasks. Moreover, high fluid intelligence appears to be accompanied by more task-free exploration.