Background: We present a fundamental theoretical framework for analysis of energy dissipation in any component of the circulatory system and formulate the full energy budget for both venous and arterial circulations. New indices allowing disease-specific subject-to-subject comparisons and disease-to-disease hemodynamic evaluation (quantifying the hemodynamic severity of one vascular disease type to the other) are presented based on this formalism.
Methods and Results: Dimensional analysis of energy dissipation rate with respect to the human circulation shows that the rate of energy dissipation is inversely proportional to the square of the patient body surface area and directly proportional to the cube of cardiac output. This result verified the established formulae for energy loss in aortic stenosis that was solely derived through empirical clinical experience. Three new indices are introduced to evaluate more complex disease states: (1) circulation energy dissipation index (CEDI), (2) aortic valve energy dissipation index (AV-EDI), and (3) total cavopulmonary connection energy dissipation index (TCPC-EDI). CEDI is based on the full energy budget of the circulation and is the proper measure of the work performed by the ventricle relative to the net energy spent in overcoming frictional forces. It is shown to be 4.01 ± 0.16 for healthy individuals and above 7.0 for patients with severe aortic stenosis. Application of CEDI index on single-ventricle venous physiology reveals that the surgically created Fontan circulation, which is indeed palliative, progressively degrades in hemodynamic efficiency with growth (p < 0.001), with the net dissipation in a typical Fontan patient (Body surface area = 1.0 m2) being equivalent to that of an average case of severe aortic stenosis. AV-EDI is shown to be the proper index to gauge the hemodynamic severity of stenosed aortic valves as it accurately reflects energy loss. It is about 0.28 ± 0.12 for healthy human valves. Moderate aortic stenosis has an AV-EDI one order of magnitude higher while clinically severe aortic stenosis cases always had magnitudes above 3.0. TCPC-EDI represents the efficiency of the TCPC connection and is shown to be negatively correlated to the size of a typical "bottle-neck" region (pulmonary artery) in the surgical TCPC pathway (p < 0.05).
Conclusions: Energy dissipation in the human circulation has been analyzed theoretically to derive the proper scaling (indexing) factor. CEDI, AV-EDI, and TCPC-EDI are proper measures of the dissipative characteristics of the circulatory system, aortic valve, and the Fontan connection, respectively.
The biomechanical principles underlying the organization of muscle activation patterns during standing balance are poorly understood. The goal of this study was to understand the influence of biomechanical inter-joint coupling on endpoint forces and accelerations induced by the activation of individual muscles during postural tasks. We calculated induced endpoint forces and accelerations of 31 muscles in a 7 degree-of-freedom, three-dimensional model of the cat hindlimb. To test the effects of inter-joint coupling, we systematically immobilized the joints (excluded kinematic degrees of freedom) and evaluated how the endpoint force and acceleration directions changed for each muscle in 7 different conditions. We hypothesized that altered inter-joint coupling due to joint immobilization of remote joints would substantially change the induced directions of endpoint force and acceleration of individual muscles. Our results show that for most muscles crossing the knee or the hip, joint immobilization altered the endpoint force or acceleration direction by more than 90° in the dorsal and sagittal planes. Induced endpoint forces were typically consistent with behaviorally observed forces only when the ankle was immobilized. We then activated a proximal muscle simultaneous with an ankle torque of varying magnitude, which demonstrated that the resulting endpoint force or acceleration direction is modulated by the magnitude of the ankle torque. We argue that this simple manipulation can lend insight into the functional effects of co-activating muscles. We conclude that inter-joint coupling may be an essential biomechanical principle underlying the coordination of proximal and distal muscles to produce functional endpoint actions during motor tasks.
Over the years, three-dimensional models of the mitral valve have generally been organized around a simplified anatomy. Leaflets have been typically modeled as membranes, tethered to discrete chordae typically modeled as one-dimensional, non-linear cables. Yet, recent, high-resolution medical images have revealed that there is no clear boundary between the chordae and the leaflets. In fact, the mitral valve has been revealed to be more of a webbed structure whose architecture is continuous with the chordae and their extensions into the leaflets. Such detailed images can serve as the basis of anatomically accurate, subject-specific models, wherein the entire valve is modeled with solid elements that more faithfully represent the chordae, the leaflets, and the transition between the two. These models have the potential to enhance our understanding of mitral valve mechanics and to re-examine the role of the mitral valve chordae, which heretofore have been considered to be ‘invisible’ to the fluid and to be of secondary importance to the leaflets. However, these new models also require a rethinking of modeling assumptions. In this study, we examine the conventional practice of loading the leaflets only and not the chordae in order to study the structural response of the mitral valve apparatus. Specifically, we demonstrate that fully resolved 3D models of the mitral valve require a fluid–structure interaction analysis to correctly load the valve even in the case of quasi-static mechanics. While a fluid–structure interaction mode is still more computationally expensive than a structural-only model, we also show that advances in GPU computing have made such models tractable.
A number of clinical, in vitro and computational studies have shown the potential for thromboembolic complications in bileaflet mechanical heart valves (BMHV), primarily due to the complex and unsteady flows in the valve hinges. These studies have focused on quantitative and qualitative parameters such as velocity magnitude, turbulent shear stresses, vortex formation, and platelet activation to identify potential for blood damage. However, experimental characterization of the whole flow fields within the valve hinges has not yet been conducted. This information can be utilized to investigate instantaneous damage to blood elements and also to validate numerical studies focusing on the hinge's complex fluid dynamics. The objective of this study was therefore to develop a high-resolution imaging system to characterize the flow fields and global velocity maps in a BMHV hinge. In this study, the steady leakage hinge flow fields representing the diastolic phase during the cardiac cycle in a 23 mm St. Jude Medical regent BMHV in the aortic position were characterized using a two-dimensional micro particle image velocimetry system. Diastolic flow was simulated by imposing a static pressure head on the aortic side. Under these conditions, a reverse flow jet from the aortic to the ventricular side was observed with velocities in the range of 1.47-3.24 m/s, whereas low flow regions were observed on the ventricular side of the hinge with viscous shear stress magnitude up to 60 N/m2. High velocities and viscous shearing may be associated with platelet activation and hemolysis, while low flow zones can cause thrombosis due to increased residence time in the hinge. Overall, this study provides a high spatial resolution experimental technique to map the fluid velocity in the BMHV hinge, which can be extended to investigate micron-scale flow domains in various prosthetic devices under different hemodynamic conditions.
Computational fluid dynamics (CFD) tools have been extensively applied to study the hemodynamics in the total cavopulmonary connection (TCPC) in patients with only a single functioning ventricle. Without the contraction of a sub-pulmonary ventricle, pulsatility of flow through this connection is low and variable across patients, which is usually neglected in most numerical modeling studies. Recent studies suggest that such pulsatility can be non-negligible and can be important in hemodynamic predictions. The goal of this work is to compare the results of an in-house numerical methodology for simulating pulsatile TCPC flow with experimental results. Digital particle image velocimetry (DPIV) was acquired on TCPC in vitro models to evaluate the capability of the CFD tool in predicting pulsatile TCPC flow fields. In vitro hemodynamic measurements were used to compare the numerical prediction of power loss across the connection. The results demonstrated the complexity of the pulsatile TCPC flow fields and the validity of the numerical approach in simulating pulsatile TCPC flow dynamics in both idealized and complex patient specific models.
Simulating realistic musculoskeletal dynamics is critical to understanding neural control of muscle activity evoked in sensorimotor feedback responses that have inherent neural transmission delays. Thus, the initial mechanical response of muscles to perturbations in the absence of any change in muscle activity determines which corrective neural responses are required to stabilize body posture. Muscle short-range stiffness, a history-dependent property of muscle that causes a rapid and transient rise in muscle force upon stretch, likely affects musculoskeletal dynamics in the initial mechanical response to perturbations. Here we identified the contributions of short-range stiffness to joint torques and angles in the initial mechanical response to support surface translations using dynamic simulation. We developed a dynamic model of muscle short-range stiffness to augment a Hill-type muscle model. Our simulations show that short-range stiffness can provide stability against external perturbations during the neuromechanical response delay. Assuming constant muscle activation during the initial mechanical response, including muscle short-range stiffness was necessary to account for the rapid rise in experimental sagittal plane knee and hip joint torques that occurs simultaneously with very small changes in joint angles and reduced root mean square errors between simulated and experimental torques by 56% and 47%, respectively. Moreover, forward simulations lacking short-range stiffness produced unreasonably large joint angle changes during the initial response. Using muscle models accounting for short-range stiffness along with other aspects of history-dependent muscle dynamics may be important to advance our ability to simulate inherently unstable human movements based on principles of neural control and biomechanics.
by
Rolando A. Gittens;
Rene Olivares-Navarrete;
Alice Cheng;
David M. Anderson;
Taylor McLachlan;
Ingrid Stephan;
Jurgen Geis-Gerstorfer;
Kenneth H. Sandhage;
Andrei G. Fedorov;
Frank Rupp;
Barbara Boyan;
Rina Tannenbaum;
Zvi Schwartz
Surface micro- and nanostructural modifications of dental and orthopedic implants have shown promising in vitro, in vivo and clinical results. Surface wettability has also been suggested to play an important role in osteoblast differentiation and osseointegration. However, the available techniques to measure surface wettability are not reliable on clinically relevant, rough surfaces. Furthermore, how the differentiation state of osteoblast lineage cells impacts their response to micro/nanostructured surfaces, and the role of wettability on this response, remain unclear. In the current study, surface wettability analyses (optical sessile drop analysis, environmental scanning electron microscopic analysis and the Wilhelmy technique) indicated hydrophobic static responses for deposited water droplets on microrough and micro/nanostructured specimens, while hydrophilic responses were observed with dynamic analyses of micro/nanostructured specimens. The maturation and local factor production of human immature osteoblast-like MG63 cells was synergistically influenced by nanostructures superimposed onto microrough titanium (Ti) surfaces. In contrast, human mesenchymal stem cells cultured on micro/nanostructured surfaces in the absence of exogenous soluble factors exhibited less robust osteoblastic differentiation and local factor production compared to cultures on unmodified microroughened Ti. Our results support previous observations using Ti6Al4V surfaces showing that recognition of surface nanostructures and subsequent cell response is dependent on the differentiation state of osteoblast lineage cells. The results also indicate that this effect may be partly modulated by surface wettability. These findings support the conclusion that the successful osseointegration of an implant depends on contributions from osteoblast lineage cells at different stages of osteoblast commitment.
Total cavopulmonary connection is the result of a series of palliative surgical repairs performed on patients with single ventricle heart defects. The resulting anatomy has complex and unsteady hemodynamics characterized by flow mixing and flow separation. Although varying degrees of flow pulsatility have been observed in vivo, non-pulsatile (time-averaged) boundary conditions have traditionally been assumed in hemodynamic modeling, and only recently have pulsatile conditions been incorporated without completely characterizing their effect or importance. In this study, 3D numerical simulations with both pulsatile and non-pulsatile boundary conditions were performed for 24 patients with different anatomies and flow boundary conditions from Georgia Tech database. Flow structures, energy dissipation rates and pressure drops were compared under rest and simulated exercise conditions. It was found that flow pulsatility is the primary factor in determining the appropriate choice of boundary conditions, whereas the anatomic configuration and cardiac output had secondary effects. Results show that the hemodynamics can be strongly influenced by the presence of pulsatile flow. However, there was a minimum pulsatility threshold, identified by defining a weighted pulsatility index (wPI), above which the influence was significant. It was shown that when wPI < 30%, the relative error in hemodynamic predictions using time-averaged boundary conditions was less than 10% compared to pulsatile simulations. In addition, when wPI < 50, the relative error was less than 20%. A correlation was introduced to relate wPI to the relative error in predicting the flow metrics with non-pulsatile flow conditions.
by
Dirk Hoyer;
Jan Zebrowski;
Dirk Cysarz;
Hernani Goncalves;
Adelina Pytlik;
Celia Amorim-Costa;
Joao Bernardes;
Diogo Ayres-de-Campos;
Otto W. Witte;
Ekkehard Schleussner;
Lisa Stroux;
Christopher Redman;
Antoniya Georgieva;
Stephen Payne;
Gari D. Clifford;
Maria G. Signorini;
Giovanni Magenes;
Fernando Andreotti;
Hagen Malberg;
Sebastian Zaunseder;
Igor Lakhno;
Uwe Schneider
Monitoring the fetal behavior does not only have implications for acute care but also for identifying developmental disturbances that burden the entire later life. The concept, of 'fetal programming', also known as 'developmental origins of adult disease hypothesis', e.g. applies for cardiovascular, metabolic, hyperkinetic, cognitive disorders. Since the autonomic nervous system is involved in all of those systems, cardiac autonomic control may provide relevant functional diagnostic and prognostic information. The fetal heart rate patterns (HRP) are one of the few functional signals in the prenatal period that relate to autonomic control and, therefore, is predestinated for its evaluation. The development of sensitive markers of fetal maturation and its disturbances requires the consideration of physiological fundamentals, recording technology and HRP parameters of autonomic control. Based on the ESGCO2016 special session on monitoring the fetal maturation we herein report the most recent results on: (i) functional fetal autonomic brain age score (fABAS), Recurrence Quantitative Analysis and Binary Symbolic Dynamics of complex HRP resolve specific maturation periods, (ii) magnetocardiography (MCG) based fABAS was validated for cardiotocography (CTG), (iii) 30 min recordings are sufficient for obtaining episodes of high variability, important for intrauterine growth restriction (IUGR) detection in handheld Doppler, (iv) novel parameters from PRSA to identify Intra IUGR fetuses, (v) evaluation of fetal electrocardiographic (ECG) recordings, (vi) correlation between maternal and fetal HRV is disturbed in pre-eclampsia. The reported novel developments significantly extend the possibilities for the established CTG methodology. Novel HRP indices improve the accuracy of assessment due to their more appropriate consideration of complex autonomic processes across the recording technologies (CTG, handheld Doppler, MCG, ECG). The ultimate objective is their dissemination into routine practice and studies of fetal developmental disturbances with implications for programming of adult diseases.
Neuromusculoskeletal models solve the basic problem of determining how the body moves under the influence of external and internal forces. Existing biomechanical modeling programs often emphasize dynamics with the goal of finding a feed-forward neural program to replicate experimental data or of estimating force contributions or individual muscles. The computation of rigid-body dynamics, muscle forces, and activation of the muscles are often performed separately. We have developed an intrinsically forward computational platform (Neuromechanic, www.neuromechanic.com) that explicitly represents the interdependencies among rigid body dynamics, frictional contact, muscle mechanics, and neural control modules. This formulation has significant advantages for optimization and forward simulation, particularly with application to neural controllers with feedback or regulatory features. Explicit inclusion of all state dependencies allows calculation of system derivatives with respect to kinematic states and muscle and neural control states, thus affording a wealth of analytical tools, including linearization, stability analyses and calculation of initial conditions for forward simulations. In this review, we describe our algorithm for generating state equations and explain how they may be used in integration, linearization, and stability analysis tools to provide structural insights into the neural control of movement.