International Journal for Numerical Methods in Biomedical Engineering最新文献

Computational fluid dynamics (CFD) simulations have shown great potentials in cardiovascular disease diagnosis and postoperative assessment. Patient-specific and well-tuned boundary conditions are key to obtaining accurate and reliable hemodynamic results. However, CFD simulations are usually performed under non-patient-specific flow conditions due to the absence of in vivo flow and pressure measurements. This study proposes a new method to overcome this challenge by tuning inlet boundary conditions using data extracted from electrocardiogram (ECG). Five patient-specific geometric models of type B aortic dissection were reconstructed from computed tomography (CT) images. Other available data included stoke volume (SV), ECG, and 4D-flow magnetic resonance imaging (MRI). ECG waveforms were processed to extract patient-specific systole to diastole ratio (SDR). Inlet boundary conditions were defined based on a generic aortic flow waveform tuned using (1) SV only, and (2) with ECG and SV (ECG + SV). 4D-flow MRI derived inlet boundary conditions were also used in patient-specific simulations to provide the gold standard for comparison and validation. Simulations using inlet flow waveform tuned with ECG + SV not only successfully reproduced flow distributions in the descending aorta but also provided accurate prediction of time-averaged wall shear stress (TAWSS) in the primary entry tear (PET) and abdominal regions, as well as maximum pressure difference, ∆P_max, from the aortic root to the distal false lumen. Compared with simulations with inlet waveform tuned with SV alone, using ECG + SV in the tuning method significantly reduced the error in false lumen ejection fraction at the PET (from 149.1% to 6.2%), reduced errors in TAWSS at the PET (from 54.1% to 5.7%) and in the abdominal region (from 61.3% to 11.1%), and improved ∆P_max prediction (from 283.1% to 18.8%) However, neither of these inlet waveforms could be used for accurate prediction of TAWSS in the ascending aorta. This study demonstrates the importance of SDR in tailoring inlet flow waveforms for patient-specific hemodynamic simulations. A well-tuned flow waveform is essential for ensuring that the simulation results are patient-specific, thereby enhancing the confidence and fidelity of computational tools in future clinical applications.

In this work, we couple a lumped-parameter closed-loop model of the cardiovascular system with a physiologically-detailed mathematical description of the baroreflex afferent pathway. The model features a classical Hodgkin–Huxley current-type model for the baroreflex afferent limb (primary neuron) and for the second-order neuron in the central nervous system. The pulsatile arterial wall distension triggers a frequency-modulated sequence of action potentials at the afferent neuron. This signal is then integrated at the brainstem neuron model. The efferent limb, representing the sympathetic and parasympathetic nervous system, is described as a transfer function acting on heart and blood vessel model parameters in order to control arterial pressure. Three in silico experiments are shown here: a step increase in the aortic pressure to evaluate the functionality of the reflex arch, a hemorrhagic episode and an infusion simulation. Through this model, it is possible to study the biophysical dynamics of the ionic currents proposed for the afferent limb components of the baroreflex during the cardiac cycle, and the way in which currents dynamics affect the cardiovascular function. Moreover, this system can be further developed to study in detail each baroreflex loop component, helping to unveil the mechanisms involved in the cardiovascular afferent information processing.

Traumatic brain injury is a significant problem worldwide. In the United States of America, around 1.7 million cases are documented annually, displaying the need for a deeper understanding of the effects on the human brain. The tests required for this assessment are very complex. Tests on cadavers may raise serious ethical questions, and in vivo crash tests are not viable. In this context, there is a great need to developing finite element head models (FEHM) to study the biomechanics of the tissues when submitted to a certain impact or acceleration/deceleration scenario. An excellent compromise between accuracy and CPU efficiency is always desirable for a FEHM, For this reason, this work focuses on the improvement of an existing head model, including the study of the behavior of the brain using distinct finite element types. The finite element type and formulation is of utmost importance for the general accuracy and efficiency of the models. Several validations were performed, comparing the simulation results against experimental data. The simulations with hexahedral elements, under specific conditions, obtained more accurate results with a lower computational cost. Using hexahedrals, a comparison was also performed using two material characterizations with more than 10 years apart, using the latest finite element head model validation experiment. Overall, the newer material model displays a less stiff response, although its implementation must always depend on the overall purpose of the model it is being applied to.

Needle syringe irrigation is frequently used in root canal therapy, and the flow pattern during irrigation can be efficiently manipulated by means of passive flow control technique, resulting in expected irrigation performance improvement. Therefore, novel needles with composite flow control structures are numerically investigated and optimized in this study. Based on the 30G needle, six single/double side-vented needles with dimple and protrusion are proposed. Two flow rates in line with clinical applications, 5.3 and 8.6 m/s, are used in the analysis. Three performance parameters are investigated. The safety of the irrigation system is evaluated by the root canal apical pressure, whereas the irrigant extension and the flushing efficiency are evaluated by the extending depth and the effective cleaning area, respectively. The results demonstrate that the shear stress of the double-side-vented needle is higher while the irrigant extension is enhanced with a dimple structure. The performance of the double-side-vented needle with a dimple is superior to that of other designs, with up to 33% improvement in extending depth and a 22% increase in effective cleaning area over the prototype. New needles do not raise risk of irrigant extrusion. Furthermore, the effect of dimple depth and outlet angle are investigated. The needle with a dimple of 0.04 mm depth shows the highest extending depth within the confines of the investigation. The effective cleaning area is significantly influenced by the needle outlets, and the effective cleaning area expands with an increase in needle outlet angle, while the extending depth gradually declines.

Pulmonary valve replacement (PVR) consists of substituting a patient's original valve with a prosthetic one, primarily addressing pulmonary valve insufficiency, which is crucially relevant in Tetralogy of Fallot repairment. While extensive clinical and computational literature on aortic and mitral valve replacements is available, PVR's post-procedural haemodynamics in the pulmonary artery and the impact of prosthetic valve dynamics remain significantly understudied. Addressing this gap, we introduce a reduced Fluid–Structure Interaction (rFSI) model, applied for the first time to the pulmonary valve. This model couples a three-dimensional computational representation of pulmonary artery haemodynamics with a one-degree-of-freedom model to account for valve structural mechanics. Through this approach, we analyse patient-specific haemodynamics pre and post PVR. Patient-specific geometries, reconstructed from CT scans, are virtually equipped with a template valve geometry. Boundary conditions for the model are established using a lumped-parameter model, fine-tuned based on clinical patient data. Our model accurately reproduces patient-specific haemodynamic changes across different scenarios: pre-PVR, six months post-PVR, and a follow-up condition after a decade. It effectively demonstrates the impact of valve implantation on sustaining the diastolic pressure gradient across the valve. The numerical results indicate that our valve model is able to reproduce overall physiological and/or pathological conditions, as preliminary assessed on two different patients. This promising approach provides insights into post-PVR haemodynamics and prosthetic valve effects, shedding light on potential implications for patient-specific outcomes.

Over the last couple of decades, image-based computational fluid dynamics (CFD) has revolutionized cardiovascular research by uncovering hidden features of wall strain, impact of vortices, and its use in treatment planning, as examples, that were simply not evident in the gold-standard catheterization studies done previously. In the work presented here, we have applied magnetic resonance imaging (MRI)-based CFD to study bladder voiding and to demonstrate the feasibility and potential of this approach. We used 3D dynamic MRI to image the bladder and urethra during voiding. A surface mesh processing tool was developed to process the bladder wall prior to executing a wall-motion driven CFD simulation of the bladder and urethra. The obtained flow rate and pressure were used to calculate urodynamic nomograms, which are currently used in the clinical setting to assess bladder voiding dysfunction. These nomograms concluded that our healthy volunteer has an unobstructed bladder and normal contractility. We calculated the work done to void the bladder and propose this as an additional quantitative metric to comprehensively assess bladder function. Further, we discuss the areas that would improve this relatively new methodology of image-based CFD in urodynamics.

We develop computational mechanical modeling and methods for the analysis and simulation of the motions of a human body. This type of work is crucial in many aspects of human life, ranging from comfort in riding, the motion of aged persons, sports performance and injuries, and many ergonomic issues. A prevailing approach for human motion studies is through lumped parameter models containing discrete masses for the parts of the human body with empirically determined spring, mass, damping coefficients. Such models have been effective to some extent; however, a much more faithful modeling method is to model the human body as it is, namely, as a continuum. We present this approach, and for comparison, we choose two digital CAD models of mannequins for a standing human body, one from the versatile software package LS-DYNA and another from open resources with some of our own adaptations. Our basic view in this paper is to regard human motion as a perturbation and vibration from an equilibrium position which is upright standing. A linear elastodynamic model is chosen for modal analysis, but a full nonlinear viscoelastoplastic extension is possible for full-body simulation. The motion and vibration of these two mannequin models is analyzed by modal analysis, where the normal vibration modes are determined. LS-DYNA is used as the supercomputing and simulation platform. Four sets of low-frequency modes are tabulated, discussed, visualized, and compared. Higher frequency modes are also selectively displayed. We have found that these modes of motion and vibration form intrinsic basic modes of biomechanical motion of the human body. This view is supported by our finding of the upright walking motion as a low-frequency mode in modal analysis. Such a “walking mode” shows the in-phase and out-of-phase movements between the legs and arms on the left and right sides of a human body, implying that this walking motion is spontaneous, likely not requiring any directives from the brain. Dynamic motions of CAD mannequins are also simulated by drop tests for comparisons and the validity of the models is discussed through Fourier frequency analysis. All computed modes of motion are collected in several sets of video animations for ease of visualization. Samples of LS-DYNA computer codes are also included for possible use by other researchers.

Virtual compression tests based on finite element analysis are representative noninvasive methods to evaluate bone strength. However, owing to the characteristic porous structure of bones, the material obtained from micro-computed tomography images in the finite-element model is not uniformly distributed. These characteristics cause differences in the apparent elastic moduli depending on the boundary conditions and affect the accuracy of bone-strength evaluation. Therefore, this study aimed to evaluate and compare the apparent elastic moduli under various, virtual-compression and shear-test boundary conditions. Four, nonuniform models were constructed with increasing model complexity. For representative boundary conditions, two, different, testing directions, and constrained surfaces were applied. As a result, the apparent elastic moduli of the nonuniform model varied up to 55.2% based on where the constrained surface was located in the single-end-cemented condition. Additionally, when connectivity in the test direction was lost, the accuracy of the apparent elastic moduli was low. A graphical comparison showed that the equivalent-stress distribution was more advantageous for analyzing load transferability and physical behavior than the strain-energy distribution. These results clearly show that the prediction accuracy of the apparent elastic moduli can be guaranteed if the boundary condition on the constraint and loading surfaces of the nonuniform model are applied symmetrically and the connectivity of the elements in the testing direction is well maintained. This study will aid in precision improvement of bone-strength-indicator determination for osteoporosis prevention.

An epicardial approach is often used in radiofrequency (RF) catheter ablation to ablate ventricular tachycardia when an endocardial approach fails. Our objective was to analyze the effect of the position of the dispersive patch (DP) on lesion size using computer modeling during epicardial approach. We compared the posterior position (patient's back), commonly used in clinical practice, to the anterior position (patient's chest). The model considered ventricular wall thicknesses between 4 and 8 mm, and electrode insertion depths between .3 and .7 mm. RF pulses were simulated with 20 W of power for 30 s duration. Statistically significant differences (P < .001) were found between both DP positions in terms of baseline impedance, RF current (at 15 s) and thermal lesion size. The anterior position involved lower impedance (130.8 ± 4.7 vs. 146.2 ± 4.9 Ω) and a higher current (401.5 ± 5.6 vs. 377.5 ± 5.1 mA). The anterior position created lesion sizes larger than the posterior position: 8.9 ± 0.4 vs. 8.4 ± 0.4 mm in maximum width, 8.6 ± 0.4 vs. 8.1 ± 0.4 mm in surface width, and 4.5 ± 0.4 vs. 4.3 ± 0.4 mm in depth. Our results suggest that: (1) the redirection of the RF currents due to repositioning the PD has little impact on lesion size and only affects baseline impedance, and (2) the differences in lesion size are only 0.5 mm wider and 0.2 mm deeper for the anterior position, which does not seem to have a clinical impact in the context of VT ablation.

Infrared thermography is gaining relevance in breast cancer assessment. For this purpose, breast segmentation in thermograms is an important task for performing automatic image analysis and detecting possible temperature changes that indicate the presence of malignancy. However, it is not a simple task since the breast limit borders, especially the top borders, often have low contrast, making it difficult to isolate the breast area. Several algorithms have been proposed for breast segmentation, but these highly depend on the contrast at the lower breast borders and on filtering algorithms to remove false edges. This work focuses on taking advantage of the distinctive inframammary shape to simplify the definition of the lower breast border, regardless of the contrast level, which indeed also provides a strong anatomical reference to support the definition of the poorly marked upper boundary of the breasts, which has been one of the major challenges in the literature. In order to demonstrate viability of the proposed technique for an automatic breast segmentation, we applied it to a database with 180 thermograms and compared their results with those reported by others in the literature. We found that our approach achieved a high performance, in terms of Intersection over Union of 0.934, even higher than that reported by artificial intelligence algorithms. The performance is invariant to breast sizes and thermal contrast of the images.