Computational analysis of cancer cell adhesion in curved vessels affected by wall shear stress for prediction of metastatic spreading.

Introduction: The dynamics of circulating tumor cells (CTCs) within blood vessels play a pivotal role in predicting metastatic spreading of cancer within the body. However, the limited understanding and method to quantitatively investigate the influence of vascular architecture on CTC dynamics hinders our ability to predict metastatic process effectively. To address this limitation, the present study was conducted to investigate the influence of blood vessel tortuosity on the behaviour of CTCs, focusing specifically on establishing methods and examining the role of shear stress in CTC-vessel wall interactions and its subsequent impact on metastasis. Methods: We computationally simulated CTC behaviour under various shear stress conditions induced by vessel tortuosity. Our computational model, based on the lattice Boltzmann method (LBM) and a coarse-grained spectrin-link membrane model, efficiently simulates blood plasma dynamics and CTC deformability. The model incorporates fluid-structure interactions and receptor-ligand interactions crucial for CTC adhesion using the immersed boundary method (IBM). Results: Our findings reveal that uniform shear stress in straight vessels leads to predictable CTC-vessel interactions, whereas in curved vessels, asymmetrical flow patterns and altered shear stress create distinct adhesion dynamics, potentially influencing CTC extravasation. Quantitative analysis shows a 25% decrease in the wall shear stress in low-shear regions and a 58.5% increase in the high-shear region. We observed high-shear regions in curved vessels to be potential sites for increased CTC adhesion and extravasation, facilitated by elevated endothelial expression of adhesion molecules. This phenomenon correlates with the increased number of adhesion bonds, which rises to approximately 40 in high-shear regions, compared to around 12 for straight vessels and approximately 5-6 in low-shear regions. The findings also indicate an optimal cellular stiffness necessary for successful CTC extravasation in curved vessels. Discussion: By the quantitative assessment of the risk of CTC extravasation as a function of vessel tortuosity, our study offers a novel tool for the prediction of metastasis risk to support the development of personalized therapeutic interventions based on individual vascular characteristics and tumor cell properties.

Mechanical Effects of Medical Device Attachment to Human Tympanic Membrane.

PURPOSE: Several treatment methods for hearing disorders rely on attaching medical devices to the tympanic membrane. This study aims to systematically analyze the effects of the material and geometrical properties and location of the medical devices attached to the tympanic membrane on middle-ear vibrations. METHODS: A finite-element model of the human middle ear was employed to simulate the effects of attachment of medical devices. Various types of material and geometrical properties, locations, and modeling scenarios were investigated for the medical device. RESULTS: The attachment of the device magnifies the effects of anti-resonances of the middle ear. Additionally, the variations of the material properties of the device significantly alter the middle-ear resonance frequency while changes in the umbo and stapes footplate motions are negligible at frequencies above 5 kHz. Furthermore, modeling the device as a point mass cannot accurately represent the implanted middle-ear behavior. The variations of the diameter and height of the medical device have negligible effects on the middle-ear vibrations at frequencies below 200 Hz but can have considerable impacts at higher frequencies. The effects of changing the device height were negligible at frequencies above 2 kHz. We also discuss the effects of medical device attachment on the vibration patterns of the tympanic membrane as well as the impacts of the variations of the location of the device on the stapes footplate responses. CONCLUSION: The findings of our study aid the development and optimization of new therapeutic devices, attached to the tympanic membrane, to have the least adverse effects on middle-ear vibrations.

Material characterization of human middle ear using machine-learning-based surrogate models.

This study aims to introduce a novel non-invasive method for rapid material characterization of middle-ear structures, taking into consideration the invaluable insights provided by the mechanical properties of ear tissues. Valuable insights into various ear pathologies can be gleaned from the mechanical properties of ear tissues, yet conventional techniques for assessing these properties often entail invasive procedures that preclude their use on living patients. In this study, in the first step, we developed machine-learning models of the middle ear to predict its responses with a significantly lower computational cost in comparison to finite-element models. Leveraging findings from prior research, we focused on the most influential model parameters: the Young's modulus and thickness of the tympanic membrane and the Young's modulus of the stapedial annular ligament. The eXtreme Gradient Boosting (XGBoost) method was implemented for creating the machine-learning models. Subsequently, we combined the created machine-learning models with Bayesian optimization (BoTorch) for fast and efficient estimation of the Young's moduli of the tympanic membrane and the stapedial annular ligament. We demonstrate that the resultant surrogate models can fairly represent the vibrational responses of the umbo, stapes footplate, and vibration patterns of the tympanic membrane at most frequencies. Also, our proposed material characterization approach successfully estimated the Young's moduli of the tympanic membrane and stapedial annular ligament (separately and simultaneously) with values of mean absolute percentage error of less than 7%. The remarkable accuracy achieved through the proposed material characterization method underscores its potential for eventual clinical applications of estimating mechanical properties of the middle-ear structures for diagnostic purposes.

Numerical study of ultra-large von Willebrand factor multimers in coagulopathy.

An excessive von Willebrand factor (VWF) secretion, coupled with a moderate to severe deficiency of ADAMTS13 activity, serves as a linking mechanism between inflammation to thrombosis. The former facilitates platelet adhesion to the vessel wall and the latter is required to cleave VWF multimers. As a result, the ultra-large VWF (UL-VWF) multimers released by Weibel-Palade bodies remain uncleaved. In this study, using a computational model based on first principles, we quantitatively show how the uncleaved UL-VWF multimers interact with the blood cells to initiate microthrombosis. We observed that platelets first adhere to unfolded and stretched uncleaved UL-VWF multimers anchored to the microvessel wall. By the end of this initial adhesion phase, the UL-VWF multimers and platelets make a mesh-like trap in which the red blood cells increasingly accumulate to initiate a gradually growing microthrombosis. Although high-shear rate and blood flow velocity are required to activate platelets and unfold the UL-VWFs, during the initial adhesion phase, the blood velocity drastically drops after thrombosis, and as a result, the wall shear stress is elevated near UL-VWF roots, and the pressure drops up to 6 times of the healthy condition. As the time passes, these trends progressively continue until the microthrombosis fully develops and the effective size of the microthrombosis and these flow quantities remain almost constant. Our findings quantitatively demonstrate the potential role of UL-VWF in coagulopathy.

Experimental measurement and numerical modeling of deformation behavior of breast cancer cells passing through constricted microfluidic channels.

During the multistep process of metastasis, cancer cells encounter various mechanical forces which make them deform drastically. Developing accurate in-silico models, capable of simulating the interactions between the mechanical forces and highly deformable cancer cells, can pave the way for the development of novel diagnostic and predictive methods for metastatic progression. Spring-network models of cancer cell, empowered by our recently proposed identification approach, promises a versatile numerical tool for developing experimentally validated models that can simulate complex interactions at cellular scale. Using this numerical tool, we presented spring-network models of breast cancer cells that can accurately replicate the experimental data of deformation behavior of the cells flowing in a fluidic domain and passing narrow constrictions comparable to microcapillary. First, using high-speed imaging, we experimentally studied the deformability of breast cancer cell lines with varying metastatic potential (MCF-7 (less invasive), SKBR-3 (medium-high invasive), and MDA-MB-231 (highly invasive)) in terms of their entry time to a constricted microfluidic channel. We observed that MDA-MB-231, that has the highest metastatic potential, is the most deformable cell among the three. Then, by focusing on this cell line, experimental measurements were expanded to two more constricted microchannel dimensions. The experimental deformability data in three constricted microchannel sizes for various cell sizes, enabled accurate identification of the unknown parameters of the spring-network model of the breast cancer cell line (MDA-MB-231). Our results show that the identified parameters depend on the cell size, suggesting the need for a systematic procedure for identifying the size-dependent parameters of spring-network models of cells. As the numerical results show, the presented cell models can simulate the entry process of the cell into constricted channels with very good agreements with the measured experimental data.

Early Detection of Risk of Neo-Sinus Blood Stasis Post-Transcatheter Aortic Valve Replacement Using Personalized Hemodynamic Analysis.

Background: Despite the demonstrated benefits of transcatheter aortic valve replacement (TAVR), subclinical leaflet thrombosis and hypoattenuated leaflet thickening are commonly seen as initial indications of decreased valve durability and augmented risk of transient ischemic attack. Methods: We developed a multiscale patient-specific computational framework to quantify metrics of global circulatory function, metrics of global cardiac function, and local cardiac fluid dynamics of the aortic root and coronary arteries. Results: Based on our findings, TAVR might be associated with a high risk of blood stagnation in the neo-sinus region due to the lack of sufficient blood flow washout during the diastole phase (e.g., maximum blood stasis volume increased by 13, 8, and 2.7 fold in the left coronary cusp, right coronary cusp, and noncoronary cusp, respectively [N = 26]). Moreover, in some patients, TAVR might not be associated with left ventricle load relief (e.g., left ventricle load reduced only by 1.2 % [N = 26]) and diastolic coronary flow improvement (e.g., maximum coronary flow reduced by 4.94%, 15.05%, and 23.59% in the left anterior descending, left circumflex coronary artery, and right coronary artery, respectively, [N = 26]). Conclusions: The transvalvular pressure gradient amelioration after TAVR might not translate into adequate sinus blood washout, optimal coronary flow, and reduced cardiac stress. Noninvasive personalized computational modeling can facilitate the determination of the most effective revascularization strategy pre-TAVR and monitor leaflet thrombosis and coronary plaque progression post-TAVR.

Relative importance and interactions of parameters of finite-element models of human middle ear.

In the last decades, finite-element models of the middle ear have been widely used to predict the middle-ear vibration outputs. Even with the simplest linear assumption for material properties of the structures in the middle ear, these models need tens of parameters. Due to the complexities of measurements of material properties of these structures, accurate estimations of the values of most of these parameters are not possible. In this study, we benefited from the stochastic finite-element model of the middle ear we had developed in the past, to perform global sensitivity analysis. For this aim, we implemented Sobol' sensitivity analysis which ranks the importance of all uncertain parameters and interactions among them at different frequencies. To decrease the computational costs, we found Sobol' indices from surrogate models that we created using stochastic finite-element results and the polynomial chaos expansion method. Based on the results, the Young's modulus and thickness of the tympanic membrane, Young's modulus and damping of the stapedial annular ligaments, and the Young's modulus of ossicles are among the parameters with the greatest impacts on vibrations of the umbo and stapes footplate. Furthermore, the most significant interactions happen between the Young's modulus and thickness of the tympanic membrane.

Impact of TAVR on coronary artery hemodynamics using clinical measurements and image-based patient-specific in silico modeling.

In recent years, transcatheter aortic valve replacement (TAVR) has become the leading method for treating aortic stenosis. While the procedure has improved dramatically in the past decade, there are still uncertainties about the impact of TAVR on coronary blood flow. Recent research has indicated that negative coronary events after TAVR may be partially driven by impaired coronary blood flow dynamics. Furthermore, the current technologies to rapidly obtain non-invasive coronary blood flow data are relatively limited. Herein, we present a lumped parameter computational model to simulate coronary blood flow in the main arteries as well as a series of cardiovascular hemodynamic metrics. The model was designed to only use a few inputs parameters from echocardiography, computed tomography and a sphygmomanometer. The novel computational model was then validated and applied to 19 patients undergoing TAVR to examine the impact of the procedure on coronary blood flow in the left anterior descending (LAD) artery, left circumflex (LCX) artery and right coronary artery (RCA) and various global hemodynamics metrics. Based on our findings, the changes in coronary blood flow after TAVR varied and were subject specific (37% had increased flow in all three coronary arteries, 32% had decreased flow in all coronary arteries, and 31% had both increased and decreased flow in different coronary arteries). Additionally, valvular pressure gradient, left ventricle (LV) workload and maximum LV pressure decreased by 61.5%, 4.5% and 13.0% respectively, while mean arterial pressure and cardiac output increased by 6.9% and 9.9% after TAVR. By applying this proof-of-concept computational model, a series of hemodynamic metrics were generated non-invasively which can help to better understand the individual relationships between TAVR and mean and peak coronary flow rates. In the future, tools such as these may play a vital role by providing clinicians with rapid insight into various cardiac and coronary metrics, rendering the planning for TAVR and other cardiovascular procedures more personalized.

A Doppler-exclusive non-invasive computational diagnostic framework for personalized transcatheter aortic valve replacement.

Given the associated risks with transcatheter aortic valve replacement (TAVR), it is crucial to determine how the implant will affect the valve dynamics and cardiac function, and if TAVR will improve or worsen the outcome of the patient. Effective treatment strategies, indeed, rely heavily on the complete understanding of the valve dynamics. We developed an innovative Doppler-exclusive non-invasive computational framework that can function as a diagnostic tool to assess valve dynamics in patients with aortic stenosis in both pre- and post-TAVR status. Clinical Doppler pressure was reduced by TAVR (52.2 ± 20.4 vs. 17.3 ± 13.8 [mmHg], p < 0.001), but it was not always accompanied by improvements in valve dynamics and left ventricle (LV) hemodynamics metrics. TAVR had no effect on LV workload in 4 patients, and LV workload post-TAVR significantly rose in 4 other patients. Despite the group level improvements in maximum LV pressure (166.4 ± 32.2 vs 131.4 ± 16.9 [mmHg], p < 0.05), only 5 of the 12 patients (41%) had a decrease in LV pressure. Moreover, TAVR did not always improve valve dynamics. TAVR did not necessarily result in a decrease (in 9 out of 12 patients investigated in this study) in major principal stress on the aortic valve leaflets which is one of the main contributors in valve degeneration and, consequently, failure of heart valves. Diastolic stresses increased significantly post-TAVR (34%, 109% and 81%, p < 0.001) for each left, right and non-coronary leaflets respectively. Moreover, we quantified the stiffness and material properties of aortic valve leaflets which correspond with the reduced calcified region average stiffness among leaflets (66%, 74% and 62%; p < 0.001; N = 12). Valve dynamics post-intervention should be quantified and monitored to ensure the improvement of patient conditions and prevent any further complications. Improper evaluation of biomechanical valve features pre-intervention as well as post-intervention may result in harmful effects post-TAVR in patients including paravalvular leaks, valve degeneration, failure of TAVR and heart failure.

Inaccuracies of deterministic finite-element models of human middle ear revealed by stochastic modelling.

For over 40 years, finite-element models of the mechanics of the middle ear have been mostly deterministic in nature. Deterministic models do not take into account the effects of inter-individual variabilities on middle-ear parameters. We present a stochastic finite-element model of the human middle ear that uses variability in the model parameters to investigate the uncertainty in the model outputs (umbo, stapes, and tympanic-membrane displacements). We demonstrate: (1) uncertainties in the model parameters can be magnified by more than three times in the umbo and stapes footplate responses at frequencies above 2 kHz; (2) middle-ear models are biased and they distort the output distributions; and (3) with increased frequency, the highly-uncertain regions spatially spread out on the tympanic membrane surface. Our results assert that we should be mindful when using deterministic finite-element middle-ear models for critical tasks such as novel device developments and diagnosis.

Reducing Long-Term Mortality Post Transcatheter Aortic Valve Replacement Requires Systemic Differentiation of Patient-Specific Coronary Hemodynamics.

Background Despite the proven benefits of transcatheter aortic valve replacement (TAVR) and its recent expansion toward the whole risk spectrum, coronary artery disease is present in more than half of the candidates for TAVR. Many previous studies do not focus on the longer-term impact of TAVR on coronary arteries, and hemodynamic changes to the circulatory system in response to the anatomical changes caused by TAVR are not fully understood. Methods and Results We developed a multiscale patient-specific computational framework to examine the effect of TAVR on coronary and cardiac hemodynamics noninvasively. Based on our findings, TAVR might have an adverse impact on coronary hemodynamics due to the lack of sufficient coronary blood flow during diastole phase (eg, maximum coronary flow rate reduced by 8.98%, 16.83%, and 22.73% in the left anterior descending, left circumflex coronary artery, and right coronary artery, respectively [N=31]). Moreover, TAVR may increase the left ventricle workload (eg, left ventricle workload increased by 2.52% [N=31]) and decrease the coronary wall shear stress (eg, maximum time averaged wall shear stress reduced by 9.47%, 7.75%, 6.94%, 8.07%, and 6.28% for bifurcation, left main coronary artery, left anterior descending, left circumflex coronary artery, and right coronary artery branches, respectively). Conclusions The transvalvular pressure gradient relief after TAVR might not result in coronary flow improvement and reduced cardiac load. Optimal revascularization strategy pre-TAVR and progression of coronary artery disease after TAVR could be determined by noninvasive personalized computational modeling.

Fracture behaviour of human skin in deep needle insertion can be captured using validated cohesive zone finite-element method.

Medical needles have shown an appreciable contribution to the development of novel medical devices and surgical technologies. A better understanding of needle-skin interactions can advance the design of medical needles, modern surgical robots, and haptic devices. This study employed finite element (FE) modelling to explore the effect of different mechanical and geometrical parameters on the needle's force-displacement relationship, the required force for the skin puncture, and generated mechanical stress around the cutting zone. To this end, we established a cohesive FE model, and identified its parameters by a three-stage parameter identification algorithm to closely replicate the experimental data of needle insertion into the human skin available in the literature. We showed that a bilinear cohesive model with initial stiffness of 5000 MPa/mm, failure traction of 2 MPa, and separation length of 1.6 mm can lead to a model that can closely replicate experimental results. The FE results indicated that while the coefficient of friction between the needle and skin substantially changes the needle reaction force, the insertion velocity does not have a noticeable effect on the reaction force. Regarding the geometrical parameters, needle cutting angle is the prominent factor in terms of stress fields generated in the skin tissue. However, the needle diameter is more influential on the needle reaction force. We also presented an energy study on the frictional dissipation, damage dissipation, and strain energy throughout the insertion process.

A systematic approach for developing mechanistic models for realistic simulation of cancer cell motion and deformation.

Understanding and predicting metastatic progression and developing novel diagnostic methods can highly benefit from accurate models of the deformability of cancer cells. Spring-based network models of cells can provide a versatile way of integrating deforming cancer cells with other physical and biochemical phenomena, but these models have parameters that need to be accurately identified. In this study we established a systematic method for identifying parameters of spring-network models of cancer cells. We developed a genetic algorithm and coupled it to the fluid-solid interaction model of the cell, immersed in blood plasma or other fluids, to minimize the difference between numerical and experimental data of cell motion and deformation. We used the method to create a validated model for the human lung cancer cell line (H1975), employing existing experimental data of its deformation in a narrow microchannel constriction considering cell-wall friction. Furthermore, using this validated model with accurately identified parameters, we studied the details of motion and deformation of the cancer cell in the microchannel constriction and the effects of flow rates on them. We found that ignoring the viscosity of the cell membrane and the friction between the cell and wall can introduce remarkable errors.

Material characterization of thin planar structures using full-field harmonic vibration response measured with stroboscopic holography.

We propose a novel material characterization method to estimate the Young's modulus of thin 2-D structures using non-modal noisy single frequency harmonic vibration data measured with holography. The method uses finite-difference discretization to apply the plate equation to all measured pixels inside the boundary of the vibrating structure and then treats the problem as a Bayesian optimization process to find the value of the Young's modulus by minimizing the Euclidian distance between the measured displacement field and repeatedly calculated displacement field using the plate equation. In order to assess the accuracy of the method, ground truth harmonic displacement magnitude fields of different plates were obtained using analytical solutions and the finite-element method and were used to estimate the Young's moduli. We applied Gaussian and non-Gaussian noise with different intensities to assess the robustness and accuracy of the proposed material characterization method in the presence of noise. We demonstrated that for multiple benchmarks for signal to noise ratio of down to 0 dB, our proposed method had errors of less than 5%. We also quantified the effects of uncertainties in the geometrical and material parameters as well as boundary conditions on the estimated Young's modulus. Furthermore, we studied the effects of the mesh size on the runtime and applied the method to experimental holography vibration measurement data of a copper plate.

Interactions of platelets with circulating tumor cells contribute to cancer metastasis.

Recent studies have suggested that platelets have a crucial role in enhancing the survival of circulating tumor cells in the bloodstream and aggravating cancer metastasis. The main function of platelets is to bind to the sites of the damaged vessels to stop bleeding. However, in cancer patients, activated platelets adhere to circulating tumor cells and exacerbate metastatic spreading. Several hypotheses have been proposed about the platelet-cancer cell interactions, but the underlying mechanisms of these interactions are not completely understood yet. In this work, we quantitatively investigated the interactions between circulating tumor cells, red blood cells, platelets, plasma flow and microvessel walls via computational modelling at the cellular scale. Our highly detailed computational model allowed us to understand and quantitatively explain the role of platelets in deformation, adhesion and survival of tumor cells in their active arrest to the endothelium.

Tympanic membrane surface motions in forward and reverse middle ear transmissions.

Characterization of Tympanic Membrane (TM) surface motions with forward and reverse stimulation is important to understanding how the TM transduces acoustical and mechanical energy in both directions. In this paper, stroboscopic opto-electronic holography is used to quantify motions of the entire TM surface induced by forward sound and reverse mechanical stimulation in human cadaveric ears from 0.25 to 18.4 kHz. The forward sound stimulus was coupled to an anatomically realistic artificial ear canal that allowed optical access to the entire TM surface, and the reverse mechanical stimulus was applied to the body of the incus by a piezo-electric stimulator. The results show clear differences in TM surface motions evoked by the two stimuli. In the forward case, TM motion is dominated by standing-wave-like modal motions that are consistent with a relatively uniform sound-pressure load over the entire TM surface. With reverse mechanical stimulation, the TM surface shows more traveling waves, consistent with a localized mechanical drive applied to the manubrium embedded in the TM. With both stimuli, the manubrium moves less than the rest of the TM, consistent with the TM acting like a compliant membrane rather than a stiff diaphragm, and also consistent with catenary behavior due to the TM's curved shape.

High-Speed Holographic Shape and Full-Field Displacement Measurements of the Tympanic Membrane in Normal and Experimentally Simulated Pathological Ears.

To improve the understanding of the middle-ear hearing mechanism and assist in the diagnosis of middle-ear diseases, we are developing a high-speed digital holographic (HDH) system to measure the shape and acoustically-induced transient displacements of the tympanic membrane (TM). In this paper, we performed measurements on cadaveric human ears with simulated common middle-ear pathologies. The frequency response function (FRF) of the normalized displacement by the stimulus (sound pressure) at each measured pixel point of the entire TM surface was calculated and the complex modal indicator function (CMIF) of the middle-ear system based on FRFs of the entire TM surface motions was used to differentiate different middle-ear pathologies. We also observed changes in the TM shape and the surface motion pattern before and after various middle-ear manipulations. The observations of distinguishable TM shapes and motion patterns in both time and frequency domains between normal and experimentally simulated pathological ears support the development of a quantitative clinical holography-based apparatus for diagnosing middle-ear pathologies.

Fluid-Structure Finite-Element Modelling and Clinical Measurement of the Wideband Acoustic Input Admittance of the Newborn Ear Canal and Middle Ear.

The anatomical differences between the newborn ear and the adult one result in different input admittance responses in newborns than those in adults. Taking into account fluid-structure interactions, we have developed a finite-element model to investigate the wideband admittance responses of the ear canal and middle ear in newborns for frequencies up to 10 kHz. We have also performed admittance measurements on a group of 23 infants with ages between 14 and 28 days, for frequencies from 250 to 8000 Hz with 1/12-octave resolution. Sensitivity analyses of the model were performed to investigate the contributions of the ear canal and middle ear to the overall admittance responses, as well as the effects of the material parameters, measurement location and geometrical variability. The model was validated by comparison with our new data and with data from the literature. The model provides a quantitative understanding of the canal and middle-ear resonances around 500 and 1800 Hz, respectively, and also predicts the effects of the first resonance mode of the middle-ear cavity (around 6 kHz) as well as the first and second standing-wave modes in the ear canal (around 7.2 and 9.6 kHz, respectively), which may explain features seen in our high-frequency-resolution clinical measurements.

Finite-Element Modelling of the Acoustic Input Admittance of the Newborn Ear Canal and Middle Ear.

Admittance measurement is a promising tool for evaluating the status of the middle ear in newborns. However, the newborn ear is anatomically very different from the adult one, and the acoustic input admittance is different than in adults. To aid in understanding the differences, a finite-element model of the newborn ear canal and middle ear was developed and its behaviour was studied for frequencies up to 2000 Hz. Material properties were taken from previous measurements and estimates. The simulation results were within the range of clinical admittance measurements made in newborns. Sensitivity analyses of the material properties show that in the canal model, the maximum admittance and the frequency at which that maximum admittance occurs are affected mainly by the stiffness parameter; in the middle-ear model, the damping is as important as the stiffness in influencing the maximum admittance magnitude but its effect on the corresponding frequency is negligible. Scaling up the geometries increases the admittance magnitude and shifts the resonances to lower frequencies. The results suggest that admittance measurements can provide more information about the condition of the middle ear when made at multiple frequencies around its resonance.