BACKGROUND: Percutaneous microwave ablation is a clinically established method for treatment of unresectable lung nodules. When planning the intervention, the size of ablation zone, which should encompass the nodule as well as a surrounding margin of normal tissue, is predicted via manufacturer-provided geometric models, which do not consider patient-specific characteristics. However, the size and shape of ablation is dependent on tissue composition and properties and can vary between patients. PURPOSE: To comparatively assess performance of a computational model-based approach and manufacturer geometric model for predicting extent of ablation zones following microwave lung ablation procedures on a retrospectively collected clinical imaging dataset. METHODS: A retrospective computed-tomography (CT) imaging dataset was assembled of 50 patients treated with microwave ablation of lung tumors at a single institution. For each case, the dataset consisted of a pre-procedure CT acquired without the ablation applicator, a peri-procedure CT scan with the ablation applicator in position, and post-procedure CT scan to assess the ablation zone extent acquired on the first follow-up visit. A physics-based computational model of microwave absorption and bioheat transfer was implemented using the finite element method, with the model geometry incorporating key tissue types within 2 cm of the applicator as informed by imaging data. The model-predicted extent of the ablation zone was estimated using the Arrhenius thermal damage model. The ablation zone predicted by the manufacturer geometric model consisted of an ellipsoid registered with the applicator position and dimensions provided by instructions for use documentation. Both ablation estimates were compared to ground truth ablation zone segmented from post-procedure CT via Dice similarity coefficient (DSC) and average absolute error (AAE). The statistically significant difference at level 0.05 in performance between both ablation prediction methods was tested with permutation test on DSC as well as AAE datasets with applied Bonferroni multiple-comparison correction. RESULTS: Receiver operating characteristic analysis of the predictive power of the volume of insufficient coverage (i.e. tumor volume which did not receive an ablative thermal dose) as an indicator of local tumor recurrence yielded an area under the curve of 0.84, illustrating the clinical significance of accurate prediction of ablation zone extents. Across all cases, AAEs were 3.65 ± 1.12 mm, and 5.11 ± 1.93 mm for patient-specific computational and manufacturer geometric models respectively. Similarly, average DSCs were 0.55 ± 0.14, and 0.46 ± 0.19 for computational and manufacturer geometric models respectively. The manufacturer geometric model overpredicted volume of the ablation zone compared to ground truth by 141% on average, whereas the patient-specific computational model overpredicted ablation zone volumes by 31.5% on average. CONCLUSIONS: Patient-specific physics-based computational models of lung microwave ablation yield improved prediction of microwave ablation extent compared to the manufacturer geometric model.
- Keywords
- image‐based modeling, lung ablation, microwave ablation, treatment planning,
- MeSH
- Ablation Techniques * methods MeSH
- Models, Biological * MeSH
- Humans MeSH
- Microwaves * therapeutic use MeSH
- Lung Neoplasms * diagnostic imaging surgery therapy MeSH
- Tomography, X-Ray Computed MeSH
- Computer Simulation * MeSH
- Retrospective Studies MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Current advances in epilepsy treatment aim to personalize and responsively adjust treatment parameters to overcome patient heterogeneity in treatment efficiency. For tailoring treatment to the individual and the current brain state, tools are required that help to identify the patient- and time-point-specific parameters of epilepsy. Computational modeling has long proven its utility in gaining mechanistic insight. Recently, the technique has been introduced as a diagnostic tool to predict individual treatment outcomes. In this article, the Wendling model, an established computational model of epilepsy dynamics, is used to automatically classify epileptic brain states in intracranial EEG from patients (n = 4) and local field potential recordings from in vitro rat data (high-potassium model of epilepsy, n = 3). Five-second signal segments are classified to four types of brain state in epilepsy (interictal, preonset, onset, ictal) by comparing a vector of signal features for each data segment to four prototypical feature vectors obtained by Wendling model simulations. The classification result is validated against expert visual assessment. Model-driven brain state classification achieved a classification performance significantly above chance level (mean sensitivity 0.99 on model data, 0.77 on rat data, 0.56 on human data in a four-way classification task). Model-driven prototypes showed similarity with data-driven prototypes, which we obtained from real data for rats and humans. Our results indicate similar electrophysiological patterns of epileptic states in the human brain and the animal model that are well-reproduced by the computational model, and captured by a key set of signal features, enabling fully automated and unsupervised brain state classification in epilepsy.
- MeSH
- Electrocorticography MeSH
- Epilepsy * MeSH
- Rats MeSH
- Humans MeSH
- Brain * MeSH
- Computer Simulation MeSH
- Cardiac Electrophysiology MeSH
- Animals MeSH
- Check Tag
- Rats MeSH
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Purpose Phonations into a tube with the distal end either in the air or submerged in water are used for voice therapy. This study explores the effective mechanisms of these therapy methods. Method The study applied a physical model complemented by calculations from a computational model, and the results were compared to those that have been reported for humans. The effects of tube phonation on vocal tract resonances and oral pressure variation were studied. The relationships of transglottic pressure variation in time Ptrans ( t) versus glottal area variation in time GA( t) were constructed. Results The physical model revealed that, for the phonation on [u:] vowel through a glass resonance tube ending in the air, the 1st formant frequency ( F1 ) decreased by 67%, from 315 Hz to 105 Hz, thus slightly above the fundamental frequency ( F0 ) that was set to 90-94 Hz . For phonation through the tube into water, F1 decreased by 91%-92%, reaching 26-28 Hz, and the water bubbling frequency Fb ≅ 19-24 Hz was just below F1 . The relationships of Ptrans ( t) versus GA( t) clearly differentiate vowel phonation from both therapy methods, and show a physical background for voice therapy with tubes. It is shown that comparable results have been measured in humans during tube therapy. For the tube in air, F1 descends closer to F0 , whereas for the tube in water, the frequency Fb occurs close to the acoustic-mechanical resonance of the human vocal tract. Conclusion In both therapy methods, part of the airflow energy required for phonation is substituted by the acoustic energy utilizing the 1st acoustic resonance. Thus, less flow energy is needed for vocal fold vibration, which results in improved vocal efficiency. The effect can be stronger in water resistance therapy if the frequency Fb approaches the acoustic-mechanical resonance of the vocal tract, while simultaneously F0 is voluntarily changed close to F1.
- MeSH
- Speech Acoustics MeSH
- Models, Anatomic MeSH
- Phonation physiology MeSH
- Glottis MeSH
- Voice Training MeSH
- Humans MeSH
- Lung physiology MeSH
- Computer Simulation MeSH
- Speech Therapy methods MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The anthropogenic toxic compound 1,2,3-trichloropropane is poorly degradable by natural enzymes. We have previously constructed the haloalkane dehalogenase DhaA31 by focused directed evolution ( Pavlova, M. et al. Nat. Chem. Biol. 2009 , 5 , 727 - 733 ), which is 32 times more active than the wild-type enzyme and is currently the most active variant known against that substrate. Recent evidence has shown that the structural basis responsible for the higher activity of DhaA31 was poorly understood. Here we have undertaken a comprehensive computational study of the main steps involved in the biocatalytic hydrolysis of 1,2,3-trichloropropane to decipher the structural basis for such enhancements. Using molecular dynamics and quantum mechanics approaches we have surveyed (i) the substrate binding, (ii) the formation of the reactive complex, (iii) the chemical step, and (iv) the release of the products. We showed that the binding of the substrate and its transport through the molecular tunnel to the active site is a relatively fast process. The cleavage of the carbon-halogen bond was previously identified as the rate-limiting step in the wild-type. Here we demonstrate that this step was enhanced in DhaA31 due to a significantly higher number of reactive configurations of the substrate and a decrease of the energy barrier to the SN2 reaction. C176Y and V245F were identified as the key mutations responsible for most of those improvements. The release of the alcohol product was found to be the rate-limiting step in DhaA31 primarily due to the C176Y mutation. Mutational dissection of DhaA31 and kinetic analysis of the intermediate mutants confirmed the theoretical observations. Overall, our comprehensive computational approach has unveiled mechanistic details of the catalytic cycle which will enable a balanced design of more efficient enzymes. This approach is applicable to deepen the biochemical knowledge of a large number of other systems and may contribute to robust strategies in the development of new biocatalysts.
- MeSH
- Biocatalysis * MeSH
- Hydrolases chemistry genetics metabolism MeSH
- Catalytic Domain MeSH
- Kinetics MeSH
- Mutation MeSH
- Computer Simulation * MeSH
- Rhodococcus enzymology MeSH
- Molecular Dynamics Simulation MeSH
- Molecular Docking Simulation MeSH
- Thermodynamics MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- haloalkane dehalogenase MeSH Browser
- Hydrolases MeSH
In biology and life sciences, fractal theory and fractional calculus have significant applications in simulating and understanding complex problems. In this paper, a compartmental model employing Caputo-type fractional and fractal-fractional operators is presented to analyze Nipah virus (NiV) dynamics and transmission. Initially, the model includes nine nonlinear ordinary differential equations that consider viral concentration, flying fox, and human populations simultaneously. The model is reconstructed using fractional calculus and fractal theory to better understand NiV transmission dynamics. We analyze the model's existence and uniqueness in both contexts and instigate the equilibrium points. The clinical epidemiology of Bangladesh is used to estimate model parameters. The fractional model's stability is examined using Ulam-Hyers and Ulam-Hyers-Rassias stabilities. Moreover, interpolation methods are used to construct computational techniques to simulate the NiV model in fractional and fractal-fractional cases. Simulations are performed to validate the stable behavior of the model for different fractal and fractional orders. The present findings will be beneficial in employing advanced computational approaches in modeling and control of NiV outbreaks.
- MeSH
- Models, Biological MeSH
- Henipavirus Infections * epidemiology prevention & control transmission MeSH
- Humans MeSH
- Computer Simulation MeSH
- Vaccination * MeSH
- Nipah Virus * immunology MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Bangladesh epidemiology MeSH
Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.
- Keywords
- ionizable lipid, lipid nanocarrier, lipid nanoparticle, liposome, molecular simulation, vesicle,
- MeSH
- Pharmaceutical Preparations chemistry administration & dosage MeSH
- Drug Delivery Systems * methods MeSH
- Humans MeSH
- Lipids * chemistry MeSH
- Nanoparticles chemistry MeSH
- Drug Carriers * chemistry MeSH
- Computer Simulation MeSH
- Molecular Dynamics Simulation MeSH
- Machine Learning MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
- Names of Substances
- Pharmaceutical Preparations MeSH
- Lipids * MeSH
- Drug Carriers * MeSH
This paper presents a comparative analysis of deterministic and stochastic computational modeling approaches for the optimal control of COVID-19. We formulate a compartmental epidemic model with perturbation by white noise that incorporates various factors influencing disease transmission. By incorporating stochastic effects, the model accounts for uncertainties inherent in real-world epidemic data. We establish the mathematical properties of the model, such as well-posedness and the existence of stationary distributions, which are crucial for understanding long-term epidemic dynamics. Moreover, the study presents an optimal control strategies to mitigate the epidemic's impact, both in deterministic and stochastic sceneries. Reported data from Algeria are used to parameterize the model, ensuring its relevance and applicability to practical satiation. Through numerical simulations, the study provides insights into the effectiveness of different control measures in managing COVID-19 outbreaks. This research contributes to advancing our understanding of epidemic dynamics and informs decision-making processes for epidemic controlling interventions.
- Keywords
- COVID-19 stochastic modeling, Extinction, Simulation, Stationary distribution, Stochastic optimized control,
- MeSH
- COVID-19 * epidemiology prevention & control transmission MeSH
- Humans MeSH
- Computer Simulation MeSH
- SARS-CoV-2 MeSH
- Stochastic Processes MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Comparative Study MeSH
This study investigates the influence of varying degrees of stenosis on blood flow within elliptic arteries, emphasizing the critical role of artery shape in clinical evaluations as opposed to the commonly studied circular arteries. Unlike prior work, this research offers a precise definition of stenosis by incorporating the measured length, height, and position of the narrowing. Employing the non-Newtonian Williamson fluid model, we conducted comprehensive numerical simulations to examine blood flow through four distinct stenosis formations. The novelty of this work lies in its accurate modeling of stenosis and use of advanced mesh generation, combined with commercial software and the finite volume method, to capture detailed hemodynamic behavior. Visualized results, including pressure profiles, velocity line graphs, and streamlines, further underscore the distinctive flow dynamics shaped by the elliptic geometry. Key findings of the obtained results reveal that blood velocity peaks near the stenosis and drops significantly post-stenosis, with notable variations in flow patterns, energy loss, and pressure distribution across different stenosis types. Further, higher velocity of blood flow is observed in elliptic arteries in comparison with circular ones. In the area of the high corners of stenotic segments, the pressure profile reaches high values. As a result of the narrowing of the arterial cross-section, the varied time shows that the post-stenotic segment of the artery has a higher pressure than the pre-stenotic section. The varied time suggests that an axially symmetric profile will eventually be the norm for the flow within the arterial portion. These insights have profound implications for improving clinical diagnosis and treatment strategies for conditions related to stenosed elliptic arteries.
A simple approach to the multiscale analysis of a plain weave reinforced composite made of basalt fabrics bonded to a high performance epoxy resin L285 Havel is presented. This requires a thorough experimental program to be performed at the level of individual constituents as well as formulation of an efficient and reliable computational scheme. The rate-dependent behavior of the polymer matrix is examined first providing sufficient data needed in the calibration step of the generalized Leonov model, which in turn is adopted in numerical simulations. Missing elastic properties of basalt fibers are derived next using nanoindentation. A series of numerical tests is carried out at the level of yarns to promote the ability of a suitably modified Mori-Tanaka micromechanical model to accurately describe the nonlinear viscoelastic response of unidirectional fibrous composites. The efficiency of the Mori-Tanaka method is then exploited in the formulation of a coupled two scale computational scheme, while at the level of textile ply the finite element computational homogenization is assumed, the two-point averaging format of the Mori-Tanaka method is applied at the level of yarn to serve as a stress updater in place of another finite element model representing the yarn microstructure as typical of FE2 based multiscale approach. Several numerical simulations are presented to support the proposed modeling methodology.
- Keywords
- Leonov model, Mori–Tanaka method, basalt fibers, multiscale computational homogenization, polymer matrix, woven composite,
- Publication type
- Journal Article MeSH
In recent years, alcohol addiction has become a major public health concern and a global threat due to its potential negative health and social impacts. Beyond the health consequences, the detrimental consumption of alcohol results in substantial social and economic burdens on both individuals and society as a whole. Therefore, a proper understanding and effective control of the spread of alcohol addictive behavior has become an appealing global issue to be solved. In this study, we develop a new mathematical model of alcohol addiction with treatment class. We analyze the dynamics of the alcohol addiction model for the first time using advanced operators known as fractal-fractional operators, which incorporate two distinct fractal and fractional orders with the well-known Caputo derivative based on power law kernels. The existence and uniqueness of the newly developed fractal-fractional alcohol addiction model are shown using the Picard-Lindelöf and fixed point theories. Initially, a comprehensive qualitative analysis of the alcohol addiction fractional model is presented. The possible equilibria of the model and the threshold parameter called the reproduction number are evaluated theoretically and numerically. The boundedness and biologically feasible region for the model are derived. To assess the stability of the proposed model, the Ulam-Hyers coupled with the Ulam-Hyers-Rassias stability criteria are employed. Moreover, utilizing effecting numerical schemes, the models are solved numerically and a detailed simulation and discussion are presented. The model global dynamics are shown graphically for various values of fractional and fractal dimensions. The present study aims to provide valuable insights for the understanding the dynamics and control of alcohol addiction within a community.
- Keywords
- Alcohol addiction model, Existence and uniqueness, Fractal–fractional Caputo operator, Simulation, Ulam–Hyers stability,
- MeSH
- Alcoholism * MeSH
- Ethanol MeSH
- Fractals MeSH
- Humans MeSH
- Behavior, Addictive * MeSH
- Computer Simulation MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Ethanol MeSH
