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Neurosurgical endoscopic training via a realistic 3-dimensional model with pathology

Waran V, Narayanan V, Karuppiah R, Thambynayagam HC, Muthusamy KA, Rahman ZA, et al.

Simul Healthc, 2015 Feb;10(1):43-8.
PMID: 25514588 DOI: 10.1097/SIH.0000000000000060

Training in intraventricular endoscopy is particularly challenging because the volume of cases is relatively small and the techniques involved are unlike those usually used in conventional neurosurgery. Present training models are inadequate for various reasons. Using 3-dimensional (3D) printing techniques, models with pathology can be created using actual patient's imaging data. This technical article introduces a new training model based on a patient with hydrocephalus secondary to a pineal tumour, enabling the models to be used to simulate third ventriculostomies and pineal biopsies.

Matched MeSH terms: Models, Biological*
Fulltext Optimization of aeration and agitation rate for lipid and gamma linolenic acid production by Cunninghamella bainieri 2A1 in submerged fermentation using response surface methodology

Saad N, Abdeshahian P, Kalil MS, Yusoff WM, Hamid AA

ScientificWorldJournal, 2014;2014:280146.
PMID: 25610901 DOI: 10.1155/2014/280146

The locally isolated filamentous fungus Cunninghamella bainieri 2A1 was cultivated in a 5 L bioreactor to produce lipid and gamma-linolenic acid (GLA). The optimization was carried out using response surface methodology based on a central composite design. A statistical model, second-order polynomial model, was adjusted to the experimental data to evaluate the effect of key operating variables, including aeration rate and agitation speed on lipid production. Process analysis showed that linear and quadratic effect of agitation intensity significantly influenced lipid production process (P < 0.01). The quadratic model also indicated that the interaction between aeration rate and agitation speed had a highly significant effect on lipid production (P < 0.01). Experimental results showed that a lipid content of 38.71% was produced in optimum conditions using an airflow rate and agitation speed of 0.32 vvm and 599 rpm, respectively. Similar results revealed that 0.058(g/g) gamma-linolenic acid was produced in optimum conditions where 1.0 vvm aeration rate and 441.45 rpm agitation rate were used. The regression model confirmed that aeration and agitation were of prime importance for optimum production of lipid in the bioreactor.

Matched MeSH terms: Models, Biological*
Fulltext Transmission and control of Plasmodium knowlesi: a mathematical modelling study

Imai N, White MT, Ghani AC, Drakeley CJ

PLoS Negl Trop Dis, 2014 Jul;8(7):e2978.
PMID: 25058400 DOI: 10.1371/journal.pntd.0002978

INTRODUCTION: Plasmodium knowlesi is now recognised as a leading cause of malaria in Malaysia. As humans come into increasing contact with the reservoir host (long-tailed macaques) as a consequence of deforestation, assessing the potential for a shift from zoonotic to sustained P. knowlesi transmission between humans is critical.
METHODS: A multi-host, multi-site transmission model was developed, taking into account the three areas (forest, farm, and village) where transmission is thought to occur. Latin hypercube sampling of model parameters was used to identify parameter sets consistent with possible prevalence in macaques and humans inferred from observed data. We then explore the consequences of increasing human-macaque contact in the farm, the likely impact of rapid treatment, and the use of long-lasting insecticide-treated nets (LLINs) in preventing wider spread of this emerging infection.
RESULTS: Identified model parameters were consistent with transmission being sustained by the macaques with spill over infections into the human population and with high overall basic reproduction numbers (up to 2267). The extent to which macaques forage in the farms had a non-linear relationship with human infection prevalence, the highest prevalence occurring when macaques forage in the farms but return frequently to the forest where they experience higher contact with vectors and hence sustain transmission. Only one of 1,046 parameter sets was consistent with sustained human-to-human transmission in the absence of macaques, although with a low human reproduction number (R(0H) = 1.04). Simulations showed LLINs and rapid treatment provide personal protection to humans with maximal estimated reductions in human prevalence of 42% and 95%, respectively.
CONCLUSION: This model simulates conditions where P. knowlesi transmission may occur and the potential impact of control measures. Predictions suggest that conventional control measures are sufficient at reducing the risk of infection in humans, but they must be actively implemented if P. knowlesi is to be controlled.

Matched MeSH terms: Models, Biological*
Modeling of growth and laccase production by Pycnoporus sanguineus

Saat MN, Annuar MS, Alias Z, Chuan LT, Chisti Y

Bioprocess Biosyst Eng, 2014 May;37(5):765-75.
PMID: 24005762 DOI: 10.1007/s00449-013-1046-8

Production of extracellular laccase by the white-rot fungus Pycnoporus sanguineus was examined in batch submerged cultures in shake flasks, baffled shake flasks and a stirred tank bioreactor. The biomass growth in the various culture systems closely followed a logistic growth model. The production of laccase followed a Luedeking-Piret model. A modified Luedeking-Piret model incorporating logistic growth effectively described the consumption of glucose. Biomass productivity, enzyme productivity and substrate consumption were enhanced in baffled shake flasks relative to the cases for the conventional shake flasks. This was associated with improved oxygen transfer in the presence of the baffles. The best results were obtained in the stirred tank bioreactor. At 28 °C, pH 4.5, an agitation speed of 600 rpm and a dissolved oxygen concentration of ~25 % of air saturation, the laccase productivity in the bioreactor exceeded 19 U L(-1 )days(-1), or 1.5-fold better than the best case for the baffled shake flask. The final concentration of the enzyme was about 325 U L(-1).

Matched MeSH terms: Models, Biological*
Automatic generation of controllers for embodied legged organisms: a Pareto evolutionary multi-objective approach

Teo J, Abbass HA

Evol Comput, 2004;12(3):355-94.
PMID: 15355605

In this paper, we investigate the use of a self-adaptive Pareto evolutionary multi-objective optimization (EMO) approach for evolving the controllers of virtual embodied organisms. The objective of this paper is to demonstrate the trade-off between quality of solutions and computational cost. We show empirically that evolving controllers using the proposed algorithm incurs significantly less computational cost when compared to a self-adaptive weighted sum EMO algorithm, a self-adaptive single-objective evolutionary algorithm (EA) and a hand-tuned Pareto EMO algorithm. The main contribution of the self-adaptive Pareto EMO approach is its ability to produce sufficiently good controllers with different locomotion capabilities in a single run, thereby reducing the evolutionary computational cost and allowing the designer to explore the space of good solutions simultaneously. Our results also show that self-adaptation was found to be highly beneficial in reducing redundancy when compared against the other algorithms. Moreover, it was also shown that genetic diversity was being maintained naturally by virtue of the system's inherent multi-objectivity.

Matched MeSH terms: Models, Biological*
Fulltext A Biogeography-Based Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem

Lim WL, Wibowo A, Desa MI, Haron H

Comput Intell Neurosci, 2016;2016:5803893.
PMID: 26819585 DOI: 10.1155/2016/5803893

The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.

Matched MeSH terms: Models, Biological*
Fulltext A newton cooperative genetic algorithm method for in silico optimization of metabolic pathway production

Ismail MA, Deris S, Mohamad MS, Abdullah A

PLoS One, 2015;10(5):e0126199.
PMID: 25961295 DOI: 10.1371/journal.pone.0126199

This paper presents an in silico optimization method of metabolic pathway production. The metabolic pathway can be represented by a mathematical model known as the generalized mass action model, which leads to a complex nonlinear equations system. The optimization process becomes difficult when steady state and the constraints of the components in the metabolic pathway are involved. To deal with this situation, this paper presents an in silico optimization method, namely the Newton Cooperative Genetic Algorithm (NCGA). The NCGA used Newton method in dealing with the metabolic pathway, and then integrated genetic algorithm and cooperative co-evolutionary algorithm. The proposed method was experimentally applied on the benchmark metabolic pathways, and the results showed that the NCGA achieved better results compared to the existing methods.

Matched MeSH terms: Models, Biological*
Fulltext Modelling the longevity of dental restorations by means of a CBR system

Aliaga IJ, Vera V, De Paz JF, García AE, Mohamad MS

Biomed Res Int, 2015;2015:540306.
PMID: 25866792 DOI: 10.1155/2015/540306

The lifespan of dental restorations is limited. Longevity depends on the material used and the different characteristics of the dental piece. However, it is not always the case that the best and longest lasting material is used since patients may prefer different treatments according to how noticeable the material is. Over the last 100 years, the most commonly used material has been silver amalgam, which, while very durable, is somewhat aesthetically displeasing. Our study is based on the collection of data from the charts, notes, and radiographic information of restorative treatments performed by Dr. Vera in 1993, the analysis of the information by computer artificial intelligence to determine the most appropriate restoration, and the monitoring of the evolution of the dental restoration. The data will be treated confidentially according to the Organic Law 15/1999 on 13 December on the Protection of Personal Data. This paper also presents a clustering technique capable of identifying the most significant cases with which to instantiate the case-base. In order to classify the cases, a mixture of experts is used which incorporates a Bayesian network and a multilayer perceptron; the combination of both classifiers is performed with a neural network.

Matched MeSH terms: Models, Biological*
D-Galactose-induced accelerated aging model: an overview

Azman KF, Zakaria R

Biogerontology, 2019 12;20(6):763-782.
PMID: 31538262 DOI: 10.1007/s10522-019-09837-y

To facilitate the process of aging healthily and prevent age-related health problems, efforts to properly understand aging mechanisms and develop effective and affordable anti-aging interventions are deemed necessary. Systemic administration of D-galactose has been established to artificially induce senescence in vitro and in vivo as well as for anti-aging therapeutic interventions studies. The aim of this article is to comprehensively discuss the use of D-galactose to generate a model of accelerated aging and its possible underlying mechanisms involved in different tissues/organs.

Matched MeSH terms: Models, Biological*
Defining and measuring trophic role similarity in food webs using regular equivalence

Luczkovich JJ, Borgatti SP, Johnson JC, Everett MG

J Theor Biol, 2003 Feb 07;220(3):303-21.
PMID: 12468282

We present a graph theoretic model of analysing food web structure called regular equivalence. Regular equivalence is a method for partitioning the species in a food web into "isotrophic classes" that play the same structural roles, even if they are not directly consuming the same prey or if they do not share the same predators. We contrast regular equivalence models, in which two species are members of the same trophic group if they have trophic links to the same set of other trophic groups, with structural equivalence models, in which species are equivalent if they are connected to the exact same other species. Here, the regular equivalence approach is applied to two published food webs: (1) a topological web (Malaysian pitcher plant insect food web) and (2) a carbon-flow web (St. Marks, Florida seagrass ecosystem food web). Regular equivalence produced a more satisfactory set of classes than did the structural approach, grouping basal taxa with other basal taxa and not with top predators. Regular equivalence models provide a way to mathematically formalize trophic position, trophic group and trophic niche. These models are part of a family of models that includes structural models used extensively by ecologists now. Regular equivalence models uncover similarities in trophic roles at a higher level of organization than do the structural models. The approach outlined is useful for measuring the trophic roles of species in food web models, measuring similarity in trophic relations of two or more species, comparing food webs over time and across geographic regions, and aggregating taxa into trophic groups that reduce the complexity of ecosystem feeding relations without obscuring network relationships. In addition, we hope the approach will prove useful in predicting the outcome of predator-prey interactions in experimental studies.

Matched MeSH terms: Models, Biological*
The effects of electrical and thermal boundary condition on the simulation of radiofrequency ablation of liver cancer for tumours located near to the liver boundary

Ooi EH, Lee KW, Yap S, Khattab MA, Liao IY, Ooi ET, et al.

Comput Biol Med, 2019 03;106:12-23.
PMID: 30665137 DOI: 10.1016/j.compbiomed.2019.01.003

Effects of different boundary conditions prescribed across the boundaries of radiofrequency ablation (RFA) models of liver cancer are investigated for the case where the tumour is at the liver boundary. Ground and Robin-type conditions (electrical field) and body temperature and thermal insulation (thermal field) conditions are examined. 3D models of the human liver based on publicly-available CT images of the liver are developed. An artificial tumour is placed inside the liver at the boundary. Simulations are carried out using the finite element method. The numerical results indicated that different electrical and thermal boundary conditions led to different predictions of the electrical potential, temperature and thermal coagulation distributions. Ground and body temperature conditions presented an unnatural physical conditions around the ablation site, which results in more intense Joule heating and excessive heat loss from the tissue. This led to thermal damage volumes that are smaller than the cases when the Robin type or the thermal insulation conditions are prescribed. The present study suggests that RFA simulations in the future must take into consideration the choice of the type of electrical and thermal boundary conditions to be prescribed in the case where the tumour is located near to the liver boundary.

Matched MeSH terms: Models, Biological*
Fulltext Corals reveal ENSO-driven synchrony of climate impacts on both terrestrial and marine ecosystems in northern Borneo

Krawczyk H, Zinke J, Browne N, Struck U, McIlwain J, O'Leary M, et al.

Sci Rep, 2020 02 28;10(1):3678.
PMID: 32111903 DOI: 10.1038/s41598-020-60525-1

Extreme climate events, such as the El Niños in 1997/1998 and 2015/16, have led to considerable forest loss in the Southeast Asian region following unprecedented drought and wildfires. In Borneo, the effects of extreme climate events have been exacerbated by rapid urbanization, accelerated deforestation and soil erosion since the 1980s. However, studies quantifying the impact of interannual and long-term (>3 decades) climatic and anthropogenic change affecting Borneo's coastal and coral reef environments are lacking. Here, we used coral cores collected in Miri-Sibuti Coral Reefs National Park, Sarawak (Malaysia) to reconstruct the spatio-temporal dynamics of sea surface temperature and oxygen isotopic composition of seawater from 1982 to 2016, based on paired oxygen isotope and Sr/Ca measurements. The results revealed rising sea surface temperatures of 0.26 ± 0.04 °C per decade since 1982. Reconstructed δ18Osw displayed positive excursion during major El Niño events of 1983, 1997/98 and 2015/16, indicating drought conditions with less river runoff, rainfall and higher ocean salinities. La Niñas were generally associated with lower δ18Osw. We observed a long-term shift from more saline conditions between 1982 and 1995 towards less saline conditions after 1995, which are in agreement with the regional freshening trend, punctuated by saline excursion during El Niños. The decadal shifts were found to be driven by the Pacific Decadal Oscillation (PDO). This study provides the first long-term data on El Niño Southern Oscillation (ENSO)-driven synchrony of climate impacts on both terrestrial and marine ecosystems in northern Borneo. Our results suggest that coral records from northern Borneo are invaluable archives to detect regional ENSO and PDO impacts, and their interaction with the Asian-Australian monsoon, on the hydrological balance in the southern South China Sea beyond the past three decades.

Matched MeSH terms: Models, Biological*
Stochastic models in seed dispersals: random walks and birth-death processes

Abdullahi A, Shohaimi S, Kilicman A, Ibrahim MH

J Biol Dyn, 2019 12;13(1):345-361.
PMID: 31056007 DOI: 10.1080/17513758.2019.1605003

Seed dispersals deal with complex systems through which the data collected using advanced seed tracking facilities pose challenges to conventional approaches, such as empirical and deterministic models. The use of stochastic models in current seed dispersal studies is encouraged. This review describes three existing stochastic models: the birth-death process (BDP), a 2 dimensional (
2

D

) symmetric random walks and a
2

D

intermittent walks. The three models possess Markovian property, which make them flexible for studying natural phenomena. Only a few of applications in ecology are found in seed dispersals. The review illustrates how the models are to be used in seed dispersals context. Using the nonlinear BDP, we formulate the individual-based models for two competing plant species while the cover time model is formulated by the symmetric and intermittent random walks. We also show that these three stochastic models can be formulated using the Gillespie algorithm. The full cover time obtained by the symmetric random walks can approximate the Gumbel distribution pattern as the other searching strategies do. We suggest that the applications of these models in seed dispersals may lead to understanding of many complex systems, such as the seed removal experiments and behaviour of foraging agents, among others.

Matched MeSH terms: Models, Biological*
Fulltext Graphery: interactive tutorials for biological network algorithms

Zeng H, Zhang J, Preising GA, Rubel T, Singh P, Ritz A

Nucleic Acids Res, 2021 07 02;49(W1):W257-W262.
PMID: 34037782 DOI: 10.1093/nar/gkab420

Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/.

Matched MeSH terms: Models, Biological*
Fulltext Experimentally testing and assessing the predictive power of species assembly rules for tropical canopy ants

Fayle TM, Eggleton P, Manica A, Yusah KM, Foster WA

Ecol Lett, 2015 Mar;18(3):254-62.
PMID: 25622647 DOI: 10.1111/ele.12403

Understanding how species assemble into communities is a key goal in ecology. However, assembly rules are rarely tested experimentally, and their ability to shape real communities is poorly known. We surveyed a diverse community of epiphyte-dwelling ants and found that similar-sized species co-occurred less often than expected. Laboratory experiments demonstrated that invasion was discouraged by the presence of similarly sized resident species. The size difference for which invasion was less likely was the same as that for which wild species exhibited reduced co-occurrence. Finally we explored whether our experimentally derived assembly rules could simulate realistic communities. Communities simulated using size-based species assembly exhibited diversities closer to wild communities than those simulated using size-independent assembly, with results being sensitive to the combination of rules employed. Hence, species segregation in the wild can be driven by competitive species assembly, and this process is sufficient to generate observed species abundance distributions for tropical epiphyte-dwelling ants.

Matched MeSH terms: Models, Biological*
Fulltext Effect of tropical forest disturbance on the competitive interactions within a diverse ant community

Gray REJ, Ewers RM, Boyle MJW, Chung AYC, Gill RJ

Sci Rep, 2018 03 23;8(1):5131.
PMID: 29572517 DOI: 10.1038/s41598-018-23272-y

Understanding how anthropogenic disturbance influences patterns of community composition and the reinforcing interactive processes that structure communities is important to mitigate threats to biodiversity. Competition is considered a primary reinforcing process, yet little is known concerning disturbance effects on competitive interaction networks. We examined how differences in ant community composition between undisturbed and disturbed Bornean rainforest, is potentially reflected by changes in competitive interactions over a food resource. Comparing 10 primary forest sites to 10 in selectively-logged forest, we found higher genus richness and diversity in the primary forest, with 18.5% and 13.0% of genera endemic to primary and logged respectively. From 180 hours of filming bait cards, we assessed ant-ant interactions, finding that despite considered aggression over food sources, the majority of ant interactions were neutral. Proportion of competitive interactions at bait cards did not differ between forest type, however, the rate and per capita number of competitive interactions was significantly lower in logged forest. Furthermore, the majority of genera showed large changes in aggression-score with often inverse relationships to their occupancy rank. This provides evidence of a shuffled competitive network, and these unexpected changes in aggressive relationships could be considered a type of competitive network re-wiring after disturbance.

Matched MeSH terms: Models, Biological*
Fulltext Population Pharmacokinetics of Clozapine: A Systematic Review

Albitar O, Harun SN, Zainal H, Ibrahim B, Sheikh Ghadzi SM

Biomed Res Int, 2020;2020:9872936.
PMID: 31998804 DOI: 10.1155/2020/9872936

Background and Objective: Clozapine is a second-generation antipsychotic drug that is considered the most effective treatment for refractory schizophrenia. Several clozapine population pharmacokinetic models have been introduced in the last decades. Thus, a systematic review was performed (i) to compare published pharmacokinetics models and (ii) to summarize and explore identified covariates influencing the clozapine pharmacokinetics models.
Methods: A search of publications for population pharmacokinetic analyses of clozapine either in healthy volunteers or patients from inception to April 2019 was conducted in PubMed and SCOPUS databases. Reviews, methodology articles, in vitro and animal studies, and noncompartmental analysis were excluded.
Results: Twelve studies were included in this review. Clozapine pharmacokinetics was described as one-compartment with first-order absorption and elimination in most of the studies. Significant interindividual variations of clozapine pharmacokinetic parameters were found in most of the included studies. Age, sex, smoking status, and cytochrome P450 1A2 were found to be the most common identified covariates affecting these parameters. External validation was only performed in one study to determine the predictive performance of the models.
Conclusions: Large pharmacokinetic variability remains despite the inclusion of several covariates. This can be improved by including other potential factors such as genetic polymorphisms, metabolic factors, and significant drug-drug interactions in a well-designed population pharmacokinetic model in the future, taking into account the incorporation of larger sample size and more stringent sampling strategy. External validation should also be performed to the previously published models to compare their predictive performances.

Matched MeSH terms: Models, Biological*
Fulltext CFD study on NACA 4415 airfoil implementing spherical and sinusoidal Tubercle Leading Edge

Aftab SMA, Ahmad KA

PLoS One, 2017;12(8):e0183456.
PMID: 28850622 DOI: 10.1371/journal.pone.0183456

The Humpback whale tubercles have been studied for more than a decade. Tubercle Leading Edge (TLE) effectively reduces the separation bubble size and helps in delaying stall. They are very effective in case of low Reynolds number flows. The current Computational Fluid Dynamics (CFD) study is on NACA 4415 airfoil, at a Reynolds number 120,000. Two TLE shapes are tested on NACA 4415 airfoil. The tubercle designs implemented on the airfoil are sinusoidal and spherical. A parametric study is also carried out considering three amplitudes (0.025c, 0.05c and 0.075c), the wavelength (0.25c) is fixed. Structured mesh is utilized to generate grid and Transition SST turbulence model is used to capture the flow physics. Results clearly show spherical tubercles outperform sinusoidal tubercles. Furthermore experimental study considering spherical TLE is carried out at Reynolds number 200,000. The experimental results show that spherical TLE improve performance compared to clean airfoil.

Matched MeSH terms: Models, Biological*
A New Framework for Analysis of Coevolutionary Systems-Directed Graph Representation and Random Walks

Chong SY, Tiňo P, He J, Yao X

Evol Comput, 2019;27(2):195-228.
PMID: 29155606 DOI: 10.1162/evco_a_00218

Studying coevolutionary systems in the context of simplified models (i.e., games with pairwise interactions between coevolving solutions modeled as self plays) remains an open challenge since the rich underlying structures associated with pairwise-comparison-based fitness measures are often not taken fully into account. Although cyclic dynamics have been demonstrated in several contexts (such as intransitivity in coevolutionary problems), there is no complete characterization of cycle structures and their effects on coevolutionary search. We develop a new framework to address this issue. At the core of our approach is the directed graph (digraph) representation of coevolutionary problems that fully captures structures in the relations between candidate solutions. Coevolutionary processes are modeled as a specific type of Markov chains-random walks on digraphs. Using this framework, we show that coevolutionary problems admit a qualitative characterization: a coevolutionary problem is either solvable (there is a subset of solutions that dominates the remaining candidate solutions) or not. This has an implication on coevolutionary search. We further develop our framework that provides the means to construct quantitative tools for analysis of coevolutionary processes and demonstrate their applications through case studies. We show that coevolution of solvable problems corresponds to an absorbing Markov chain for which we can compute the expected hitting time of the absorbing class. Otherwise, coevolution will cycle indefinitely and the quantity of interest will be the limiting invariant distribution of the Markov chain. We also provide an index for characterizing complexity in coevolutionary problems and show how they can be generated in a controlled manner.

Matched MeSH terms: Models, Biological*
Fulltext Assessing mechanical ventilation asynchrony through iterative airway pressure reconstruction

Chiew YS, Tan CP, Chase JG, Chiew YW, Desaive T, Ralib AM, et al.

Comput Methods Programs Biomed, 2018 Apr;157:217-224.
PMID: 29477430 DOI: 10.1016/j.cmpb.2018.02.007

BACKGROUND AND OBJECTIVE: Respiratory mechanics estimation can be used to guide mechanical ventilation (MV) but is severely compromised when asynchronous breathing occurs. In addition, asynchrony during MV is often not monitored and little is known about the impact or magnitude of asynchronous breathing towards recovery. Thus, it is important to monitor and quantify asynchronous breathing over every breath in an automated fashion, enabling the ability to overcome the limitations of model-based respiratory mechanics estimation during asynchronous breathing ventilation.
METHODS: An iterative airway pressure reconstruction (IPR) method is used to reconstruct asynchronous airway pressure waveforms to better match passive breathing airway waveforms using a single compartment model. The reconstructed pressure enables estimation of respiratory mechanics of airway pressure waveform essentially free from asynchrony. Reconstruction enables real-time breath-to-breath monitoring and quantification of the magnitude of the asynchrony (MAsyn).
RESULTS AND DISCUSSION: Over 100,000 breathing cycles from MV patients with known asynchronous breathing were analyzed. The IPR was able to reconstruct different types of asynchronous breathing. The resulting respiratory mechanics estimated using pressure reconstruction were more consistent with smaller interquartile range (IQR) compared to respiratory mechanics estimated using asynchronous pressure. Comparing reconstructed pressure with asynchronous pressure waveforms quantifies the magnitude of asynchronous breathing, which has a median value MAsyn for the entire dataset of 3.8%.
CONCLUSION: The iterative pressure reconstruction method is capable of identifying asynchronous breaths and improving respiratory mechanics estimation consistency compared to conventional model-based methods. It provides an opportunity to automate real-time quantification of asynchronous breathing frequency and magnitude that was previously limited to invasively method only.

Matched MeSH terms: Models, Biological*

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