Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

High-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer based on probability density evolution method

This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.

Uncertainty quantification of mechanism motion based on coupled mechanism—motor dynamic model for ammunition delivery system

In this paper,a dynamic modeling method of motor driven electromechanical system is presented,and the uncertainty quantification of mechanism motion is investigated based on this method.The main contribution is to propose a novel mechanism-motor coupling dynamic modeling method,in which the relationship between mechanism motion and motor rotation is established according to the geometric coordination of the system.The advantages of this include establishing intuitive coupling between the mechanism and motor,facilitating the discussion for the influence of both mechanical and electrical parameters on the mechanism,and enabling dynamic simulation with controller to take the randomness of the electric load into account.Dynamic simulation considering feedback control of ammunition delivery system is carried out,and the feasibility of the model is verified experimentally.Based on probability density evolution theory,we comprehensively discuss the effects of system parameters on mechanism motion from the perspective of uncertainty quantization.Our work can not only provide guidance for engineering design of ammunition delivery mechanism,but also provide theoretical support for modeling and uncertainty quantification research of mechatronics system.

Quantification of the concrete freeze–thaw environment across the Qinghai–Tibet Plateau based on machine learning algorithms

The reasonable quantification of the concrete freezing environment on the Qinghai–Tibet Plateau(QTP) is the primary issue in frost resistant concrete design, which is one of the challenges that the QTP engineering managers should take into account. In this paper, we propose a more realistic method to calculate the number of concrete freeze–thaw cycles(NFTCs) on the QTP. The calculated results show that the NFTCs increase as the altitude of the meteorological station increases with the average NFTCs being 208.7. Four machine learning methods, i.e., the random forest(RF) model, generalized boosting method(GBM), generalized linear model(GLM), and generalized additive model(GAM), are used to fit the NFTCs. The root mean square error(RMSE) values of the RF, GBM, GLM, and GAM are 32.3, 4.3, 247.9, and 161.3, respectively. The R^(2) values of the RF, GBM, GLM, and GAM are 0.93, 0.99, 0.48, and 0.66, respectively. The GBM method performs the best compared to the other three methods, which was shown by the results of RMSE and R^(2) values. The quantitative results from the GBM method indicate that the lowest, medium, and highest NFTC values are distributed in the northern, central, and southern parts of the QTP, respectively. The annual NFTCs in the QTP region are mainly concentrated at 160 and above, and the average NFTCs is 200 across the QTP. Our results can provide scientific guidance and a theoretical basis for the freezing resistance design of concrete in various projects on the QTP.

2D Q-compensated multi-component elastic Gaussian beam migration

Elastic waves are affected by viscoelasticity during the propagation through the Earth,resulting in energy attenuation and phase distortion,in turn resulting in low seismic imaging accuracy.Therefore,viscoelasticity should be considered in seismic migration imaging.We propose a Q compensated multicomponent elastic Gaussian beam migration(Q-EGBM)method to(1)separate the elastic-wave data into longitudinal(P)and transverse(S)waves to perform PP-wave and PS-wave imaging;(2)recover the amplitude loss caused by attenuation;(3)correct phase distortions caused by dispersion;(4)improve the resolution of migration imaging.In this paper,to accomplish(2),(3),and(4),we derive complex-valued traveltimes in viscoelastic media.The results of numerical experiments using a simple five-layer model and a sophisticated BP gas model show that the method presented here has significant advantages in recovering energy decay and correcting phase distortion,as well as significantly improving imaging resolution.

Uncertainty quantification of predicting stable structures for high-entropy alloys using Bayesian neural networks

High entropy alloys(HEAs)have excellent application prospects in catalysis because of their rich components and configuration space.In this work,we develop a Bayesian neural network(BNN)based on energies calculated with density functional theory to search the configuration space of the CoNiRhRu HEA system.The BNN model was developed by considering six independent features of Co-Ni,Co-Rh,CoRu,Ni-Rh,Ni-Ru,and Rh-Ru in different shells and energies of structures as the labels.The root mean squared error of the energy predicted by BNN is 1.37 me V/atom.Moreover,the influence of feature periodicity on the energy of HEA in theoretical calculations is discussed.We found that when the neural network is optimized to a certain extent,only using the accuracy indicator of root mean square error to evaluate model performance is no longer accurate in some scenarios.More importantly,we reveal the importance of uncertainty quantification for neural networks to predict new structures of HEAs with proper confidence based on BNN.

Molecular diagnosis and direct quantification of cereal cyst nematode(Heterodera filipjevi) from field soil using TaqMan real-time PCR

Heterodera filipjevi continues to be a major threat to wheat production worldwide.Rapid detection and quantification of cyst nematodes are essential for more effective control against this nematode disease.In the present study,a TaqManminor groove binder(TaqMan-MGB)probe-based fluorescence quantitative real-time PCR(qPCR)was successfully developed and used for quantifying H.filipjevi from DNA extracts of soil.The primers and probe designed from the obtained RAPD-SCAR marker fragments of H.filipjevi showed high specificity to H.filipjevi using DNA from isolatesconfirmed species of 23 Heterodera spp.,1 Globodera spp.and 3 Pratylenchus spp.The qPCR assay is highly sensitive and provides improved H.filipjevi detection sensitivity of as low as 4^(-3) single second-stage juvenile(J2)DNAs,10^(-3) female DNAs,and 0.01μgμL^(-1) genomic DNAs.A standard curve relating to the threshold cycle and log values of nematode numbers was generated and validated from artificially infested soils and was used to quantify H.filipjevi in naturally infested field soils.There was a high correlation between the H.filipjevi numbers estimated from 32 naturally infested field soils by both conventional methods and the numbers quantified using the qPCR assay.qPCR potentially provides a useful platform for the efficient detection and quantification of H.filipjevi directly from field soils and to quantify this species directly from DNA extracts of field soils.

Host cell protein quantification workflow using optimized standards combined with data-independent acquisition mass spectrometry

Monitoring of host cell proteins(HCPs)during the manufacturing of monoclonal antibodies(mAb)has become a critical requirement to provide effective and safe drug products.Enzyme-linked immunosorbent assays are still the gold standard methods for the quantification of protein impurities.However,this technique has several limitations and does,among others,not enable the precise identification of proteins.In this context,mass spectrometry(MS)became an alternative and orthogonal method that delivers qualitative and quantitative information on all identified HCPs.However,in order to be routinely implemented in biopharmaceutical companies,liquid chromatography-MS based methods still need to be standardized to provide highest sensitivity and robust and accurate quantification.Here,we present a promising MS-based analytical workflow coupling the use of an innovative quantification standard,the HCP Profiler solution,with a spectral library-based data-independent acquisition(DIA)method and strict data validation criteria.The performances of the HCP Profiler solution were compared to more conventional standard protein spikes and the DIA approach was benchmarked against a classical datadependent acquisition on a series of samples produced at various stages of the manufacturing process.While we also explored spectral library-free DIA interpretation,the spectral library-based approach still showed highest accuracy and reproducibility(coefficients of variation<10%)with a sensitivity down to the sub-ng/mg mAb level.Thus,this workflow is today mature to be used as a robust and straightforward method to support mAb manufacturing process developments and drug products quality control.

Progress and prediction of multicomponent quantification in complex systems with practical LC-UV methods

Complex systems exist widely,including medicines from natural products,functional foods,and biological samples.The biological activity of complex systems is often the result of the synergistic effect of multiple components.In the quality evaluation of complex samples,multicomponent quantitative analysis(MCQA)is usually needed.To overcome the difficulty in obtaining standard products,scholars have proposed achieving MCQA through the“single standard to determine multiple components(SSDMC)”approach.This method has been used in the determination of multicomponent content in natural source drugs and the analysis of impurities in chemical drugs and has been included in the Chinese Pharmacopoeia.Depending on a convenient(ultra)high-performance liquid chromatography method,how can the repeatability and robustness of the MCQA method be improved?How can the chromatography conditions be optimized to improve the number of quantitative components?How can computer software technology be introduced to improve the efficiency of multicomponent analysis(MCA)?These are the key problems that remain to be solved in practical MCQA.First,this review article summarizes the calculation methods of relative correction factors in the SSDMC approach in the past five years,as well as the method robustness and accuracy evaluation.Second,it also summarizes methods to improve peak capacity and quantitative accuracy in MCA,including column selection and twodimensional chromatographic analysis technology.Finally,computer software technologies for predicting chromatographic conditions and analytical parameters are introduced,which provides an idea for intelligent method development in MCA.This paper aims to provide methodological ideas for the improvement of complex system analysis,especially MCQA.

Optimization of extended warranty cost for multi-component systems with economic dependence based on group maintenance

During extended warranty(EW)period,maintenance events play a key role in controlling the product systems within normal operations.However,the modelling of failure process and maintenance optimization is complicated owing to the complex features of the product system,namely,components of the multi-component system are interdependent with each other in some form.For the purpose of optimizing the EW pricing decision of the multi-component system scientifically and rationally,taking the series multi-component system with economic dependence sold with EW policy as a research object,this paper optimizes the imperfect preventive maintenance(PM)strategy from the standpoint of EW cost.Taking into consideration adjusting the PM moments of the components in the system,a group maintenance model is developed,in which the system is repaired preventively in accordance with a specified PM base interval.In order to compare with the system EW cost before group maintenance,the system EW cost model before group maintenance is developed.Numerical example demonstrates that offering group maintenance programs can reduce EW cost of the system to a great extent,thereby reducing the EW price,which proves to be a win-win strategy to manufacturers and users.

Effects of CH_(4)/CO_(2) multi-component gas on components and properties of tight oil during CO_(2) utilization and storage: Physical experiment and composition numerical simulation

An essential technology of carbon capture, utilization and storage-enhanced oil recovery (CCUS-EOR) for tight oil reservoirs is CO_(2) huff-puff followed by associated produced gas reinjection. In this paper, the effects of multi-component gas on the properties and components of tight oil are studied. First, the core displacement experiments using the CH_(4)/CO_(2) multi-component gas are conducted to determine the oil displacement efficiency under different CO_(2) and CH_(4) ratios. Then, a viscometer and a liquid density balance are used to investigate the change characteristics of oil viscosity and density after multi-component gas displacement with different CO_(2) and CH_(4) ratios. In addition, a laboratory scale numerical model is established to validate the experimental results. Finally, a composition model of multi-stage fractured horizontal well in tight oil reservoir considering nano-confinement effects is established to investigate the effects of multi-component gas on the components of produced dead oil and formation crude oil. The experimental results show that the oil displacement efficiency of multi-component gas displacement is greater than that of single-component gas displacement. The CH_(4) decreases the viscosity and density of light oil, while CO_(2) decreases the viscosity but increases the density. And the numerical simulation results show that CO_(2) extracts more heavy components from the liquid phase into the vapor phase, while CH_(4) extracts more light components from the liquid phase into the vapor phase during cyclic gas injection. The multi-component gas can extract both the light components and the heavy components from oil, and the balanced production of each component can be achieved by using multi-component gas huff-puff.

Analysis on the formation principle and present situation of nano phase state of multi-component self-assembly of traditional Chinese compound medicine decoction

Traditional Chinese medicine decoction is a complex polydispersed phase system containing real solution,colloid solution,emulsion and suspension.The compound decoction of traditional Chinese medicine has complex components,including saponins,alkaloids,polysaccharides,flavonoids,amino acids and so on,which can be self-assembled to form gels,fibers,micelles,vesicles and so on.The self-assembled nano-phase not only neutralizes the single drug and reduces the toxicity and side effects,but also has its own pharmacological effects,which complement each other to achieve synergistic effect,so as to achieve the role of drug supplement,which is of research significance.The formation principle,solubilization and synergism principle and characterization method of multi-component self-assembly of traditional Chinese medicine compound decoction are discussed in this paper.

Detection and quantification of Pb and Cr in oysters using laser-induced breakdown spectroscopy

The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is still limited by its low sensitivity when targeting trace heavy metals.In this work,we compare three sample enrichment methods,namely drying,carbonization,and ashing,for increasing detection sensitivity by LIBS analysis for Pb and Cr in oyster samples.The results demonstrate that carbonization can remove a significant amount of the contributions of organic elements C,H,N and O;meanwhile,the signals of the metallic elements such as Cu,Pb,Sr,Ca,Cr and Mg are enhanced by3–6 times after carbonization,and further enhanced by 5–9 times after ashing.Such enhancement is not only due to the more concentrated metallic elements in the sample compared to the dried ones,but also the unifying of the matter in carbonized and ashed samples from which higher plasma temperature and electron density are observed.This condition favors the detection of trace elements.According to the calibration curves with univariate and multivariate analysis,the ashing method is considered to be the best choice.The limits of detection of the ashing method are 0.52 mg kg-1 for Pb and0.08 mg kg-1 for Cr,which can detect the presence of heavy metals in the oysters exceeding the maximum limits of Pb and Cr required by the Chinese national standard.This method provides a promising application for the heavy metal contamination monitoring in the aquatic product industry.

Two-point Dixon and six-point Dixon magnetic resonance techniques in the detection,quantification and grading of hepatic steatosis

BACKGROUND Hepatic steatosis is a very common problem worldwide.AIM To assess the performance of two-and six-point Dixon magnetic resonance(MR)techniques in the detection,quantification and grading of hepatic steatosis.METHODS A single-center retrospective study was performed in 62 patients with suspected parenchymal liver disease.MR sequences included two-point Dixon,six-point Dixon,MR spectroscopy(MRS)and MR elastography.Fat fraction(FF)estimates on the Dixon techniques were compared to the MRS-proton density FF(PDFF).Statistical tests used included Pearson’s correlation and receiver operating characteristic.RESULTS FF estimates on the Dixon techniques showed excellent correlation(≥0.95)with MRS-PDFF,and excellent accuracy[area under the receiver operating characteristic(AUROC)≥0.95]in:(1)Detecting steatosis;and(2)Grading severe steatosis,(P<0.001).In iron overload,two-point Dixon was not evaluable due to confounding T2*effects.FF estimates on six-point Dixon vs MRS-PDFF showed a moderate correlation(0.82)in iron overload vs an excellent correlation(0.97)without iron overload,(P<0.03).The accuracy of six-point Dixon in grading mild steatosis improved(AUROC:0.59 to 0.99)when iron overload cases were excluded.The excellent correlation(>0.9)between the Dixon techniques vs MRSPDFF did not change in the presence of liver fibrosis(P<0.01).CONCLUSION Dixon techniques performed satisfactorily for the evaluation of hepatic steatosis but with exceptions.

Hepatic MR imaging using IDEAL-IQ sequence:Will Gd-EOB-DTPA interfere with reproductivity of fat fraction quantification?

BACKGROUND Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence(IDEAL-IQ)is based on chemical shift-based water and fat separation technique to get proton density fat fraction.Multiple studies have shown that using IDEAL-IQ to test the stability and repeatability of liver fat is acceptable and has high accuracy.AIM To explore whether Gadoxetate Disodium(Gd-EOB-DTPA)interferes with the measurement of the hepatic fat content quantified with the IDEAL-IQ and to evaluate the robustness of this technique.METHODS IDEAL-IQ was used to quantify the liver fat content at 3.0T in 65 patients injected with Gd-EOB-DTPA contrast.After injection,IDEAL-IQ was estimated four times,and the fat fraction(FF)and R2* were measured at the following time points:Precontrast,between the portal phase(70 s)and the late phase(180 s),the delayed phase(5 min)and the hepatobiliary phase(20 min).One-way repeated-measures analysis was conducted to evaluate the difference in the FFs between the four time points.Bland-Altman plots were adopted to assess the FF changes before and after injection of the contrast agent.P<0.05 was considered statistically significant.RESULTS The assessment of the FF at the four time points in the liver,spleen and spine showed no significant differences,and the measurements of hepatic FF yielded good consistency between T1 and T2[95%confidence interval:-0.6768%,0.6658%],T1 and T3(-0.3900%,0.3178%),and T1 and T4(-0.3750%,0.2825%).R2* of the liver,spleen and spine increased significantly after injection(P<0.0001).CONCLUSION Using the IDEAL-IQ sequence to measure the FF,we can obtain results that will not be affected by Gd-EOB-DTPA.The high reproducibility of the IDEAL-IQ sequence makes it available in the scanning interval to save time during multiphase examinations.

运用Real-time quantification PCR方法建立副溶血性弧菌在即食虾中的生长预测模型

运用Real-time quantification PCR(real-time qPCR)方法建立副溶血性弧菌在即食虾中生长预测模型。首先构建质粒标准品,梯度稀释后建立标准曲线,然后用Real-time qPCR方法检测虾中副溶血性弧菌的数量,最后建立37℃下即食虾中副溶血性弧菌生长预测模型,并与传统涂布计数方法进行比较。结果表明,Real-time qPCR方法和传统计数方法均可建立Gmopertz模型、Logistic模型和Richards模型,模型拟合的相关系数R2均在0.9以上。基于Real-timeqPCR方法省时省力、特异性好等优点,用Real-time qPCR方法建立微生物预测模型是未来预测微生物学领域的一种发展趋势。

规划设计学中的调查分析法14—数量化Ⅰ类(Quantification Theory Type Ⅰ)

回归及重回归分析和预测,被广泛地应用于各个行业中。但是,有些相当于回归分析中的说明变数,不是数量数据,而是非数量数据,例如:影响入园人数的因素有星期(平日、休日)、天气状况(晴天、阴天、雨雪天等)、季节(春、夏、秋、冬)等。这些因素因为不是“量”的数据,所以不能用回归或重回归等方法进行分析和预测,但这种情况在规划设计的调查中经常出现,所以数量化Ⅰ类,可以帮助人们进行与回归分析和预测相同的分析,这是十分有效的一种分析方法。

Precore/basal core promoter mutants quantification throughout phases of hepatitis B virus infection by Simpleprobe

AIM:To investigate precore/basal core promoter(PC/BCP) mutants throughout hepatitis B virus(HBV) infection and to determine their relationship to hepatitis B early antigen(HBeA g) titers.METHODS:We enrolled 191 patients in various stages of HBV infection at the Huashan Hospital and the Taizhou Municipal Hospital from 2010 to 2012.None of the patients received antiviral therapy.HBV DNA from serum,was quantified by real-time PCR.The HBV genotype was determined by direct sequencing of the S gene.We used the Simpleprobe ultrasensitivequantitative method to detect PC/BCP mutants in each patient.We compared the strain number,percentage,and the changes in PC/BCP mutants in different phases,and analyzed the relationship between PC/BCP mutants and HBe Ag by multiple linear regression and logistic regression.RESULTS:Patients with HBV infection(n = 191) were assigned to groups by phase:Immune tolerance(IT) = 55,Immune clearance(IC) = 67,Low-replicative(LR) = 49,and HBeA g-negative hepatitis(ENH) = 20.Of the patients(male,112; female,79) enrolled,122 were HBe Ag-positive and 69 were HBe Ag-negative.The median age was 33 years(range:18-78 years).PC and BCP mutation detection rates were 84.82%(162/191) and 96.86%(185/191),respectively.In five HBe Ag-negative cases,we detected double mutation G1896A/G1899 A.The logarithm value of PC mutant quantities(log10 PC) significantly differed in IT,IC,and LR phases,as well as in the ENH phase(F = 49.350,P < 0.001).The logarithm value of BCP mutant quantities(log10 BCP) also differed during the four phases(F = 25.530,P < 0.001).Log10 PC and log10 BCP values were high in the IT and IC phases,decreased in the LR phase,and increased in the ENH phase,although the absolute value at this point remained lower than that in the IT and IC phases.PC mutant quantity per total viral load(PC%) and BCP mutant quantity per total viral load(BCP%) differed between phases(F = 20.040,P < 0.001; F = 10.830,P < 0.001),with PC% and BCP% gradually increasing in successive phases.HBeA g titers negatively correlated with PC%(Spearman's rho =-0.354,P < 0.001) and BCP%(Spearman's rho =-0.395,P < 0.001).The negative correlation between PC% and HBeA g status was significant(B =-5.281,P = 0.001),but there was no such correlation between BCP% and HBeA g status(B =-0.523,P = 0.552).CONCLUSION:PC/BCP mutants become predominant in a dynamic and continuous process.Log10 PC,log10 BCP,PC% and BCP% might be combined to evaluate disease progression.PC% determines HBeA g status.

Value of elastography point quantification in improving the diagnostic accuracy of early diabetic kidney disease

BACKGROUND Diabetic kidney disease(DKD)is a common complication of diabetes.The patient’s prognosis is poor once DKD progresses to advanced stage.Accurate diagnosis and timely treatment of early DKD are important for improving patient’s prognosis and reducing mortality.AIM To explore the value of elastography point quantification(ElastPQ)in improving the accuracy of early DKD diagnosis.METHODS A total of 69 patients with type 2 diabetes were recruited from Naval Military Medical University Affiliated Gongli Hospital.Patients were divided into early DKD group and medium DKD group according to pathological results and urinary albumin excretion rate(UAER).Another 40 patients with simple diabetes were included as the diabetes group.The baseline data,laboratory diagnostic indicators,and ultrasound indicators for each patient were recorded.The differences of the indicators in the three groups were compared.Multivariate logistic regression was used to analyze the influencing factors of the development from simple diabetes into early DKD and from early DKD into medium DKD.Receiver operating characteristic analyses of potential indicators in identifying early DKD and medium DKD,and early DKD and simple diabetes were established.RESULTS Multivariate logistic regression analysis showed that UAER(P<0.001),renocortical Young's Modulus(YM)(P<0.001),and renal parenchymal thickness(P=0.013)were the independent influencing factors of the development from early DKD into medium DKD.Diabetes duration(P=0.041),UAER(P=0.034),and renocortical YM(P=0.017)were the independent influencing factors of the development from simple diabetes into early DKD.Receiver operating characteristic analysis indicated that UAER,renocortical YM,and renal parenchymal thickness were accurate in identifying early DKD and medium DKD[all area under curve(AUC)>0.9].The accuracy of UAER(AUC=0.744),diabetes duration(AUC=0.757),and renocortical YM(AUC=0.782)for the diagnosis of early DKD and simple diabetes were limited.However,the combined diagnosis of UAER,diabetes duration,and renocortical YM was accurate in identifying early DKD and simple diabetes(AUC=0.906),which was significantly higher than any of the three indicators(all P<0.05).CONCLUSION ElastPQ is of great value in the diagnosis of early DKD.When combined with the diabetes duration and UAER,it is expected to diagnose accurately early DKD.

Quantification of epicardial fat:Which method can predict significant coronary artery disease?

AIM:To compare the predictive value of three methods of epicardial fat(EF) assessment for presence of significant coronary artery disease(CAD) [i.e.,epicardial fat volume(EFV),EFV indexed with body surface area(EFV/BSA) and EFV indexed with body mass index(EFV/BMI)].METHODS:The study was performed on 170 patients(85 women and 85 men) with clinical suspicion of CAD.They aged 26-89 years with a median age of 54 years.The patients were classified into three groups:Group 1:58 patients with normal coronary arteries; group 2:48 patients with non-significant CAD and group 3:64 patients with significant CAD.The three methods for assessment of epicardial fat were retrospectively studied to determine the best method to predict the presence of significant CAD.RESULTS:The three methods for epicardial fat quantification and measurements,i.e.,EFV,EFV/BSA and EFV/BMI with post- hoc analysis showed a significant difference between patients with significant coronary artery disease compared to the normal group.Receiver operating characteristic curve analysis showed no significant difference between the three methods of epicardial fat measurements,the area under curve ranging between 0.6 and 0.62.The optimal cut-off was 80.3 cm3 for EFV,2.4 cm3/m2 for EFV indexed with BMI and 41.7 cm3/(kg/m2) for EFV indexed with BSA.For this cut-off the sensitivity ranged between 0.92 and 0.94,while specificity varied from 0.31 to 0.35.CONCLUSION:Any one of the three methods for assessment of epicardial fat can be used to predict significant CAD since all have the same equivalent predictive value.