目的主动脉夹层疾病对主动脉血管壁各层的力学性质和微观结构的影响尚没有系统的研究。本文通过对比正常和发生A型夹层的人体升主动脉组织各层的力学性质和微观结构来探究该问题。方法从13例A型主动脉夹层患者和5例无主动脉疾病的供体...目的主动脉夹层疾病对主动脉血管壁各层的力学性质和微观结构的影响尚没有系统的研究。本文通过对比正常和发生A型夹层的人体升主动脉组织各层的力学性质和微观结构来探究该问题。方法从13例A型主动脉夹层患者和5例无主动脉疾病的供体中共采集了18个升主动脉标本。对每个升主动脉标本进一步分解以获得3个组织样本:主动脉壁全层、内膜-中膜层和外膜层。对每个组织样本进行双轴拉伸测试获得实验应力拉伸比数据,采用Fung-Type材料模型对实验数据进行拟合并计算组织硬度。采用Elastin Van Gieson染色和Masson染色来量化组织中弹性纤维和胶原纤维密度。采用统计分析以确定夹层主动脉和正常主动脉组织各层的力学和微观结构性质是否存在显著差异。结果在拉伸比为1.30时,夹层组内膜-中膜层样本的硬度在长轴方向上显著高于正常组(P=0.0068),而在其他方向或其他层组织中没有发现显著差异。尽管两组之间的弹性纤维或胶原纤维密度没有显著差异,但夹层组的所有3个组织层的弹性纤维密度通常较低,但胶原纤维密度较高。结论与正常主动脉组织相比,夹层主动脉组织中内膜-中膜层的弹性纤维密度较低,而组织硬度却较高,表明内膜-中膜层组织硬度可能是主动脉夹层的潜在生物标志物。展开更多
目的仅根据冠状动脉斑块形态难以有效识别具有破裂倾向并导致临床重大不良事件的易损斑块。斑块生物力学与斑块破裂密切相关。如何利用这些力学信息对斑块破裂程度进行评估仍是一项重大挑战。方法获取了40名冠心病患者的冠脉斑块在体光...目的仅根据冠状动脉斑块形态难以有效识别具有破裂倾向并导致临床重大不良事件的易损斑块。斑块生物力学与斑块破裂密切相关。如何利用这些力学信息对斑块破裂程度进行评估仍是一项重大挑战。方法获取了40名冠心病患者的冠脉斑块在体光学相干断层影像,并根据其斑块形态特征将斑块分为3组:20个稳定斑块、10个易损斑块和10个破裂斑块。对每个斑块进行有限元力学仿真,并提取斑块纤维帽和肩部区域的斑块应力峰值进行后续分析。基于斑块应力峰值提出斑块破裂风险的力学评估方案,从生物力学角度对3组斑块进行分组,并与形态学分组结果进行对比,计算两种分组的一致性。结果破裂和易损斑块的斑块应力峰值显著高于稳定斑块(P<0.0001和P=0.0007),而破裂和易损斑块之间没有发现显著差异(P=0.8538)。以150 k Pa和230 k Pa为斑块应力阈值建立了力学评估方案从而对斑块进行分组,对稳定斑块、易损斑块、破裂斑块的分组结果与形态学分组结果重合率分别为17/20、5/10和7/10。结论该斑块力学评估方案与形态学分组的高度一致性证明了其能有效评估冠脉斑块破裂风险的能力。特别对于稳定斑块,两种分组结果的高度一致表明结合斑块力学和形态可以可靠地识别仅具有稳定斑块的患者,以避免不必要的手术干预。展开更多
Plaque erosion,together with plaque rupture,is a common cause for acute coronary syndrome(ACS).Plaque erosion alone is responsible for about one third of the patients with ACS.Eroded plaque is defined as thrombosed,en...Plaque erosion,together with plaque rupture,is a common cause for acute coronary syndrome(ACS).Plaque erosion alone is responsible for about one third of the patients with ACS.Eroded plaque is defined as thrombosed,endothelium-absent and non-ruptured but often-inflamed plaques based on histological findings.Even though there is efficient imaging technologies to detect the eroded plaque in vivo and tailored treatment strategy has also been developed for ACScaused by erosion in clinics,the pathogenesis mechanisms that cause plaque erosion are not fully understood.It is widely postulated that thrombus formation and endothelial apoptosis(the precursors of plaque erosion)have closed association with biomechanical conditions in the coronary vessel.Revealing of the mechanical conditions in the eroded plaque could advance our knowledge in understanding the formation of plaque erosion.To this end,patient-specific OCT-based fluid-structure interaction(FSI)models were developed to investigate the plaque biomechanical conditions and investigate the impact of erosioninduced inflammation on biomechanical conditions.In vivo OCTand Biplane X-ray angiographic data of eroded coronary plaque were acquired from one male patient(age:64). OCT images were segmented manually with external elastic membrane contour and the trailing edge of the lipid-rich necrotic core(lipid)assumed to have positive remodeling ratio 1.1.Locations with luminal surface having direct contact with intraluminal thrombus on OCT images were identified erosion sites.Fusion of OCT and biplane X-ray angiographic data were performed to obtain the 3D coronary geometry.OCT-based FSI models with pre-shrink-stretch process and anisotropic material properties were constructed following previously established procedures.To reflect tissue weakening caused by erosion-induced inflammation,the material stiffness of plaque intima at the erosion site was adjust to one tenth of un-eroded fibrous plaque tissue.Three FSI models were constructed to investigate the impacts of inflammation and lipid component on plaque biomechanics:M1,without erosion(this means plaque intima at the erosion sites were not softened)and without inclusion of lipid component;M2,with erosion but no lipid;M3,with erosion and inclusion of lipid.FSI models were solved by ADINA to obtain the biomechanical conditions at peak blood pressure including plaque wall stress/strain(PWS/PWSn)and flow wall shear stress(WSS).The average values of three biomechanical conditions at the erosion sites and at the fibrous cap overlaying lipid component were calculated from three models for analysis.The results of M1 and M2 were compared to investigate the impact of erosion-induced inflammation on plaque biomechanics.Mean PWS value decreases from 49.98 kPa to 18.83 kPa(62.32%decrease)while Mean PWSn value increases from 0.123 1 to 0.138 4(12%increase)as the material stiffness becomes 10times soft.Comparing M2 and M3 at the cap sites,M3(with inclusion of lipid)will elevates mean PWS and PWSn values by48.59%and 16.09%,respectively.The impacts of erosion and lipid on flow shear stress were limited(<2%).To conclude,erosion-induced inflammation would lead to lower stress distribution but larger strain distribution,while lipid would elevate both stress and strain conditions.This shows the influence of erosion and lipid component has impacts on stress/strain cal-culations which are closely related to plaque assessment.展开更多
A parameter, known as the parameter of humidification vibration deformation, was proposed, describing quantitatively the impact of water content on vibration settlement deformation, and its relationship with humidific...A parameter, known as the parameter of humidification vibration deformation, was proposed, describing quantitatively the impact of water content on vibration settlement deformation, and its relationship with humidification water content, dynamic shear stress peak value, initial consolidation stress and vibration frequency was built. The result shows that 1） the parameter of humidification vibration deformation increases with the vibration shear stress peak value increasing. 2） The humidification water content has significant influence on the curve of the parameter of humidification vibration deformation and the peak vibration shear stress. When the humidification water content is low, the curve increases slowly. However, when the humidification water content is high, the curve increases rapidly. 3） Initial consolidation stress has significant influence on the humidification vibration deformation coefficient. When initial consolidation stress is not large enough to destroy the loess structure, with initial consolidation stress increasing, the humidification vibration deformation coefficient decreases. On the contrary, the humidification vibration deformation coefficient increases with initial consolidation stress increasing. 4） With the increase of vibration time, the parameter of humidification vibration settlement shows an increasing trend overall. The initial dynamic shear stress peak value and humidification water content all have significant effects on the curve of the parameter of humidification vibration settlement and vibration time. However, the humidification water content is even more significant.展开更多
Background Cardiovascular diseases are closely linked to atherosclerotic plaque development and rupture.Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis,pre...Background Cardiovascular diseases are closely linked to atherosclerotic plaque development and rupture.Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis,prevention,and treatment.Generalized linear mixed models(GLMM)is an extension of linear model for categorical responses while considering the correlation among observations.Methods Magnetic resonance image(MRI)data of carotid atheroscleroticplaques were acquired from 20 patients with consent obtained and 3D thin-layer models were constructed to calculate plaque stress and strain for plaque progression prediction.Data for ten morphological and biomechanical risk factors included wall thickness(WT),lipid percent(LP),minimum cap thickness(MinCT),plaque area(PA),plaque burden(PB),lumen area(LA),maximum plaque wall stress(MPWS),maximum plaque wall strain(MPWSn),average plaque wall stress(APWS),and average plaque wall strain(APWSn)were extracted from all slices for analysis.Wall thickness increase(WTI),plaque burden increase(PBI)and plaque area increase(PAI) were chosen as three measures for plaque progression.Generalized linear mixed models(GLMM)with 5-fold cross-validation strategy were used to calculate prediction accuracy for each predictor and identify optimal predictor with the highest prediction accuracy defined as sum of sensitivity and specificity.All 201 MRI slices were randomly divided into 4 training subgroups and 1 verification subgroup.The training subgroups were used for model fitting,and the verification subgroup was used to estimate the model.All combinations(total1023)of 10 risk factors were feed to GLMM and the prediction accuracy of each predictor were selected from the point on the ROC(receiver operating characteristic)curve with the highest sum of specificity and sensitivity.Results LA was the best single predictor for PBI with the highest prediction accuracy(1.360 1),and the area under of the ROC curve(AUC)is0.654 0,followed by APWSn(1.336 3)with AUC=0.6342.The optimal predictor among all possible combinations for PBI was the combination of LA,PA,LP,WT,MPWS and MPWSn with prediction accuracy=1.414 6(AUC=0.715 8).LA was once again the best single predictor for PAI with the highest prediction accuracy(1.184 6)with AUC=0.606 4,followed by MPWSn(1. 183 2)with AUC=0.6084.The combination of PA,PB,WT,MPWS,MPWSn and APWSn gave the best prediction accuracy(1.302 5)for PAI,and the AUC value is 0.6657.PA was the best single predictor for WTI with highest prediction accuracy(1.288 7)with AUC=0.641 5,followed by WT(1.254 0),with AUC=0.6097.The combination of PA,PB,WT,LP,MinCT,MPWS and MPWS was the best predictor for WTI with prediction accuracy as 1.314 0,with AUC=0.6552.This indicated that PBI was a more predictable measure than WTI and PAI. The combinational predictors improved prediction accuracy by 9.95%,4.01%and 1.96%over the best single predictors for PAI,PBI and WTI(AUC values improved by9.78%,9.45%,and 2.14%),respectively.Conclusions The use of GLMM with 5-fold cross-validation strategy combining both morphological and biomechanical risk factors could potentially improve the accuracy of carotid plaque progression prediction.This study suggests that a linear combination of multiple predictors can provide potential improvement to existing plaque assessment schemes.展开更多
China Cardiovascular Disease Report 2017(Summary)pointed out that at present,cardiovascular diseases(CVD)account for the highest number of deaths among urban and rural residents.In the middle or later stages of athero...China Cardiovascular Disease Report 2017(Summary)pointed out that at present,cardiovascular diseases(CVD)account for the highest number of deaths among urban and rural residents.In the middle or later stages of atherosclerosis,the plaques become increasingly unstable with high chance to rupture,which may lead acute death from coronary heart diseases.Medical imaging and image-based computational modeling have been used in recent years to quantify ather-osclerotic plaque morphological and biomechanical characteristics and predict the coronary plaque growth and rupture processes.Analyzing the vulnerability of plaques effectively could lead to better patient screening strategies and enable physicians to adopt timely and necessary intervention or conservative treatment.Earlier investigations of vulnerable plaques were mostly based on histopathological data.With the accumulation of experience in pathology and the gradual enrichment of autopsy materials,the criteria for the diagnosis of vulnerable plaques appeared in 2001,mainly manifested as the necrotic lipid nuclei,fibrous caps that are infiltrated by a large number of macrophages,and fibrous cap thickness less than 65μm.Because of the obvious importance of the thin fibrous cap in the study of plaque vulnerability,it has been a focus of attention by many investigations.Watson,M.G.et al.are concerned about the formation of early fibrous caps in recent years.The presentation of local maximum stress on plaque further confirmed the importance of thin fibrous cap.The development of medical images has greatly promoted the study of coronary atherosclerosis.Compared with autopsy ex vivo,medical image could provide plaque data under in vivo conditions and greatly promote the study of coronary atherosclerosis.Huang XY et al.used ex vivo magnetic resonance imaging(MRI)to study the relationship between plaque wall stress(PWS)and death caused by coronary artery disease.Due to technical limitations and the accessibility of the coronary artery in the body,MRI is not widely used for in vivo coronary studies.Interventional intravascular ultrasound(IVUS),with an image resolution of 150-200μm,has been used in research and clinical practice to identify plaques,quantify plaque morphology,and characterize plaque components.More recently,optical coherence tomography(OCT),with its resolution of 5-10μm,has emerged as an imaging modality which can be used to detect thin fibrous caps and improve diagnostic accuracy.It is commonly believed that mechanical forces play an important role in plaque progression and rupture.Image-based biomechanical plaque models have been developed and used to quantify plaque mechanical conditions and seek their linkage to plaque progression and vulnerability development activities.Based on recent advances in imaging and modeling,this paper attempts to provide a brief review on plaque research,including histological classification,image preparation,biomechanical modeling and analysis methods including medical imaging techniques represented by intravascular ultrasound(IVUS)and optical coherence tomography(OCT),computational modeling and their applications in plaque progression and vulnerability analyses and predictions.The clinical application and future development direction are also briefly described.We focus more on human coronary plaque modeling and mainly included results from our group for illustration purpose.We apologize in advance for our limitations.展开更多
Objective Patients with repaired tetralogy of Fallot(rTOF)account for the majority of cases with late onset right ventricle(RV)failure.The current surgical approach,including pulmonary valve replacement/insertion(PVR)...Objective Patients with repaired tetralogy of Fallot(rTOF)account for the majority of cases with late onset right ventricle(RV)failure.The current surgical approach,including pulmonary valve replacement/insertion(PVR),has yielded mixed results with some patients recover RV function and some do not.An innovative surgical approach was proposed to help ventricle to contract and improve RV function qualified by ejection fraction with one or more active contracting bands.Computational biomechanical modelling is a widely used method in cardiovascular study for investigation of mechanisms governing disease development,quantitative diagnostic and treatment strategies and improving surgical designs for better outcome.Muscle active contraction caused by zero-load sarcomere shortening leads to change of zero-load configurations.In lieu of experimenting using real surgery on animal or human,computational simulations(virtual surgery)were performed to test different band combination and insertion options to identify optimal surgery design and band insertion plan.Methods Cardiac magnetic resonance(CMR)data were obtained from one rTOF patient(sex:male,age:22.5 y)before pulmonary valve replacement surgery.The patient was suffering from RV dilation and dysfunction with RV end-systole volume 254.49ml and end-diastole volume 406.91 mL.A total of 15 computational RV/LV/Patch/Band combination models based on(CMR)imaging were constructed to investigate the influence of different band insertion surgery plans.These models included 5 different band insertion models combined and 3 different band contraction ratio(10%,15%and 20%band zero-stress length reduction).These models included 5 different band insertion models:Model 1 with one band at anterior to the middle of papillary muscle;Model 2 with one band at posterior to the middle of papillary muscle;Model 3 with 2 bands which are the ones from Models 1&2 combined;Model 4 with a band at the base of the papillary muscle;Model 5 with 3 bands which is a combination of Models 3&4.A pre-shrink process was performed on in-vivo begin-filling and end-systole MRI data to obtain diastole and systole zero4oad ventricle geometries.An extra 5%-8%shrinkage was applied to obtain corresponding systole zero-load geometry reflecting myocardium sarcomere shortening.The zero-load band length in systole was 10%,15%and 20%shorter than that in diastole according to their corresponding contraction ratio.The nonlinear Mooney-Rivlin model was used to describe the ventricle material properties with their material parameter values adjusted to match measured data with CMR.The band material properties were in the same scale with healthy right ventricle.The RV/LV/Band model construction and solution procedures were the same as described.Results Model 5 with band contraction ratio of 20%has the ability to improve RV ejection fraction to 41.07%,which represented a 3.61%absolute improvement,or 9.6%relative improvement using pre-PVR ejection fraction as the baseline number.The ejection fractions for Models 1-4 with band contraction ratio of 20%were 39.28%,39.47%,38.87%and 40.34%respectively.Compared to models with band contraction ratio15%and 20%,models with band contraction ratio 10%has the least ability on RV ejection fraction improvement with ejection fraction 38.28%,38.00%,38.81%,38.50%and 39.36%corresponding to Models 1-5.Conclusions This pilot work demonstrated that the band insertion surgery may have great potential to improve post-PVR RV cardiac function for patients with repaired TOF.More band contraction ratio and inserted band number may lead to better post-surgery outcome.Further investigations using in-vitro animal experiments and final patient studies are warranted.展开更多
Background Tetralogy of Fallot(TOF)is the most common cyanotic heart defect,accounting for 10%of all congenital defects.Pulmonary valve stenosis(PVS)is one common right ventricular outflow tract obstruction problem in...Background Tetralogy of Fallot(TOF)is the most common cyanotic heart defect,accounting for 10%of all congenital defects.Pulmonary valve stenosis(PVS)is one common right ventricular outflow tract obstruction problem in patients with TOF.Congenital bicuspid pulmonary valve(BPV)is a condition of valvular stenosis,which morphologic feature is the presence of only two pulmonary leaflets instead of the normal tri-leaflet.Congenitally BPV are uncommon and the occurrence is often associated with TOF.Methods The three-dimensional geometric reconstruction of pulmonary root(PR)were based on well-accepted mathematical analytic models with physiological parameters obtained from a typical sample of the pulmonary root used in clinical surgery.The PR geometry included valvular leaflets,sinuses,interleaflet triangles and annulus.The dynamic computational models of normal PR with tri-leaflet and PR with BPV in patients with TOF were developed to investigate the effect of geometric structure of BPV on valve stress and strain distributions and the geometric orifice area.Mechanical properties of pulmonary valve leaflet were obtained from biaxial testing of human pulmonary valve left leaflet,and characterized by an anisotropic Mooney-Rivlin model.The complete cardiac cycle was simulated to observe valve leaflet dynamic stress and strain behaviors.Results Our results indicated that stress/strain distribution patterns of normal tri-leaflet pulmonary valve(TPV)and the BPV were different on valve leaflets when the valve was fully open,but they were similar when valves were completely closed.When the valve was fully open,the BPV maximum stress value on the leaflets was 218.1 kPa,which was 128.0%higher than of the normal TPV value(95.6 kPa),and BPV maximum strain value on the leaflets was 70.7%higher than of the normal TPV.The location of the maximum stress from TPV and BPV were also different,which were found at the bottom of the valve near the leaflet attachment for TPV and the vicinity of cusp of the fusion of two leaflets for BPV,respectively.During the valve was fully open,the stress distribution in the interleaflet triangles region of the PR was more asymmetric in the BPV model compared with that in the normal TPV model,and the largest change on the PR with the geometrical variations in the two models was 39.6%in maximum stress.This stress asymmetry indicates that BPV may be one of the causes of post-stenotic pulmonary artery dilatation and aneurysm in patients with TOF.The cusp of the BPV model showed significant eccentricity during peak systolic period,and its geometric orifice area value in the completely opened position of valve was reduced 57.5%from that of the normal TPV model.Conclusions Our initial results demonstrated that valve geometrical variations with BPV may be a potential risk factor linked to occurrence of PVS in patients with TOF.Computational models could be used as an effective tool to identifying possible linkage between pulmonary valve malformation disease development and biomechanical factors,better design of artificial valves and new surgical procedures without testing those on patients.Large-scale clinical studies are needed to validate these preliminary findings.展开更多
Background Cardiovascular diseases are closely associated with atherosclerotic plaque development and rupture.Traditional medical imaging techniques such as magnetic resonance imaging(MRI)and intravascular ultrasound(...Background Cardiovascular diseases are closely associated with atherosclerotic plaque development and rupture.Traditional medical imaging techniques such as magnetic resonance imaging(MRI)and intravascular ultrasound(IVUS)were unable to identify vulnerable plaques due to their limited resolution.Fortunately,optical coherence tomography(OCT)is an advanced intravascular imaging technique developed in recent years which has high resolution approximately 10 microns and could provide more accurate morphology of coronary plaque.In particular,it has the ability to identify plaques with fibrous cap thickness<65μm,an accepted threshold value for vulnerable plaques.However,segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective.To overcome time consumption,several methodologies have been proposed for automatic segmentation of OCT images but most of these methods were still limited by intricate image preprocessing and expensive computation.In this research,two automatic segmentation methods for intracoronary OCT image based on support vector machine(SVM)and convolutional neural network(CNN)were performed to identify the plaque region and characterize plaque components.Methods In vivo IVUS and OCT coronary plaque data from 5 patients were acquired at Emory University with patient’s consent obtained.OCT were obtained from ILUMIEN OPTIS System(St.Jude,Minnesota,MN).The OCT catheter was traversed to the segment of interest and the catheter pullback was limited at a rate of 20 mm/sec.Following the OCT image acquisition,the IVUS catheter was traversed distally though the artery to the same coronary segment(Volcano Therapeutics,Rancho Cordova)and the catheter pullback speed was at a standard rate of 0.5 mm/sec.Seventy-seven matched IVUS and OCT slices with good image quality and lipid cores were selected for our segmentation study.Manual OCT segmentation was performed by experts and used as gold standard in the automatic segmentations.VH-IVUS was used as references and guide by the experts in the manual segmentation process.Three plaque component tissue classes were identified from OCT images in this work:lipid tissue(LT),fibrous tissue(FT)and background(BG).Procedures using two machine learning methods(CNN and SVM)were developed to segment OCT images,respectively.For CNN method,the U-Net architecture was selected due to its good performance in very different biomedical segmentation and very few annotated images.For SVM method,local binary patterns(LBPs),gray level co-occurrence matrices(GLCMs)which contains contrast,correlation,energy and homogeneity,entropy and mean value were calculated as features and assembled to feed SVM classifier.The accuracies of two segmentation methods were evaluated and compared using the OCT dataset.Segmentation accuracy is defined as the ratio of the number of pixels correctly classified over the total number of pixels.Results The overall classification accuracy based CNN method reached 95.8%,and the accuracies for LT,FT and BG were 86.8%,83.4%,and 98.2%,respectively.The overall classification accuracy based SVM was 71.9%,and per-class accuracy for LT,FT and BG was 75.4%,78.3%,and67.0%,respectively.Conclusions The two methods proposed can automatically identify plaque region and characterize plaque compositions for OCT images and potentially reduce the time spent by doctors in segmenting and evaluating coronary plaque OCT images.CNN provided better segmentation accuracies compared to those achieved by SVM.展开更多
文摘目的主动脉夹层疾病对主动脉血管壁各层的力学性质和微观结构的影响尚没有系统的研究。本文通过对比正常和发生A型夹层的人体升主动脉组织各层的力学性质和微观结构来探究该问题。方法从13例A型主动脉夹层患者和5例无主动脉疾病的供体中共采集了18个升主动脉标本。对每个升主动脉标本进一步分解以获得3个组织样本:主动脉壁全层、内膜-中膜层和外膜层。对每个组织样本进行双轴拉伸测试获得实验应力拉伸比数据,采用Fung-Type材料模型对实验数据进行拟合并计算组织硬度。采用Elastin Van Gieson染色和Masson染色来量化组织中弹性纤维和胶原纤维密度。采用统计分析以确定夹层主动脉和正常主动脉组织各层的力学和微观结构性质是否存在显著差异。结果在拉伸比为1.30时,夹层组内膜-中膜层样本的硬度在长轴方向上显著高于正常组(P=0.0068),而在其他方向或其他层组织中没有发现显著差异。尽管两组之间的弹性纤维或胶原纤维密度没有显著差异,但夹层组的所有3个组织层的弹性纤维密度通常较低,但胶原纤维密度较高。结论与正常主动脉组织相比,夹层主动脉组织中内膜-中膜层的弹性纤维密度较低,而组织硬度却较高,表明内膜-中膜层组织硬度可能是主动脉夹层的潜在生物标志物。
文摘目的仅根据冠状动脉斑块形态难以有效识别具有破裂倾向并导致临床重大不良事件的易损斑块。斑块生物力学与斑块破裂密切相关。如何利用这些力学信息对斑块破裂程度进行评估仍是一项重大挑战。方法获取了40名冠心病患者的冠脉斑块在体光学相干断层影像,并根据其斑块形态特征将斑块分为3组:20个稳定斑块、10个易损斑块和10个破裂斑块。对每个斑块进行有限元力学仿真,并提取斑块纤维帽和肩部区域的斑块应力峰值进行后续分析。基于斑块应力峰值提出斑块破裂风险的力学评估方案,从生物力学角度对3组斑块进行分组,并与形态学分组结果进行对比,计算两种分组的一致性。结果破裂和易损斑块的斑块应力峰值显著高于稳定斑块(P<0.0001和P=0.0007),而破裂和易损斑块之间没有发现显著差异(P=0.8538)。以150 k Pa和230 k Pa为斑块应力阈值建立了力学评估方案从而对斑块进行分组,对稳定斑块、易损斑块、破裂斑块的分组结果与形态学分组结果重合率分别为17/20、5/10和7/10。结论该斑块力学评估方案与形态学分组的高度一致性证明了其能有效评估冠脉斑块破裂风险的能力。特别对于稳定斑块,两种分组结果的高度一致表明结合斑块力学和形态可以可靠地识别仅具有稳定斑块的患者,以避免不必要的手术干预。
基金supported in part by NSFC ( 11672001,11802060)Jiangsu NSF ( BK20180352)Jiangsu Province Science and Technology Agency ( BE2016785)
文摘Plaque erosion,together with plaque rupture,is a common cause for acute coronary syndrome(ACS).Plaque erosion alone is responsible for about one third of the patients with ACS.Eroded plaque is defined as thrombosed,endothelium-absent and non-ruptured but often-inflamed plaques based on histological findings.Even though there is efficient imaging technologies to detect the eroded plaque in vivo and tailored treatment strategy has also been developed for ACScaused by erosion in clinics,the pathogenesis mechanisms that cause plaque erosion are not fully understood.It is widely postulated that thrombus formation and endothelial apoptosis(the precursors of plaque erosion)have closed association with biomechanical conditions in the coronary vessel.Revealing of the mechanical conditions in the eroded plaque could advance our knowledge in understanding the formation of plaque erosion.To this end,patient-specific OCT-based fluid-structure interaction(FSI)models were developed to investigate the plaque biomechanical conditions and investigate the impact of erosioninduced inflammation on biomechanical conditions.In vivo OCTand Biplane X-ray angiographic data of eroded coronary plaque were acquired from one male patient(age:64). OCT images were segmented manually with external elastic membrane contour and the trailing edge of the lipid-rich necrotic core(lipid)assumed to have positive remodeling ratio 1.1.Locations with luminal surface having direct contact with intraluminal thrombus on OCT images were identified erosion sites.Fusion of OCT and biplane X-ray angiographic data were performed to obtain the 3D coronary geometry.OCT-based FSI models with pre-shrink-stretch process and anisotropic material properties were constructed following previously established procedures.To reflect tissue weakening caused by erosion-induced inflammation,the material stiffness of plaque intima at the erosion site was adjust to one tenth of un-eroded fibrous plaque tissue.Three FSI models were constructed to investigate the impacts of inflammation and lipid component on plaque biomechanics:M1,without erosion(this means plaque intima at the erosion sites were not softened)and without inclusion of lipid component;M2,with erosion but no lipid;M3,with erosion and inclusion of lipid.FSI models were solved by ADINA to obtain the biomechanical conditions at peak blood pressure including plaque wall stress/strain(PWS/PWSn)and flow wall shear stress(WSS).The average values of three biomechanical conditions at the erosion sites and at the fibrous cap overlaying lipid component were calculated from three models for analysis.The results of M1 and M2 were compared to investigate the impact of erosion-induced inflammation on plaque biomechanics.Mean PWS value decreases from 49.98 kPa to 18.83 kPa(62.32%decrease)while Mean PWSn value increases from 0.123 1 to 0.138 4(12%increase)as the material stiffness becomes 10times soft.Comparing M2 and M3 at the cap sites,M3(with inclusion of lipid)will elevates mean PWS and PWSn values by48.59%and 16.09%,respectively.The impacts of erosion and lipid on flow shear stress were limited(<2%).To conclude,erosion-induced inflammation would lead to lower stress distribution but larger strain distribution,while lipid would elevate both stress and strain conditions.This shows the influence of erosion and lipid component has impacts on stress/strain cal-culations which are closely related to plaque assessment.
基金Foundation item： Project（51178392） supported by the National Natural Science Foundation of China
文摘A parameter, known as the parameter of humidification vibration deformation, was proposed, describing quantitatively the impact of water content on vibration settlement deformation, and its relationship with humidification water content, dynamic shear stress peak value, initial consolidation stress and vibration frequency was built. The result shows that 1） the parameter of humidification vibration deformation increases with the vibration shear stress peak value increasing. 2） The humidification water content has significant influence on the curve of the parameter of humidification vibration deformation and the peak vibration shear stress. When the humidification water content is low, the curve increases slowly. However, when the humidification water content is high, the curve increases rapidly. 3） Initial consolidation stress has significant influence on the humidification vibration deformation coefficient. When initial consolidation stress is not large enough to destroy the loess structure, with initial consolidation stress increasing, the humidification vibration deformation coefficient decreases. On the contrary, the humidification vibration deformation coefficient increases with initial consolidation stress increasing. 4） With the increase of vibration time, the parameter of humidification vibration settlement shows an increasing trend overall. The initial dynamic shear stress peak value and humidification water content all have significant effects on the curve of the parameter of humidification vibration settlement and vibration time. However, the humidification water content is even more significant.
基金supported in part by National Sciences Foundation of China grant ( 11672001)Jiangsu Province Science and Technology Agency grant ( BE2016785)supported in part by Postgraduate Research & Practice Innovation Program of Jiangsu Province grant ( KYCX18_0156)
文摘Background Cardiovascular diseases are closely linked to atherosclerotic plaque development and rupture.Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis,prevention,and treatment.Generalized linear mixed models(GLMM)is an extension of linear model for categorical responses while considering the correlation among observations.Methods Magnetic resonance image(MRI)data of carotid atheroscleroticplaques were acquired from 20 patients with consent obtained and 3D thin-layer models were constructed to calculate plaque stress and strain for plaque progression prediction.Data for ten morphological and biomechanical risk factors included wall thickness(WT),lipid percent(LP),minimum cap thickness(MinCT),plaque area(PA),plaque burden(PB),lumen area(LA),maximum plaque wall stress(MPWS),maximum plaque wall strain(MPWSn),average plaque wall stress(APWS),and average plaque wall strain(APWSn)were extracted from all slices for analysis.Wall thickness increase(WTI),plaque burden increase(PBI)and plaque area increase(PAI) were chosen as three measures for plaque progression.Generalized linear mixed models(GLMM)with 5-fold cross-validation strategy were used to calculate prediction accuracy for each predictor and identify optimal predictor with the highest prediction accuracy defined as sum of sensitivity and specificity.All 201 MRI slices were randomly divided into 4 training subgroups and 1 verification subgroup.The training subgroups were used for model fitting,and the verification subgroup was used to estimate the model.All combinations(total1023)of 10 risk factors were feed to GLMM and the prediction accuracy of each predictor were selected from the point on the ROC(receiver operating characteristic)curve with the highest sum of specificity and sensitivity.Results LA was the best single predictor for PBI with the highest prediction accuracy(1.360 1),and the area under of the ROC curve(AUC)is0.654 0,followed by APWSn(1.336 3)with AUC=0.6342.The optimal predictor among all possible combinations for PBI was the combination of LA,PA,LP,WT,MPWS and MPWSn with prediction accuracy=1.414 6(AUC=0.715 8).LA was once again the best single predictor for PAI with the highest prediction accuracy(1.184 6)with AUC=0.606 4,followed by MPWSn(1. 183 2)with AUC=0.6084.The combination of PA,PB,WT,MPWS,MPWSn and APWSn gave the best prediction accuracy(1.302 5)for PAI,and the AUC value is 0.6657.PA was the best single predictor for WTI with highest prediction accuracy(1.288 7)with AUC=0.641 5,followed by WT(1.254 0),with AUC=0.6097.The combination of PA,PB,WT,LP,MinCT,MPWS and MPWS was the best predictor for WTI with prediction accuracy as 1.314 0,with AUC=0.6552.This indicated that PBI was a more predictable measure than WTI and PAI. The combinational predictors improved prediction accuracy by 9.95%,4.01%and 1.96%over the best single predictors for PAI,PBI and WTI(AUC values improved by9.78%,9.45%,and 2.14%),respectively.Conclusions The use of GLMM with 5-fold cross-validation strategy combining both morphological and biomechanical risk factors could potentially improve the accuracy of carotid plaque progression prediction.This study suggests that a linear combination of multiple predictors can provide potential improvement to existing plaque assessment schemes.
基金supported in part by NIH grant ( R01 EB004759)Jiangsu Province Science and Technology Agency grant ( BE2016785)
文摘China Cardiovascular Disease Report 2017(Summary)pointed out that at present,cardiovascular diseases(CVD)account for the highest number of deaths among urban and rural residents.In the middle or later stages of atherosclerosis,the plaques become increasingly unstable with high chance to rupture,which may lead acute death from coronary heart diseases.Medical imaging and image-based computational modeling have been used in recent years to quantify ather-osclerotic plaque morphological and biomechanical characteristics and predict the coronary plaque growth and rupture processes.Analyzing the vulnerability of plaques effectively could lead to better patient screening strategies and enable physicians to adopt timely and necessary intervention or conservative treatment.Earlier investigations of vulnerable plaques were mostly based on histopathological data.With the accumulation of experience in pathology and the gradual enrichment of autopsy materials,the criteria for the diagnosis of vulnerable plaques appeared in 2001,mainly manifested as the necrotic lipid nuclei,fibrous caps that are infiltrated by a large number of macrophages,and fibrous cap thickness less than 65μm.Because of the obvious importance of the thin fibrous cap in the study of plaque vulnerability,it has been a focus of attention by many investigations.Watson,M.G.et al.are concerned about the formation of early fibrous caps in recent years.The presentation of local maximum stress on plaque further confirmed the importance of thin fibrous cap.The development of medical images has greatly promoted the study of coronary atherosclerosis.Compared with autopsy ex vivo,medical image could provide plaque data under in vivo conditions and greatly promote the study of coronary atherosclerosis.Huang XY et al.used ex vivo magnetic resonance imaging(MRI)to study the relationship between plaque wall stress(PWS)and death caused by coronary artery disease.Due to technical limitations and the accessibility of the coronary artery in the body,MRI is not widely used for in vivo coronary studies.Interventional intravascular ultrasound(IVUS),with an image resolution of 150-200μm,has been used in research and clinical practice to identify plaques,quantify plaque morphology,and characterize plaque components.More recently,optical coherence tomography(OCT),with its resolution of 5-10μm,has emerged as an imaging modality which can be used to detect thin fibrous caps and improve diagnostic accuracy.It is commonly believed that mechanical forces play an important role in plaque progression and rupture.Image-based biomechanical plaque models have been developed and used to quantify plaque mechanical conditions and seek their linkage to plaque progression and vulnerability development activities.Based on recent advances in imaging and modeling,this paper attempts to provide a brief review on plaque research,including histological classification,image preparation,biomechanical modeling and analysis methods including medical imaging techniques represented by intravascular ultrasound(IVUS)and optical coherence tomography(OCT),computational modeling and their applications in plaque progression and vulnerability analyses and predictions.The clinical application and future development direction are also briefly described.We focus more on human coronary plaque modeling and mainly included results from our group for illustration purpose.We apologize in advance for our limitations.
基金supported in part by National Sciences Foundation of China grants ( 11672001, 81571691,81771844)
文摘Objective Patients with repaired tetralogy of Fallot(rTOF)account for the majority of cases with late onset right ventricle(RV)failure.The current surgical approach,including pulmonary valve replacement/insertion(PVR),has yielded mixed results with some patients recover RV function and some do not.An innovative surgical approach was proposed to help ventricle to contract and improve RV function qualified by ejection fraction with one or more active contracting bands.Computational biomechanical modelling is a widely used method in cardiovascular study for investigation of mechanisms governing disease development,quantitative diagnostic and treatment strategies and improving surgical designs for better outcome.Muscle active contraction caused by zero-load sarcomere shortening leads to change of zero-load configurations.In lieu of experimenting using real surgery on animal or human,computational simulations(virtual surgery)were performed to test different band combination and insertion options to identify optimal surgery design and band insertion plan.Methods Cardiac magnetic resonance(CMR)data were obtained from one rTOF patient(sex:male,age:22.5 y)before pulmonary valve replacement surgery.The patient was suffering from RV dilation and dysfunction with RV end-systole volume 254.49ml and end-diastole volume 406.91 mL.A total of 15 computational RV/LV/Patch/Band combination models based on(CMR)imaging were constructed to investigate the influence of different band insertion surgery plans.These models included 5 different band insertion models combined and 3 different band contraction ratio(10%,15%and 20%band zero-stress length reduction).These models included 5 different band insertion models:Model 1 with one band at anterior to the middle of papillary muscle;Model 2 with one band at posterior to the middle of papillary muscle;Model 3 with 2 bands which are the ones from Models 1&2 combined;Model 4 with a band at the base of the papillary muscle;Model 5 with 3 bands which is a combination of Models 3&4.A pre-shrink process was performed on in-vivo begin-filling and end-systole MRI data to obtain diastole and systole zero4oad ventricle geometries.An extra 5%-8%shrinkage was applied to obtain corresponding systole zero-load geometry reflecting myocardium sarcomere shortening.The zero-load band length in systole was 10%,15%and 20%shorter than that in diastole according to their corresponding contraction ratio.The nonlinear Mooney-Rivlin model was used to describe the ventricle material properties with their material parameter values adjusted to match measured data with CMR.The band material properties were in the same scale with healthy right ventricle.The RV/LV/Band model construction and solution procedures were the same as described.Results Model 5 with band contraction ratio of 20%has the ability to improve RV ejection fraction to 41.07%,which represented a 3.61%absolute improvement,or 9.6%relative improvement using pre-PVR ejection fraction as the baseline number.The ejection fractions for Models 1-4 with band contraction ratio of 20%were 39.28%,39.47%,38.87%and 40.34%respectively.Compared to models with band contraction ratio15%and 20%,models with band contraction ratio 10%has the least ability on RV ejection fraction improvement with ejection fraction 38.28%,38.00%,38.81%,38.50%and 39.36%corresponding to Models 1-5.Conclusions This pilot work demonstrated that the band insertion surgery may have great potential to improve post-PVR RV cardiac function for patients with repaired TOF.More band contraction ratio and inserted band number may lead to better post-surgery outcome.Further investigations using in-vitro animal experiments and final patient studies are warranted.
基金supported in part by National Sciences Foundation of China grants ( 11672001, 81571691 and 81771844)
文摘Background Tetralogy of Fallot(TOF)is the most common cyanotic heart defect,accounting for 10%of all congenital defects.Pulmonary valve stenosis(PVS)is one common right ventricular outflow tract obstruction problem in patients with TOF.Congenital bicuspid pulmonary valve(BPV)is a condition of valvular stenosis,which morphologic feature is the presence of only two pulmonary leaflets instead of the normal tri-leaflet.Congenitally BPV are uncommon and the occurrence is often associated with TOF.Methods The three-dimensional geometric reconstruction of pulmonary root(PR)were based on well-accepted mathematical analytic models with physiological parameters obtained from a typical sample of the pulmonary root used in clinical surgery.The PR geometry included valvular leaflets,sinuses,interleaflet triangles and annulus.The dynamic computational models of normal PR with tri-leaflet and PR with BPV in patients with TOF were developed to investigate the effect of geometric structure of BPV on valve stress and strain distributions and the geometric orifice area.Mechanical properties of pulmonary valve leaflet were obtained from biaxial testing of human pulmonary valve left leaflet,and characterized by an anisotropic Mooney-Rivlin model.The complete cardiac cycle was simulated to observe valve leaflet dynamic stress and strain behaviors.Results Our results indicated that stress/strain distribution patterns of normal tri-leaflet pulmonary valve(TPV)and the BPV were different on valve leaflets when the valve was fully open,but they were similar when valves were completely closed.When the valve was fully open,the BPV maximum stress value on the leaflets was 218.1 kPa,which was 128.0%higher than of the normal TPV value(95.6 kPa),and BPV maximum strain value on the leaflets was 70.7%higher than of the normal TPV.The location of the maximum stress from TPV and BPV were also different,which were found at the bottom of the valve near the leaflet attachment for TPV and the vicinity of cusp of the fusion of two leaflets for BPV,respectively.During the valve was fully open,the stress distribution in the interleaflet triangles region of the PR was more asymmetric in the BPV model compared with that in the normal TPV model,and the largest change on the PR with the geometrical variations in the two models was 39.6%in maximum stress.This stress asymmetry indicates that BPV may be one of the causes of post-stenotic pulmonary artery dilatation and aneurysm in patients with TOF.The cusp of the BPV model showed significant eccentricity during peak systolic period,and its geometric orifice area value in the completely opened position of valve was reduced 57.5%from that of the normal TPV model.Conclusions Our initial results demonstrated that valve geometrical variations with BPV may be a potential risk factor linked to occurrence of PVS in patients with TOF.Computational models could be used as an effective tool to identifying possible linkage between pulmonary valve malformation disease development and biomechanical factors,better design of artificial valves and new surgical procedures without testing those on patients.Large-scale clinical studies are needed to validate these preliminary findings.
基金supported in part by National Sciences Foundation of China grant ( 11672001)Jiangsu Province Science and Technology Agency grant ( BE2016785)
文摘Background Cardiovascular diseases are closely associated with atherosclerotic plaque development and rupture.Traditional medical imaging techniques such as magnetic resonance imaging(MRI)and intravascular ultrasound(IVUS)were unable to identify vulnerable plaques due to their limited resolution.Fortunately,optical coherence tomography(OCT)is an advanced intravascular imaging technique developed in recent years which has high resolution approximately 10 microns and could provide more accurate morphology of coronary plaque.In particular,it has the ability to identify plaques with fibrous cap thickness<65μm,an accepted threshold value for vulnerable plaques.However,segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective.To overcome time consumption,several methodologies have been proposed for automatic segmentation of OCT images but most of these methods were still limited by intricate image preprocessing and expensive computation.In this research,two automatic segmentation methods for intracoronary OCT image based on support vector machine(SVM)and convolutional neural network(CNN)were performed to identify the plaque region and characterize plaque components.Methods In vivo IVUS and OCT coronary plaque data from 5 patients were acquired at Emory University with patient’s consent obtained.OCT were obtained from ILUMIEN OPTIS System(St.Jude,Minnesota,MN).The OCT catheter was traversed to the segment of interest and the catheter pullback was limited at a rate of 20 mm/sec.Following the OCT image acquisition,the IVUS catheter was traversed distally though the artery to the same coronary segment(Volcano Therapeutics,Rancho Cordova)and the catheter pullback speed was at a standard rate of 0.5 mm/sec.Seventy-seven matched IVUS and OCT slices with good image quality and lipid cores were selected for our segmentation study.Manual OCT segmentation was performed by experts and used as gold standard in the automatic segmentations.VH-IVUS was used as references and guide by the experts in the manual segmentation process.Three plaque component tissue classes were identified from OCT images in this work:lipid tissue(LT),fibrous tissue(FT)and background(BG).Procedures using two machine learning methods(CNN and SVM)were developed to segment OCT images,respectively.For CNN method,the U-Net architecture was selected due to its good performance in very different biomedical segmentation and very few annotated images.For SVM method,local binary patterns(LBPs),gray level co-occurrence matrices(GLCMs)which contains contrast,correlation,energy and homogeneity,entropy and mean value were calculated as features and assembled to feed SVM classifier.The accuracies of two segmentation methods were evaluated and compared using the OCT dataset.Segmentation accuracy is defined as the ratio of the number of pixels correctly classified over the total number of pixels.Results The overall classification accuracy based CNN method reached 95.8%,and the accuracies for LT,FT and BG were 86.8%,83.4%,and 98.2%,respectively.The overall classification accuracy based SVM was 71.9%,and per-class accuracy for LT,FT and BG was 75.4%,78.3%,and67.0%,respectively.Conclusions The two methods proposed can automatically identify plaque region and characterize plaque compositions for OCT images and potentially reduce the time spent by doctors in segmenting and evaluating coronary plaque OCT images.CNN provided better segmentation accuracies compared to those achieved by SVM.
