Objective:To perform a meta-analysis to evaluate the diagnostic performance of computed tomography(CT) and transthoracic echocardiography(TTE) in complex congenital heart diseases(CHD) in China.Methods:MEDLINE,Cochran...Objective:To perform a meta-analysis to evaluate the diagnostic performance of computed tomography(CT) and transthoracic echocardiography(TTE) in complex congenital heart diseases(CHD) in China.Methods:MEDLINE,Cochrane library and China National Knowledge Infrastructure(CNKI) database from January 1966 to October 2010,were searched for initial studies in China.All the studies,published in English or Chinese,used TTE,CT,or both as diagnostic tests for CHD and reported the rate of true-positive,true-negative,false-positive and false-negative diagnoses of CHD from TTE and CT findings with the surgical results as the 'gold-standard'(15 studies,XX patients) were collected.The statistic software package,'Meta-Disc 1.4',was used to conduct data analysis.A covariate analysis was used to evaluate the influence of patient or study-related factors on sensitivity.Results:Pooled sensitivity for diagnosis of CHD were 95% [95% confidence interval(CI):94%~96%] for CT studies and 87%(95% CI:85%~88%) for TTE studies.The difference between the pooled sensitivity of CT and that of TTE was statistically significant(P<0.001).TTE had higher sensitivity [0.96(95% CI:0.94~0.97)] for cardiac malformation but lower sensitivity [0.78(95% CI:0.76~0.81)] for extracardiac malformation than CT.Conclusion:CT can provide added diagnostic information compared with TTE in patients with CHD in China,especially for patients suspected of extracardiac malformation.展开更多
A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d...A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d<0.075 mm,0.075 mm≤d<0.1 mm,0.1 mm≤d<0.2 mm,0.2 mm≤d<0.5 mm and 0.5 mm≤d<1.0 mm)to study the structures and particle contacts of granite residual soil.The X-ray micro computed tomography method was used to reconstruct the microstructure of granite residual soil.The particle was identified and regularized using principal component analysis(PCA).The particle contacts and geometrical characteristics in 3D space were analyzed and summarized using statistical analyses.The results demonstrate that the main types of contact among the particles are face-face,face-angle,face-edge,edge-edge,edge-angle and angle-angle contacts for particle sizes less than 0.2 mm.When the particle sizes are greater than 0.2 mm,the contacts are effectively summarized as face-face,face-angle,face-edge,edge-edge,edge-angle,angle-angle,sphere-sphere,sphere-face,sphere-edge and sphere-angle contacts.The differences in porosity among the original sample,reconstructed sample and regularized sample are closely related to the water-swelling and water-disintegrable characteristics of granite residual soil.展开更多
Micro computed tomography (Micro-CT) was applied to obtain three-dimensional images of the microstructure of cement paste (water-to-cement mass ratio of 0.5) at different ages. By using the Amira software, component p...Micro computed tomography (Micro-CT) was applied to obtain three-dimensional images of the microstructure of cement paste (water-to-cement mass ratio of 0.5) at different ages. By using the Amira software, component phases of the cement paste such as pores, hydration products, and unhydrated clinker particles were segmented from each other based on their 3D image grey levels; their relative contents were also calculated with the software, and the data are 61.2%, 0% and 38.8% at the beginning of hydration and 11.8%, 78.5% and 9.7% at 28 d age, respectively. The hydration degree of cement paste at different ages was compared with the experimental data acquired by loss on ignition (LOI) tests. The results show that the calculated and measured data reasonably agree with each other, which indicates that micro-CT is a useful and reliable approach to characterize the micro structure evolution of hydrating cement paste.展开更多
A finite element reconstruction algorithm for ultrasound tomography based on the Helmholtz equation in frequency domain is presented to monitor the grouting defects in reinforced concrete structures.In this algorithm,...A finite element reconstruction algorithm for ultrasound tomography based on the Helmholtz equation in frequency domain is presented to monitor the grouting defects in reinforced concrete structures.In this algorithm,a hybrid regularizations-based iterative Newton method is implemented to provide stable inverse solutions.Furthermore,a dual mesh scheme and an adjoint method are adopted to reduce the computation cost and improve the efficiency of reconstruction.Simultaneous reconstruction of both acoustic velocity and attenuation coefficient for a reinforced concrete model is achieved with multiple frequency data.The algorithm is evaluated with numerical simulation under various practical scenarios including varied transmission/receiving modes,different noise levels,different source/detector numbers,and different contrast levels between the heterogeneity and background region.Results obtained suggest that the algorithm is insensitive to noise,and the reconstructions are quantitatively accurate in terms of the location,size and acoustic properties of the target over a range of contrast levels.展开更多
Objective To observe the value of self-supervised deep learning artificial intelligence(AI)noise reduction technology based on the nearest adjacent layer applicated in ultra-low dose CT(ULDCT)for urinary calculi.Metho...Objective To observe the value of self-supervised deep learning artificial intelligence(AI)noise reduction technology based on the nearest adjacent layer applicated in ultra-low dose CT(ULDCT)for urinary calculi.Methods Eighty-eight urinary calculi patients were prospectively enrolled.Low dose CT(LDCT)and ULDCT scanning were performed,and the effective dose(ED)of each scanning protocol were calculated.The patients were then randomly divided into training set(n=75)and test set(n=13),and a self-supervised deep learning AI noise reduction system based on the nearest adjacent layer constructed with ULDCT images in training set was used for reducing noise of ULDCT images in test set.In test set,the quality of ULDCT images before and after AI noise reduction were compared with LDCT images,i.e.Blind/Referenceless Image Spatial Quality Evaluator(BRISQUE)scores,image noise(SD ROI)and signal-to-noise ratio(SNR).Results The tube current,the volume CT dose index and the dose length product of abdominal ULDCT scanning protocol were all lower compared with those of LDCT scanning protocol(all P<0.05),with a decrease of ED for approximately 82.66%.For 13 patients with urinary calculi in test set,BRISQUE score showed that the quality level of ULDCT images before AI noise reduction reached 54.42%level but raised to 95.76%level of LDCT images after AI noise reduction.Both ULDCT images after AI noise reduction and LDCT images had lower SD ROI and higher SNR than ULDCT images before AI noise reduction(all adjusted P<0.05),whereas no significant difference was found between the former two(both adjusted P>0.05).Conclusion Self-supervised learning AI noise reduction technology based on the nearest adjacent layer could effectively reduce noise and improve image quality of urinary calculi ULDCT images,being conducive for clinical application of ULDCT.展开更多
Dual-layer spectral detector CT is a new spectrum CT imaging technology based on detector being able to obtain both images similar to true plain and spectral images in one time scanning.The reconstructed multi-paramet...Dual-layer spectral detector CT is a new spectrum CT imaging technology based on detector being able to obtain both images similar to true plain and spectral images in one time scanning.The reconstructed multi-parameter spectral images can not only improve image quality,enhance tissue contrast,increase the visualization and detection ability of occult lesions,but also provide qualitative and quantitative analysis of the lesions,so as to provide more imaging information and multi-dimensional diagnostic basis.The research progresses of dual-layer spectral detector CT for preoperative evaluation on colorectal cancer were reviewed in this article.展开更多
Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quan...Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1—L3 vertebrae were measured based on QCT.Spongy bones of T5—T10 vertebrae were segmented as ROI,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,ML Bagging-OP and Rad Bagging-OP had the best performances for classification of OP.In test set,AUC of ML Bagging-OP,Rad Bagging-OP and DL OP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P>0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of Ax-G±1.96 s),which were highly positively correlated(r=0.910—0.974,all P<0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.展开更多
Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium...Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium oxalate monohydrate stone group(group A,n=373),anhydrous uric acid stone group(group B,n=86),carbonate apatite group(group C,n=30),ammonium urate stone group(group D,n=28)and ammonium magnesium phosphate hexahydrate stone group(group E,n=26)according to the composition of calculi,also divided into training set and test set at the ratio of 7∶3.Radiomics features were extracted and screened based on plain CT images of urinary system.Five binary task models(model A—E corresponding to group A—E)and a quinary task model were constructed using least absolute shrinkage and selection operator algorithm for predicting the composition of calculi in vivo.Then receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of binary task models,while the accuracy,precision,recall and F1 score were used to evaluate the predictive efficacy of the quinary task model.Results All binary task models had good efficacy for predicting the composition of urinary calculi in vivo,with AUC of 0.860—0.948 in training set and of 0.856—0.933 in test set.The accuracy,precision,recall and F1 score of the quinary task model for predicting the composition of in vivo urinary calculi was 82.25%,83.79%,46.23%and 0.596 in training set,respectively,while was 80.63%,75.26%,43.48%and 0.551 in test set,respectively.Conclusion Binary task radiomics models based on preoperative plain CT had good efficacy for predicting the composition of in vivo urinary calculi,while the quinary task radiomics model had high accuracy but relatively poor stability.展开更多
Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were col...Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were collected(segmented dataset),and chest CT data of 984 patients were screened from the COVID 19-CT dataset(10 cases were randomly selected as whole test dataset,the remaining 974 cases were selected as layer selection dataset).T7—T8 layer was classified based on convolutional neural network(CNN)derived networks,including ResNet,ResNeXt,MobileNet,ShuffleNet,DenseNet,EfficientNet and ConvNeXt,then the accuracy,precision,recall and specificity were used to evaluate the performance of layer selection dataset.The skeletal muscle(SM),subcutaneous adipose tissue(SAT),intermuscular adipose tissue(IMAT)and visceral adipose tissue(VAT)were segmented using classical fully CNN(FCN)derived network,including FCN,SegNet,UNet,Attention UNet,UNET++,nnUNet,UNeXt and CMUNeXt,then Dice similarity coefficient(DSC),intersection over union(IoU)and 95 Hausdorff distance(HD)were used to evaluate the performance of segmented dataset.The automatic body composition analysis system was constructed based on optimal layer selection network and segmentation network,the mean absolute error(MAE),root mean squared error(RMSE)and standard deviation(SD)of MAE were used to evaluate the performance of automatic system for testing the whole test dataset.Results The accuracy,precision,recall and specificity of DenseNet network for automatically classifying T7—T8 layer from chest CT images was 95.06%,84.83%,92.27%and 95.78%,respectively,which were all higher than those of the other layer selection networks.In segmentation of SM,SAT,IMAT and overall,DSC and IoU of UNet++network were all higher,while 95HD of UNet++network were all lower than those of the other segmentation networks.Using DenseNet as the layer selection network and UNet++as the segmentation network,MAE of the automatic body composition analysis system for predicting SM,SAT,IMAT,VAT and MAE was 27.09,6.95,6.65 and 3.35 cm 2,respectively.Conclusion The body composition analysis system based on chest CT could be used to assess content of chest muscle and adipose.Among them,the UNet++network had better segmentation performance in adipose tissue than SM.展开更多
Objective To observe the correlations of chest CT quantitative parameters in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with blood eosinophil(EOS)level.Methods Chest CT data of 16...Objective To observe the correlations of chest CT quantitative parameters in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with blood eosinophil(EOS)level.Methods Chest CT data of 162 AECOPD patients with elevated eosinophils were retrospectively analyzed.The patients were divided into low EOS group(n=105)and high EOS group(n=57)according to the absolute counting of blood EOS.The quantitative CT parameters,including the number of whole lung bronchi and the volume of blood vessels,low-attenuation area percentage(LAA%)of whole lung,of left/right lung and each lobe of lung,as well as the luminal diameter(LD),wall thickness(WT),wall area(WA)and WA percentage of total bronchial cross-section(WA%)of grade 3 to 8 bronchi were compared between groups.Spearman correlations were performed to analyze the correlations of quantitative CT parameters with blood EOS level.Results LAA%of the whole lung,of the left/right lung and each lobe of lung,as well as of the upper lobe of right lung LD grade 4,middle lobe of right lung WT grade 5,upper lobe of right lung WA grade 4,middle lobe of right lung WA grade 5 and lower lobe of left lung WA grade 3 in low EOS group were all higher than those in high EOS group(all P<0.05).Except for the upper lobe of right lung LD grade 4,the above quantitative CT indexes being significant different between groups were all weakly and negatively correlated with blood EOS level(r=-0.335 to-0.164,all P<0.05).Conclusion Chest CT quantitative parameters of AECOPD patients were correlated with blood EOS level,among which LAA%,a part of WT and WA were all weakly negatively correlated with blood EOS level.展开更多
Objective To observe the efficacy of deep learning(DL)model based on PET/CT and its combination with Cox proportional hazard model for predicting progressive disease(PD)of lung invasive adenocarcinoma within 5 years a...Objective To observe the efficacy of deep learning(DL)model based on PET/CT and its combination with Cox proportional hazard model for predicting progressive disease(PD)of lung invasive adenocarcinoma within 5 years after surgery.Methods The clinical,PET/CT and 5-year follow-up data of 250 patients with lung invasive adenocarcinoma were retrospectively analyzed.According to PD or not,the patients were divided into the PD group(n=71)and non-PD group(n=179).The basic data and PET/CT findings were compared between groups,among which the quantitative variables being significant different between groups were transformed to categorical variables using receiver operating characteristic(ROC)curve and corresponding cut-off value.Multivariant Cox proportional hazard model was used to select independent predicting factors of PD of lung invasive adenocarcinoma within 5 years after surgery.The patients were divided into training,validation and test sets at the ratio of 6∶2∶2,and PET/CT data in training set and validation set were used to train model and tuning parameters to build the PET/CT DL model,and the combination model was built in serial connection of DL model and the predictive factors.In test set,the efficacy of each model for predicting PD of lung invasive adenocarcinoma within 5 years after surgery was assessed and compared using the area under the curve(AUC).Results Patients'gender and smoking status,as well as the long diameter,SUV max and SUV mean of lesions measured on PET images,the long diameter,short diameter and type of lesions showed on CT were statistically different between groups(all P<0.05).Smoking(HR=1.787[1.053,3.031],P=0.031)and lesion SUV max>4.15(HR=5.249[1.062,25.945],P=0.042)were both predictors of PD of lung invasive adenocarcinoma within 5 years after surgery.In test set,the AUC of PET/CT DL model for predicting PD was 0.847,of the combination model was 0.890,of the latter was higher than of the former(P=0.036).Conclusion DL model based on PET/CT had high efficacy for predicting PD of lung invasive adenocarcinoma within 5 years after surgery.Combining with Cox proportional hazard model could further improve its predicting efficacy.展开更多
X-ray computed tomography(CT)has been an important technology in paleontology for several decades.It helps researchers to acquire detailed anatomical structures of fossils non-destructively.Despite its widespread appl...X-ray computed tomography(CT)has been an important technology in paleontology for several decades.It helps researchers to acquire detailed anatomical structures of fossils non-destructively.Despite its widespread application,developing an efficient and user-friendly method for segmenting CT data continues to be a formidable challenge in the field.Most CT data segmentation software operates on 2D interfaces,which limits flexibility for real-time adjustments in 3D segmentation.Here,we introduce Curves Mode in Drishti Paint 3.2,an open-source tool for CT data segmentation.Drishti Paint 3.2 allows users to manually or semi-automatically segment the CT data in both 2D and 3D environments,providing a novel solution for revisualizing CT data in paleontological studies.展开更多
Objective To observe value of 0D-1D coupling model and 3D fluid-structure interaction(FSI)model based on coronary CT angiography(CCTA)for displaying hemodynamic characteristics of coronary artery stenosis.Methods Base...Objective To observe value of 0D-1D coupling model and 3D fluid-structure interaction(FSI)model based on coronary CT angiography(CCTA)for displaying hemodynamic characteristics of coronary artery stenosis.Methods Based on CCTA data of the stenosed left anterior descending branch(LAD)in a patient with coronary heart disease,an 0D-1D coupling model and 3D FSI model were built,respectively.Then hemodynamic characteristic indexes,including the pressure,flow velocity and wall shear stress(WSS)were obtained in every 0.01 s during 1 s at 5 sampling points(i.e.sampling point 1—5)using these 2 models,respectively,and the consistencies of the results between models were evaluated with Spearman correlation coefficient r s.Results The time consuming for construction of 0D-1D coupling model and 3D FSI model was 0.033 min and 704 min,respectively.Both models showed basically distribution of the pressure,flow velocity and WSS of the stenosed LAD.For more details,the pressure at the stenosed segment of LAD and the proximal segment of stenosis were both higher,which gradually decreased at the distal segment of stenosis,and the flow velocity at the proximal segment of stenosis was in a relatively slow and uniform condition,with significantly increased flow velocity and WSS at the stenosed segment.Compared with 3D FSI model,0D-1D vascular coupling model was relatively unrefined and lack of distal flow lines when displaying blood flow velocity.For sampling point 2 at the stenosed segment of LAD,no significant consistency for pressure between 2 models was found(P=0.118),but strong consistency for the flow velocity and WSS(r s=0.730,0.807,both P<0.05).The consistencies of pressure,flow velocity and WSS between 2 models at the proximal and distal segment of stenosis,i.e.1,3—5 sampling points were week to moderate(r s=0.237—0.669,all P<0.05).Conclusion 0D-1D coupling model exhibited outstanding computational efficiency and might provide relatively reasonable results,while 3D FSI model showed higher accuracy for details and streamline when simulating LAD stenosis.展开更多
A novel method was developed to establish a realistic three dimensional(3D) network model representing pore space in low permeability sandstone.Digital core of rock sample was established by the combination of micro-C...A novel method was developed to establish a realistic three dimensional(3D) network model representing pore space in low permeability sandstone.Digital core of rock sample was established by the combination of micro-CT scanning and image processing,then 3D pore-throat network model was extracted from the digital core through analyzing pore space topology,calculating pore-throat parameters and simplifying the shapes of pores and throats.The good agreements between predicted and measured porosity and absolute permeability verified the validity of this new network model.Gas-water flow mechanism was studied by using pore-scale simulations,and the influence of pore structure parameters,including coordination number,aspect ratio and shape factor,on gas-water flow,was investigated.The present simulation results show that with the increment of coordination number,gas flow ability in network improves and the effect of invading water on blocking gas flow weakens.The smaller the aspect ratio is,the stronger the anisotropy of the network is,resulting in the increase of seepage resistance.It is found that the shape factor mainly affects the end points in relative permeability curves,and for a highly irregular pore or throat with a small shape factor,the irreducible water saturation(Swi) and residual gas saturation(Sgr) are relatively high.展开更多
Micro porosity in aluminum alloys may contribute to fatigue life degradation, which can largely limit the application of alloys. Therefore, the fatigue life of a commercial 7050-T7451 thick plate and an experimental p...Micro porosity in aluminum alloys may contribute to fatigue life degradation, which can largely limit the application of alloys. Therefore, the fatigue life of a commercial 7050-T7451 thick plate and an experimental plate with different porosities was compared in this study. The X-ray computed tomography(XCT) was utilized to characterize the size, number density and spatial distribution of porosity inside various samples, and the fracture surface of fatigued specimens was compared by using scanning electron microscope(SEM). The results showed that the fatigue cracks prefer to initiate from constituent particles in the commercial alloy. Whereas the micro porosity is the predominant site for crack nucleation and subsequent failure in the experimental one. The presence of micro porosity in experimental7050-T7451 thick plate may reduce the fatigue life by an order of magnitude or more compared with the defect-free alloy. The pores close to sample surface are the main fatigue crack initiation site, among which larger and deeper pore leads to a shorter fatigue life. The crack initiation is also affected by the pore geometry and direction. Besides, the overall porosity inside the bulk can affect the crack propagation during fatigue tests.展开更多
Background and objective Low-density computed tomography(LDCT)improved early lung cancer diagnosis but introduces an excess of false-positive pulmonary nodules data.Hence,accurate diagnosis of early-stage lung cancer ...Background and objective Low-density computed tomography(LDCT)improved early lung cancer diagnosis but introduces an excess of false-positive pulmonary nodules data.Hence,accurate diagnosis of early-stage lung cancer remains challenging.The purpose of the study was to assess the feasibility of using circulating tumour cells(CTCs)to differentiate malignant from benign pulmonary nodules.Materials and methods 122 patients with suspected malignant pulmonary nodules detected on chest CT in preparation for surgery were prospectively recruited.Peripheral blood samples were collected before surgery,and CTCs were identified upon isolation by size of epithelial tumour cells and morphological analysis.Laser capture microdissection,MALBAC amplification,and whole-exome sequencing were performed on 8 samples.The diagnostic efficacy of CTCs counting,and the genomic variation profile of benign and malignant CTCs samples were analysed.Results Using 2.5 cells/5 m L as the cut-off value,the area under the receiver operating characteristic curve was of 0.651(95%confidence interval:0.538-0.764),with a sensitivity and specificity of 0.526 and 0.800,respectively,and positive and negative predictive values of 91.1%and 30.3%,respectively.Distinct sequence variations differences in DNA damage repair-related and driver genes were observed in benign and malignant samples.TP53 mutations were identified in CTCs of four malignant cases;in particular,g.7578115T>C,g.7578645C>T,and g.7579472G>C were exclusively detected in all four malignant samples.Conclusion CTCs play an ancillary role in the diagnosis of pulmonary nodules.TP53 mutations in CTCs might be used to identify benign and malignant pulmonary nodules.展开更多
As an innovative propulsion technique, combustion mechanism of laser-augmented chemical propulsion has still to be ascertained. Benefiting from high nitrogen content and thermal stability, 5-aminotetrazole is a suitab...As an innovative propulsion technique, combustion mechanism of laser-augmented chemical propulsion has still to be ascertained. Benefiting from high nitrogen content and thermal stability, 5-aminotetrazole is a suitable ingredient for LACP. Under a flowing nitrogen environment, two kinds of unique burning surfaces were observed to occur for 5-ATZ, used as a single reacting propellant ingredient with the addition of carbon, under laser ablation. Both surfaces are hollow structures and differ by the possible presence of edges. Using micro computed tomography, the 3D perspective structures of both surfaces were revealed. Resorting to various characterization methods, a unified formation mechanism for both surfaces is proposed. This mechanism specifically applies to laser ablation, but could be crucial to common burning mechanisms in LACP.展开更多
As an innovative propulsion technique, laser augmented chemical propulsion(LACP) seems superior to the traditional ones. However, the corresponding combustion theories have still to be ascertained for LACP. Burning ra...As an innovative propulsion technique, laser augmented chemical propulsion(LACP) seems superior to the traditional ones. However, the corresponding combustion theories have still to be ascertained for LACP. Burning rate of 5-aminotetrazole(5-ATZ) propellant has been studied by testing pressed samples under different combustor pressures and laser powers. Based on micro computed tomography(Micro CT),an advanced thickness-over-time(TOT) method to characterize the regression of the produced nonplanar burning surface is established. Because of a shell structure covering the combustion surface,the burning rate of the implemented 5-ATZ propellant is not constant during laser ablation. Resorting to functional fitting, a new law of non-constant burning including the effect of the observed unique burning surface structures is proposed. Accordingly, applicable combustion conditions of 5-ATZ based propellants have been preliminarily speculated for future research activities.展开更多
文摘Objective:To perform a meta-analysis to evaluate the diagnostic performance of computed tomography(CT) and transthoracic echocardiography(TTE) in complex congenital heart diseases(CHD) in China.Methods:MEDLINE,Cochrane library and China National Knowledge Infrastructure(CNKI) database from January 1966 to October 2010,were searched for initial studies in China.All the studies,published in English or Chinese,used TTE,CT,or both as diagnostic tests for CHD and reported the rate of true-positive,true-negative,false-positive and false-negative diagnoses of CHD from TTE and CT findings with the surgical results as the 'gold-standard'(15 studies,XX patients) were collected.The statistic software package,'Meta-Disc 1.4',was used to conduct data analysis.A covariate analysis was used to evaluate the influence of patient or study-related factors on sensitivity.Results:Pooled sensitivity for diagnosis of CHD were 95% [95% confidence interval(CI):94%~96%] for CT studies and 87%(95% CI:85%~88%) for TTE studies.The difference between the pooled sensitivity of CT and that of TTE was statistically significant(P<0.001).TTE had higher sensitivity [0.96(95% CI:0.94~0.97)] for cardiac malformation but lower sensitivity [0.78(95% CI:0.76~0.81)] for extracardiac malformation than CT.Conclusion:CT can provide added diagnostic information compared with TTE in patients with CHD in China,especially for patients suspected of extracardiac malformation.
基金Projects(41572277,41877229)supported by the National Natural Science Foundation of ChinaProject(2015A030313118)supported by the Natural Science Foundation of Guangdong Province,ChinaProject(201607010023)supported by the Science and Technology Program of Guangzhou,China
文摘A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d<0.075 mm,0.075 mm≤d<0.1 mm,0.1 mm≤d<0.2 mm,0.2 mm≤d<0.5 mm and 0.5 mm≤d<1.0 mm)to study the structures and particle contacts of granite residual soil.The X-ray micro computed tomography method was used to reconstruct the microstructure of granite residual soil.The particle was identified and regularized using principal component analysis(PCA).The particle contacts and geometrical characteristics in 3D space were analyzed and summarized using statistical analyses.The results demonstrate that the main types of contact among the particles are face-face,face-angle,face-edge,edge-edge,edge-angle and angle-angle contacts for particle sizes less than 0.2 mm.When the particle sizes are greater than 0.2 mm,the contacts are effectively summarized as face-face,face-angle,face-edge,edge-edge,edge-angle,angle-angle,sphere-sphere,sphere-face,sphere-edge and sphere-angle contacts.The differences in porosity among the original sample,reconstructed sample and regularized sample are closely related to the water-swelling and water-disintegrable characteristics of granite residual soil.
基金Project(2009CB623201) supported by the National Basic Research Program of ChinaProjects(50902106, 51272193) supported by the National Natural Science Foundation of ChinaProject(NCET-10-0660) supported by New Century Excellent Talents in Universities of China
文摘Micro computed tomography (Micro-CT) was applied to obtain three-dimensional images of the microstructure of cement paste (water-to-cement mass ratio of 0.5) at different ages. By using the Amira software, component phases of the cement paste such as pores, hydration products, and unhydrated clinker particles were segmented from each other based on their 3D image grey levels; their relative contents were also calculated with the software, and the data are 61.2%, 0% and 38.8% at the beginning of hydration and 11.8%, 78.5% and 9.7% at 28 d age, respectively. The hydration degree of cement paste at different ages was compared with the experimental data acquired by loss on ignition (LOI) tests. The results show that the calculated and measured data reasonably agree with each other, which indicates that micro-CT is a useful and reliable approach to characterize the micro structure evolution of hydrating cement paste.
基金Project(31200748)supported by the National Natural Science Foundation of China
文摘A finite element reconstruction algorithm for ultrasound tomography based on the Helmholtz equation in frequency domain is presented to monitor the grouting defects in reinforced concrete structures.In this algorithm,a hybrid regularizations-based iterative Newton method is implemented to provide stable inverse solutions.Furthermore,a dual mesh scheme and an adjoint method are adopted to reduce the computation cost and improve the efficiency of reconstruction.Simultaneous reconstruction of both acoustic velocity and attenuation coefficient for a reinforced concrete model is achieved with multiple frequency data.The algorithm is evaluated with numerical simulation under various practical scenarios including varied transmission/receiving modes,different noise levels,different source/detector numbers,and different contrast levels between the heterogeneity and background region.Results obtained suggest that the algorithm is insensitive to noise,and the reconstructions are quantitatively accurate in terms of the location,size and acoustic properties of the target over a range of contrast levels.
文摘Objective To observe the value of self-supervised deep learning artificial intelligence(AI)noise reduction technology based on the nearest adjacent layer applicated in ultra-low dose CT(ULDCT)for urinary calculi.Methods Eighty-eight urinary calculi patients were prospectively enrolled.Low dose CT(LDCT)and ULDCT scanning were performed,and the effective dose(ED)of each scanning protocol were calculated.The patients were then randomly divided into training set(n=75)and test set(n=13),and a self-supervised deep learning AI noise reduction system based on the nearest adjacent layer constructed with ULDCT images in training set was used for reducing noise of ULDCT images in test set.In test set,the quality of ULDCT images before and after AI noise reduction were compared with LDCT images,i.e.Blind/Referenceless Image Spatial Quality Evaluator(BRISQUE)scores,image noise(SD ROI)and signal-to-noise ratio(SNR).Results The tube current,the volume CT dose index and the dose length product of abdominal ULDCT scanning protocol were all lower compared with those of LDCT scanning protocol(all P<0.05),with a decrease of ED for approximately 82.66%.For 13 patients with urinary calculi in test set,BRISQUE score showed that the quality level of ULDCT images before AI noise reduction reached 54.42%level but raised to 95.76%level of LDCT images after AI noise reduction.Both ULDCT images after AI noise reduction and LDCT images had lower SD ROI and higher SNR than ULDCT images before AI noise reduction(all adjusted P<0.05),whereas no significant difference was found between the former two(both adjusted P>0.05).Conclusion Self-supervised learning AI noise reduction technology based on the nearest adjacent layer could effectively reduce noise and improve image quality of urinary calculi ULDCT images,being conducive for clinical application of ULDCT.
文摘Dual-layer spectral detector CT is a new spectrum CT imaging technology based on detector being able to obtain both images similar to true plain and spectral images in one time scanning.The reconstructed multi-parameter spectral images can not only improve image quality,enhance tissue contrast,increase the visualization and detection ability of occult lesions,but also provide qualitative and quantitative analysis of the lesions,so as to provide more imaging information and multi-dimensional diagnostic basis.The research progresses of dual-layer spectral detector CT for preoperative evaluation on colorectal cancer were reviewed in this article.
文摘Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1—L3 vertebrae were measured based on QCT.Spongy bones of T5—T10 vertebrae were segmented as ROI,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,ML Bagging-OP and Rad Bagging-OP had the best performances for classification of OP.In test set,AUC of ML Bagging-OP,Rad Bagging-OP and DL OP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P>0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of Ax-G±1.96 s),which were highly positively correlated(r=0.910—0.974,all P<0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.
文摘Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium oxalate monohydrate stone group(group A,n=373),anhydrous uric acid stone group(group B,n=86),carbonate apatite group(group C,n=30),ammonium urate stone group(group D,n=28)and ammonium magnesium phosphate hexahydrate stone group(group E,n=26)according to the composition of calculi,also divided into training set and test set at the ratio of 7∶3.Radiomics features were extracted and screened based on plain CT images of urinary system.Five binary task models(model A—E corresponding to group A—E)and a quinary task model were constructed using least absolute shrinkage and selection operator algorithm for predicting the composition of calculi in vivo.Then receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of binary task models,while the accuracy,precision,recall and F1 score were used to evaluate the predictive efficacy of the quinary task model.Results All binary task models had good efficacy for predicting the composition of urinary calculi in vivo,with AUC of 0.860—0.948 in training set and of 0.856—0.933 in test set.The accuracy,precision,recall and F1 score of the quinary task model for predicting the composition of in vivo urinary calculi was 82.25%,83.79%,46.23%and 0.596 in training set,respectively,while was 80.63%,75.26%,43.48%and 0.551 in test set,respectively.Conclusion Binary task radiomics models based on preoperative plain CT had good efficacy for predicting the composition of in vivo urinary calculi,while the quinary task radiomics model had high accuracy but relatively poor stability.
文摘Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were collected(segmented dataset),and chest CT data of 984 patients were screened from the COVID 19-CT dataset(10 cases were randomly selected as whole test dataset,the remaining 974 cases were selected as layer selection dataset).T7—T8 layer was classified based on convolutional neural network(CNN)derived networks,including ResNet,ResNeXt,MobileNet,ShuffleNet,DenseNet,EfficientNet and ConvNeXt,then the accuracy,precision,recall and specificity were used to evaluate the performance of layer selection dataset.The skeletal muscle(SM),subcutaneous adipose tissue(SAT),intermuscular adipose tissue(IMAT)and visceral adipose tissue(VAT)were segmented using classical fully CNN(FCN)derived network,including FCN,SegNet,UNet,Attention UNet,UNET++,nnUNet,UNeXt and CMUNeXt,then Dice similarity coefficient(DSC),intersection over union(IoU)and 95 Hausdorff distance(HD)were used to evaluate the performance of segmented dataset.The automatic body composition analysis system was constructed based on optimal layer selection network and segmentation network,the mean absolute error(MAE),root mean squared error(RMSE)and standard deviation(SD)of MAE were used to evaluate the performance of automatic system for testing the whole test dataset.Results The accuracy,precision,recall and specificity of DenseNet network for automatically classifying T7—T8 layer from chest CT images was 95.06%,84.83%,92.27%and 95.78%,respectively,which were all higher than those of the other layer selection networks.In segmentation of SM,SAT,IMAT and overall,DSC and IoU of UNet++network were all higher,while 95HD of UNet++network were all lower than those of the other segmentation networks.Using DenseNet as the layer selection network and UNet++as the segmentation network,MAE of the automatic body composition analysis system for predicting SM,SAT,IMAT,VAT and MAE was 27.09,6.95,6.65 and 3.35 cm 2,respectively.Conclusion The body composition analysis system based on chest CT could be used to assess content of chest muscle and adipose.Among them,the UNet++network had better segmentation performance in adipose tissue than SM.
文摘Objective To observe the correlations of chest CT quantitative parameters in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with blood eosinophil(EOS)level.Methods Chest CT data of 162 AECOPD patients with elevated eosinophils were retrospectively analyzed.The patients were divided into low EOS group(n=105)and high EOS group(n=57)according to the absolute counting of blood EOS.The quantitative CT parameters,including the number of whole lung bronchi and the volume of blood vessels,low-attenuation area percentage(LAA%)of whole lung,of left/right lung and each lobe of lung,as well as the luminal diameter(LD),wall thickness(WT),wall area(WA)and WA percentage of total bronchial cross-section(WA%)of grade 3 to 8 bronchi were compared between groups.Spearman correlations were performed to analyze the correlations of quantitative CT parameters with blood EOS level.Results LAA%of the whole lung,of the left/right lung and each lobe of lung,as well as of the upper lobe of right lung LD grade 4,middle lobe of right lung WT grade 5,upper lobe of right lung WA grade 4,middle lobe of right lung WA grade 5 and lower lobe of left lung WA grade 3 in low EOS group were all higher than those in high EOS group(all P<0.05).Except for the upper lobe of right lung LD grade 4,the above quantitative CT indexes being significant different between groups were all weakly and negatively correlated with blood EOS level(r=-0.335 to-0.164,all P<0.05).Conclusion Chest CT quantitative parameters of AECOPD patients were correlated with blood EOS level,among which LAA%,a part of WT and WA were all weakly negatively correlated with blood EOS level.
文摘Objective To observe the efficacy of deep learning(DL)model based on PET/CT and its combination with Cox proportional hazard model for predicting progressive disease(PD)of lung invasive adenocarcinoma within 5 years after surgery.Methods The clinical,PET/CT and 5-year follow-up data of 250 patients with lung invasive adenocarcinoma were retrospectively analyzed.According to PD or not,the patients were divided into the PD group(n=71)and non-PD group(n=179).The basic data and PET/CT findings were compared between groups,among which the quantitative variables being significant different between groups were transformed to categorical variables using receiver operating characteristic(ROC)curve and corresponding cut-off value.Multivariant Cox proportional hazard model was used to select independent predicting factors of PD of lung invasive adenocarcinoma within 5 years after surgery.The patients were divided into training,validation and test sets at the ratio of 6∶2∶2,and PET/CT data in training set and validation set were used to train model and tuning parameters to build the PET/CT DL model,and the combination model was built in serial connection of DL model and the predictive factors.In test set,the efficacy of each model for predicting PD of lung invasive adenocarcinoma within 5 years after surgery was assessed and compared using the area under the curve(AUC).Results Patients'gender and smoking status,as well as the long diameter,SUV max and SUV mean of lesions measured on PET images,the long diameter,short diameter and type of lesions showed on CT were statistically different between groups(all P<0.05).Smoking(HR=1.787[1.053,3.031],P=0.031)and lesion SUV max>4.15(HR=5.249[1.062,25.945],P=0.042)were both predictors of PD of lung invasive adenocarcinoma within 5 years after surgery.In test set,the AUC of PET/CT DL model for predicting PD was 0.847,of the combination model was 0.890,of the latter was higher than of the former(P=0.036).Conclusion DL model based on PET/CT had high efficacy for predicting PD of lung invasive adenocarcinoma within 5 years after surgery.Combining with Cox proportional hazard model could further improve its predicting efficacy.
文摘X-ray computed tomography(CT)has been an important technology in paleontology for several decades.It helps researchers to acquire detailed anatomical structures of fossils non-destructively.Despite its widespread application,developing an efficient and user-friendly method for segmenting CT data continues to be a formidable challenge in the field.Most CT data segmentation software operates on 2D interfaces,which limits flexibility for real-time adjustments in 3D segmentation.Here,we introduce Curves Mode in Drishti Paint 3.2,an open-source tool for CT data segmentation.Drishti Paint 3.2 allows users to manually or semi-automatically segment the CT data in both 2D and 3D environments,providing a novel solution for revisualizing CT data in paleontological studies.
文摘Objective To observe value of 0D-1D coupling model and 3D fluid-structure interaction(FSI)model based on coronary CT angiography(CCTA)for displaying hemodynamic characteristics of coronary artery stenosis.Methods Based on CCTA data of the stenosed left anterior descending branch(LAD)in a patient with coronary heart disease,an 0D-1D coupling model and 3D FSI model were built,respectively.Then hemodynamic characteristic indexes,including the pressure,flow velocity and wall shear stress(WSS)were obtained in every 0.01 s during 1 s at 5 sampling points(i.e.sampling point 1—5)using these 2 models,respectively,and the consistencies of the results between models were evaluated with Spearman correlation coefficient r s.Results The time consuming for construction of 0D-1D coupling model and 3D FSI model was 0.033 min and 704 min,respectively.Both models showed basically distribution of the pressure,flow velocity and WSS of the stenosed LAD.For more details,the pressure at the stenosed segment of LAD and the proximal segment of stenosis were both higher,which gradually decreased at the distal segment of stenosis,and the flow velocity at the proximal segment of stenosis was in a relatively slow and uniform condition,with significantly increased flow velocity and WSS at the stenosed segment.Compared with 3D FSI model,0D-1D vascular coupling model was relatively unrefined and lack of distal flow lines when displaying blood flow velocity.For sampling point 2 at the stenosed segment of LAD,no significant consistency for pressure between 2 models was found(P=0.118),but strong consistency for the flow velocity and WSS(r s=0.730,0.807,both P<0.05).The consistencies of pressure,flow velocity and WSS between 2 models at the proximal and distal segment of stenosis,i.e.1,3—5 sampling points were week to moderate(r s=0.237—0.669,all P<0.05).Conclusion 0D-1D coupling model exhibited outstanding computational efficiency and might provide relatively reasonable results,while 3D FSI model showed higher accuracy for details and streamline when simulating LAD stenosis.
基金Project(2013CB228005) supported by the National Program on Key Fundamental Research Project of ChinaProject(14ZB0047) supported by the Department of Education of Sichuan Province,China
文摘A novel method was developed to establish a realistic three dimensional(3D) network model representing pore space in low permeability sandstone.Digital core of rock sample was established by the combination of micro-CT scanning and image processing,then 3D pore-throat network model was extracted from the digital core through analyzing pore space topology,calculating pore-throat parameters and simplifying the shapes of pores and throats.The good agreements between predicted and measured porosity and absolute permeability verified the validity of this new network model.Gas-water flow mechanism was studied by using pore-scale simulations,and the influence of pore structure parameters,including coordination number,aspect ratio and shape factor,on gas-water flow,was investigated.The present simulation results show that with the increment of coordination number,gas flow ability in network improves and the effect of invading water on blocking gas flow weakens.The smaller the aspect ratio is,the stronger the anisotropy of the network is,resulting in the increase of seepage resistance.It is found that the shape factor mainly affects the end points in relative permeability curves,and for a highly irregular pore or throat with a small shape factor,the irreducible water saturation(Swi) and residual gas saturation(Sgr) are relatively high.
基金Project(2019KJ2X08-4) supported by Chinalco Technology Development Project Fund,China。
文摘Micro porosity in aluminum alloys may contribute to fatigue life degradation, which can largely limit the application of alloys. Therefore, the fatigue life of a commercial 7050-T7451 thick plate and an experimental plate with different porosities was compared in this study. The X-ray computed tomography(XCT) was utilized to characterize the size, number density and spatial distribution of porosity inside various samples, and the fracture surface of fatigued specimens was compared by using scanning electron microscope(SEM). The results showed that the fatigue cracks prefer to initiate from constituent particles in the commercial alloy. Whereas the micro porosity is the predominant site for crack nucleation and subsequent failure in the experimental one. The presence of micro porosity in experimental7050-T7451 thick plate may reduce the fatigue life by an order of magnitude or more compared with the defect-free alloy. The pores close to sample surface are the main fatigue crack initiation site, among which larger and deeper pore leads to a shorter fatigue life. The crack initiation is also affected by the pore geometry and direction. Besides, the overall porosity inside the bulk can affect the crack propagation during fatigue tests.
基金supported by the grant from China-Japan Friendship Hospital Talent Introduction Research Start-up Fund(to Guang ying ZHU)(No.2016-RC-4)。
文摘Background and objective Low-density computed tomography(LDCT)improved early lung cancer diagnosis but introduces an excess of false-positive pulmonary nodules data.Hence,accurate diagnosis of early-stage lung cancer remains challenging.The purpose of the study was to assess the feasibility of using circulating tumour cells(CTCs)to differentiate malignant from benign pulmonary nodules.Materials and methods 122 patients with suspected malignant pulmonary nodules detected on chest CT in preparation for surgery were prospectively recruited.Peripheral blood samples were collected before surgery,and CTCs were identified upon isolation by size of epithelial tumour cells and morphological analysis.Laser capture microdissection,MALBAC amplification,and whole-exome sequencing were performed on 8 samples.The diagnostic efficacy of CTCs counting,and the genomic variation profile of benign and malignant CTCs samples were analysed.Results Using 2.5 cells/5 m L as the cut-off value,the area under the receiver operating characteristic curve was of 0.651(95%confidence interval:0.538-0.764),with a sensitivity and specificity of 0.526 and 0.800,respectively,and positive and negative predictive values of 91.1%and 30.3%,respectively.Distinct sequence variations differences in DNA damage repair-related and driver genes were observed in benign and malignant samples.TP53 mutations were identified in CTCs of four malignant cases;in particular,g.7578115T>C,g.7578645C>T,and g.7579472G>C were exclusively detected in all four malignant samples.Conclusion CTCs play an ancillary role in the diagnosis of pulmonary nodules.TP53 mutations in CTCs might be used to identify benign and malignant pulmonary nodules.
基金supported by the Shanghai Aerospace Science & Technology Innovation Fund (Grant No. SAST201363)the Fundamental Research Funds for the Central Universities (Grant No. 30919012102 in part)。
文摘As an innovative propulsion technique, combustion mechanism of laser-augmented chemical propulsion has still to be ascertained. Benefiting from high nitrogen content and thermal stability, 5-aminotetrazole is a suitable ingredient for LACP. Under a flowing nitrogen environment, two kinds of unique burning surfaces were observed to occur for 5-ATZ, used as a single reacting propellant ingredient with the addition of carbon, under laser ablation. Both surfaces are hollow structures and differ by the possible presence of edges. Using micro computed tomography, the 3D perspective structures of both surfaces were revealed. Resorting to various characterization methods, a unified formation mechanism for both surfaces is proposed. This mechanism specifically applies to laser ablation, but could be crucial to common burning mechanisms in LACP.
基金supported by the Shanghai Aerospace Science & Technology Innovation Fund (grant No. SAST201363)the Fundamental Research Funds for the Central Universities (grant No. 30919012102 in part)。
文摘As an innovative propulsion technique, laser augmented chemical propulsion(LACP) seems superior to the traditional ones. However, the corresponding combustion theories have still to be ascertained for LACP. Burning rate of 5-aminotetrazole(5-ATZ) propellant has been studied by testing pressed samples under different combustor pressures and laser powers. Based on micro computed tomography(Micro CT),an advanced thickness-over-time(TOT) method to characterize the regression of the produced nonplanar burning surface is established. Because of a shell structure covering the combustion surface,the burning rate of the implemented 5-ATZ propellant is not constant during laser ablation. Resorting to functional fitting, a new law of non-constant burning including the effect of the observed unique burning surface structures is proposed. Accordingly, applicable combustion conditions of 5-ATZ based propellants have been preliminarily speculated for future research activities.
