2020 Computing in Cardiology最新文献_第3页

Quantification of Ventricular Repolarization Fluctuations in Patients With Myocardial Infarction 心肌梗死患者心室复极波动的定量分析

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.168

Martin Schmidt, R. Dunker, H. Malberg, S. Zaunseder

{"title":"Quantification of Ventricular Repolarization Fluctuations in Patients With Myocardial Infarction","authors":"Martin Schmidt, R. Dunker, H. Malberg, S. Zaunseder","doi":"10.22489/CinC.2020.168","DOIUrl":"https://doi.org/10.22489/CinC.2020.168","url":null,"abstract":"The objective of this study was to quantify ventricular repolarization fluctuations in patients with myocardial infarction (MI) by a novel ECG waveform morphology based QT interval variability (QTV) measure. We analyzed recordings of 79 MI patients and 69 healthy control subjects included in the Physikalisch-Technische Bunde-sanstalt diagnostic ECG database. To characterize the QT interval waveform, we employed two-dimensional signal warping (2DSW). Based on the two-dimensional template adaptation to every beat, a novel parameter QTfluc has been developed to take into account complex QT interval's waveform fluctuations in time and amplitude. To demonstrate the power of QTfluc we (1) compared MI patients and healthy subjects and (2) examined the stability of various QTV measures including QTfluc in relation to QT interval boundary shifts. A comparison of QTfluc with standard QTV measures showed a significant improvement (ef-fect size increased up to 60 %) in discriminating between MI patients and healthy subjects. QT interval boundary shifts showed significant less impact (by factor 10) on the stability of QTfluc in comparison to standard QTV measures. The proposed measure showed significant improved characterization of ventricular repolarization lability in MI patients. Moreover, QTfluc showed more stable characteristics and is less dependent on QT interval boarders.","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129801992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Modelling Left Atrial Flow and Blood Coagulation for Risk of Thrombus Formation in Atrial Fibrillation 左房血流和血液凝固对房颤血栓形成风险的模拟

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/cinc.2020.219

A. Qureshi, Omar S Darwish, D. Dillon-Murphy, H. Chubb, Steven Williams, D. Nechipurenko, F. Ataullakhanov, D. Nordsletten, O. Aslanidi, A. Vecchi

{"title":"Modelling Left Atrial Flow and Blood Coagulation for Risk of Thrombus Formation in Atrial Fibrillation","authors":"A. Qureshi, Omar S Darwish, D. Dillon-Murphy, H. Chubb, Steven Williams, D. Nechipurenko, F. Ataullakhanov, D. Nordsletten, O. Aslanidi, A. Vecchi","doi":"10.22489/cinc.2020.219","DOIUrl":"https://doi.org/10.22489/cinc.2020.219","url":null,"abstract":"Atrial fibrillation (AF) diminishes left atrial (LA) mechanical function and impairs blood flow. The latter can lead to blood stasis and increased risk of thrombus formation and stroke. We investigate this risk by studying the effects of LA flow in sinus rhythm (SR) and AF on blood coagulation dynamics. Patient-specific computational fluid dynamics (CFD) simulations were coupled with the reaction-diffusion-convection equation for thrombin. Patient LA wall motions driving the flow were reconstructed from Cine MRI data during SR and AF. 15 cardiac cycles were simulated for each patient to evaluate the likelihood of thrombus formation in the critical left atrial appendage (LAA) and right inferior pulmonary vein (RIPV) regions. The simulations showed that mean blood flow velocity in the LA cavity was substantially decreased (47%) during AF compared to SR. Specifically in LAA, mean flow velocities decreased from 0.06m/s in SR to 0.035m/s in AF, leading to enhanced thrombin generation. In the RIPV, higher mean flow velocities (0.16m/s) enabled thrombin washout through the mitral valve irrespective of SR or AF. This study proposes a novel modelling approach for quantifying the likelihood of AF-related thrombogenesis within LA and demonstrates increased risk of thrombus formation in the LAA when compared with the RIPV.","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129116662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Potassium Monitoring From Multilead T-wave Morphology Changes During Hemodyalisis: Periodic Versus Principal Component Analysis 血肿期间多导联t波形态变化的钾监测:周期性与主成分分析

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.199

Flavio Palmieri, P. Gomis, J. E. Ruiz, D. Ferreira, A. Martín-Yebra, E. Pueyo, P. Laguna, J. P. Martínez, J. Ramírez

{"title":"Potassium Monitoring From Multilead T-wave Morphology Changes During Hemodyalisis: Periodic Versus Principal Component Analysis","authors":"Flavio Palmieri, P. Gomis, J. E. Ruiz, D. Ferreira, A. Martín-Yebra, E. Pueyo, P. Laguna, J. P. Martínez, J. Ramírez","doi":"10.22489/CinC.2020.199","DOIUrl":"https://doi.org/10.22489/CinC.2020.199","url":null,"abstract":"Background: End-stage renal disease (ESRD) patients undergoing hemodyalisis therapy (HD) experience blood potassium ([K+]) variations that are reflected on the T-wave (TW) morphology. Methods: We evaluated the performance of different lead space reduction (LSR) methods: principal component analysis (PCA), maximising the TW energy, and two derived versions of periodic component analysis (πCA) named πCA<inf>B</inf> and πCA<inf>T</inf>, maximising the QRST or TW beat periodicity. We applied these methods to 12-lead electrocardiogram (ECG) from 24 ESRD-HD patients. Then, we derived three markers of TW morphology changes (d<inf>u</inf><inf>w</inf>, d<inf>w</inf> and d<inf>^</inf><inf>w,c</inf>), comparing an average TW derived every 30 min with that at the HD end, from the PCA, πCA<inf>B</inf> and πCA<inf>T</inf> based leads having the highest TW energy content. Similarities between these three methods were assessed by using Bland-Altman plots and the linear fitting error (∊) evaluated from the 12<inf>th</inf> to the 44<inf>th</inf> h of ECG recordings after the HD onset. Results: All series of d<inf>u</inf><inf>w</inf>, d<inf>w</inf> and d<inf>^</inf><inf>w,c</inf> values showed good degree of mutual agreement (median bias ≤. 0.5 ms) and a small deviation from linearity in the [K+] increasing stage (median ∊ ≤ 3.3 ms). Conclusions: PCA andπCA can be used interchangeably to track TW changes in ESRD-HD patients, in this type of low noise contamination ECG recordings.","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"376 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123499195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Changes in QRS and T-wave Loops Subsequent to an Increase in Left Ventricle Globularity as in Intrauterine Growth Restriction: a Simulation Study 宫内生长受限导致左心室球形增加后QRS和t波环的变化:一项模拟研究

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.438

F. Bueno-Palomeque, Konstantinos A. Mountris, A. Mincholé, N. Ortigosa, E. Pueyo, P. Laguna

{"title":"Changes in QRS and T-wave Loops Subsequent to an Increase in Left Ventricle Globularity as in Intrauterine Growth Restriction: a Simulation Study","authors":"F. Bueno-Palomeque, Konstantinos A. Mountris, A. Mincholé, N. Ortigosa, E. Pueyo, P. Laguna","doi":"10.22489/CinC.2020.438","DOIUrl":"https://doi.org/10.22489/CinC.2020.438","url":null,"abstract":"Cardiovascular remodeling induced by intrauterine growth restriction manifests in adulthood by more globular ventricles, as evidenced by in vivo measurements. The angle between the dominant vectors of the QRS and T-wave loops has been reported to be significantly altered as a result of the induced remodeling. To investigate whether the more globular ventricular shape was a major factor contributing to such alteration, we performed electrophysiological simulations in a human biventricular model for control and in a model obtained by deforming the control one to represent a more spherical left ventricle (SLV). Transmural ventricular heterogeneities and a Purkinje network were included. 12-lead ECGs were calculated, from which spatial QRS and T-wave angles were computed. The angle between the T-wave and the XZ-plane was found to increase in the SLV model, showing a variation similar to that reported in in vivo studies. However, the angle between the dominant vectors of the QRS and T-wave loops projected onto the XY-plane was lower for control, contrary to clinical observations in IUGR adults. Other clinical results could not be reproduced in our simulations either. Our findings suggest that a more globular left ventricular shape leads to changes in the angles of QRS and T-wave loops, but further research is needed to fully understand these changes and the underlying mechanisms.","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126398952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Combining Scatter Transform and Deep Neural Networks for Multilabel Electrocardiogram Signal Classification 结合散射变换和深度神经网络的多标签心电图信号分类

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.133

Maximilian P. Oppelt, Maximilian Riehl, Felix P. Kemeth, Jan Steffan

{"title":"Combining Scatter Transform and Deep Neural Networks for Multilabel Electrocardiogram Signal Classification","authors":"Maximilian P. Oppelt, Maximilian Riehl, Felix P. Kemeth, Jan Steffan","doi":"10.22489/CinC.2020.133","DOIUrl":"https://doi.org/10.22489/CinC.2020.133","url":null,"abstract":"An essential part for the accurate classification of electrocardiogram (ECG) signals is the extraction of informative yet general features, which are able to discriminate diseases. Cardiovascular abnormalities manifest themselves in features on different time scales: small scale morphological features, such as missing P-waves, as well as rhythmical features apparent on heart rate scales. For this reason we incorporate a variant of the complex wavelet transform, called a scatter transform, in a deep residual neural network (ResNet). The former has the advantage of being derived from theory, making it well behaved under certain transformations of the input. The latter has proven useful in ECG classification, allowing feature extraction and classification to be learned in an end-to-end manner. Through the incorporation of trainable layers in between scatter transforms, the model gains the ability to combine information from different channels, yielding more informative features for the classification task and adapting them to the specific domain. For evaluation, we submitted our model in the official phase in the PhysioNet/Computing in Cardiology Challenge 2020. Our (Team Triage) approach achieved a challenge validation score of 0.640, and full test score of 0.485, placing us 4th out of 41 in the official ranking.","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126546670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Frequency Coupling and Sensitivity Spectral Measures of the Respiratory Sinus Arrhythmia System in Response to Increasing Respiratory Frequency 呼吸窦性心律失常系统响应呼吸频率增加的频率耦合和灵敏度谱测量

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.026

A. Guillén-Mandujano, S. Carrasco-Sosa, P. Coello-Caballero

{"title":"Frequency Coupling and Sensitivity Spectral Measures of the Respiratory Sinus Arrhythmia System in Response to Increasing Respiratory Frequency","authors":"A. Guillén-Mandujano, S. Carrasco-Sosa, P. Coello-Caballero","doi":"10.22489/CinC.2020.026","DOIUrl":"https://doi.org/10.22489/CinC.2020.026","url":null,"abstract":"In 19 healthy subjects we assessed the effects of chirped respiratory frequency (RF) from 0.05 to 0.8 Hz, and of standing (STC) on the 130-s time courses of the central frequency and power of the high frequency components of RR (<inf>CFE</inf>HF<inf>RR</inf>, <inf>PE</inf>HF<inf>RR</inf>) and of respiration (<inf>CFE</inf>HF<inf>RES</inf>, <inf>PE</inf>HF<inf>RES</inf>), estimated by a time-frequency distribution. We took as indexes of respiratory sinus arrhythmia (RSA) frequency coupling (RSA<inf>FC</inf>) the <inf>CFE</inf>HF<inf>RES</inf>-<inf>CFE</inf>HF<inf>RR</inf> relation, their difference (Δ<inf>CFE</inf>HF) and coherence (RSA<inf>co</inf>), and the alpha index as RSA sensitivity (RSAs). The effects of RF on RSA measures were distinctive in three RF ranges, with precise limits at 0.09±0. 005, 0.18±0.03, 0.51±0.10 and 0.81±0.03 Hz. In the low, mid and high RF ranges, respectively: <inf>CFE</inf>HF<inf>RR</inf> was first unchanged, proportional to RF (r=0.97±0.03), then constant again; RSA<inf>co</inf> was 0.73±0.06, 0.97±0.03 and 0.78±0.08; RSA<inf>s</inf> was 135±34 ms/l, proportional to RF (r=-0. 79±0.08), and 62±30 ms/l; Δ<inf>CFE</inf>HF was greater than 0.02 Hz in the three RF stages. STC decreased mean RSA<inf>s</inf> (p<0.02) in all RF stages. RSA<inf>FC</inf> and RSA<inf>s</inf> measures vary as function of RF, showing three stages with precise RF limits and distinctive functionality, respectively: low for RSA<inf>FC</inf> but high for RSA<inf>s</inf>, optimal and linear for both, and reduced for both measures. Baroreflex activation significantly depresses RSA<inf>s</inf>.","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"116 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125721070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Identification of Cardiac Arrhythmias From 12-lead ECG Using Beat-wise Analysis and a Combination of CNN and LSTM 利用心跳分析和CNN与LSTM相结合的方法识别12导联心电图中的心律失常

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.127

M. Alkhodari, L. Hadjileontiadis, A. Khandoker

{"title":"Identification of Cardiac Arrhythmias From 12-lead ECG Using Beat-wise Analysis and a Combination of CNN and LSTM","authors":"M. Alkhodari, L. Hadjileontiadis, A. Khandoker","doi":"10.22489/CinC.2020.127","DOIUrl":"https://doi.org/10.22489/CinC.2020.127","url":null,"abstract":"Throughout the years, there have been many attempts to develop an accurate cardiac arrhythmias identification algorithm. However, despite achieving acceptable results, they have been only applied on either small or homogeneous data-sets. A study was developed herein to identify cardiac arrhythmias from varied-length 12-lead ECG signals obtained from the PhysioNet/Computing in Cardiology Challenge 2020 and acquired from a wide set of sources. Our team, Care4MyHeart, developed an approach that starts by analyzing the labels of the database. Then, applying various signal processing techniques to denoise the 12-lead signals. After that a beat-by-beat segmentation procedure was followed to identify the most significant beats in exhibiting the arrhythmia within the signals. A CNN+BiLSTM model was then trained and evaluated on the training set using 10-fold cross-validation scheme as well as on hidden validation and testing sets. Our approach achieved a challenge validation score of 0.379 and full test score of 0.146 on the hidden validation and testing sets, respectively. Our team was ranked the 26th out of 41 entries in this year's Challenge.","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127967309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Simulation of the Hemodynamic Effects of the Left Atrial Appendage Occlusion in Atrial Fibrillation: Preliminary Results 心房颤动左心耳闭塞血流动力学模拟:初步结果

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.302

N. D'Alessandro, A. Masci, A. Andalò, L. Dede’, C. Tomasi, A. Quarteroni, C. Corsi

引用次数: 5

Analysis of Cardiac Dynamics in Patients With Chagas Disease Using PCA 用PCA分析查加斯病患者心脏动力学

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.286

M. Vizcardo, D. Cornejo, E. Alvarez

{"title":"Analysis of Cardiac Dynamics in Patients With Chagas Disease Using PCA","authors":"M. Vizcardo, D. Cornejo, E. Alvarez","doi":"10.22489/CinC.2020.286","DOIUrl":"https://doi.org/10.22489/CinC.2020.286","url":null,"abstract":"Chagas disease American trypanosomiasis is caused by a flagellated parasite: trypanosoma cruzi, transmitted by an insect of the genus Triatoma and also by blood transfusions. In Latin America the number of infected people is approximately 6 million, with a population exposed to the risk of infection of 70 million people. It is our interest to develop a low-cost, non-invasive methodology capable of describing cardiac dynamics within 24 hours and thus finding descriptors of dynamics that allow early detection of cardiac abnormality caused by T. cruzi. We analyzed the first and second principal components of the PCA of the 8 HRV indices of the 24-hour RR records in patients with ECG abnormalities (CH2), patients without ECG abnormalities (CH1) who had positive results Serological findings for Chagas disease and healthy (Control) matched for sex and age. We found significant differences (p-value<0.05) between the three groups Control-CH1, Control-CH2 and CH1-CH2 up to 5 continuous hours in dynamics between the, using the HRV heart rate variability indices and the PCA principal component analysis method, and we also found a lower distance from the mean dynamics in the Control group (0.020267), then the CH1 group (0.027922) and finally in group CH2 (0.034812).","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130841499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Variability of Electrocardiographic Imaging Within and Between Leadsets 导联内和导联间心电图成像的可变性

2020 Computing in Cardiology Pub Date : 2020-09-13 DOI: 10.22489/CinC.2020.097

J. Stoks, B. V. Rees, S. A. Groeneveld, Diantha J. M. Schipaanboord, L. Blom, R. Hassink, M. Cluitmans, R. Peeters, P. Volders

{"title":"Variability of Electrocardiographic Imaging Within and Between Leadsets","authors":"J. Stoks, B. V. Rees, S. A. Groeneveld, Diantha J. M. Schipaanboord, L. Blom, R. Hassink, M. Cluitmans, R. Peeters, P. Volders","doi":"10.22489/CinC.2020.097","DOIUrl":"https://doi.org/10.22489/CinC.2020.097","url":null,"abstract":"The variability of the inverse solution provided by electrocardiographic imaging (ECGI) is largely unknown when comparing different leadsets or (similar) beats. In four patients, we compared activation times (ATs), recovery times (RTs), and correlation coefficients during QRS complex and STT segment between: 1) consecutive sinus beats within one leadset, and 2) multiple beats for two leadsets. Furthermore, reasons behind differences in RT were investigated. Zero-th order Tikhonov regularization was used to reconstruct ventricular epicardial potentials. A spatiotemporal estimation method was then used to determine the ATs and RTs from the reconstructed epicardial electrograms. Inter-leadset differences were generally low for ATs, but exceeded intra-leadset beat-to-beat variations. RTs, however, showed larger variation independent of leadset. Differences in RTs between beats or leadsets could partially be explained by low T-wave amplitudes and high levels of noise, which suggests that RT determination may require more advanced methods in these cases. These findings increase our understanding of the consequences of electrode placement for the inverse solution, as well as our understanding of the complexities of recovery time estimation in ECGI.","PeriodicalId":407282,"journal":{"name":"2020 Computing in Cardiology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131125432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0