Magnetic resonance imaging最新文献

{"title":"Radiomic features of dynamic contrast-enhanced MRI can predict Ki-67 status in head and neck squamous cell carcinoma","authors":"Lu Yang ,&nbsp;Longwu Yu ,&nbsp;Guangzi Shi ,&nbsp;Lingjie Yang ,&nbsp;Yu Wang ,&nbsp;Riyu Han ,&nbsp;Fengqiong Huang ,&nbsp;Yinfeng Qian ,&nbsp;Xiaohui Duan","doi":"10.1016/j.mri.2024.110276","DOIUrl":"10.1016/j.mri.2024.110276","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aimed to investigate the potential of radiomic features derived from dynamic contrast-enhanced MRI (DCE-MRI) in predicting Ki-67 and p16 status in head and neck squamous cell carcinoma (HNSCC).</div></div><div><h3>Materials and methods</h3><div>A cohort of 124 HNSCC patients who underwent pre-surgery DCE-MRI were included and divided into training and test set (7:3), further subgroup analysis was performed for 104 cases with oral squamous cell carcinoma (OSCC). Radiomics features were extracted from DCE images. The least absolute shrinkage and selection operator (LASSO) was used for radiomics features selection, and receiver operating characteristics analysis for predictive performance assessment. The nomogram's performance was evaluated using decision curve analysis (DCA).</div></div><div><h3>Results</h3><div>Ten DCE-MRI features were identified to build the predictive model of HNSCC, demonstrating excellent predictive value for Ki-67 status in both the training set (AUC of 0.943) and test set (AUC of 0.801). The nomograms based on the predictive model showed good fit in the calibration curves (<em>p</em> &gt; 0.05), and DCA indicated its high clinical usefulness. In subgroup analysis of OSCC, fourteen features were selected to build the predictive model for Ki-67 status with an AUC of 0.960 in training set and 0.817 in test set. No features could be included to establish a model to predict p16 status.</div></div><div><h3>Conclusion</h3><div>The radiomics model utilizing DCE-MRI features could effectively predict Ki-67 status in HNSCC patients, offering potential for noninvasive preoperative prediction of Ki-67 status.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"116 ","pages":"Article 110276"},"PeriodicalIF":2.1,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142687383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GraFMRI: A graph-based fusion framework for robust multi-modal MRI reconstruction","authors":"Shahzad Ahmed ,&nbsp;Feng Jinchao ,&nbsp;Javed Ferzund ,&nbsp;Muhammad Usman Ali ,&nbsp;Muhammad Yaqub ,&nbsp;Malik Abdul Manan ,&nbsp;Atif Mehmood","doi":"10.1016/j.mri.2024.110279","DOIUrl":"10.1016/j.mri.2024.110279","url":null,"abstract":"<div><h3>Purpose</h3><div>This study introduces GraFMRI, a novel framework designed to address the challenges of reconstructing high-quality MRI images from undersampled k-space data. Traditional methods often suffer from noise amplification and loss of structural detail, leading to suboptimal image quality. GraFMRI leverages Graph Neural Networks (GNNs) to transform multi-modal MRI data (T1, T2, PD) into a graph-based representation, enabling the model to capture intricate spatial relationships and inter-modality dependencies.</div></div><div><h3>Methods</h3><div>The framework integrates Graph-Based Non-Local Means (NLM) Filtering for effective noise suppression and Adversarial Training to reduce artifacts. A dynamic attention mechanism enables the model to focus on key anatomical regions, even when fully-sampled reference images are unavailable. GraFMRI was evaluated on the IXI and fastMRI datasets using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) as metrics for reconstruction quality.</div></div><div><h3>Results</h3><div>GraFMRI consistently outperforms traditional and self-supervised reconstruction techniques. Significant improvements in multi-modal fusion were observed, with better preservation of information across modalities. Noise suppression through NLM filtering and artifact reduction via adversarial training led to higher PSNR and SSIM scores across both datasets. The dynamic attention mechanism further enhanced the accuracy of the reconstructions by focusing on critical anatomical regions.</div></div><div><h3>Conclusion</h3><div>GraFMRI provides a scalable, robust solution for multi-modal MRI reconstruction, addressing noise and artifact challenges while enhancing diagnostic accuracy. Its ability to fuse information from different MRI modalities makes it adaptable to various clinical applications, improving the quality and reliability of reconstructed images.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"116 ","pages":"Article 110279"},"PeriodicalIF":2.1,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142676371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Progress in MRI is NOT ubiquitous","authors":"John C. Gore","doi":"10.1016/j.mri.2024.110273","DOIUrl":"10.1016/j.mri.2024.110273","url":null,"abstract":"<div><div>There has been tremendous progress in MRI over the past 40+ years, driven by advances in technology as well as human ingenuity, with considerable impact in medicine. However, our understanding of how to account for, and interpret, MRI properties <em>quantitatively</em> lags behind these technical advances. This lack of understanding will limit our ability to make full use of quantitative metrics in the future, and much more work is needed to bridge this knowledge gap.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"115 ","pages":"Article 110273"},"PeriodicalIF":2.1,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142648472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Manual data labeling, radiology, and artificial intelligence: It is a dirty job, but someone has to do it","authors":"Teodoro Martín-Noguerol ,&nbsp;Pilar López-Úbeda ,&nbsp;Félix Paulano-Godino ,&nbsp;Antonio Luna","doi":"10.1016/j.mri.2024.110280","DOIUrl":"10.1016/j.mri.2024.110280","url":null,"abstract":"<div><div>In this letter to the editor, authors highlight the key role of data labeling in training AI models for medical imaging, discussing the complexities, resource demands, costs, and the relevance of quality control in the labeling process including the potential and limitations of AI tools for automated labeling. The article underlines that labeling quality is essential for the accuracy of AI models and the safety of their clinical applications, highlighting the legal responsibilities of labelers in cases where improper labeling leads to AI errors.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"116 ","pages":"Article 110280"},"PeriodicalIF":2.1,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effects of reference selection methods on PROPELLER MRI","authors":"Yilong Liu ,&nbsp;Bing Zhang ,&nbsp;Jintang Ye ,&nbsp;Zhe Zhang ,&nbsp;Renyuan Liu ,&nbsp;Ming Li ,&nbsp;Xiaodong Chen ,&nbsp;Taihui Yu ,&nbsp;Biling Liang ,&nbsp;Xiaoying Wang ,&nbsp;Rui Li ,&nbsp;Chun Yuan ,&nbsp;Hua Guo","doi":"10.1016/j.mri.2024.110275","DOIUrl":"10.1016/j.mri.2024.110275","url":null,"abstract":"<div><div>PROPELLER MRI has been shown effective for rigid motion compensation, while the performance of existing PROPELLER reconstruction methods critically depend on selecting a proper reference blade.</div><div>In this work, we proposed a robust implementation for PROPELLER reconstruction, which was incorporated with different reference selection methods, including single blade reference (SBR), combined blades reference (CBR), grouped blades reference (GBR) and Pipe et al.'s revised method, which requires no blade reference (NBR).</div><div>Both simulation and <em>in vivo</em> studies were performed to evaluate the precision and robustness of motion estimation for reference selection methods. <em>In vivo</em> data sets from 10 volunteers with instructed motion and 11 patients with random motion were collected and images were scored independently and blindly by two experienced radiologists.</div><div>Both simulation and <em>in vivo</em> studies demonstrate that the four reference selection methods have similar performances according to visual inspection. In our tests, one iteration for the motion estimation can be sufficient for SBR, CBR, or GBR, and comparable to NBR in terms of image quality for clinical diagnosis. With two iterations, SBR, CBR, and GBR are comparable to NBR in terms of motion estimation precision. With our proposed PROPELLER reconstruction, reference selection is not critical for robust motion correction. NBR with no iterations and SBR, CBR, and GBR with two iterations are recommended for accurate motion correction.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"116 ","pages":"Article 110275"},"PeriodicalIF":2.1,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection challenges of temporal encephaloceles in epilepsy: A retrospective analysis","authors":"Alexander V. Ortiz ,&nbsp;Jarrod J. Eisma ,&nbsp;Dann Martin ,&nbsp;Andre H. Lagrange ,&nbsp;Cari Motuzas ,&nbsp;William Nobis ,&nbsp;Bassel W. Abou-Khalil ,&nbsp;Victoria L. Morgan ,&nbsp;Jonah Fox","doi":"10.1016/j.mri.2024.110272","DOIUrl":"10.1016/j.mri.2024.110272","url":null,"abstract":"<div><div>Temporal encephaloceles (TEs) are herniations of cerebral parenchyma through structural defects in the floor of the middle cranial fossa. They are a relatively common, but only relatively recently identified potential cause of drug-resistant epilepsy. Uncontrolled epilepsy is associated with many negative long term health consequences including a heightened risk of death. The most effective treatment for drug-resistant epilepsy is surgery. One of the most predictive factors associated with successful surgery is identification of an abnormality on imaging. However, TEs can be difficult to detect and are often overlooked on neuroimaging studies. Improving our ability to accurately detect TEs by MRI is an important step in improving surgical outcomes in patients with drug-resistant epilepsy. We performed a review on existing imaging modalities for detecting TEs and report on our attempt to use a voxel-based morphometry (VBM) algorithm to detect TEs in T1-weighted MRIs of 81 patients from a database comprised of 25 patients with confirmed encephaloceles and 56 controls. Our program's sensitivity and specificity were compared to those of two neuroradiologists and two epileptologists using visualization during surgery as the gold standard. On average, the neuroradiologists and epileptologists had sensitivities of 41 % and 58 % and specificities of 81 % and 60 % while our VBM-based approach had sensitivities and specificities ranging from 11 % to 50 % and 0.2 % to 17 %, respectively. This work provides an overview of the different imaging modalities utilized in the detection of TEs and highlights the difficulties associated with their detection for both experienced physicians and cutting-edge computational methods. Our findings suggest that VBM-based methods could potentially be used to enhance clinicians' ability to detect TEs thereby facilitating surgical planning, improving surgical outcomes by allowing for more specific targeting, and bettering the long-term health and well-being of patients with drug-resistant epilepsy secondary to TEs.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"115 ","pages":"Article 110272"},"PeriodicalIF":2.1,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142622520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cystic Fibrosis or asthma? Discerning dyspnea with hyperpolarizaed xenon gas magnetic resonance imaging","authors":"David Wang ,&nbsp;Cody Thornburgh ,&nbsp;Harjeet Singh ,&nbsp;Zach Holliday","doi":"10.1016/j.mri.2024.110271","DOIUrl":"10.1016/j.mri.2024.110271","url":null,"abstract":"<div><div>Hyperpolarized Xenon MRI (HPG MRI) has been studied for its potential use in assessing lung function in patients with cystic fibrosis (CF) and in patients with asthma. We present a case of a man with overlapping cystic fibrosis and allergic asthma with severe obstructive lung disease in which spirometry and computed topography (CT) imaging was unable to determine the primary cause for his uncontrolled symptoms. HPG MRI was used to guide a tissue biopsy and determine the primary driver to be allergic asthma. After starting targeted therapy for severe asthma, his symptoms have greatly improved.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"115 ","pages":"Article 110271"},"PeriodicalIF":2.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142568622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intravascular enhancement sign at 3D T1-weighted turbo spin echo sequence is associated with cerebral atherosclerotic stenosis","authors":"Bo Wang ,&nbsp;Feng Ouyang ,&nbsp;Qin Wu ,&nbsp;Jingting Chen ,&nbsp;Jie Liu ,&nbsp;Zihe Xu ,&nbsp;Lianjiang Lv ,&nbsp;Nianzu Yu ,&nbsp;Xianjun Zeng","doi":"10.1016/j.mri.2024.110270","DOIUrl":"10.1016/j.mri.2024.110270","url":null,"abstract":"<div><h3>Objective</h3><div>Intravascular enhancement sign (IVES) at three-dimensional T1-weighted turbo spin echo (3D T1W TSE) sequence may be a simple hemodynamic maker. This study aims to investigate the association between IVES and features of intracranial atherosclerotic stenosis (ICAS).</div></div><div><h3>Method</h3><div>Retrospective analysis of clinical and imaging data of patients who underwent high resolution-vessel wall imaging (HR-VWI) examination from May 2021 to May 2023. The number of IVES vessels and ICAS features at HR-VWI were extracted by two neuroradiologists. Paired comparisons and correlation analysis on these indicators were performed.</div></div><div><h3>Results</h3><div>A total of 118 patients with ICAS in the first segment of the middle cerebral artery and accompanied by unilateral IVES were enrolled. Compared to the non-IVES side, a higher incidence of ischemic events and intraplaque hemorrhage (IPH), higher degree of vascular stenosis and enhancement, lower remodeling index, and lower signal intensity ratio (SIR) were found in subjects with IVES. In the ICAS with IVES, 79.66 % showed severe stenosis and occlusion; in the ICAS with severe stenosis and occlusion, 89.5 % showed IVES in the distal. A multivariable logistic regression model identified the vascular stenosis degree (OR = 1.922; 95 %CI [1.37–2.692]; <em>P</em> &lt; 0.001), enhanced-degree (OR = 2.486; 95 %CI [1.315–4.698]; <em>P</em> = 0.005), position (OR = 2.869; 95 %CI [1.255–6.560]; <em>P</em> = 0.012), and SIR (OR = 0.032; 95 %CI [0.004–0.275]; <em>P</em> = 0.002) were independent association with the presence of IVES. The area under the curve was 0.911 for the use of IVES vessel quantities to identify severe stenosis and occlusion of arterial lumen.</div></div><div><h3>Conclusion</h3><div>The number of IVES vessels was associated with the local features of ICAS, which may indicate severe stenosis and occlusion in the major branches of the proximal artery.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"115 ","pages":"Article 110270"},"PeriodicalIF":2.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142568699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring of lung stiffness for long-COVID patients using magnetic resonance elastography (MRE)","authors":"Sabine F. Bensamoun ,&nbsp;Kiaran P. McGee ,&nbsp;Mashhour Chakouch ,&nbsp;Philippe Pouletaut ,&nbsp;Fabrice Charleux","doi":"10.1016/j.mri.2024.110269","DOIUrl":"10.1016/j.mri.2024.110269","url":null,"abstract":"<div><h3>Purpose</h3><div>Transaxial CT imaging is the main clinical imaging modality for the assessment of COVID-induced lung damage. However, this type of data does not quantify the functional properties of the lung. The objective is to provide non-invasive personalized cartographies of lung stiffness for long-COVID patients using MR elastography (MRE) and follow-up the evolution of this quantitative mapping over time.</div></div><div><h3>Methods</h3><div>Seven healthy and seven long-COVID participants underwent CT and MRE imaging at total lung capacity. After CT test, a senior radiologist visually analyzed the lung structure. Less than one month later, a first MRI (1.5 T, GRE sequence) lung density test followed by a first MRE (SE-EPI sequence) test were performed. Gadolinium-doped water phantom and a pneumatic driver (vibration frequency: 50 Hz), placed on the sternum, were used for MRI and MRE tests, respectively. Personalized cartographies of the stiffness were obtained, by two medical imaging engineers, using a specific post processing (MMDI algorithm). The monitoring (lung density, stiffness) was carried out no later than 11 months for each COVID patient. Wilcoxon's tests and an intra-class correlation coefficient (ICC) were used for statistical analysis.</div></div><div><h3>Results</h3><div>The density for long-COVID patients was significantly (<em>P</em> = 0.047) greater (170 kg.m⁻³) compared to healthy (125 kg.m⁻³) subjects. After the first MRE test, the stiffness measured for the healthy subjects was in the same range (median value (interquartile range, IQR): 0.93 (0.09) kPa), while the long-COVID patients showed a larger stiffness range (from 1.39 kPa to 2.05 kPa). After a minimum delay of 5 months, the second MRE test showed a decrease of stiffness (from 22 % to 40 %) for every long-COVID patient. The inter-operator agreement was excellent (intra-class correlation coefficient: 0.93 [0.78–0.97]).</div></div><div><h3>Conclusion</h3><div>The MRE test is sensitive enough to monitor disease-induced change in lung stiffness (increase with COVID symptoms and decrease with recovery). This non-invasive modality could yield complementary information as a new imaging biomarker to follow up long-COVID patients.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"115 ","pages":"Article 110269"},"PeriodicalIF":2.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142568720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"vSHARP: Variable Splitting Half-quadratic ADMM algorithm for reconstruction of inverse-problems","authors":"George Yiasemis ,&nbsp;Nikita Moriakov ,&nbsp;Jan-Jakob Sonke ,&nbsp;Jonas Teuwen","doi":"10.1016/j.mri.2024.110266","DOIUrl":"10.1016/j.mri.2024.110266","url":null,"abstract":"<div><div>Medical Imaging (MI) tasks, such as accelerated parallel Magnetic Resonance Imaging (MRI), often involve reconstructing an image from noisy or incomplete measurements. This amounts to solving ill-posed inverse problems, where a satisfactory closed-form analytical solution is not available. Traditional methods such as Compressed Sensing (CS) in MRI reconstruction can be time-consuming or prone to obtaining low-fidelity images. Recently, a plethora of Deep Learning (DL) approaches have demonstrated superior performance in inverse-problem solving, surpassing conventional methods. In this study, we propose vSHARP (variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse Problems), a novel DL-based method for solving ill-posed inverse problems arising in MI. vSHARP utilizes the Half-Quadratic Variable Splitting method and employs the Alternating Direction Method of Multipliers (ADMM) to unroll the optimization process. For data consistency, vSHARP unrolls a differentiable gradient descent process in the image domain, while a DL-based denoiser, such as a U-Net architecture, is applied to enhance image quality. vSHARP also employs a dilated-convolution DL-based model to predict the Lagrange multipliers for the ADMM initialization. We evaluate vSHARP on tasks of accelerated parallel MRI Reconstruction using two distinct datasets and on accelerated parallel dynamic MRI Reconstruction using another dataset. Our comparative analysis with state-of-the-art methods demonstrates the superior performance of vSHARP in these applications.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"115 ","pages":"Article 110266"},"PeriodicalIF":2.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142503198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}