arXiv - PHYS - Medical Physics最新文献

{"title":"Separation of Sodium Signals Between Mono- and Bi-Exponential T2 Decays via Multi-TE Single-Quantum Sodium (23Na) MRI","authors":"Yongxian QianBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Ying-Chia LinBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Xingye ChenBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USAVilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA, Tiejun ZhaoSiemens Medical Solutions USA, New York, NY, USA, Karthik LakshmananBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Yulin GeBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Yvonne W. LuiBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USADepartment of Radiology, NYU Langone Health, New York, NY, USA, Fernando E. BoadaBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USANow at Department of Radiology, Stanford University, Stanford, CA, USA","doi":"arxiv-2407.09868","DOIUrl":"https://doi.org/arxiv-2407.09868","url":null,"abstract":"Purpose. It is a long standing pursuit in sodium (23Na) MRI to separate\u0000signals between mono and bi exponential T2 decays in the human brain, due to\u0000lack of clinically translational solutions under the restriction of\u0000intrinsically low signal to noise ratio (SNR). Here we propose a new technique\u0000called multi TE single quantum (MSQ) sodium MRI to address the challenge.\u0000Methods. We exploit an intrinsic difference in T2 decay between mono and bi\u0000exponential sodium signals by acquiring SQ images at multiple TEs and\u0000performing voxel based matrix inversions on these SQ images. The MSQ method was\u0000then investigated on numerical models, agar phantoms, and human brains for the\u0000feasibility on clinical scanners at 3T. Results. The whole brain T2* spectrum\u0000of FID signals from the study subjects showed sparse peaks (2 to 4 peaks),\u0000suggesting a global set of T2* values (T2*fr, T2*bs, T2*bl) applicable to the\u0000separation. The simulations indicated a small impact (3.9 to 5.6 percent) of\u0000T2* variation on accuracy of the separation, and the phantom experiments showed\u0000a high accuracy of the separation, 95.8 percent for mono T2 sodium and 72.5 to\u000080.4 percent for biT2 sodium. The human studies demonstrated feasibility of the\u0000separation and potentials of highlighting abnormal brain regions in the biT2\u0000sodium images. Conclusion. The MSQ technique has been shown, via the numerical\u0000simulations, phantom experiments, and human brain studies, to be able to\u0000separate mono and bi T2 sodium signals using a two TE sampling scheme and a\u0000global set of T2* values. However, MSQ has limitations and requires cautions in\u0000practice. Keywords. sodium MRI, single quantum MRI, triple quantum MRI,\u0000neuroimaging, neurodegeneration","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721240","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}

{"title":"Characterization of a Biosensor Based on Graphene Field Effect Transistors for Body Fluid Analytes: Channel Resistance","authors":"Ricardo Bravo, Ricardo Silva, Eric Barret, John Brunnings, Adianette Segarra","doi":"arxiv-2407.09656","DOIUrl":"https://doi.org/arxiv-2407.09656","url":null,"abstract":"Field-Effect Transistors with graphene channels or GFETs are an interesting\u0000alternative for the detection of analytes in biological fluids since the\u0000electrical behavior of the channel changes when exposed to a sample (among\u0000other detection strategies). In this work a preliminary characterization is\u0000made in terms of the resistance of the channel for a commercial device that has\u0000GFETs of 1 and 3 channels for cases of dry and wet gate at atmospheric\u0000pressure. The channel resistance was obtained by sweeping the drain-source\u0000voltage from -1 to +1V and measuring the drain current in a test station\u0000developed for this purpose, for gate cases with and without a PBS 0.001X\u0000reference solution. The ohmic response of the channel is linear current with\u0000respect to voltage, being greater resistance in the case of wet gate. An\u0000increase in resistance with respect to voltage was observed that it is\u0000important to review. It was possible to make the ohmic characterization of the\u0000channel and a series of recommendations are suggested to continue this\u0000research.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141722459","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}

{"title":"FEBio FINESSE: An open-source finite element simulation approach to estimate in vivo heart valve strains using shape enforcement","authors":"Devin W. Laurence, Patricia M. Sabin, Analise M. Sulentic, Matthew Daemer, Steve A. Maas, Jeffrey A. Weiss, Matthew A. Jolley","doi":"arxiv-2407.09629","DOIUrl":"https://doi.org/arxiv-2407.09629","url":null,"abstract":"Finite element simulations are an enticing tool to evaluate heart valve\u0000function in healthy and diseased patients; however, patient-specific\u0000simulations derived from 3D echocardiography are hampered by several technical\u0000challenges. In this work, we present an open-source method to enforce matching\u0000between finite element simulations and in vivo image-derived heart valve\u0000geometry in the absence of patient-specific material properties, leaflet\u0000thickness, and chordae tendineae structures. We evaluate FEBio Finite Element\u0000Simulations with Shape Enforcement (FINESSE) using three synthetic test cases\u0000covering a wide range of model complexity. Our results suggest that FINESSE can\u0000be used to not only enforce finite element simulations to match an\u0000image-derived surface, but to also estimate the first principal leaflet strains\u0000within +/- 0.03 strain. Key FINESSE considerations include: (i) appropriately\u0000defining the user-defined penalty, (ii) omitting the leaflet commissures to\u0000improve simulation convergence, and (iii) emulating the chordae tendineae\u0000behavior via prescribed leaflet free edge motion or a chordae emulating force.\u0000We then use FINESSE to estimate the in vivo valve behavior and leaflet strains\u0000for three pediatric patients. In all three cases, FINESSE successfully matched\u0000the target surface with median errors similar to or less than the smallest\u0000voxel dimension. Further analysis revealed valve-specific findings, such as the\u0000tricuspid valve leaflet strains of a 2-day old patient with HLHS being larger\u0000than those of two 13-year old patients. The development of this open source\u0000pipeline will enable future studies to begin linking in vivo leaflet mechanics\u0000with patient outcomes","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721241","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}

{"title":"Latent Spaces Enable Transformer-Based Dose Prediction in Complex Radiotherapy Plans","authors":"Edward Wang, Ryan Au, Pencilla Lang, Sarah A. Mattonen","doi":"arxiv-2407.08650","DOIUrl":"https://doi.org/arxiv-2407.08650","url":null,"abstract":"Evidence is accumulating in favour of using stereotactic ablative body\u0000radiotherapy (SABR) to treat multiple cancer lesions in the lung. Multi-lesion\u0000lung SABR plans are complex and require significant resources to create. In\u0000this work, we propose a novel two-stage latent transformer framework (LDFormer)\u0000for dose prediction of lung SABR plans with varying numbers of lesions. In the\u0000first stage, patient anatomical information and the dose distribution are\u0000encoded into a latent space. In the second stage, a transformer learns to\u0000predict the dose latent from the anatomical latents. Causal attention is\u0000modified to adapt to different numbers of lesions. LDFormer outperforms a\u0000state-of-the-art generative adversarial network on dose conformality in and\u0000around lesions, and the performance gap widens when considering overlapping\u0000lesions. LDFormer generates predictions of 3-D dose distributions in under 30s\u0000on consumer hardware, and has the potential to assist physicians with clinical\u0000decision making, reduce resource costs, and accelerate treatment planning.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613007","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}

{"title":"Large Language Model-Augmented Auto-Delineation of Treatment Target Volume in Radiation Therapy","authors":"Praveenbalaji Rajendran, Yong Yang, Thomas R. Niedermayr, Michael Gensheimer, Beth Beadle, Quynh-Thu Le, Lei Xing, Xianjin Dai","doi":"arxiv-2407.07296","DOIUrl":"https://doi.org/arxiv-2407.07296","url":null,"abstract":"Radiation therapy (RT) is one of the most effective treatments for cancer,\u0000and its success relies on the accurate delineation of targets. However, target\u0000delineation is a comprehensive medical decision that currently relies purely on\u0000manual processes by human experts. Manual delineation is time-consuming,\u0000laborious, and subject to interobserver variations. Although the advancements\u0000in artificial intelligence (AI) techniques have significantly enhanced the\u0000auto-contouring of normal tissues, accurate delineation of RT target volumes\u0000remains a challenge. In this study, we propose a visual language model-based RT\u0000target volume auto-delineation network termed Radformer. The Radformer utilizes\u0000a hierarichal vision transformer as the backbone and incorporates large\u0000language models to extract text-rich features from clinical data. We introduce\u0000a visual language attention module (VLAM) for integrating visual and linguistic\u0000features for language-aware visual encoding (LAVE). The Radformer has been\u0000evaluated on a dataset comprising 2985 patients with head-and-neck cancer who\u0000underwent RT. Metrics, including the Dice similarity coefficient (DSC),\u0000intersection over union (IOU), and 95th percentile Hausdorff distance (HD95),\u0000were used to evaluate the performance of the model quantitatively. Our results\u0000demonstrate that the Radformer has superior segmentation performance compared\u0000to other state-of-the-art models, validating its potential for adoption in RT\u0000practice.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141588470","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}

{"title":"3D E-textile for Exercise Physiology and Clinical Maternal Health Monitoring","authors":"Junyi Zhao, Chansoo Kim, Weilun Li, Zichao Wen, Zhili Xiao, Yong Wang, Shantanu Chakrabartty, Chuan Wang","doi":"arxiv-2407.07954","DOIUrl":"https://doi.org/arxiv-2407.07954","url":null,"abstract":"Electronic textiles (E-textiles) offer great wearing comfort and\u0000unobtrusiveness, thus holding potential for next-generation health monitoring\u0000wearables. However, the practical implementation is hampered by challenges\u0000associated with poor signal quality, substantial motion artifacts, durability\u0000for long-term usage, and non-ideal user experience. Here, we report a\u0000cost-effective E-textile system that features 3D microfiber-based electrodes\u0000for greatly increasing the surface area. The soft and fluffy conductive\u0000microfibers disperse freely and securely adhere to the skin, achieving a low\u0000impedance at the electrode-skin interface even in the absence of gel. A\u0000superhydrophobic fluorinated self-assembled monolayer was deposited on the\u0000E-textile surface to render it waterproof while retaining the electrical\u0000conductivity. Equipped with a custom-designed motion-artifact canceling\u0000wireless data recording circuit, the E-textile system could be integrated into\u0000a variety of smart garments for exercise physiology and health monitoring\u0000applications. Real-time multimodal electrophysiological signal monitoring,\u0000including electrocardiogram (ECG) and electromyography (EMG), was successfully\u0000carried out during strenuous cycling and even underwater swimming activities.\u0000Furthermore, a multi-channel E-textile was developed and implemented in\u0000clinical patient studies for simultaneous real-time monitoring of maternal ECG\u0000and uterine EMG signals, incorporating spatial-temporal potential mapping\u0000capabilities.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613008","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}

{"title":"A Practical Guide to Transcranial Ultrasonic Stimulation from the IFCN-endorsed ITRUSST Consortium","authors":"Keith R Murphy, Tulika Nandi, Benjamin Kop, Takahiro Osada, W Apoutou N'Djin, Maximilian Lueckel, Kevin A Caulfield, Anton Fomenko, Hartwig R Siebner, Yoshikazu Ugawa, Lennart Verhagen, Sven Bestmann, Eleanor Martin, Kim Butts Pauly, Elsa Fouragnan, Til Ole Bergmann","doi":"arxiv-2407.07646","DOIUrl":"https://doi.org/arxiv-2407.07646","url":null,"abstract":"Low-intensity Transcranial Ultrasonic Stimulation (TUS) is a non-invasive\u0000brain stimulation technique enabling cortical and deep brain targeting with\u0000unprecedented spatial accuracy. Given the high rate of adoption by new users\u0000with varying levels of expertise and interdisciplinary backgrounds, practical\u0000guidelines are needed to ensure state-of-the-art TUS application and\u0000reproducible outcomes. Therefore, the International Transcranial Ultrasonic\u0000Stimulation Safety and Standards (ITRUSST) consortium has formed a\u0000subcommittee, endorsed by the International Federation of Clinical\u0000Neurophysiology (IFCN), to develop recommendations for best practice in TUS\u0000applications in humans. The practical guide presented here provides a brief\u0000introduction into ultrasound physics and sonication parameters. It explains the\u0000requirements of TUS lab equipment and transducer selection and discusses\u0000experimental design and procedures alongside potential confounds and control\u0000conditions. Finally, the guide elaborates on essential steps of application\u0000planning for stimulation safety and efficacy, as well as considerations when\u0000combining TUS with neuroimaging, electrophysiology, or other brain stimulation\u0000techniques. We hope that this practical guide to TUS will assist both novice\u0000and experienced users in planning and conducting high-quality studies and\u0000provide a solid foundation for further advancements in this promising field.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584616","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}

{"title":"Motion simulation of radio-labeled cells in whole-body positron emission tomography","authors":"Nils Marquardt, Tobias Hengsbach, Marco Mauritz, Benedikt Wirth, Klaus Schäfers","doi":"arxiv-2407.07709","DOIUrl":"https://doi.org/arxiv-2407.07709","url":null,"abstract":"Cell tracking is a subject of active research gathering great interest in\u0000medicine and biology. Positron emission tomography (PET) is well suited for\u0000tracking radio-labeled cells in vivo due to its exceptional sensitivity and\u0000whole-body capability. For validation, ground-truth data is desirable that\u0000realistically mimics the flow of cells in a clinical situation. This study\u0000develops a workflow (CeFloPS) for simulating moving radio-labeled cells in a\u0000human phantom. From the XCAT phantom, the blood vessels are reduced to nodal\u0000networks along which cells can move and distribute to organs and tissues. The\u0000movement is directed by the blood flow which is calculated in each node using\u0000the Hagen-Poiseuille equation and Kirchhoffs laws assuming laminar flow. Organs\u0000are voxelized and movement of cells from artery entry to vein exit is generated\u0000via a biased 3D random walk. The probabilities of whether cells move or stay in\u0000tissues are derived from rate constants of physiologically based compartment\u0000modeling. PET listmode data is generated using the Monte-Carlo simulation\u0000framework GATE based on the definition of a large-body PET scanner with cell\u0000paths as moving radioactive sources and the XCAT phantom providing attenuation\u0000data. From the flow simulation of 10000 cells, 100 sample cells were further\u0000processed by GATE and listmode data was reconstructed into images for\u0000comparison. As demonstrated by comparisons of simulated and reconstructed cell\u0000distributions, CeFloPS can realistically simulate the cell behavior of\u0000whole-body PET providing valuable data for development and validation of cell\u0000tracking algorithms.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584614","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}

{"title":"Low-dose, high-resolution CT of infant-sized lungs via propagation-based phase contrast","authors":"James A. Pollock, Kaye Morgan, Linda C. P. Croton, Emily J. Pryor, Kelly J. Crossley, Christopher J. Hall, Daniel Hausermann, Anton Maksimenko, Stuart B. Hooper, Marcus J. Kitchen","doi":"arxiv-2407.06527","DOIUrl":"https://doi.org/arxiv-2407.06527","url":null,"abstract":"Many lung diseases and abnormalities require detailed visualisation of the\u0000lungs for accurate diagnosis and treatment. High-resolution computed tomography\u0000(CT) is the gold-standard technique for non-invasive lung disease detection,\u0000but it presents a risk to the patient through the relatively high ionising\u0000radiation dose required. Utilising the X-ray phase information may allow\u0000improvements in image resolution at equal or lower radiation levels than\u0000current clinical imaging. Propagation-based phase-contrast imaging requires\u0000minimal adaption of existing medical systems, and is well suited to lung\u0000imaging due to the strong phase gradients introduced by the lung-air material\u0000interface. Herein, propagation-based phase contrast CT is demonstrated for\u0000large animals, namely lambs, as a model for paediatric patients, using\u0000monochromatic radiation and a photon-counting detector at the Imaging and\u0000Medical Beamline of the Australian Synchrotron. Image quality, normalised\u0000against radiation dose, was optimised as a function of the beam energy and\u0000propagation distance, with the optimal conditions used to test the available\u0000image quality at very low radiation dose. Noise-limited spatial resolution was\u0000measured using Fourier ring correlation, and dosimetry was performed through\u0000Monte Carlo simulation calibrated against air kerma. The resulting CT images\u0000demonstrate superior resolution to existing high-resolution CT systems, pushing\u0000dose to the quantum limit to comply with current Australian guidelines for\u0000infant chest CT exposure (<2.5 mSv effective dose). Constituent raw projections\u0000are shown to have significant proportions of pixels with zero photon counts\u0000that would create severe information loss in conventional CT, which was\u0000prevented through phase retrieval.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141575154","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}

{"title":"Predicting Mesoscopic Larmor Frequency Shifts in White Matter with Diffusion MRI -- An In-Silico Monte-Carlo Study","authors":"Anders Dyhr Sandgaard, Sune Nørhøj Jespersen","doi":"arxiv-2407.06694","DOIUrl":"https://doi.org/arxiv-2407.06694","url":null,"abstract":"This study aims to validate if MRI can measure anisotropic mesoscopic Larmor\u0000frequency shifts from white matter axonal microstructure relative to the B0\u0000direction and if dMRI can estimate this anisotropy. Recent models describe how\u0000mesoscopic Larmor frequency shifts depend on induced magnetic fields by axons,\u0000described by an orientation distribution function. Using Monte-Carlo\u0000simulations of MRI signals in mesoscopic white matter axon substrates, we show\u0000MRI can estimate this mesoscopic frequency shift and dMRI can estimate its\u0000orientation dependence.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141575155","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}