Radiology最新文献

{"title":"A Deep Learning Model for Three-Dimensional Determination of Whole Thoracic Vertebral Bone Mineral Density from Noncontrast Chest CT: The Multi-Ethnic Study of Atherosclerosis.","authors":"Quincy A Hathaway, Arta Kasaeian, Tommy Pan, David A Bluemke, Elena Ghotbi, Joshua G Klein, Hamza Ahmed Ibad, Chris Dailing, Geoffrey H Tison, R Graham Barr, Wendy Post, Matthew Allison, João A C Lima, Matthew Budoff, Shadpour Demehri","doi":"10.1148/radiol.242133","DOIUrl":"10.1148/radiol.242133","url":null,"abstract":"<p><p>Background Recent studies have investigated how deep learning (DL) algorithms applied to CT using two-dimensional (2D) segmentation (sagittal or axial planes) can calculate bone mineral density (BMD) and predict osteoporosis-related outcomes. Purpose To determine whether TotalSegmentator, an nnU-net algorithm, can measure three-dimensional (3D) vertebral body BMD across consistently imaged thoracic levels (T1-T10) at any conventional, noncontrast chest CT examination. Materials and Methods This study is a secondary analysis of a multicenter (<i>n</i> = 6) prospective cohort, the Multi-Ethnic Study of Atherosclerosis (MESA). Participants underwent noncontrast chest CT with (<i>n</i> = 296) and without (<i>n</i> = 2660) a phantom. In 594 participants, manual segmentation for T1-T10 vertebrae was performed on axial and sagittal planes. TotalSegmentator provided 3D vertebral body segmentation of T1-T10 levels with further postprocessing to remove cortical bone. Two-dimensional axial and sagittal DL-derived algorithms were developed and compared with 3D model performance. Dice and intersection-over-union scores were calculated. Vertebral BMD-derived data, integrated with the Fracture Risk Assessment Tool with no BMD (FRAXnb), were used to predict incident vertebral fractures (VFx) in participants from the follow-up MESA Examination 6 (<i>n</i> = 1304). Results This study included 2956 participants (1546 [52%] female; age, 69 years ± 9 [SD]), with longitudinal data obtained approximately 6.2 years later in a subset of 1304 participants. DL-derived 3D segmentations were correlated with manual axial (Dice score, 0.93; 95% CI: 0.92, 0.95) and sagittal (Dice score, 0.91; 95% CI: 0.88, 0.93) segmentations. DL-derived 2D axial and sagittal BMD measurements had higher uncertainty compared with DL-derived 3D BMD measurements (average SDs, 2D axial and 2D sagittal vs 3D BMD: 65 mg/cm³ and 59 mg/cm³ vs 41 mg/cm³, respectively; both <i>P</i> < .001). Three-dimensional vertebral BMD with FRAXnb demonstrated better performance in predicting incident VFx (area under the receiver operating characteristic curve [AUC], 0.82) compared with FRAXnb alone (AUC, 0.66; <i>P</i> = .03). Conclusion A multilevel DL algorithm for measuring 3D whole thoracic vertebral BMD using conventional chest CT determined distinct BMD patterns from whole thoracic vertebrae and provided incremental value in predicting VFx. ClinicalTrials.gov identifier: NCT00005487 © RSNA, 2025 <i>Supplemental material is available for this article</i>. See also the editorial by Steiger in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e242133"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11950887/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"O-RADS US Version 2022 Improves Patient Risk Stratification When Compared with O-RADS US Version 2019.","authors":"Roni Yoeli-Bik, Jacques S Abramowicz, Kristen Wroblewski, Leonhard Donle, Ryan E Longman, Ernst Lengyel","doi":"10.1148/radiol.242200","DOIUrl":"10.1148/radiol.242200","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e242200"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11950876/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Stage Deep Learning Model for Adrenal Nodule Detection on CT Images: A Retrospective Study.","authors":"Chang Ho Ahn, Taewoo Kim, Kyungmin Jo, Seung Shin Park, Min Joo Kim, Ji Won Yoon, Taek Min Kim, Sang Youn Kim, Jung Hee Kim, Jaegul Choo","doi":"10.1148/radiol.231650","DOIUrl":"https://doi.org/10.1148/radiol.231650","url":null,"abstract":"<p><p>Background The detection and classification of adrenal nodules are crucial for their management. Purpose To develop and test a deep learning model to automatically depict adrenal nodules on abdominal CT images and to simulate triaging performance in combination with human interpretation. Materials and Methods This retrospective study (January 2000-December 2020) used an internal dataset enriched with adrenal nodules for model training and testing and an external dataset reflecting real-world practice for further simulated testing in combination with human interpretation. The deep learning model had a two-stage architecture, a sequential detection and segmentation model, trained separately for the right and left adrenal glands. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for nodule detection and intersection over union for nodule segmentation. Results Of a total of 995 patients in the internal dataset, the AUCs for detecting right and left adrenal nodules in internal test set 1 (<i>n</i> = 153) were 0.98 (95% CI: 0.96, 1.00; <i>P</i> < .001) and 0.93 (95% CI: 0.87, 0.98; <i>P</i> < .001), respectively. These values were 0.98 (95% CI: 0.97, 0.99; <i>P</i> < .001) and 0.97 (95% CI: 0.96, 0.97; <i>P</i> < .001) in the external test set (<i>n</i> = 12 080) and 0.90 (95% CI: 0.84, 0.95; <i>P</i> < .001) and 0.89 (95% CI: 0.85, 0.94; <i>P</i> < .001) in internal test set 2 (<i>n</i> = 1214). The median intersection over union was 0.64 (IQR, 0.43-0.71) and 0.53 (IQR, 0.40-0.64) for right and left adrenal nodules, respectively. Combining the model with human interpretation achieved high sensitivity (up to 100%) and specificity (up to 99%), with triaging performance from 0.77 to 0.98. Conclusion The deep learning model demonstrated high performance and has the potential to improve detection of incidental adrenal nodules. © RSNA, 2025 <i>Supplemental material is available for this article.</i> See also the editorial by Malayeri and Turkbey in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e231650"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guided Antiplatelet Therapy for Stent-Treated Intracranial Aneurysms: A Cluster-Randomized Trial.","authors":"Yangyang Zhou, Jun Wang, Wenqiang Li, Jian Liu, Anxin Wang, Yisen Zhang, Shiqing Mu, Ruhang Xie, Qichen Peng, Limin Zhang, Bin Luo, Yuanli Zhao, Yang Wang, Ziqing Zhang, Yixin Lin, Pinyuan Zhang, Jiren Zhang, Liang Li, Xiangdong Yin, Fushun Xiao, Yunpeng Lin, Xiaoning Liu, Yang Bian, Simin Wang, Jingwei Li, Xiaoli Zhang, David M Hasan, Timo Krings, Hongqi Zhang, Xinjian Yang","doi":"10.1148/radiol.241509","DOIUrl":"https://doi.org/10.1148/radiol.241509","url":null,"abstract":"<p><p>Background During neurointerventional treatment of intracranial aneurysms (IAs), poor antiplatelet drug response increases the risk of a cerebral ischemic event (IE). Replacing clopidogrel with ticagrelor may reduce this risk. Purpose To determine whether platelet function test (PFT)-guided antiplatelet therapy reduces incidence of IEs compared with standard dual antiplatelet therapy (SDAT; daily oral aspirin and clopidogrel, 100 mg and 75 mg, respectively) in patients undergoing endovascular intervention for IAs. Materials and Methods In this prospective, multicenter, cluster-randomized trial, 16 neurointerventional teams were randomly allocated to eight test and eight control clusters. Between May and August 2023, test group participants underwent PFT. Test group participants who showed poor antiplatelet response were administered an increased aspirin dose or were switched from clopidogrel to ticagrelor. The control group was administered SDAT. The primary outcome was any cerebral IE within 30 days after the procedure. The exploratory outcomes were any IE within 7 days, modified Rankin Scale score, and all-cause mortality within 30 days. The safety outcome measure was any bleeding event within 30 days. All outcome analyses were performed using generalized linear mixed-effects models. Results A total of 590 participants were included (median age, 58 years; 374 women). IE incidence within 30 days was lower in the test group than in the control group (6.8% [20 of 295] vs 13.2% [39 of 295]; odds ratio [OR], 0.54; 95% CI: 0.31, 0.94; <i>P</i> = .03) and within 7 days (4.1% [12 of 295] vs 10.8% [32 of 295]; OR, 0.48; 95% CI: 0.25, 0.89; <i>P</i> = .02) after undergoing the procedure. There was no evidence of a difference between the test group and the control group in modified Rankin Scale scores (0.33 vs 0.49, respectively; <i>P</i> = .11) or mortality (0.3% [one of 295] vs 2.0% [six of 295], respectively; <i>P</i> = .54). Furthermore, there was no evidence of a between-group difference in bleeding event incidence (24.1% [71 of 295] vs 31.2% [92 of 295]; OR, 0.67; 95% CI: 0.30, 1.5; <i>P</i> = .32). Conclusion PFT-guided antiplatelet therapy was associated with reduced IE incidence. Administration of 60 mg of ticagrelor did not increase bleeding event incidence. Clinicaltrials.gov Identifier: NCT05825391 © RSNA, 2025 <i>Supplemental material is available for this article.</i> See also the editorial by Kallmes and Altschul in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e241509"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRI-based Deep Learning Algorithm for Assisting Clinically Significant Prostate Cancer Detection: A Bicenter Prospective Study.","authors":"Young Joon Lee, Hyong Woo Moon, Moon Hyung Choi, Seung Eun Jung, Yong Hyun Park, Ji Youl Lee, Dong Hwan Kim, Sung Eun Rha, Sang Hoon Kim, Kyu Won Lee, Yeong-Jin Choi, Young Sub Lee, Woojoo Lee, Seungjae Lee, Robert Grimm, Heinrich von Busch, Dongyeob Han, Bin Lou, Ali Kamen","doi":"10.1148/radiol.232788","DOIUrl":"10.1148/radiol.232788","url":null,"abstract":"<p><p>Background Although artificial intelligence is actively being developed for prostate MRI, few studies have prospectively validated these tools. Purpose To compare the diagnostic performance of a commercial deep learning algorithm (DLA) and radiologists' clinical reports for cancer detection in participants from two hospitals using histopathologic findings from biopsy specimens as the reference standard. Materials and Methods This prospective bicenter study enrolled participants suspected of having prostate cancer (PCa) who were scheduled for biopsy based on clinical information, including prostate MRI, from December 2022 to July 2023. Targeted prostate biopsies were performed for lesions with Prostate Imaging Reporting and Data System (PI-RADS) scores of 3 or higher, identified by either radiologists or the DLA. PI-RADS classifications by radiologists (using all imaging sequences), the DLA (using biparametric MRI), and the scenario in which radiologist-based PI-RADS 3 scores were modulated with DLA-based PI-RADS scores were compared using the area under the receiver operating characteristic curve (AUC) with DeLong and McNemar tests. Results A total of 259 lesions, including 117 clinically significant PCas (csPCas) (Gleason grade group ≥2), were evaluated in 205 men (median age, 68 years; age range, 47-90 years). At per-lesion analysis, the DLA had a lower sensitivity (94 of 117; 80%) and higher positive predictive value (PPV) (94 of 163; 58%) for detecting csPCa than did the radiologists (109 of 117 [93%] and 109 of 227 [48%]; <i>P</i> = .02 and <i>P</i> = .008, respectively). At per-participant analysis, incorporation of the DLA increased specificity from 23 of 108 (21%) to 48 of 108 (44%) (<i>P</i> = .001), with similar sensitivity (96 of 97 [99%] vs 93 of 97 [96%]; <i>P</i> = .74). There was no evidence of a difference in the AUC between radiologist-based and DLA-based PI-RADS score (0.77 [95% CI: 0.70, 0.82] vs 0.79 [95% CI: 0.73, 0.85]; <i>P</i> = .73). Conclusion The DLA demonstrated lower sensitivity but a greater PPV than radiologists for detecting csPCa in a biopsy setting. Using DLA results when radiologists' interpretations are indeterminate could improve specificity while maintaining sensitivity. International Clinical Trials Registry Platform registration no. KCT0006947 © RSNA, 2025 <i>Supplemental material is available for this article</i>.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e232788"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photon-Counting CT: Technology, Current and Potential Future Clinical Applications, and Overview of Approved Systems and Those in Various Stages of Research and Development.","authors":"Fides R Schwartz, Aaron D Sodickson, Perry J Pickhardt, Dushyant V Sahani, Michael H Lev, Rajiv Gupta","doi":"10.1148/radiol.240662","DOIUrl":"10.1148/radiol.240662","url":null,"abstract":"<p><p>Photon-counting CT (PCCT) has emerged as a transformative technology, with the potential to herald a new era of clinical capabilities. This review provides an overview of the current status and potential future developments of PCCT, including basic physics principles and technical implementation by different vendors, with special attention to applications that have not, to date, been emphasized in the literature. The technologic underpinnings that distinguish PCCT scanners from traditional energy-integrating detector (EID) CT scanners with dual-energy capability are discussed. The inherent challenges of PCCT and the innovative breakthroughs that have enabled key PCCT features, such as enhanced image resolution, material discrimination, and radiation dose efficiency, are reviewed. Two categories of clinical applications are considered: <i>(a)</i> applications that are possible with current-generation EID CT but may be improved with the higher spatial, temporal, and contrast resolution of PCCT (eg, CT angiographic vasculitis imaging with high spatial, contrast, and temporal resolution and ultra-high-spatial-resolution \"opportunistic\" osseous imaging) and <i>(b)</i> potential future applications that are not currently feasible with EID CT but that may become possible and practical with PCCT (eg, reduced need for serial follow-up imaging with advanced CT or MRI because of more complete, definitive imaging evaluation with PCCT at first presentation).</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e240662"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11950899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coronary Plaque Quantification with Ultrahigh-Spatial-Resolution Photon-counting Detector CT: Intraindividual Comparison with Energy-integrating Detector CT.","authors":"Milán Vecsey-Nagy, Giuseppe Tremamunno, U Joseph Schoepf, Chiara Gnasso, Emese Zsarnóczay, Nicola Fink, Dmitrij Kravchenko, Moritz C Halfmann, Jim O'Doherty, Bálint Szilveszter, Pál Maurovich-Horvat, Ismail Mikdat Kabakus, Pal Spruill Suranyi, Tilman Emrich, Akos Varga-Szemes","doi":"10.1148/radiol.241479","DOIUrl":"https://doi.org/10.1148/radiol.241479","url":null,"abstract":"<p><p>Background Other than enhancing the accuracy of stenosis measurements, the improved spatial resolution of photon-counting detector (PCD) CT may have an impact on quantitative plaque assessment at coronary CT angiography (CCTA). Purpose To evaluate the effect of PCD CT on coronary plaque quantification and characterization compared with that of energy-integrating detector (EID) CT. Materials and Methods Consecutive participants undergoing clinically indicated CCTA at EID CT (192 × 0.6-mm collimation) were enrolled to undergo ultrahigh-spatial-resolution (UHR) PCD CT (120 × 0.2-mm collimation) within 30 days. PCD CT was performed using equivalent or lower CT dose index and equivalent contrast media volume as the clinical scan. Total, calcified, fibrotic, and low-attenuation coronary plaque volumes were quantified and compared between scanners. Intra- and interreader reproducibility was assessed for both systems. Results A total of 164 plaques from 48 participants were segmented on both scans. Total plaque volume was lower at PCD CT compared with EID CT (723.5 mm³ [IQR, 500.6-1184.7 mm³] vs 1084.7 mm³ [IQR, 710.7-1609.8 mm³]; <i>P</i> < .001). UHR-based segmentations produced lower fibrotic (325.4 mm³ [IQR, 151.7-519.2 mm³] vs 627.7 mm³ [IQR, 385.8-795.1 mm³], respectively; <i>P</i> < .001) and higher low-attenuation plaque volumes (72.1 mm³ [IQR, 38.6-161.9 mm³] vs 58.1 mm³ [IQR, 23.4-102.3 mm³], respectively; <i>P</i> = .004) than EID CT-based measurements. Calcified plaque volumes did not differ significantly between PCD CT and EID CT (344.5 mm³ [IQR, 174.3-605.7 mm³] vs 342.1 mm³ [IQR, 180.4-607.5 mm³], respectively; <i>P</i> = .13). Total, calcified, and fibrotic plaque volumes demonstrated excellent agreement between repeated measurements and between readers for both PCD CT and EID CT (all intraclass correlation coefficients [ICCs] > 0.90). Whereas low-attenuation plaque volume had strong intrareader (ICC, 0.84; 95% CI: 0.57, 0.94) and interreader (ICC, 0.92; 95% CI: 0.81, 0.97) agreements for PCD CT, EID CT showed only moderate (ICC, 0.62; 95% CI: 0.11, 0.86) and poor (ICC, 0.47; 95% CI: 0.01, 0.79) intrareader and interreader reproducibility. Conclusion Compared with EID CT, PCD CT UHR imaging reduced segmented coronary plaque volume by nearly one-third and improved reproducibility of low-attenuation plaque measurements. © RSNA, 2025 <i>Supplemental material is available for this article.</i></p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e241479"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"US Screening for Liver Lesions in Patients at Risk for HCC: How Well Does LI-RADS US Scoring System Perform?","authors":"Richard G Barr","doi":"10.1148/radiol.250596","DOIUrl":"https://doi.org/10.1148/radiol.250596","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e250596"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143701352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opportunistic Reduction of Disability and Mortality from Osteoporotic Fractures.","authors":"Peter Steiger","doi":"10.1148/radiol.250478","DOIUrl":"https://doi.org/10.1148/radiol.250478","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e250478"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prostate Cancer Screening: Empirical Clinical Practice for 70 Years.","authors":"Takeshi Takahashi","doi":"10.1148/radiol.242184","DOIUrl":"https://doi.org/10.1148/radiol.242184","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e242184"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}