Clinical ImagingPub Date : 2024-11-26DOI: 10.1016/j.clinimag.2024.110370
Lucy Y. Lei , Osher N.Y. Lee , Charlotte J. Yong-Hing , Nicolas Murray , Ismail T. Ali , Adnan M. Sheikh , Harneet Cheema , Faisal Khosa
{"title":"Impact factors and publication times of original scientific research in radiology journals","authors":"Lucy Y. Lei , Osher N.Y. Lee , Charlotte J. Yong-Hing , Nicolas Murray , Ismail T. Ali , Adnan M. Sheikh , Harneet Cheema , Faisal Khosa","doi":"10.1016/j.clinimag.2024.110370","DOIUrl":"10.1016/j.clinimag.2024.110370","url":null,"abstract":"<div><h3>Purpose</h3><div>The time from article submission to publication in peer-reviewed scientific journals is variable and can be prolonged, which slows the dissemination of research and can influence the academic progress of authors. This study evaluated the publication times for articles in radiology journals, in particular the relationship between turnaround times and journal impact factors (IFs).</div></div><div><h3>Methods</h3><div>Bibliometric data was obtained from Journal Citation Reports to conduct a comparative analysis of radiology journals against those in other disciplines of clinical medicine using highest IF, median IF, cited half-life, immediacy index, and number of journals. Journals from various radiology subcategories were further examined to assess IF trends over time. The Pearson correlation coefficient was used to identify any statistically significant relationships between IF and other variables.</div></div><div><h3>Results</h3><div>Among 28 medical disciplines, there was a significant positive correlation of 0.63 between the number of journals and the highest journal IF of a given discipline. Among 135 radiology journals categorized into 12 subcategories, there was a similar significant correlation of 0.64. For high-ranking radiology journals, the median time from submission to publication online was 22.7 weeks [IQR = 9.3] and median time from submission to publication in print was 37.9 weeks [IQR = 7.1]. The former time interval showed a positive correlation of 0.58 with journal IF at <em>p</em> < 0.05.</div></div><div><h3>Conclusion</h3><div>There is wide variation in the time from submission to publication in radiology journals. Authors can expect a longer turnaround time when publishing in higher-impact journals.</div></div>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"118 ","pages":"Article 110370"},"PeriodicalIF":1.8,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748247","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}
Clinical ImagingPub Date : 2024-11-26DOI: 10.1016/j.clinimag.2024.110369
Elinor Laws , Joanne Palmer , Joseph Alderman , Ojasvi Sharma , Victoria Ngai , Thomas Salisbury , Gulmeena Hussain , Sumiya Ahmed , Gagandeep Sachdeva , Sonam Vadera , Bilal Mateen , Rubeta Matin , Stephanie Kuku , Melanie Calvert , Jacqui Gath , Darren Treanor , Melissa McCradden , Maxine Mackintosh , Judy Gichoya , Hari Trivedi , Xiaoxuan Liu
{"title":"Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review","authors":"Elinor Laws , Joanne Palmer , Joseph Alderman , Ojasvi Sharma , Victoria Ngai , Thomas Salisbury , Gulmeena Hussain , Sumiya Ahmed , Gagandeep Sachdeva , Sonam Vadera , Bilal Mateen , Rubeta Matin , Stephanie Kuku , Melanie Calvert , Jacqui Gath , Darren Treanor , Melissa McCradden , Maxine Mackintosh , Judy Gichoya , Hari Trivedi , Xiaoxuan Liu","doi":"10.1016/j.clinimag.2024.110369","DOIUrl":"10.1016/j.clinimag.2024.110369","url":null,"abstract":"<div><h3>Purpose</h3><div>There are many radiological datasets for breast cancer, some which have supported the development of AI medical devices for breast cancer screening and image classification. This review aims to identify mammography datasets (including digitised screen film mammography, 2D digital mammography and digital breast tomosynthesis) used in the development of AI technologies and present their characteristics, including their transparency of documentation, content, populations included and accessibility.</div></div><div><h3>Materials and methods</h3><div>MEDLINE and Google Dataset searches identified studies describing AI technology development and referencing breast imaging datasets up to June 2024. The characteristics of each dataset are summarised. In particular, the accompanying documentation was reviewed with a focus on diversity and inclusion of populations represented within each dataset.</div></div><div><h3>Results</h3><div>254 datasets were referenced in the literature search, 190 were privately held, 36 had barriers which prevented access, and 28 were accessible. Most datasets originated from Europe, East Asia and North America. There was poor reporting of individuals' attributes: 32 (12 %) datasets reported race or ethnicity; 76 (30 %) reported female/male categories with only one dataset explicitly defining whether these categories represented sex or gender attributes.</div></div><div><h3>Conclusion</h3><div>Through this review, we demonstrate gaps in the data landscape for mammography, highlighting poor representation globally. To ensure datasets in breast imaging have maximum utility for researchers, their characteristics should be documented and limitations of datasets, such as their representativeness of populations and settings, should inform scientific efforts to translate data-driven insights into technologies and discoveries.</div></div>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"118 ","pages":"Article 110369"},"PeriodicalIF":1.8,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748245","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}
Clinical ImagingPub Date : 2024-11-26DOI: 10.1016/j.clinimag.2024.110371
Ronnie W. AlRamahi , Andrew Woerner , Hassan Rizvi , Eric J. Monroe
{"title":"Complicated appendicitis in the pediatric patient: interventional perspectives","authors":"Ronnie W. AlRamahi , Andrew Woerner , Hassan Rizvi , Eric J. Monroe","doi":"10.1016/j.clinimag.2024.110371","DOIUrl":"10.1016/j.clinimag.2024.110371","url":null,"abstract":"<div><div>This pictorial review provides a comprehensive visual and textual overview of interventional radiology approaches in treating complicated appendicitis and other abdominal abscesses in children. This review discusses the incidence and complications associated with appendicitis in pediatric patients, highlighting the role of percutaneous drainage in managing appendicitis with abscesses. We present common mimics of intra-abdominal abscesses from other diseases such as tubo-ovarian abscesses, inflammatory bowel disease, and lymphomatous bowel involvement, emphasizing imaging pitfalls that can mimic appendiceal abscesses. The review also covers interventional radiology considerations, including antibiotic indications, local anesthesia considerations for children, the comparison between percutaneous and endocavitary approaches, and the roles of fibrinolytics are discussed here. Detailed discussions on catheter selection and insertion techniques, such as Seldinger and trocar, are provided along with post-procedure management strategies. These include drain maintenance, navigating drain associated complications, and determining when to remove the drain. Through high-quality images and concise descriptions, we illustrate procedural intricacies and clinical scenarios encountered in practice, offering a valuable educational resource for clinicians managing pediatric abscesses.</div></div>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"118 ","pages":"Article 110371"},"PeriodicalIF":1.8,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748249","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}
Clinical ImagingPub Date : 2024-11-26DOI: 10.1016/j.clinimag.2024.110372
Seyedeh Zahra Mousavi , Reza Moshfeghinia , Hossein Molavi Vardanjani , Mohammad Reza Sasani
{"title":"Opportunistic screening of osteoporosis by CT scan compared to DXA: A systematic review and meta-analysis","authors":"Seyedeh Zahra Mousavi , Reza Moshfeghinia , Hossein Molavi Vardanjani , Mohammad Reza Sasani","doi":"10.1016/j.clinimag.2024.110372","DOIUrl":"10.1016/j.clinimag.2024.110372","url":null,"abstract":"<div><div>The efficacy of opportunistic osteoporosis screening with computed tomography (CT) scans obtained for other indications has not yet been implemented by the current guidelines. We aimed to compile available evidence on the efficacy of osteoporosis screening with CT scans obtained for other indications compared with dual X-ray absorptiometry (DXA).</div><div>Studies comparing the diagnostic performance of the CT scan with the DXA published before 2023 were retrieved. We conducted a bias assessment using the Newcastle-Ottawa Scale for cross-sectional studies. Correlation coefficients (CC), area under the curve (AUC), sensitivity, and specificity of the CT scans compared with the DXA were meta-analyzed with random effects modeling. 41 studies fulfilled the inclusion/exclusion criteria. The included studies reported weak to very strong CC (0.35 to 0.95) and low to high accuracy for opportunistic osteoporosis screening with CT scans. The meta-analysis showed a moderate pooled CC of 0.59 (95 % CI: 0.53–0.64, P-value<0.001), and a relatively high AUC of 0.81 (95 % CI: 0.78–0.84, P-value<0.001). Subgroup analysis based on age and menopausal status did not show significant between-group differences. Significantly higher accuracy measures were estimated for CT scans of the proximal femur compared to other anatomic regions (CC: 0.70, 95 % CI: 0.57–0.82; AUC: 0.79, 95 % CI: 0.72–0.87), North American cases (CC: 0.66, 95 % CI: 0.52–0.80; AUC: 0.82, 95 % CI: 0.82–0.83), and populations with a higher percentage of women (CC: 0.60, 95 % CI: 0.52–0.69; AUC: 0.86, 95 % CI: 0.83–0.89). We observed a moderate performance of opportunistic osteoporosis screening with CT scans obtained for other indications.</div></div>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"118 ","pages":"Article 110372"},"PeriodicalIF":1.8,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748246","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}
Clinical ImagingPub Date : 2024-11-22DOI: 10.1016/j.clinimag.2024.110367
Zainab Ahmad Ramadan (Zainab A. Ramadan), Amel Helmy Elmorsy (Amel Helmy), Saher Ebrahim Taman (Saher Taman), Fatmaelzahraa Abdelfattah Denewar (FA Denewar)
{"title":"Inter-observer and intra-observer agreement of bone reporting and data system (Bone-RADS) in the interpretation of bone tumors on computed tomography","authors":"Zainab Ahmad Ramadan (Zainab A. Ramadan), Amel Helmy Elmorsy (Amel Helmy), Saher Ebrahim Taman (Saher Taman), Fatmaelzahraa Abdelfattah Denewar (FA Denewar)","doi":"10.1016/j.clinimag.2024.110367","DOIUrl":"10.1016/j.clinimag.2024.110367","url":null,"abstract":"<div><h3>Objective</h3><div>To assess inter-observer & intra-observer agreement of the American College of Radiology (ACR) bone reporting and data system (Bone-RADS) in the interpretation of bone tumors on computed tomography (CT).</div></div><div><h3>Methods</h3><div>This retrospective study included 273 bone tumors 184 (67.4 %) benign and 89 (32.6 %) malignant. Two blinded radiologists independently reviewed the CT images to assess the defined CT features of bone lesions and assign a bone-RADS category. A third observer reviewed the CT images twice with one month interval and reported the specified CT features and final bone-RADS category for bone lesions. Inter-observer and intra-observer agreement of bone-RADS were analyzed.</div></div><div><h3>Results</h3><div>There was almost perfect inter-observer agreement between the two reviewers for all defined variables as well as bone-RADS categories (Kappa = 92.2 %). Overall intra-observer agreement was also perfect for all defined CT features and bone RADS categories with higher percentage than inter-observer one (κ = 98.3 %).</div></div><div><h3>Conclusion</h3><div>Bone-RADS is an effective clinical tool for practicing radiologists in the risk assessment and management of bone tumors with perfect agreement among observers. To our knowledge, no studies have been conducted for assessing reliability or validity of the recent ACR Bone-RADS using CT. Hence, this study could serve as a cornerstone for further upcoming studies to assess the reproducibility and validity of the ACR Bone-RADS.</div></div>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"117 ","pages":"Article 110367"},"PeriodicalIF":1.8,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142721758","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}
Clinical ImagingPub Date : 2024-11-22DOI: 10.1016/j.clinimag.2024.110366
Osman Melih Topcuoglu, Betul Uzunoglu , Tolga Orhan, Ekin Bora Basaran, Ayşegul Gormez, Ozgur Sarica
{"title":"A real-world comparison of the diagnostic performances of six different TI-RADS guidelines, including ACR-/Kwak-/K-/EU-/ATA-/C-TIRADS","authors":"Osman Melih Topcuoglu, Betul Uzunoglu , Tolga Orhan, Ekin Bora Basaran, Ayşegul Gormez, Ozgur Sarica","doi":"10.1016/j.clinimag.2024.110366","DOIUrl":"10.1016/j.clinimag.2024.110366","url":null,"abstract":"<div><h3>Purpose</h3><div>To compare the diagnostic performance of six different currently available guidelines including the American College of Radiology Thyroid Imaging and Reporting Data System (ACR-TIRADS), Kwak-TIRADS, Korean TIRADS (K-TIRADS), European TIRADS (EU-TIRADS), American Thyroid Association (ATA) and Chinese TIRADS (C-TIRADS), in differentiating malignant from benign thyroid nodules (TN).</div></div><div><h3>Materials and methods</h3><div>In this single-center study, between January-2007 and September-2023, ultrasound (US) images of TNs that were pathologically proven either by surgery or by fine needle aspiration biopsy (FNAB), were retrospectively evaluated and categorized according to six different currently available guidelines. Area under curve (AUC), sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively) and miss rates for malignancy (MRM) were calculated for each guideline.</div></div><div><h3>Results</h3><div>A total of 829 TNs (<em>n</em> = 234 malignant and <em>n</em> = 595 benign) were included. AUC, sensitivity, specificity, PPV, NPV and accuracy for ACR-TIRADS were 0.786, 99.8 %, 27.1 %, 31.92 %, 99.73 % and 54.6 %, respectively; for Kwak-TIRADS 0.839, 97.8 %, 42.1 %, 36.29 %, 98.11 % and 63.1 %, respectively; for K-TIRADS 0.797, 97.6 %, 41.6 %, 36.01 %, 84.85 % and 62.8, respectively, for EU-TIRADS 0.766, 97.8 %, 35.6 %, 33.89 %, 97.92 % and 59.1 %, respectively, for ATA 0.788, 97.5 %, 49.8 %, 32.86 %, 88.16 % and 64.2 %, respectively and for C-TIRADS 0.842, 0 %, 92.8 %, 54.3 %, 39.53 %, 90.42 %, and 68.8 % respectively. MRM regarding ACR-/Kwak-/K-/EU−/ATA-/C-TIRADS were 2.2 %, 0.5 %, 2.9 %, 2.5 %, 3.3 % and 0.1 %, respectively.</div></div><div><h3>Conclusion</h3><div>Six different currently available TIRADS guidelines can provide effective differentiation of malignant TNs from benign ones with similar diagnostic performances. However; C-TIRADS offered the highest AUC and the lowest MRM than the other guidelines, in this series.</div></div>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"117 ","pages":"Article 110366"},"PeriodicalIF":1.8,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701255","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}
Clinical ImagingPub Date : 2024-11-20DOI: 10.1016/j.clinimag.2024.110365
Seyedeh Panid Madani , Alireza Mohseni , Mohammad Mirza-Aghazadeh-Attari , Haneyeh Shahbazian , Shadi Afyouni , Ali Borhani , Ghazal Zandieh , Daniel Laheru , Ihab R. Kamel
{"title":"Role of volumetric tumor enhancement on CT in predicting overall survival in patients with unresectable pancreatic ductal adenocarcinoma","authors":"Seyedeh Panid Madani , Alireza Mohseni , Mohammad Mirza-Aghazadeh-Attari , Haneyeh Shahbazian , Shadi Afyouni , Ali Borhani , Ghazal Zandieh , Daniel Laheru , Ihab R. Kamel","doi":"10.1016/j.clinimag.2024.110365","DOIUrl":"10.1016/j.clinimag.2024.110365","url":null,"abstract":"<div><h3>Purpose</h3><div>To assess the utility of volumetric tumor enhancement on CT to predict tumor treatment response and the overall survival (OS) of patients with PDAC undergoing FOLFIRINOX-based systemic chemotherapy. Additionally, we aim to explore the performance of a novel model that incorporates relevant volumetric CT-derived parameters to the established RECIST 1.1 in predicting both treatment response and OS.</div></div><div><h3>Material and methods</h3><div>In this retrospective single-institution study, 127 patients with PDAC who received FOLFIRINOX neoadjuvant chemotherapy between December 2012 and November 2021 were included. Manual volumetric segmentation of the single largest tumor was performed on portal venous phase images. Total and enhancing tumor volumes were calculated. Response by RECIST 1.1 was compared to response by tumor volume and enhancing tumor volume on follow-up CT.</div></div><div><h3>Results</h3><div>There was no association between overall survival and RECIST 1.1 (p-value = 0.284), volumetric RECIST (p-value = 0.402), and other volumetric CT variables, except for a percentage reduction in enhancing tumor volume (p-value = 0.043). Using univariate survival analysis for categorical thresholds defined by CART, the percentage change in enhancing tumor volume was associated with OS (p-value = 0.018). There was also a significant association between baseline enhancing tumor volume and OS (p-value <0.0001). Using these two categories, we defined a multivariable model associated with OS (p-value <0.0001).</div></div><div><h3>Conclusion</h3><div>Percentage reduction in enhancing tumor volume was related to OS in non-surgical PDAC patients treated with FOLFIRINOX chemotherapy and could potentially be incorporated into patient survival prediction models.</div></div>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"117 ","pages":"Article 110365"},"PeriodicalIF":1.8,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142721757","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}
Clinical ImagingPub Date : 2024-11-20DOI: 10.1016/j.clinimag.2024.110361
Shaun Johnson , Nathan Amann , Shweta Ravi , Ameya Nayate , Michael Wien , Inas Mohamed , Karin Herrmann , Navid Faraji
{"title":"A month-long case-based bootcamp improves subjective and objective radiology knowledge for first-year radiology residents","authors":"Shaun Johnson , Nathan Amann , Shweta Ravi , Ameya Nayate , Michael Wien , Inas Mohamed , Karin Herrmann , Navid Faraji","doi":"10.1016/j.clinimag.2024.110361","DOIUrl":"10.1016/j.clinimag.2024.110361","url":null,"abstract":"<div><h3>Purpose</h3><div>First-year radiology residents enter residency with varying degrees of prior knowledge regarding radiology, which can be difficult for both trainees and physician educators looking to provide instruction. Recognizing this dilemma, we propose the adoption of a blended learning model PGY-2 radiology bootcamp at the start of training to give a structured foundation of imaging concepts.</div></div><div><h3>Methods</h3><div>20 total PGY-2 radiology residents spanning two cohorts of 10, one from 2022 and another from 2023, were included in a 4-week blended learning-style bootcamp at the beginning of their training. Effectiveness of the implementation was assessed using subjective Likert-scale surveys and an objective knowledge-based examination.</div></div><div><h3>Results</h3><div>Subjective confidence in basic radiology skills significantly improved for all modalities in the combined 2022-2023 results. Objective performance on the knowledge-based examination significantly improved in both cohorts, with no significant discrepancies in baseline scores between 2022 and 2023.</div></div><div><h3>Conclusions</h3><div>We recommend the implementation of a flipped-classroom, blended learning-style bootcamp for PGY-2 radiology residents. Our results demonstrated both subjective and objective improvement in radiology resident confidence and clinical knowledge, in addition to an early introduction to the institutional PACS.</div></div>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"117 ","pages":"Article 110361"},"PeriodicalIF":1.8,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142721759","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}
Clinical ImagingPub Date : 2024-11-19DOI: 10.1016/j.clinimag.2024.110364
Aparna Singhal
{"title":"Managing career transition decisions in medicine: a commentary and review of challenges and strategies","authors":"Aparna Singhal","doi":"10.1016/j.clinimag.2024.110364","DOIUrl":"10.1016/j.clinimag.2024.110364","url":null,"abstract":"","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"117 ","pages":"Article 110364"},"PeriodicalIF":1.8,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748363","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}