Emergency Radiology最新文献

{"title":"Diagnostic accuracy & clinical importance of AI confidence for extremity fracture detection: 2,508-patient retrospective cohort.","authors":"Sabine Morris Delhez, Thomas Breiner Enøe, Oke Gerke, Bjarke Viberg, Pia Iben Pietersen, Benjamin Schnack Brandt Rasmussen, Janni Jensen","doi":"10.1007/s10140-026-02546-3","DOIUrl":"https://doi.org/10.1007/s10140-026-02546-3","url":null,"abstract":"<p><strong>Purpose: </strong>To estimate diagnostic performance of a deep learning algorithm for extremity fracture detection on radiographs in patients aged ≥ 2 years using a refined reference standard. Secondary, to compare positive predictive value (PPV) by the algorithm's built-in confidence level (high vs. low) and diagnostic performance between adults (≥ 18 years) and children.</p><p><strong>Methods: </strong>This retrospective single-center study consecutively included patients with radiography of a suspected extremity fracture between January and December 2024. The index test was the algorithm output (bounding boxes with confidence). The reference standard was the radiology report with discordant cases adjudicated by follow-up imaging when available or specialist review. Sensitivity, specificity, PPV and negative predictive value (NPV) were calculated with 95% confidence intervals; differences were tested using the McNemar and a score test and patient-clustered logistic regression.</p><p><strong>Results: </strong>There were 2,508 patients, median age 34 years (range 2-105), 1,236 males; 815 patients had a total of 1,028 fractures. Per-fracture sensitivity and PPV were 92.7% (95% CI: 90.9-94.5) and 87.6% (95% CI: 85.5-89.7); Specificity and NPV were 94.4% (95% CI: 93.2-95.4) and 96.6% (95% CI: 95.6-97.4). PPV for high-confidence was superior to low-confidence detections (99.1% vs 59.1%, p < 0.001). Children had higher per-fracture PPV than adults (91.7% vs. 86.1%; p= 0.01), with no significant difference in per-fracture sensitivity, or case-wise performance.</p><p><strong>Conclusion: </strong>The algorithm showed good diagnostic performance for extremity fracture detection on radiographs. The AI's confidence stratification strongly influenced PPV, and higher PPV was seen among children.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149016243","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":"Computed tomography findings associated with gangrenous cholecystitis: a systematic review and meta-analysis.","authors":"Hideya Itagaki, Tomoyuki Endo","doi":"10.1007/s10140-026-02544-5","DOIUrl":"https://doi.org/10.1007/s10140-026-02544-5","url":null,"abstract":"<p><p>Gangrenous cholecystitis (GC) is a severe form of acute cholecystitis associated with perforation, sepsis, and increased mortality. Although computed tomography (CT) is useful for evaluating complicated cholecystitis, the relative diagnostic value of individual CT findings for identifying GC remains unclear. This review aimed to evaluate the association between individual CT findings and histopathologically confirmed GC and to summarize the diagnostic performance of these findings for preoperative assessment. We searched PubMed, Web of Science, Ichushi-Web, and the Cochrane Central Register of Controlled Trials from inception to March 1, 2026, and also screened Google Scholar for eligible studies. Eligible studies included those that enrolled patients with acute cholecystitis who underwent CT and had GC confirmed histopathologically. Two reviewers independently screened studies, extracted data, and assessed quality using the QUADAS-2 tool. Pooled odds ratios (ORs) were calculated with a DerSimonian-Laird random-effects model. When 2 × 2 data were available, we estimated pooled sensitivity and specificity using a bivariate random-effects model fitted by restricted maximum likelihood, from which we derived likelihood ratios and their confidence intervals; we examined model stability in sensitivity analyses. Ten retrospective studies involving 786 patients (310 GC and 476 non-GC) were included; eight studies (724 patients; 268 GC and 456 non-GC) contributed to the quantitative synthesis and two to the qualitative synthesis only. Absent gallbladder wall enhancement (OR 10.23, 95% CI 5.67-18.46) and wall irregularity (OR 10.26, 95% CI 5.80-18.17) were strongly associated with GC, as was pericholecystic stranding (OR 4.82, 95% CI 1.76-13.24). Absent wall enhancement (sensitivity 0.49, specificity 0.91, positive likelihood ratio 5.65) and wall irregularity (sensitivity 0.43, specificity 0.94, positive likelihood ratio 7.14) both combined high specificity with moderate sensitivity; their confidence intervals overlapped, and the findings were not compared directly. Pooled estimates were robust to the assumed between-study correlation and to omitting individual studies. Absent wall enhancement, wall irregularity, and pericholecystic inflammatory changes are useful CT findings for the preoperative assessment of suspected GC. Because the available evidence derives from surgically treated cohorts and the findings were not compared directly, these results should be regarded as hypothesis-generating and warrant prospective validation in unselected patients undergoing CT for suspected acute cholecystitis.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012103","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":"Chest radiography: an underappreciated source of litigation exposure in emergency radiology.","authors":"Tyler C Mezrich, Melissa A Davis, Joseph J Cavallo, Jonathan L Mezrich","doi":"10.1007/s10140-026-02547-2","DOIUrl":"https://doi.org/10.1007/s10140-026-02547-2","url":null,"abstract":"<p><strong>Purpose: </strong>Chest radiographs are the most frequently performed imaging examination yet remain vulnerable to interpretive errors, particularly in the high-volume emergency radiology setting. This analysis reviewed published cases in a legal database involving chest radiograph interpretation to highlight recurring medicolegal themes and their implications for emergency radiology practice. While published legal opinions cannot estimate malpractice incidence, they provide valuable insight into potentially modifiable sources of diagnostic error.</p><p><strong>Methods: </strong>A retrospective review of the LEXIS/NEXIS legal database identified publishedopinions from July 1, 2021, to July 14, 2026 involving chest radiograph interpretation. Manually reviewed cases in which chest radiograph interpretation contributed meaningfully to the litigation were analyzed thematically. Medicare Physician Fee Schedule reimbursement and work relative value unit (RVU) data were reviewed for economic context.</p><p><strong>Results: </strong>Fifty-four published cases met inclusion criteria. The most frequent themes involvedfailure to diagnose cancers/masses/tumors (n = 16, 29.6%), cardiovascular abnormalities (13.0%), infection (13.0%), trauma (11.1%), and misplaced lines/tubes(11.1%). Although published opinions represent only a subset of malpractice claims,they demonstrated recurring patterns of perceptual and communication-related error within a high examination volume practice environment characterized by lowreimbursement and RVU assignment.</p><p><strong>Conclusion: </strong>Published judicial opinions, though representing only a fraction of claims, illustrate preventable errors in a high-volume modality relevant to emergency radiologists.Findings support continued emphasis on structured search patterns, comparison with prior examinations, effective communication, and, where available, adjunctive AI-assistanceas a second reader to help mitigate risk.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012087","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":"Comments on \"Shortening MRI scanning time for acute ischemic stroke: analysis of the effect of 3.0T MRI compressed sensing deep learning reconstruction\".","authors":"Hasan Nawaz Tahir, Mohammad Idrees, Umema Tariq, Muhammad Zuhair Yusuf, Yousaf Ali","doi":"10.1007/s10140-026-02548-1","DOIUrl":"10.1007/s10140-026-02548-1","url":null,"abstract":"","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149001493","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":"Diagnostic accuracy of deep learning models for detecting wrist and distal forearm fractures in pediatric patients: A systematic review and meta-analysis.","authors":"Danial Sharifi Razavi, Mohammadali Seiri, Mehrdad Farrokhi","doi":"10.1007/s10140-026-02545-4","DOIUrl":"https://doi.org/10.1007/s10140-026-02545-4","url":null,"abstract":"<p><strong>Purpose: </strong>Pediatric wrist and distal forearm fractures are common but can be challenging to diagnose due to age-related skeletal differences and complex fracture patterns. Deep learning models may improve fracture detection; however, their diagnostic performance in pediatric wrist injuries remains unclear. This study aimed to evaluate the diagnostic accuracy and clinical utility of deep learning models for detecting wrist and distal forearm fractures in children.</p><p><strong>Methods: </strong>In this systematic review and diagnostic meta-analysis, MEDLINE, Web of Science, and Scopus were searched from inception to July 2026. Quality appraisal was performed using the QUADAS-2 tool. Diagnostic parameters were estimated using Meta-Disc software and the MIDAS package in Stata. Meta-regression analyses were performed to explore potential sources of heterogeneity.</p><p><strong>Results: </strong>Deep learning models achieved a pooled sensitivity of 0.93 (95% CI, 0.92-0.95) and specificity of 0.85 (95% CI, 0.83-0.87) for fracture detection. The positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 6.83 (95% CI, 5.27-8.84) and 0.08 (95% CI, 0.05-0.12), respectively. The area under the summary receiver operating characteristic (SROC) curve was 0.96.</p><p><strong>Conclusion: </strong>Deep learning models demonstrate high diagnostic performance for detecting wrist and distal forearm fractures in pediatric patients, with particular potential as decision-support tools for fracture exclusion. Diagnostic performance varied by imaging modality and model type, with ultrasonography-based models showing higher specificity and commercially available models showing higher sensitivity. However, limited evidence, methodological heterogeneity, and insufficient external validation highlight the need for prospective multicenter studies before widespread clinical implementation.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148982382","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":"Diagnostic yield of repeat CT pulmonary angiography after a negative examination in the emergency department.","authors":"Natalia Gorelik, Tiffany Fung, Eliana Sacher, Lorenna Mendonça de Albuquerque, Joseph Najjar, Erfan Sadri, Sylvain Grange, José A Correa","doi":"10.1007/s10140-026-02541-8","DOIUrl":"https://doi.org/10.1007/s10140-026-02541-8","url":null,"abstract":"<p><strong>Purpose: </strong>Although repeat CT pulmonary angiography (CTPA) after a negative index examination in the emergency department (ED) is common, its diagnostic utility remains uncertain. This study aimed to determine the incidence and diagnostic yield of repeat CTPA after a negative index examination in the ED.</p><p><strong>Methods: </strong>This retrospective cohort study included adults undergoing CTPA across three EDs at our center from 2016 to 2017. CTPA results were classified as positive, negative, or other (equivocal or negative with reported limitations) based on radiology reports. Patients with a negative index CTPA were followed for two years to identify repeat examinations. Diagnostic yield of repeat CTPA at 1 month, 1 year, and 2 years was compared with that of the index examination using a likelihood ratio test for nested proportions.</p><p><strong>Results: </strong>Among 3,112 patients (median age, 60.1 years; 59.1% women), 331 (10.6%) had a positive index CTPA. Of 2,412 patients with a negative index examination, 297 (12.3%) underwent repeat CTPA within 2 years, including 202 (8.4%) performed in our ED. The diagnostic yield of repeat CTPA performed in our ED was lower than that of the index examination: 3.8% (1/26; p = 0.20) at 1 month, 6.0% (9/150; p = 0.051) at 1 year, and 6.4% (13/202; p = 0.04) at 2 years.</p><p><strong>Conclusion: </strong>Repeat CTPA after a negative examination demonstrated a lower diagnostic yield than initial imaging, highlighting an opportunity for more selective use of repeat CTPA guided by clinical pretest probability.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148918775","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":"Clinical and radiographic findings that impact treatment: a study of 418 proximal humerus fractures.","authors":"Julian Forero-Millan, Wondwossen T Lerebo, Vandan S Patel, Lewis Fanney, Alexandre Arkader, Jie C Nguyen","doi":"10.1007/s10140-026-02534-7","DOIUrl":"10.1007/s10140-026-02534-7","url":null,"abstract":"<p><strong>Purpose: </strong>Regional skeletal maturation can influence injury pattern and treatment selection. This study aimed to systematically characterize pediatric proximal humerus fractures to identify radiographic findings that impact treatment selection.</p><p><strong>Methods: </strong>This IRB-approved retrospective comparative study included pediatric patients (< 18 years), who underwent pre-treatment radiographic examination for proximal humerus fractures (2014-2024). Demographics, injury mechanism, skeletal maturity, physeal involvement and pattern, maximum displacement, angulation, and treatment were collected. Findings between surgically and non-surgically treated fractures were compared using descriptive statistics and using optimal cutoff values, determined using the receiver operating characteristic (ROC) analysis and the Youden index, with additional regression modeling to identify independent predictors of surgery.</p><p><strong>Results: </strong>This study of 418 children (mean age, 9.8 ± 3.6 years; 53.1% girls, 46.9% boys) included fractures in 90.0% skeletally immature, 8.9% maturing, and 1.2% mature humeri. A minority had physeal involvement (14.0%) and underwent surgical treatment (10.0%). Overall, median fracture displacement (relative to shaft width) was 24% (IQR, 12%-53%) and angulation was 14° (IQR, 8-23°) with optimal thresholds identified at > 42% and > 22°, respectively. In the adjusted multivariable logistic regression, independent predictors for surgery included fracture displacement > 42% (OR: 13.3, 95% CI: 4.2-41.7, P < 0.01), age > 12 years (OR: 7.2, 95% CI: 2.2-24.1, P < 0.01), and a non-fall injury mechanism (OR: 6.3, 95% CI: 2.4-16.7, P < 0.01).</p><p><strong>Conclusion: </strong>In our study group, fracture displacement, together with older age and a non-fall injury mechanism, independently impacts management of pediatric patients with acute proximal humerus fractures.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148873415","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":"Early and delayed acute kidney injury after contrast-enhanced CT in critically ill adults: a target trial emulation.","authors":"Daniele Orso, Giovanni Aldegheri, Federico Fonda, Giacomo Bacchetti, Manuela Lugano, Chiara Zuiani, Rossano Girometti, Giorgio Della Rocca","doi":"10.1007/s10140-026-02537-4","DOIUrl":"https://doi.org/10.1007/s10140-026-02537-4","url":null,"abstract":"<p><strong>Purpose: </strong>To assess whether intravenous iodinated contrast administered for computed tomography is associated with early or delayed acute kidney injury (AKI) in critically ill adults.</p><p><strong>Methods: </strong>We conducted a retrospective target trial emulation using the Medical Information Mart for Intensive Care IV (MIMIC-IV), a single-center, deidentified electronic health record database of hospital and intensive care admissions. Adults undergoing contrast-enhanced CT (CECT) or non-contrast CT (NCCT) during or immediately before intensive care admission were included. The primary outcome was creatinine-defined AKI within 48 h. Inverse probability of treatment weighting (IPTW) addressed measured confounding.</p><p><strong>Results: </strong>Among 7,772 patients, 5,319 underwent CECT and 2,453 underwent NCCT. AKI within 48 h occurred in 19.3% and 20.4%, respectively. CECT was not associated with AKI within 48-72 h, time to first AKI through 7 days, renal replacement therapy within 7 days, or longitudinal creatinine trajectories.</p><p><strong>Conclusion: </strong>CECT was not associated with early or cumulative 7-day creatinine-defined AKI in critically ill adults. Residual confounding remains possible, particularly because acute illness severity, imaging indication, and post-index events were incompletely captured.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148863970","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 rare and underrecognized complication of sickle cell disease in a pediatric patient: acute soft head syndrome.","authors":"Aanchal Gupta, Blaise Jones, Dan Pham, Omar Niss, Marguerite Caré","doi":"10.1007/s10140-026-02531-w","DOIUrl":"https://doi.org/10.1007/s10140-026-02531-w","url":null,"abstract":"<p><p>Acute soft head syndrome (ASHS) is an extremely rare and underrecognized complication of Sickle Cell Disease (SCD), and limited awareness can lead to misdiagnosis as infection or trauma. We report the case of a 16-year-old male with hemoglobin SS (HbSS) SCD who presented to the emergency department with headache and progressive periorbital swelling during a vaso-occlusive crisis. MRI demonstrated multifocal calvarial infarctions with overlying hemorrhagic subperiosteal collections and subgaleal edema without evidence of osteomyelitis or orbital cellulitis. Symptoms improved with conservative therapy, including analgesia and packed red blood cell transfusion (pRBC). This report emphasizes the need for a high index of suspicion and familiarity with characteristic MRI findings of calvarial bone infarcts and ASHS, as early recognition can prevent misdiagnosis and support timely optimization of sickle cell care.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148808448","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":"Artificial intelligence and the phantom pneumothorax: Clinical reasoning still matters.","authors":"Fulvio Cacciapuoti, Antonio Ruocco, Salvatore Crispo, Massimiliana Abbate, Giuseppina Dell'Aversano Orabona, Osvaldo Cuomo, Ciro Mauro","doi":"10.1007/s10140-026-02533-8","DOIUrl":"https://doi.org/10.1007/s10140-026-02533-8","url":null,"abstract":"<p><p>Artificial intelligence (AI) has become increasingly integrated into chest radiograph interpretation, demonstrating excellent diagnostic performance for several thoracic abnormalities, including pneumothorax. Nevertheless, current AI systems remain predominantly image-based and do not inherently incorporate procedural or clinical information into diagnostic interpretation. We report the case of an 81-year-old man who underwent uncomplicated left-sided dual-chamber permanent pacemaker implantation. Routine post-procedural chest radiography, analyzed by an AI-assisted interpretation system, generated a positive alert for a right apical pneumothorax, highlighting the suspected abnormality with automated visual annotation. The alert was immediately considered clinically discordant by the treating team, given the left-sided venous access, normal oxygen saturation, hemodynamic stability, and absence of respiratory symptoms. Because of this clinicoradiological discordance, chest computed tomography was performed and definitively excluded pneumothorax, confirming a false-positive AI interpretation. The patient required no additional intervention and experienced an uneventful recovery. This case highlights the importance of integrating AI-generated findings with procedural details, bedside clinical assessment, and, when clinically indicated, confirmatory imaging in the presence of clinicoradiological discordance. Although AI can accurately identify many radiographic abnormalities, accurate diagnosis ultimately depends on integrating imaging findings with procedural information, clinical presentation, and pre-test probability. This case also emphasizes that AI should be regarded as a clinical decision-support tool rather than an autonomous diagnostic system and highlights the continuing importance of physician oversight in ensuring patient safety during AI-assisted post-procedural imaging interpretation.</p>","PeriodicalId":11623,"journal":{"name":"Emergency Radiology","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148789374","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}