European Radiology最新文献

{"title":"Topogram-based anatomical labelling of CT series: anatomy-aware CT data processing using deep learning.","authors":"Yutong Wen, Judith Kohnke, Vicky Parmar, Christian Bojahr, Kamyar Arzideh, Cynthia Sabrina Schmidt, Anton Sheahan Quinsten, Maximilian Lindholz, Matteo Mancino, Benedikt Schaarschmidt, Lale Umutlu, Michael Forsting, Johannes Haubold, Felix Nensa, Katarzyna Borys, René Hosch","doi":"10.1007/s00330-026-12830-y","DOIUrl":"https://doi.org/10.1007/s00330-026-12830-y","url":null,"abstract":"<p><strong>Objectives: </strong>This study provides a Rapid Analysis and Processing of Image Data (RAPID) framework that combines deep learning-based CT topogram analysis with DICOM spatial geometry to enable reliable anatomical labelling of CT series independent of inconsistent textual metadata.</p><p><strong>Materials and methods: </strong>In this single-centre retrospective study, three YOLOv8-based models comprising the RAPID framework were trained on CT topograms to perform global anatomical classification, body-region detection, and landmark detection. Classification used 83207 topograms (20,802 test), while landmark and body region detection models were trained on 2000 (500 test) and 1926 (481 test) topograms, respectively, collected between 2003 and 2022. Model performance was evaluated using the F1 score and mAP50, with additional external validation on the external cohort. Furthermore, three radiologists independently reviewed 150 randomly selected predictions for detection models using a Likert-scale-based clinical assessment with inter-rater agreement.</p><p><strong>Results: </strong>Across a total of 65,250 patients (median age, 62 years; interquartile range, 23; 44% female) included in training and testing, inference performance achieved an overall internal F1 score of 0.920 and an external score of 0.970 for classification. Body region and landmark detection achieved internal mAP50 values of 0.993 and 0.958, with corresponding F1 scores of 0.996 and 0.957, respectively. The external mAP scores for detection tasks were 0.952 and 0.926, with corresponding F1 scores of 0.929 and 0.905, respectively. Experts' reviews were generally consistent with the technical evaluation.</p><p><strong>Conclusion: </strong>RAPID enables accurate image-derived anatomical labelling of CT series using topograms.</p><p><strong>Key points: </strong>Question Reliable anatomy-based CT series labelling is essential for clinical workflows, but the traditional approach that relies on inconsistent DICOM metadata requires manual review and limits scalability. Findings The three proposed deep learning models achieved high performance in identifying anatomical regions and landmarks, with expert assessments in agreement with the quantitative evaluation. Clinical relevance Deep Learning-based analysis of CT topograms with DICOM-derived spatial geometry, enables reliable and reproducible image-based anatomical labelling of CT series, reducing reliance on inconsistent DICOM attributes and improving data consistency and scalability for clinical applications.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148886876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to the Letter to the Editor: Thyroid incidentalomas detected on ¹⁸F-fluorodeoxyglucose positron emission tomography with computed tomography in cancer patients: imaging clues for further evaluation.","authors":"Myoung Kyoung Kim, Soo Yeon Hahn, Joon Young Choi","doi":"10.1007/s00330-026-12832-w","DOIUrl":"https://doi.org/10.1007/s00330-026-12832-w","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148886800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI in breast ultrasound for pregnant and lactating patients: opportunities and real-world challenges.","authors":"Antonio Portaluri, Ritse M Mann","doi":"10.1007/s00330-026-12851-7","DOIUrl":"https://doi.org/10.1007/s00330-026-12851-7","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148879516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying optimal dose head CT acquisition techniques through cluster analysis from 904,209 scans.","authors":"Berk Yildirim, Denise Bos, Taewoon Kang, Carly Stewart, Timothy P Szczykutowicz, Rebecca Smith-Bindman","doi":"10.1007/s00330-026-12842-8","DOIUrl":"https://doi.org/10.1007/s00330-026-12842-8","url":null,"abstract":"<p><strong>Objectives: </strong>To identify clinically established and frequently utilized routine head computed tomography (CT) acquisition techniques in children and adults that achieve lower radiation.</p><p><strong>Materials and methods: </strong>The level of the analysis is at the CT scan (series) level. CT acquisition parameters were analyzed from a large, international CT dose registry. Scans were analyzed separately in adults and children, and by approach (helical or axial), resulting in four strata. K-means clustering, an unsupervised machine learning approach, assigned the scans into clusters based on the following acquisition parameters: Tube current, voltage, collimation, scan length, and for helical scans, pitch. Effective patient diameter, unadjusted and patient size-adjusted dose-length product (DLP), and volume CT dose index (CTDI_vol) were compared across clusters.</p><p><strong>Results: </strong>864,182 CT scans in adults and 40,027 scans in children between January 1, 2015, and March 11, 2021, were included in the analysis. Scans were classified into seven helical and six axial clusters in adults, six helical and four axial clusters in children. In all four strata, the mean size-adjusted DLP varied more than two-fold, and up to 3.4-fold, across the clusters. For example, for adult helical scans (the largest strata), the size-adjusted DLP ranged from 372 mGy·cm to 998 mGy·cm (relative dose 2.7) across clusters. Clusters with the lowest radiation generally utilized lower tube current and voltage, but protocols utilized various approaches to result in lower doses.</p><p><strong>Conclusion: </strong>There remains a large variation in the radiation dose within frequently used head CT acquisition techniques. Clustering analysis enables identifying protocols with lower doses.</p><p><strong>Key points: </strong>Question Is there a large variation in the doses used for routine head CT, and can we identify best-practice, lowest dose approaches for scanning? Findings Across each stratum (adult/pediatric, helical/axial), the mean size-adjusted DLP varied by more than two-fold across the CT scan clusters, reflecting significant differences in radiation. Clinical relevance Many routine head CT acquisition techniques use excessive radiation doses. Standardizing practice to the lowest dose clusters would result in significant reductions in patient dose.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148879547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contrast-enhanced MRI improves diagnostic accuracy in stage Tis-T1 rectal cancer: a head-to-head comparison with endorectal ultrasound.","authors":"Lijuan Wan, Diliang Li, Yaqing Kong, Guoxu Zhao, Fan Yang, Mengwen Liu, Zhe Gao, Wenwen Fan, Yuan Liu, Hongmei Zhang","doi":"10.1007/s00330-026-12565-w","DOIUrl":"10.1007/s00330-026-12565-w","url":null,"abstract":"<p><strong>Objective: </strong>To investigate whether the addition of contrast-enhanced sequences improves the diagnostic value of MRI in Tis-T1 rectal cancer and to compare its diagnostic performance with that of endorectal ultrasound (ERUS).</p><p><strong>Materials and methods: </strong>Patients with pathologically confirmed Tis-T2 rectal cancer who underwent curative resection between January 2020 and December 2023 were enrolled. All patients underwent preoperative MRI (including contrast-enhanced sequencing) and ERUS. Tumor shape and the status of muscularis propria (SMP) were evaluated on T2-weighted images by a radiologist, whereas submucosal enhancing stripe (SES) was assessed on contrast-enhanced MRI. An MRI-based combined model was constructed by integrating tumor shape, SMP, and SES features. ERUS-based tumor staging was performed by an endoscopist. The diagnostic performance of SMP, SES, the combined model, and ERUS in identifying stage Tis-T1 lesions was evaluated. The area under the receiver operating characteristic curves (AUCs) was calculated, and statistical differences were assessed using the DeLong method.</p><p><strong>Results: </strong>In total, 136 patients (mean age: 60 ± 10 years; 78 men) with 138 lesions (82 Tis-T1 and 56 T2 lesions) were enrolled. The AUC values for SMP, SES, the combined model, and ERUS were 0.762 (95% confidence interval [CI]: 0.682-0.830), 0.861 (95% CI: 0.792-0.914), 0.915 (95% CI: 0.856-0.956), and 0.806 (95% CI: 0.730-0.868), respectively. Adding contrast-enhanced MRI feature significantly improved the diagnostic performance over the common approach (combined model vs SMP: AUC difference = 0.154; p < 0.001), and the combined model was also better than ERUS (AUC difference = 0.109; p = 0.003).</p><p><strong>Conclusion: </strong>Incorporating contrast-enhanced MRI improves stage Tis-T1 rectal cancer diagnostic accuracy and outperforms ERUS.</p><p><strong>Key points: </strong>Question Can adding contrast-enhanced MRI feature improve the diagnostic performance of MRI in identifying stage Tis-T1 rectal cancer compared to ERUS? Findings The MRI-based combined model incorporating contrast-enhanced and T2WI features achieved the best diagnostic performance (AUC value: 0.915), significantly superior to that of ERUS (p = 0.003). Clinical relevance Incorporating contrast-enhanced MRI offers a more reliable basis for personalized organ-sparing treatment planning and provides a foundation for future clinical practice guidelines.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6887-6898"},"PeriodicalIF":6.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147766460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The augmentation myth: AI, economics, and workforce substitution in radiology.","authors":"Renato Cuocolo, Merel Huisman","doi":"10.1007/s00330-026-12568-7","DOIUrl":"10.1007/s00330-026-12568-7","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6928-6930"},"PeriodicalIF":6.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147766627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bone marrow R2* correlates with liver iron load and is associated with decreased survival in patients with cirrhosis without liver iron overload.","authors":"Seong Woo Cho, Youngjune Kim, June Park, Jae Hyon Park","doi":"10.1007/s00330-026-12614-4","DOIUrl":"10.1007/s00330-026-12614-4","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate vertebral bone-marrow (BM) iron content using R2* relaxometry in patients with cirrhosis, determine its correlation with hematologic and hepatic indices, and assess the relationship between BM iron overload and survival.</p><p><strong>Materials and methods: </strong>This retrospective study analyzed 190 patients who underwent liver magnetic resonance elastography between January 2018 and October 2024. Liver and vertebral BM R2* values were measured, and liver iron concentration (LIC) was estimated. Patients were categorized into normal, mild, or moderate liver and vertebral BM iron overload groups. Correlations were assessed using Spearman's rank correlation coefficient, independent predictors were assessed using binary logistic regression, and survival was analyzed using Cox proportional hazards regression.</p><p><strong>Results: </strong>Vertebral BM iron overload was observed in 28.7%, 51.5%, and 85.6% of patients with normal, mild, and moderate liver iron overload, respectively, wherein moderate iron overload comprised of 23.3%, 35.2%, and 50.0% of these groups. Vertebral BM R2* correlated with liver R2* and LIC (r = 0.347; p < 0.001), ferritin (r = 0.210; p = 0.004), and total iron-binding capacity (TIBC) (r = -0.186; p = 0.019). Liver R2* (odds ratio (OR), 1.010; p = 0.002) and TIBC (OR, 0.990; p = 0.035) were independent predictors of moderate vertebral BM iron overload. Vertebral BM R2* showed no correlation with liver function markers or Child-Pugh score. However, among patients without liver iron overload, moderate vertebral BM iron overload was associated with 5-year overall mortality (hazard ratio (HR), 3.981; p = 0.014).</p><p><strong>Conclusion: </strong>Vertebral BM R2* correlated with LIC and was associated with decreased survival in patients with normal liver iron.</p><p><strong>Key points: </strong>Question Do vertebral bone-marrow R2* values correlate with liver iron metrics in patients with cirrhosis, and are they associated with overall survival? Findings Higher vertebral bone-marrow R2* values were observed across liver iron categories and were associated with poorer survival among patients with normal liver iron. Clinical relevance Vertebral bone-marrow R2* quantification may provide additional information for risk assessment in patients with cirrhosis with normal liver iron.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"7032-7046"},"PeriodicalIF":6.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147873854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the Editor: Deep learning TMJ MRI-reader-level equivalence is a foundation, not a finish line.","authors":"Carlos Fernando Mourão, Antonio Coutinho, Luiz Eduardo Juliasse, Rodrigo Dos Santos Pereira","doi":"10.1007/s00330-026-12606-4","DOIUrl":"10.1007/s00330-026-12606-4","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"7375-7376"},"PeriodicalIF":6.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147835480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting early response to ablative radiotherapy in oligometastatic disease: a scoping review of radiomics-based machine learning and deep learning models.","authors":"Raquel García-Pablo, Marta Canela-Capdevila, Alberto Martínez-Caballero, Rocío Benavides-Villareal, Albert Moragas-Fernández, Andrea Jiménez-Franco, Berta Piqué-Smith, Camila Montesinos-Guevara, Jordi Camps, Jorge Joven, Angel Torrado-Carvajal, Meritxell Arenas","doi":"10.1007/s00330-026-12590-9","DOIUrl":"10.1007/s00330-026-12590-9","url":null,"abstract":"<p><strong>Objectives: </strong>Oligometastatic disease represents an intermediate stage of cancer, often treated with surgery or ablative radiotherapy (ART). This scoping review aimed to systematically summarize current evidence on the use of radiomics, including machine learning and deep learning approaches, to predict response to ART. We also aimed to assess the methodological quality and reporting transparency of published studies, identifying gaps and opportunities for future research.</p><p><strong>Materials and methods: </strong>A systematic search in PubMed, Web of Science, Scopus, Embase, Cochrane, and Google Scholar identified studies that used radiomics for predicting ART response. Two reviewers independently selected and assessed the methodological quality using the Radiomics Quality Score (RQS) and the METhodological RadiomICs Score (METRICS). In addition, reporting transparency was evaluated using the CheckList for EvaluAtion of Radiomics research (CLEAR). This scoping review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews guidelines.</p><p><strong>Results: </strong>The systematic search identified 9463 records, of which 29 studies (3946 patients) were included. Most studies used MRI-derived features, with 24 focusing on brain metastases. Radiomics-based models demonstrated variable predictive performance (area under the curve, AUC: 0.69-0.95), with deep learning models achieving the highest accuracies (AUC: 0.85-1.00). Methodological quality of the studies was moderate (mean RQS: 13; METRICS: 64.2-78%).</p><p><strong>Conclusion: </strong>Radiomics-based models show potential for identifying patients unlikely to benefit from ART, but their clinical implementation remains limited, especially for extracranial metastases. Future research should focus on multicenter, prospective studies with standardized protocols, incorporating clinical and dosimetric data for broader clinical application.</p><p><strong>Key points: </strong>Question Can radiomics-based predictive models reliably assess treatment response to ablative radiotherapy in oligometastatic disease, and how robust is the current methodological evidence supporting their use? Findings Radiomics models show encouraging predictive performance, mainly for brain metastases, yet substantial methodological heterogeneity and limited validation hinder their clinical translation. Clinical relevance Radiomics-based prediction models hold potential for identifying patients unlikely to benefit from ablative radiotherapy, enabling more personalized treatment. Further prospective, multicenter, and methodologically standardized studies are essential before clinical implementation.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6997-7009"},"PeriodicalIF":6.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451257/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147766592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photon counting detector CT contrast agent-reduced transcatheter aortic valve reconstruction planning: a comparative study.","authors":"Yannik C Layer, Alexander Isaak, Narine Mesropyan, Patrick A Kupczyk, Dmitrij Kravchenko, Marilia Voigt, Tatjana Dell, Julian A Luetkens, Daniel Kuetting","doi":"10.1007/s00330-026-12613-5","DOIUrl":"10.1007/s00330-026-12613-5","url":null,"abstract":"<p><strong>Objectives: </strong>Continuous efforts are made to reduce contrast media, improving patient safety, reducing environmental risks, and addressing recurring supply shortages. The aim of this study was to evaluate contrast agent-reduced CT protocols for transcatheter aortic valve reconstruction (TAVR) planning in photon counting detector CT (PCDCT).</p><p><strong>Materials and methods: </strong>162 BMI-matched examinations with standard dose contrast media (SCD; 80 mL; Iohexol 300 mg/mL; 81 examinations) and reduced contrast media dose (RCD; 50 mL; 81 examinations) for TAVR planning on a PCDCT were included in this retrospective monocentric study. Virtual monoenergetic reconstructions (VMI) at 70 keV, 60 keV and 50 keV of contrast agent-reduced examinations were compared with polyenergetic images. Quantitatively, regions-of-interest (ROIs) were placed in the abdominal aorta, iliac bifurcation, femoral artery, left ventricle and trapezius muscles. Signal-to-noise-ratio (SNR) and contrast-to-noise-ratio (CNR) were calculated. Qualitatively, diagnostic quality and contrast were assessed on a visual grading scale of 1 (non-diagnostic) - 5 (excellent) and contrast agent dose was estimated.</p><p><strong>Results: </strong>Averaged, SNR and CNR decreased by 8.71% and 16.78%, respectively, on PCDCT with reduced contrast dose (RCD vs. SCD; both p < 0.001). VMI50keV increased SNR by 44.10% (p < 0.001) and CNR by 52.73% (p < 0.001) compared with SCD. In the ascending aorta, SNR increased from 19.80 ± 6.24 (SCD) to 35.78 ± 13.20 (RCD_VMI50keV) and CNR from 18.84 ± 7.78 to 29.77 ± 16.70. Median contrast intensity was 5 for SCD, 4 for RCD_CR, and 5 for RCD_VMI50keV.</p><p><strong>Conclusion: </strong>The diagnostic efficacy of TAVR planning assessment using PCDCT with minimized contrast agent dosing is preserved, presenting a practical approach to conserve contrast media.</p><p><strong>Key points: </strong>Question The aim of the study was to implement a PCDCT-adapted contrast media dose protocol to reduce contrast agent volume at sufficient diagnostic quality. Findings PCDCT enables substantial contrast dose reduction for TAVR planning with maintained diagnostic image quality. Low-keV virtual monoenergetic image reconstructions compensate for the reduced iodine concentration. Clinical relevance The study demonstrates the potential of contrast media reduction of PCD-CT in clinical routine. This can benefit patients with renal impairment, for example, and reduce the negative effects of iodinated contrast media on the environment.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"7095-7104"},"PeriodicalIF":6.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147835478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}