JACC. Cardiovascular imaging最新文献

{"title":"Good FFRCT Test-Retest Reproducibility","authors":"Nadia Iraqi MD, Martin Bødtker Mortensen MD, PhD, Niels Peter Rønnow Sand MD, PhD, Martin Busk MD, PhD, Kristian Tækker Madsen MD, PhD, Erik Lerkevang Grove MD, PhD, Kamilla Bech Pedersen RT, Helle Kanstrup MD, PhD, Timothy A. Fairbairn MD, PhD, Erik Parner MSc, PhD, Jesper Møller Jensen MD, PhD, Bjarne Linde Nørgaard MD, PhD","doi":"10.1016/j.jcmg.2025.02.009","DOIUrl":"10.1016/j.jcmg.2025.02.009","url":null,"abstract":"","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":"18 7","pages":"Pages 834-837"},"PeriodicalIF":12.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144119801","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":"Prognostic Time Frame of Plaque and Hemodynamic Characteristics and Integrative Risk Prediction for Acute Coronary Syndrome","authors":"Seokhun Yang MD , Jae Wook Jung MD , Sang-Hyeon Park MD , Jinlong Zhang MD , Keehwan Lee MD , Doyeon Hwang MD , Kyu-Sun Lee MD , Sang-Hoon Na MD , Joon-Hyung Doh MD , Chang-Wook Nam MD , Tae Hyun Kim MD , Eun-Seok Shin MD , Eun Ju Chun MD , Su-Yeon Choi MD , Hyun Kuk Kim MD , Young Joon Hong MD , Hun-Jun Park MD , Song-Yi Kim MD , Mirza Husic MD , Jess Lambrechtsen MD , Bon-Kwon Koo MD","doi":"10.1016/j.jcmg.2025.02.003","DOIUrl":"10.1016/j.jcmg.2025.02.003","url":null,"abstract":"<div><h3>Background</h3><div>The relevant time frame for predicting future acute coronary syndrome (ACS) based on coronary lesion characteristics remains uncertain.</div></div><div><h3>Objectives</h3><div>The aim of this study was to investigate the association of lesion characteristics with test-to-event time and their prognostic impact on ACS.</div></div><div><h3>Methods</h3><div>The EMERALD II (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary CT Angiography and Computational Fluid Dynamics II) study analyzed 351 patients who underwent coronary computed tomography angiography (CTA) and experienced ACS between 1 month and 3 years of follow-up. Lesions identified on coronary CTA were classified as culprit (n = 363) or nonculprit (n = 2,088) on the basis of invasive coronary angiography findings at the time of ACS. Core laboratory coronary CTA analyses assessed 4 domains: degree of stenosis, plaque burden, number of adverse plaque characteristics (APC) (low-attenuation plaque, positive remodeling, spotty calcification, and napkin-ring sign), and changes in coronary CTA–derived fractional flow reserve across the lesion (ΔFFR<sub>CT</sub>). Patients were categorized into short (<1 year), mid (1-2 years), and long (2-3 years) test-to-event time groups.</div></div><div><h3>Results</h3><div>Patient characteristics, including cardiovascular risk factors, did not differ across short, mid, and long test-to-event groups (<em>P ></em> 0.05 for all), and the proportion of ACS culprit lesions was similar (<em>P =</em> 0.552). Among culprit lesions, shorter test-to-event time was associated with higher luminal stenosis, plaque burden, and ΔFFR<sub>CT</sub> (<em>P</em> for trend < 0.001 for all). The predictability for ACS culprit lesions based on the combined 4 characteristics tended to decrease over time and significantly reduced beyond 2 years (AUC: 0.851 vs 0.741; <em>P =</em> 0.006). In predicting ACS risk within test-to-event time <2 years using obstructive lesions (stenosis ≥ 50%), APC ≥2, plaque burden ≥70%, and ΔFFR<sub>CT</sub> ≥0.10, the risk was elevated compared to the average proportion of lesions becoming ACS culprit (12.1%) in the following subsets: lesions with 4 characteristics (proportion of lesions becoming ACS culprit: 49.3%; <em>P <</em> 0.001), lesions with 3 characteristics (obstructive lesions with plaque burden ≥70% and either ΔFFR<sub>CT</sub> ≥0.10 [proportion of lesions becoming ACS culprit: 33.0%; <em>P <</em> 0.001] or APC ≥2 [proportion of lesions becoming ACS culprit: 31.2%; <em>P <</em> 0.001]), and lesions with 2 characteristics (plaque burden ≥70% and ΔFFR<sub>CT</sub> ≥0.10; proportion of lesions becoming ACS culprit: 21.5%; <em>P =</em> 0.016).</div></div><div><h3>Conclusions</h3><div>Increased luminal stenosis, plaque burden, and ΔFFR<sub>CT</sub> were associated with shorter test-to-ACS event time. The prognostic impact of lumen, plaque, and local hemodynamic charact","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":"18 7","pages":"Pages 784-795"},"PeriodicalIF":12.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143872002","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":"Statin Therapy Persistence Following Opportunistic Screening for Coronary Artery Calcium on Nongated Chest CTs","authors":"Sarkis G. Bouladian BS, Summer Ngo BS, Domenico Mastrodicasa MD, David Eng MS, Nishith Khandwala MS, Doug Sousa BS, Akshay S. Chaudhari PhD, David J. Maron MD, Fatima Rodriguez MD, MPH, Alexander T. Sandhu MD, MS","doi":"10.1016/j.jcmg.2025.03.007","DOIUrl":"10.1016/j.jcmg.2025.03.007","url":null,"abstract":"","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":"18 7","pages":"Pages 841-843"},"PeriodicalIF":12.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144078141","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":"Challenges and Strategies for Deep Learning in Cardiovascular Imaging","authors":"David Pasdeloup PhD ,&nbsp;Andreas Østvik PhD ,&nbsp;Sindre Olaisen MD, PhD ,&nbsp;Eirik Skogvoll MD, PhD ,&nbsp;Havard Dalen MD, PhD ,&nbsp;Lasse Lovstakken PhD","doi":"10.1016/j.jcmg.2025.02.011","DOIUrl":"10.1016/j.jcmg.2025.02.011","url":null,"abstract":"<div><h3>Background</h3><div>Automated measurements in cardiac imaging with the use of deep learning (DL) is a highly active area of research and innovation. However, some concerns challenge the translation of DL methods from research to clinical implementation.</div></div><div><h3>Objectives</h3><div>The authors evaluated 3 challenges for cardiac measurements by DL using left ventricular ejection fraction (LVEF) for management of heart failure and discuss mitigation strategies.</div></div><div><h3>Methods</h3><div>Using 3 different populations (N = 3,538), automated LVEF measurements were obtained with the use of supervised end-to-end learning and analyzed in terms of HF management. Three common challenges related to evaluation metrics, training data, and model generalization were studied.</div></div><div><h3>Results</h3><div>For the evaluation challenge, the authors identified significant unreliability of the AUC when applied to dichotomized heart failure diagnosis. Specifically, AUC varied from 0.71 to 0.98 owing solely to changes in population characteristics. For the training data challenge, model performance could be enhanced even after reducing the number of training subjects by 40%. For the generalization challenge, a performance degradation was observed compared with internal data when testing the model on external data. Integrating medical imaging domain knowledge in the DL framework effectively helped to recover performance and improve generalizability.</div></div><div><h3>Conclusions</h3><div>Both training data and generalization aspects challenge the performance of DL algorithms for automated cardiac measurements. In addition, evaluation metrics challenge the ability to detect underperforming algorithms. By considering evaluation metrics and training data distribution, and incorporating imaging domain knowledge, the design and evaluation of DL models can be improved, leading to more robust models, improved interpretation, and easier comparison across data sets. These findings may guide researchers and clinicians in implementing DL models for cardiovascular imaging.</div></div>","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":"18 7","pages":"Pages 751-764"},"PeriodicalIF":12.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144569899","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":"Comprehensive Lesion Assessment for the Prediction of Acute Coronary Syndrome","authors":"Andrew Lin MBBS, BMedSc, PhD,&nbsp;Nitesh Nerlekar MBBS, PhD, MPH","doi":"10.1016/j.jcmg.2025.04.002","DOIUrl":"10.1016/j.jcmg.2025.04.002","url":null,"abstract":"","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":"18 7","pages":"Pages 796-798"},"PeriodicalIF":12.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144078136","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":"Extent and Features of Late Gadolinium Enhancement Stratify Arrhythmic Risk in Patients With Biopsy-Proven Sarcoidosis","authors":"Alessia Azzu MD, PhD ,&nbsp;Alexios S. Antonopoulos MD, PhD ,&nbsp;Joseph Okafor MD ,&nbsp;Marco Morosin MD ,&nbsp;Emmanuel Androulakis MD, PhD ,&nbsp;Suzan Hatipoglu MD ,&nbsp;Batool Almogheer MD ,&nbsp;Raheel Ahmed MD ,&nbsp;Raad Mohiaddin MD, PhD ,&nbsp;Francisco Alpendurada MD, PhD ,&nbsp;Cemil Izgi MD ,&nbsp;Amrit Lota MD, PhD ,&nbsp;Kshama Wechalekar MD ,&nbsp;Rajdeep Khattar MD, PhD ,&nbsp;Athol Wells MD, PhD ,&nbsp;John Baksi MD, PhD ,&nbsp;Rakesh Sharma MD, PhD ,&nbsp;Vasileios Kouranos MD, PhD ,&nbsp;Dudley J. Pennell MD","doi":"10.1016/j.jcmg.2025.02.012","DOIUrl":"10.1016/j.jcmg.2025.02.012","url":null,"abstract":"<div><h3>Background</h3><div>Risk assessment in cardiac sarcoidosis remains challenging.</div></div><div><h3>Objectives</h3><div>This study explored the prognostic value of myocardial late gadolinium enhancement (LGE) in sarcoidosis patients.</div></div><div><h3>Methods</h3><div>The study cohort included 324 patients with biopsy-proven sarcoidosis. LGE extent, pattern, and location were analyzed. The primary endpoint was ventricular tachycardia (VT) or ventricular fibrillation (VF) or appropriate device therapy. Secondary endpoints were hospitalization for heart failure (HF) or heart transplantation (HTx) and all-cause mortality.</div></div><div><h3>Results</h3><div>Over a 4.6-year follow-up, 30 patients (9.3%) reached the primary endpoint. HF/HTx occurred in 15 patients (4.6%) and all-cause mortality in 41 (12.7%). LGE extent was independently predictive of the primary endpoint (per SD change: HR: 1.03 [95% CI: 1.00-1.06]; <em>P =</em> 0.047), but not of HF/HTx (<em>P =</em> 0.30) or all-cause mortality (<em>P =</em> 0.50). Further to LGE extent, LGE on the right ventricular (RV) septum (HR: 5.43 [95% CI: 2.61-11.30]; <em>P &lt;</em> 0.001), RV free wall (HR: 4.30 [95% CI: 1.99-9.27]; <em>P &lt;</em> 0.001), and multifocal LGE (HR: 4.62 [95% CI: 2.19-9.72]; <em>P &lt;</em> 0.001) were strongly predictive of the arrhythmia endpoint. Based on these findings, we propose an algorithm that identifies 4 patient subgroups and stratifies well the arrhythmia risk in biopsy-proven sarcoidosis patients (cumulative event rates: 1%, 11%, 23%, and 44%, respectively; chi-square = 44.7; <em>P =</em> 1.084 × 10⁻⁹). Compared with the Heart Rhythm Society classification system, this approach significantly enhanced model performance (chi-square = 8.02; <em>P =</em> 0.046) and risk discrimination (ΔAUC = 0.082; <em>P =</em> 0.019), and reclassified 43% of the population (9% to higher and 34% to lower risk categories).</div></div><div><h3>Conclusions</h3><div>The authors propose a new risk stratification approach based on LGE features for assessing the risk of life-threatening ventricular arrhythmias in patients with biopsy-proven sarcoidosis.</div></div>","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":"18 7","pages":"Pages 768-780"},"PeriodicalIF":12.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144569902","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":"Predicting Arrhythmic Risk in Cardiac Sarcoidosis Using Late Gadolinium Enhancement","authors":"Amit R. Patel MD,&nbsp;Nisha Hosadurg MBBS, MS","doi":"10.1016/j.jcmg.2025.06.002","DOIUrl":"10.1016/j.jcmg.2025.06.002","url":null,"abstract":"","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":"18 7","pages":"Pages 781-783"},"PeriodicalIF":12.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144569903","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":"Disease Progression in Exercise-Induced Arrhythmogenic Cardiomyopathy Compared With Arrhythmogenic Right Ventricular Cardiomyopathy.","authors":"Linda T Aaserud, Christine Rootwelt-Norberg, Paul A S Olsen, Christian K Five, Anna I Castrini, Eivind W Aabel, Kristina H Haugaa, Øyvind H Lie","doi":"10.1016/j.jcmg.2025.03.018","DOIUrl":"https://doi.org/10.1016/j.jcmg.2025.03.018","url":null,"abstract":"<p><strong>Background: </strong>Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inheritable heart disease, whereas exercise-induced arrhythmogenic cardiomyopathy (EiAC) is a proposed acquired similar phenotype in athletes. The differences in disease progression between these entities are not well understood.</p><p><strong>Objectives: </strong>This study aims to assess structural, functional, and arrhythmic disease progression in EiAC compared with ARVC.</p><p><strong>Methods: </strong>This longitudinal cohort study included EiAC patients who were competitive endurance athletes (>24 MET-hours/week for >6 consecutive years) referred due to ventricular arrhythmias (VA), without inherited or genetic factors or other evident causes, and genotype-positive ARVC patients with a definite diagnosis and their genotype-positive family members for comparison. Disease progression was assessed by repeated echocardiographic examinations and incident VA during long-term follow-up.</p><p><strong>Results: </strong>The authors included 125 ARVC patients (61 women, aged 38 ± 17 years) and 41 EiAC patients (6 women, aged 45 ± 13 years) and followed them for 96 months (Q1-Q3: 73-132 months) and 82 months (Q1-Q3: 50-118 months), respectively. The authors analyzed 730 echocardiographic examinations (538 ARVC, 192 EiAC). Right ventricular (RV) structure and function remained stable in EiAC patients, whereas those in ARVC patients deteriorated during follow-up. The 5-year and 10-year cumulative incidences of VA were similar between EiAC and ARVC patients.</p><p><strong>Conclusions: </strong>RV structure and function deteriorated in ARVC patients but remained stable in EiAC patients during follow-up. The incidence of VA was high in both populations. These results indicate that EiAC patients should be followed closely over time regardless of structural and functional progression.</p>","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":" ","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144600454","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":"Comparative Prognosis by Stress ECG and Stress Imaging: Results From the ISCHEMIA Trial.","authors":"Leslee J Shaw, Lawrence M Phillips, Jonathon Leipsic, Samuel Broderick, Jennifer H Mieres, Thomas H Marwick, Matthias G Friedrich, Todd Miller, Renato D Lopes, Benjamin Chow, Rodrigo Cerci, Ron Blankstein, Marcelo DiCarli, David J Maron, Judith S Hochman, Karen P Alexander, Gregg W Stone, Sean O'Brien, Bernard R Chaitman, Raymond Y Kwong, Michael H Picard, Daniel S Berman, Harmony R Reynolds","doi":"10.1016/j.jcmg.2025.03.016","DOIUrl":"10.1016/j.jcmg.2025.03.016","url":null,"abstract":"<p><strong>Background: </strong>Limited contemporary evidence exists on risk prediction by stress imaging and exercise electrocardiography (ECG) among patients with chronic coronary syndromes (CCS). Objectives From the ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) study, prognosis was examined by core laboratory-defined stress imaging and exercise ECG findings in CCS patients.</p><p><strong>Methods: </strong>A total of 5,179 patients (qualifying by stress nuclear imaging [n = 2,567], echocardiography [n = 1,085], cardiac magnetic resonance [CMR] [n = 257], and ECG [n = 1,270]) were randomized. Cox models assessed associations between trial endpoints and the number of scarred and ischemic segments, rest/stress left ventricular ejection fraction (LVEF), and ST-segment depression. HRs and 95% CIs were calculated per millimeter, segment, or 5% of LVEF. We examined prognostic models for the following trial endpoints: 1) the trial's primary endpoint of cardiovascular (CV) death, myocardial infarction (MI), resuscitated cardiac arrest, or hospitalization for unstable angina or heart failure; 2) CV death; 3) spontaneous MI; 4) procedural MI; and 5) type 2 MI.</p><p><strong>Results: </strong>The number of scarred segments (HR: 1.07 [95% CI: 1.02-1.13]; P = 0.0209), rest LVEF (HR: 0.88 [95% CI: 0.83-0.93]; P < 0.001), and stress LVEF (HR: 0.87 [95% CI: 0.83-0.91]; P < 0.001) predicted the trial's primary endpoint of CV death, MI, resuscitated cardiac arrest, or hospitalization for unstable angina or heart failure. The extent of scar and rest/stress LVEF on echocardiography and nuclear imaging predicted several trial endpoints. The number of ischemic segments predicted spontaneous (HR: 1.08 [95% CI: 1.03-1.14]; P = 0.0104) and procedural MI (HR: 1.14 [95% CI: 1.03-1.25]; P = 0.0015) but was of borderline significance for the trial's primary endpoint (P = 0.0746). Ischemia extent by CMR predicted the trial's primary endpoint (P = 0.0068) and spontaneous MI (P = 0.0042).</p><p><strong>Conclusions: </strong>ISCHEMIA trial findings from 320 worldwide centers revealed that stress imaging and exercise ECG measures exhibited a variable association with key trial endpoints delineating risk patterns for ischemia and infarction. Stress CMR ischemia predicted several trial endpoints, supporting an expanded role in the evaluation of patients with CCS (ISCHEMIA [International Study of Comparative Health Effectiveness With Medical and Invasive Approaches]; NCT01471522).</p>","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":" ","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12252255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144600432","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":"Myocardial Scar and Arrhythmic Risk Stratification in Ischemic Left Ventricular Systolic Dysfunction.","authors":"Holly Morgan, Amedeo Chiribiri, Muhummad Sohaib Nazir, Hassan Zaidi, Jennifer Mancio, Ebraham Alskaf, Matthew Dodd, Martin Bishop, Christopher Aldo Rinaldi, Divaka Perera","doi":"10.1016/j.jcmg.2025.05.012","DOIUrl":"https://doi.org/10.1016/j.jcmg.2025.05.012","url":null,"abstract":"","PeriodicalId":14767,"journal":{"name":"JACC. Cardiovascular imaging","volume":" ","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144600455","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}