Current Medical Imaging Reviews最新文献

{"title":"Differentiation of Minute Pulmonary Meningothelial-Like Nodules and Adenocarcinoma In situ with CT Radiomics.","authors":"Yawen Zhang, Leilei Zhou, Jun Yao, Hai Xu, Yu-Chen Chen, Xiaomin Yong","doi":"10.2174/0115734056354822250217045544","DOIUrl":"https://doi.org/10.2174/0115734056354822250217045544","url":null,"abstract":"<p><strong>Background: </strong>An effective preoperative diagnosis between minute pulmonary meningothelial-like nodules (MPMNs) and adenocarcinoma in situ (AIS) can provide clinicians with appropriate treatment strategies.</p><p><strong>Objective: </strong>This study aimed to differentiate MPMNs from AIS via computed tomography (CT) radiomics approaches.</p><p><strong>Methods: </strong>Clinical and imaging data from fifty-one patients diagnosed with MPMNs and 55 patients diagnosed with AIS were collected from Jiangsu Province Hospital and Nanjing First Hospital from January 2016 to December 2022. All patients underwent chest CT scans before surgery. All CT images were segmented with ITK-SNAP software, and the radiomics features were further extracted with the Python PyRadiomics package. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select the optimal radiomics features for the construction of the model. The ROC curve was used to evaluate the diagnostic efficacy of the model.</p><p><strong>Results: </strong>After feature reduction and selection, 16 radiomics features were selected to construct the radiomics model. In the test set, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the k-nearest neighbor model were 87.5%, 88.9%, 96.9%, 77.8%, and 88.5%, respectively, and the AUC of the ROC curve was 0.969 (95% CI: 0.72-1.00).</p><p><strong>Conclusion: </strong>The CT radiomics model has exhibited high diagnostic value in the differential diagnosis between MPMNs and AIS.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665311","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}

{"title":"A Case of Bronchogenic Cyst Detected by Ultrasound.","authors":"Lei Zhang, Dong-Hui Ji, Kuo-Peng Liang","doi":"10.2174/0115734056347512250219063009","DOIUrl":"https://doi.org/10.2174/0115734056347512250219063009","url":null,"abstract":"<p><strong>Background: </strong>Bronchogenic cysts are congenital cystic anomalies of the bronchus that originate from abnormal development of the bronchial tree during the embryonic period. Their common manifestation is a space-occupying lesion in the lungs or mediastinum. Common imaging modalities for detecting bronchogenic cysts include chest X-ray and chest computed tomography (CT) scans.</p><p><strong>Case presentation: </strong>A 24-year-old female presented with an abnormal space-occupying lesion in the mediastinum detected through imaging examinations. Echocardiography revealed a cystic mass located between the descending aorta and the right pulmonary artery. A CT scan identified a low-density mass with a distinct density relative to adjacent tissues, situated near the left main bronchus. The final diagnosis of a bronchogenic cyst was established following surgical intervention and pathological examination.</p><p><strong>Conclusion: </strong>Bronchogenic cysts are rare congenital anomalies. Common clinical symptoms include chest pain, cough, and dyspnea. On standard chest radiographs and CT scans, most cysts present as homogenous water-density shadows, with the mediastinum being the most frequently affected location. The diagnosis is confirmed through pathological examination. Surgical intervention remains the most effective treatment method, typically resulting in a favorable prognosis.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665306","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}

{"title":"Clinical Evaluation of ODIS-1 Orthodontic Operation and Image Quality of Digital Imaging System.","authors":"Yuanli Zhang, Hong Huang, Chongzhi Yin, Guizhi Zhang, Yang Wang, Rui Gao, Jinlin Song","doi":"10.2174/0115734056345020250223150845","DOIUrl":"https://doi.org/10.2174/0115734056345020250223150845","url":null,"abstract":"<p><strong>Background: </strong>With the rapid development of computer technology, the application of digital technology to the display and processing of medical images has become a common concern. In recent years, oral digital imaging technology has received more and more attention.</p><p><strong>Objective: </strong>This paper mainly aims at the ODIS-1 oral digital imaging system to analyze and study the image quality and image aims at the ODIS-1 oral digital imaging system to analyze and study the image quality and processing technology, of which X-ray imaging is indispensable.</p><p><strong>Methods: </strong>In this paper, the ODIS-1 digital scanning technology is used to detect different types of dental tissues, and its application in diagnosing oral diseases is evaluated. This paper takes 320 inpatients as the research object and uses Kodak dental film to compare the image quality of different positions.</p><p><strong>Results: </strong>It is found that there is no significant difference in image quality between the maxillary anterior teeth and mandibular anterior teeth and the maxillary posterior teeth and mandibular posterior teeth (P>0.05); the image quality of maxillary anterior teeth, mandibular anterior teeth, and maxillary posterior teeth and mandibular teeth are significantly different (P<0.05); among the various positions of the ODIS-1 oral digital imaging system, the image quality of the anterior teeth area is the best, while the image quality of the maxillary posterior teeth area is the worst.</p><p><strong>Conclusion: </strong>However, the system has a variety of image post-processing functions, which can adjust the brightness and contrast of the image arbitrarily, select the area of interest in the image according to the detection requirements, and perform local amplification, edge enhancement, and other technologies to make the image achieve the best effect. In the case of poor image quality, the clarity of the image can be further improved through image post-processing and analysis.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606821","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}

{"title":"Left Basal Ganglia Stroke-induced more Alterations of Functional Connectivity: Evidence from an fMRI Study.","authors":"Qianqian Mao, Heng Wang, Jun Yao, Huiyou Chen, Yu-Chen Chen, Xindao Yin, Zhengqian Wang","doi":"10.2174/0115734056344477250222060225","DOIUrl":"https://doi.org/10.2174/0115734056344477250222060225","url":null,"abstract":"<p><strong>Background: </strong>The basal ganglia area is a frequent site of stroke, which commonly causes intricate functional impairments. This study aims to uncover disparities in static and dynamic functional connectivity (FC) of the brain in patients afflicted with left-sided basal ganglia stroke (L-BGS) and right-sided basal ganglia region stroke (R-BGS), furthermore scrutinising the mechanism behind the lateralisation of the stroke.</p><p><strong>Methods: </strong>A total of 23 patients with L-BGS and 20 patients with R-BGS were recruited, alongside 20 healthy control subjects. Resting-state functional magnetic resonance imaging and sliding window techniques were employed to conduct static and dynamic FC analyses on both patient groups and controls, which can enable a more refined evaluation of the variations in neural signals.</p><p><strong>Results: </strong>The inter-network connectivity analysis showed significant changes only in the L-BGS patient group (p < 0.05). The R-BGS group showed increased connectivity in the auditory and posterior visual networks, while the L-BGS group showed reduced connectivity. In dynamic connectivity analyses, the L-BGS group exhibited greater positive network connectivity reorganization.</p><p><strong>Conclusion: </strong>Within one month of stroke onset, the L-BGS group showed a more pronounced impairment of inter-network connectivity, alongside enhanced FC compensatory changes of a positive nature. Differential changes in the two patient groups may provide useful information for individualized rehabilitation strategies.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574675","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}

{"title":"Application Value of A Clinical Radiomic Nomogram for Identifying Diabetic Nephropathy and Nondiabetic Renal Disease.","authors":"Xiaoling Liu, Weihan Xiao, Jing Qiao, Xiachuan Qin","doi":"10.2174/0115734056332507250210105723","DOIUrl":"https://doi.org/10.2174/0115734056332507250210105723","url":null,"abstract":"<p><strong>Objective: </strong>An ultrasound-based radiomics Machine Learning Model (ML) was utilized to assess non-invasively the conditions of diabetic nephropathy and non-diabetic renal disease in diabetic patients.</p><p><strong>Methods: </strong>A retrospective examination was conducted on 166 diabetic patients who had undergone renal biopsies guided by ultrasound, with the group comprising 114 individuals diagnosed with diabetic nephropathy and 52 with non-diabetic renal disease. The participants were randomly divided into the training set and the testing set (7:3). Following the extraction of radiomics features from the renal ultrasound images, a univariate analysis was conducted, and the Least Absolute Shrinkage And Selection Operator (LASSO) algorithm was applied to select the most significant features. Three ML algorithms were applied to construct the prediction models. Subsequently, the patients' clinical characteristics were evaluated through both univariate and multivariate logistic regression analyses, which facilitated the development of a clinical model, following a clinical radiomics model was formulated, integrating the radiomics scores (Radscore), along with the independent clinical variables identified through the screening process. The diagnostic performance of the three models constructed was evaluated using the receiver operating characteristic (ROC) curve analysis.</p><p><strong>Results: </strong>Among the three radiomics ML models, the logistic regression (LR) model achieved the best performance, with the area under the curve (AUC) values of 0.872 (95%CI, 0.800-0.944) and 0.836 (95%CI, 0.716-0.957) for the training set and the testing set, respectively. The decision curve analysis (DCA) verified the clinical practicability of the ML model. Within the same testing set, the AUC of the clinical model was 0.761 (95%CI, 0.606-0.916). The nomogram model based on clinical features plus Radscore showed the best discrimination, with an AUC value of 0.881 (95%CI, 0.779-0.982), which was better than that of the single clinical model and the radiomics model.</p><p><strong>Conclusion: </strong>The ML model of radiomics based on ultrasound images has potential value in the non-invasive differential diagnosis of patients with diabetic nephropathy. The nomogram constructed based on rad score and clinical features could effectively distinguish DN from NDRD.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494328","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}

{"title":"Intestinal Lipoma Acting as a Lead Point of Intussusception: A Case Series.","authors":"Mei-Ying Jian, Xiao-Yan Luo, Xiu-Qin Luo, Ai-Fang Jin, Zhe-Huang Luo","doi":"10.2174/0115734056337435250206100026","DOIUrl":"https://doi.org/10.2174/0115734056337435250206100026","url":null,"abstract":"<p><strong>Background: </strong>Lipomas represent a rare benign etiology of intussusception in adults, affecting both the small intestine and the colon. Diagnosing intussusception in adults can be challenging, and there are no reports on the use of positron emission tomography/CT (PET/CT) in the diagnosis of lipoma-induced intussusception. This study aimed to preliminarily explore the potential diagnostic utility of 18F-FDG PET/CT in the diagnosis of intussusception caused by lipomas.</p><p><strong>Methods: </strong>We conducted a retrospective review of the clinical characteristics and imaging findings of three patients diagnosed with lipoma-induced intussusception using 18F-FDG PET/CT from 2019 to 2023 at our hospital.</p><p><strong>Results: </strong>The three cases presented with diverse clinical presentations and were diagnosed based on PET/CT imaging. Surgical confirmation was obtained in two cases. Lipomas were identified in both the small intestine and the colon, with one case displaying increased metabolic activity on FDG uptake, suggesting a possible link between FDG uptake and clinical severity.</p><p><strong>Conclusion: </strong>Lipoma is a benign cause of intussusception that can occur in both the small intestine and the colon. The symptoms of adult intussusception are often atypical and variable. Imaging modalities, particularly PET/CT, are instrumental in diagnosing intussusception due to lipomas, differentiating between benign and malignant causes, and assessing the severity to inform treatment strategies.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460679","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}

{"title":"Impact of CT-Relevant Skeletal Muscle Parameters on Post-Chemotherapy Survival in Patients with Unresectable Pancreatic Ductal Adenocarcinoma.","authors":"Siying Zhang, Zhenping Wu, Guo Sa, Zhan Feng, Feng Chen","doi":"10.2174/0115734056356822250205174104","DOIUrl":"https://doi.org/10.2174/0115734056356822250205174104","url":null,"abstract":"<p><strong>Purpose: </strong>The study aimed to investigate the association of CT-relevant skeletal muscle parameters, such as sarcopenia and myosteatosis, with survival outcomes in patients receiving chemotherapy for unresectable pancreatic ductal adenocarcinoma (PDAC).</p><p><strong>Methods: </strong>In this retrospective analysis, patients who began chemotherapy for unresectable PDAC were included. Sarcopenia and myosteatosis were assessed on pretreatment CT at the L3 level by skeletal muscle index and mean muscle attenuation with predefined cutoff values. The Cox proportional hazards model was used to analyze the factors associated with progression-free survival (PFS) and overall survival (OS).</p><p><strong>Results: </strong>A total of 150 patients were enrolled. Compared to patients without sarcopenia, patients with sarcopenia had significantly worse PFS (p=0.003) and OS (p<0.001). Patients with myosteatosis had significantly worse PFS (p=0.01) and OS (p=0.002) compared to those without myosteatosis. In multivariate analysis, after adjusting for age, sex, tumor size, location, treatment modality, smoking, drinking, underlying diseases, and partial laboratory tests, sarcopenia remained an independent predictor of PFS (p=0.006) and OS (p<0.001). Myosteatosis remained an independent predictor of OS (p=0.008), but not of PFS.</p><p><strong>Conclusion: </strong>Sarcopenia and myosteatosis are independent prognostic factors for patients with unresectable pancreatic ductal adenocarcinoma after chemotherapy.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451024","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}

{"title":"I-Brainer: Artificial intelligence/Internet of Things (AI/IoT)-Powered Detection of Brain Cancer.","authors":"Abdullahi Umar Ibrahim, Ikedichukwu Onyemaucheya Nwaneri, Mercel Vubangsi, Fadi Al-Turjman","doi":"10.2174/0115734056333393250117164020","DOIUrl":"https://doi.org/10.2174/0115734056333393250117164020","url":null,"abstract":"<p><strong>Background/objective: </strong>Brain tumour is characterized by its aggressive nature and low survival rate and thus regarded as one of the deadliest diseases. Thus, miss-diagnosis or miss-classification of brain tumour can lead to miss treatment or incorrect treatment and reduce survival chances. Therefore, there is need to develop a technique that can identify and detect brain tumour at early stages.</p><p><strong>Methods: </strong>Here, we proposed a framework titled I-Brainer which is an Artificial Intelligence/Internet of Things (AI/IoT)-powered classification of MRI. We employed a Br35H+SARTAJ brain MRI dataset which contain 7023 total images which include No tumour, pituitary, meningioma and glioma. In order to accurately classified MRI into 4-class, we developed LeNet model from scratch, implemented 2 pretrained models which include EfficientNet and ResNet-50 as well feature extraction of these models coupled with 2 Machine Learning classifiers k-Nearest Neighbours (KNN) and Support Vector Machines (SVM).</p><p><strong>Result: </strong>Evaluation and comparison of the performance of 3 models has shown that EfficientNet+SVM achieved the best result in terms of AUC (99%) and ResNet-50-KNN ranked higher in terms of accuracy (94%) on testing dataset.</p><p><strong>Conclusion: </strong>This framework can be harness by patients residing in remote areas and as confirmatory approach for medical experts.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143366807","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}

{"title":"Withdrawal to: Assessing Pulmonary Embolisms on Unenhanced CT Images Using Electron Density Images Derived from Dual-Layer Spectral Detector CT: A Single-centre Prospective Study Conducted at the Emergency Department","authors":"Huayang Du, Xin Sui, Ruijie Zhao, Jiaru Wang, Ying Ming, Sirong Piao, Jinhua Wang, Xiaomei Lu, Lan Song, Wei Song","doi":"10.2174/0115734056316803241021102932","DOIUrl":"10.2174/0115734056316803241021102932","url":null,"abstract":"<p><p>Since the authors are not responding to the editor’s requests to fulfill the editorial requirement, the article has been withdrawn.</p><p><p>Bentham Science apologizes to the readers of the journal for any inconvenience this may have caused. The Bentham Editorial Policy on Article Withdrawal can be found at https://benthamscience.com/editorial-policies-main.php</p><p><strong>Bentham science disclaimer: </strong>It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure, or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication, the authors agree that the publishers have the legal right to take appropriate action against the authors if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016024","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}

{"title":"Study Hotspot and Trend in the Field of Shear Wave Elastography: A Bibliometric Analysis from 2004 to 2024.","authors":"Jingjing Zhao, Linping Pian, Jie Chen, Quanjiang Wang, Feiyan Han, Yameng Liu","doi":"10.2174/0115734056353590250109081225","DOIUrl":"https://doi.org/10.2174/0115734056353590250109081225","url":null,"abstract":"<p><strong>Background: </strong>The objective of this study was to comprehensively review the literature on Shear Wave Elastography (SWE), a non-invasive imaging technique prevalent in medical ultrasound. SWE is instrumental in assessing superficial glandular tissues, abdominal organs, tendons, joints, carotid vessels, and peripheral nerve tissues, among others. By employing bibliometric analysis, we aimed to encapsulate the scholarly contributions over the past two decades, identifying key research areas and tracing the evolutionary trajectory of SWE.</p><p><strong>Methods: </strong>For this study, we selected research articles related to SWE published between 2004 and March 2024 from the Web of Science Core Collection (WOSCC). We utilized sophisticated bibliometric tools, such as CiteSpace, VOSviewer, and SCImago Graphica, to analyze the trends in annual publications, contributing countries and institutions, journals, authors, co-cited authors, co-cited references, and keywords.</p><p><strong>Results: </strong>Our analysis yielded a total of 3606 papers. China emerged as the leading country in terms of publication output, with a strong collaborative relationship with the United States. Sun Yat-Sen University was identified as the institution with the highest number of publications. The keyword \"transient elastography\" was the most prevalent, with \"acoustic radiation force\" being a focal point in the initial stages of SWE research. Recently, Contrast-enhanced Ultrasound (CEUS) has emerged as a new research focus, signaling a potential direction for future research and development.</p><p><strong>Conclusion: </strong>The global research landscape for SWE is projected to expand continuously. Future research is likely to concentrate on the integrated application of SWE and CEUS for diagnostic purposes, along with exploring the clinical utility of multimodal ultrasound that synergistically combines SWE with other ultrasound technologies. This bibliometric research offers a comprehensive overview of the SWE literature, guiding researchers in their pursuit of further exploration and discovery.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015950","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}