Tomography最新文献

{"title":"Radiation Overuse in Intensive Care Units.","authors":"Chiara Zanon, Costanza Bini, Alessandro Toniolo, Tommaso Benetti, Emilio Quaia","doi":"10.3390/tomography10020015","DOIUrl":"10.3390/tomography10020015","url":null,"abstract":"<p><p>Radiological imaging is essential for acute patient management in Intensive Care Units (ICUs); however, it introduces the risk of exposure to ionizing radiation. This review synthesizes research on radiation exposure in ICU settings, highlighting its rise during the COVID-19 pandemic and the rise in repetitive imaging. Our analysis extends to radiation safety thresholds, revealing that some ICU patients exceed the diagnostic reference level, emphasizing the need to balance diagnostic utility against potential long-term risks, such as cancer. Prospective studies have demonstrated an increase in the median cumulative effective dose in patients with trauma over time, prompting calls for improved awareness and monitoring. Moreover, innovative dose-reduction strategies and optimized protocols, especially in neuro-ICUs, promise to mitigate these risks. This review highlights the essential but risky role of radiological imaging in critical care. It advocates for rigorous radiation management protocols to safeguard patient health while ensuring the continuity of high-quality medical care.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 2","pages":"193-202"},"PeriodicalIF":1.9,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10892508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139934078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cerebral Microvascular Perfusion Assessed in Elderly Adults by Spin-Echo Dynamic Susceptibility Contrast MRI at 7 Tesla.","authors":"Elles P Elschot, Walter H Backes, Marieke van den Kerkhof, Alida A Postma, Abraham A Kroon, Jacobus F A Jansen","doi":"10.3390/tomography10010014","DOIUrl":"10.3390/tomography10010014","url":null,"abstract":"<p><p>Perfusion measures of the total vasculature are commonly derived with gradient-echo (GE) dynamic susceptibility contrast (DSC) MR images, which are acquired during the early passes of a contrast agent. Alternatively, spin-echo (SE) DSC can be used to achieve specific sensitivity to the capillary signal. For an improved contrast-to-noise ratio, ultra-high-field MRI makes this technique more appealing to study cerebral microvascular physiology. Therefore, this study assessed the applicability of SE-DSC MRI at 7 T. Forty-one elderly adults underwent 7 T MRI using a multi-slice SE-EPI DSC sequence. The cerebral blood volume (CBV) and cerebral blood flow (CBF) were determined in the cortical grey matter (CGM) and white matter (WM) and compared to values from the literature. The relation of CBV and CBF with age and sex was investigated. Higher CBV and CBF values were found in CGM compared to WM, whereby the CGM-to-WM ratios depended on the amount of largest vessels excluded from the analysis. CBF was negatively associated with age in the CGM, while no significant association was found with CBV. Both CBV and CBF were higher in women compared to men in both CGM and WM. The current study verifies the possibility of quantifying cerebral microvascular perfusion with SE-DSC MRI at 7 T.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 1","pages":"181-192"},"PeriodicalIF":2.2,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10819808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139514205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accelerated Hypofractionated Magnetic Resonance Guided Adaptive Radiation Therapy for Ultracentral Lung Tumors.","authors":"Alonso La Rosa, Kathryn E Mittauer, Nema Bassiri, Amy E Rzepczynski, Michael D Chuong, Sreenija Yarlagadda, Tugce Kutuk, Nicole C McAllister, Matthew D Hall, Alonso N Gutierrez, Ranjini Tolakanahalli, Minesh P Mehta, Rupesh Kotecha","doi":"10.3390/tomography10010013","DOIUrl":"10.3390/tomography10010013","url":null,"abstract":"<p><p>Radiotherapy for ultracentral lung tumors represents a treatment challenge, considering the high rates of high-grade treatment-related toxicities with stereotactic body radiation therapy (SBRT) or hypofractionated schedules. Accelerated hypofractionated magnetic resonance-guided adaptive radiation therapy (MRgART) emerged as a potential game-changer for tumors in these challenging locations, in close proximity to central organs at risk, such as the trachea, proximal bronchial tree, and esophagus. In this series, 13 consecutive patients, predominantly male (<i>n</i> = 9), with a median age of 71 (range (R): 46-85), underwent 195 MRgART fractions (all 60 Gy in 15 fractions) to metastatic (<i>n</i> = 12) or primary ultra-central lung tumors (<i>n</i> = 1). The median gross tumor volumes (GTVs) and planning target volumes (PTVs) were 20.72 cc (R: 0.54-121.65 cc) and 61.53 cc (R: 3.87-211.81 cc), respectively. The median beam-on time per fraction was 14 min. Adapted treatment plans were generated for all fractions, and indications included GTV/PTV undercoverage, OARs exceeding tolerance doses, or both indications in 46%, 18%, and 36% of fractions, respectively. Eight patients received concurrent systemic therapies, including immunotherapy (four), chemotherapy (two), and targeted therapy (two). The crude in-field loco-regional control rate was 92.3%. No CTCAE grade 3+ toxicities were observed. Our results offer promising insights, suggesting that MRgART has the potential to mitigate toxicities, enhance treatment precision, and improve overall patient care in the context of ultracentral lung tumors.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 1","pages":"169-180"},"PeriodicalIF":2.2,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10820032/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139514201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lumbar Disc Degeneration Is Linked to Dorsal Subcutaneous Fat Thickness at the L1-L2 Intervertebral Disc Level Measured by MRI.","authors":"Ibrahem Hussain Kanbayti, Abdulrahman S Al-Buqami, Mohammad H Alsheikh, Saad M Al-Malki, Ibrahim Hadadi, Adnan Alahmadi, Bander S Almutairi, Hamzah H Ahmed","doi":"10.3390/tomography10010012","DOIUrl":"10.3390/tomography10010012","url":null,"abstract":"<p><strong>Background: </strong>Obese individuals have a higher risk of degenerative disc disease (DDD). Currently, body mass index is not sensitive enough to differentiate between muscle and fat distribution, and obesity-related health issues are linked to the way body fat is distributed. Therefore, this study aims to investigate the association between the dorsal subcutaneous fat thickness (DSFT) of the lumbar spine, an alternative measurement tool of body fat distribution, and DDD.</p><p><strong>Methods: </strong>A total of 301 patients with DDD and 123 participants without the disease were recruited. Using length functions of magnetic resonance imaging (MRI) console, the DSFT of L1 to S1 intervertebral disc levels was measured in mid-sagittal spin-echo T2 weighted image. The Mann-Whitney U test and Chi-squared test (X2) were utilized to examine any variations between the case and control groups. Logistic regression models were built to explore the association of the DSFT with DDD.</p><p><strong>Results: </strong>The logistical regression model showed a positive association between DDD and DSFT [OR: 1.30, 95% CI: 1.02-1.64, <i>p =</i> 0.03]. In the stratified logistic regression analysis, a positive association was found between DDD and DSFT among younger participants and females [OR _young: 1.48; 95% CI (1.02-2.20); <i>p =</i> 0.04-OR _female: 1.37; 95% CI (1-1.88); <i>p =</i> 0.05].</p><p><strong>Conclusions: </strong>Younger females with thicker DSFT at the L1-L2 level are more likely to develop DDD. This suggests that increased DSFT may be a contributing factor to DDD.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 1","pages":"159-168"},"PeriodicalIF":2.2,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10820047/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139514210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-Domain Reconstruction Network Incorporating Multi-Level Wavelet Transform and Recurrent Convolution for Sparse View Computed Tomography Imaging.","authors":"Juncheng Lin, Jialin Li, Jiazhen Dou, Liyun Zhong, Jianglei Di, Yuwen Qin","doi":"10.3390/tomography10010011","DOIUrl":"10.3390/tomography10010011","url":null,"abstract":"<p><p>Sparse view computed tomography (SVCT) aims to reduce the number of X-ray projection views required for reconstructing the cross-sectional image of an object. While SVCT significantly reduces X-ray radiation dose and speeds up scanning, insufficient projection data give rise to issues such as severe streak artifacts and blurring in reconstructed images, thereby impacting the diagnostic accuracy of CT detection. To address this challenge, a dual-domain reconstruction network incorporating multi-level wavelet transform and recurrent convolution is proposed in this paper. The dual-domain network is composed of a sinogram domain network (SDN) and an image domain network (IDN). Multi-level wavelet transform is employed in both IDN and SDN to decompose sinograms and CT images into distinct frequency components, which are then processed through separate network branches to recover detailed information within their respective frequency bands. To capture global textures, artifacts, and shallow features in sinograms and CT images, a recurrent convolution unit (RCU) based on convolutional long and short-term memory (Conv-LSTM) is designed, which can model their long-range dependencies through recurrent calculation. Additionally, a self-attention-based multi-level frequency feature normalization fusion (MFNF) block is proposed to assist in recovering high-frequency components by aggregating low-frequency components. Finally, an edge loss function based on the Laplacian of Gaussian (LoG) is designed as the regularization term for enhancing the recovery of high-frequency edge structures. The experimental results demonstrate the effectiveness of our approach in reducing artifacts and enhancing the reconstruction of intricate structural details across various sparse views and noise levels. Our method excels in both performance and robustness, as evidenced by its superior outcomes in numerous qualitative and quantitative assessments, surpassing contemporary state-of-the-art CNNs or Transformer-based reconstruction methods.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 1","pages":"133-158"},"PeriodicalIF":1.9,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11154272/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139514206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introduction to Special Issue Imaging in Cancer Diagnosis.","authors":"Chiara Zanon, Emilio Quaia, Filippo Crimì","doi":"10.3390/tomography10010009","DOIUrl":"10.3390/tomography10010009","url":null,"abstract":"<p><p>In the field of oncology, the precision of cancer imaging is the cornerstone of oncological patient care [...].</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 1","pages":"101-104"},"PeriodicalIF":2.2,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10820471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139514208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modern Subtype Classification and Outlier Detection Using the Attention Embedder to Transform Ovarian Cancer Diagnosis.","authors":"S M Nuruzzaman Nobel, S M Masfequier Rahman Swapno, Md Ashraful Hossain, Mejdl Safran, Sultan Alfarhood, Md Mohsin Kabir, M F Mridha","doi":"10.3390/tomography10010010","DOIUrl":"10.3390/tomography10010010","url":null,"abstract":"<p><p>Ovarian cancer, a deadly female reproductive system disease, is a significant challenge in medical research due to its notorious lethality. Addressing ovarian cancer in the current medical landscape has become more complex than ever. This research explores the complex field of Ovarian Cancer Subtype Classification and the crucial task of Outlier Detection, driven by a progressive automated system, as the need to fight this unforgiving illness becomes critical. This study primarily uses a unique dataset painstakingly selected from 20 esteemed medical institutes. The dataset includes a wide range of images, such as tissue microarray (TMA) images at 40× magnification and whole-slide images (WSI) at 20× magnification. The research is fully committed to identifying abnormalities within this complex environment, going beyond the classification of subtypes of ovarian cancer. We proposed a new Attention Embedder, a state-of-the-art model with effective results in ovarian cancer subtype classification and outlier detection. Using images magnified WSI, the model demonstrated an astonishing 96.42% training accuracy and 95.10% validation accuracy. Similarly, with images magnified via a TMA, the model performed well, obtaining a validation accuracy of 94.90% and a training accuracy of 93.45%. Our fine-tuned hyperparameter testing resulted in exceptional performance on independent images. At 20× magnification, we achieved an accuracy of 93.56%. Even at 40× magnification, our testing accuracy remained high, at 91.37%. This study highlights how machine learning can revolutionize the medical field's ability to classify ovarian cancer subtypes and identify outliers, giving doctors a valuable tool to lessen the severe effects of the disease. Adopting this novel method is likely to improve the practice of medicine and give people living with ovarian cancer worldwide hope.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 1","pages":"105-132"},"PeriodicalIF":1.9,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11154515/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139514212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Hounsfield Units and Factors Associated with Fragmentation of Renal Stones by Extracorporeal Shock Wave Lithotripsy: A Computerized Tomography Study.","authors":"Abdallah Saud Alharbi, Moawia Gameraddin, Awadia Gareeballah, Zahra Jibril Shrwani, Moa'ath Abdullah Sindi, Hassan Ibrahim Alsaedi, Abdulaziz A Qurashi, Khalid M Aloufi, Abdullah Fahad A Alshamrani, Amel F Alzain","doi":"10.3390/tomography10010008","DOIUrl":"10.3390/tomography10010008","url":null,"abstract":"<p><p>The success rate of extracorporeal shock wave lithotripsy (ESWL) is influenced by various factors, including stone density, and is determined through computed tomography scans in terms of Hounsfield units (HU).</p><p><strong>Materials and methods: </strong>This retrospective single-center study was conducted in the King Fahad Hospital. Sixty-seven adult patients with renal and ureteric stones were selected randomly and enrolled in the study. Their ages ranged from 20 to 69 years. The patients were examined with non-contrast enhancement (NCCT) to assess the HU of their stones and were consequently treated with ESWL.</p><p><strong>Results: </strong>Of the 67 patients, 37.3% had stones that were completely fragmented, while 62.7% had stones that were partially fragmented. The HU, location of the stone, multiplicity of the stone, and patient age were found to be significant factors contributing to stone fragility (<i>p</i>-values < 0.05). The HU data were found to have a positive significant linear correlation with serum calcium (r = 0.28, <i>p</i>-value = 0.036), while serum acid had a negative correlation (r = -0.55, <i>p</i>-value < 0.001). Thus, the probability of calcium-containing stone formation increases with increased HU. In contrast, uric acid stone formation likely develops with decreasing HU with serum uric acid. Renal stones in patients with diabetes mellitus and hypertension were not completely fragmented compared to those without clinical history.</p><p><strong>Conclusions: </strong>Mean HU, location of the stone, laterality, stone status, and the number of ESWL sessions are the most significant factors affecting stone fragility. CT attenuation values can predict the composition of stones from serum calcium and uric acid examinations. Hypertension and diabetes mellitus are risk factors for renal stone fragmentation.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 1","pages":"90-100"},"PeriodicalIF":2.2,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10821390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139514203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Use of Pre-Chemoradiotherapy Total Masseter Muscle Volume as a Novel Predictor of Radiation-Induced Trismus in Locally Advanced Nasopharyngeal Carcinoma Patients","authors":"E. Somay, E. Topkan, U. Pehlivan, B. Yilmaz, Ali Ayberk Besen, Huseyin Mertsoylu, B. Pehlivan, U. Selek","doi":"10.3390/tomography10010007","DOIUrl":"https://doi.org/10.3390/tomography10010007","url":null,"abstract":"Background: We sought to determine whether pretreatment total masseter muscle volume (TMMV) measures can predict radiation-induced trismus (RIT) in patients with locally advanced nasopharyngeal carcinoma (LA-NPC) receiving concurrent chemoradiotherapy (C-CRT). Methods: We retrospectively reviewed the medical records of LA-NPC patients who received C-CRT and had pretreatment maximum mouth openings (MMO) greater than 35 mm. MMO of 35 mm or less after C-CRT were considered RIT. We employed receiver operating characteristic (ROC) curve analysis to explore the correlation between pre-treatment TMMV readings and RIT status. Results: Out of the 112 eligible patients, 22.0% of them received a diagnosis of RIT after C-CRT. The optimal TMMV cutoff that was significantly linked to post-C-CRT RIT rates was determined to be 35.0 cc [area under the curve: 79.5%; sensitivity: 75.0%; and specificity: 78.6%; Youden index: 0.536] in the ROC curve analysis. The incidence of RIT was significantly higher in patients with TMMV ≤ 5.0 cc than in those with TMMV > 35.0 cc [51.2% vs. 8.7%; Odds ratio: 6.79; p < 0.001]. A multivariate logistic regression analysis revealed that pre-C-CRT MMO ≤ 41.6 mm (p = 0.001), mean masticatory apparatus dose V56.5 ≥ 34% group (p = 0.002), and TMMV ≤ 35 cc were the independent predictors of significantly elevated rates of RIT. Conclusion: The presence of a smaller pretreatment TMMV is a reliable and independent novel biological marker that can confidently predict higher RIT rates in LA-NPC patients who receive C-CRT.","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"75 14","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139440408","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":"The Role of Major Salivary Gland Ultrasound in the Diagnostic Workup of Sicca Syndrome: A Large Single-Centre Study","authors":"Giulia Vallifuoco, P. Falsetti, Marco Bardelli, E. Conticini, Stefano Gentileschi, C. Baldi, S. G. Al Khayyat, L. Cantarini, B. Frediani","doi":"10.3390/tomography10010006","DOIUrl":"https://doi.org/10.3390/tomography10010006","url":null,"abstract":"(1) Objective: To determine the diagnostic accuracy of major salivary gland ultrasonography (SGUS) in primary Sjogren’s syndrome (SS), we used the Outcome Measures in Rheumatology Clinical Trials (OMERACT) scoring system on a large single-centre cohort of patients with sicca syndrome. (2) Method: We retrospectively collected the clinical, imaging and serological data of all the patients referred with a suspicion of SS who underwent SGUS and minor salivary glands biopsy. (3) Results: A total of 132 patients were included. The SGUS scores were correlated between the two sides (p < 0.001). The diagnostic cut-off for SS (AUROC: 0.7408) was 6 for the SGUS-global sum (sensitivity: 32.43%; specificity: 96.84%). The cut-off with the highest specificity for SS diagnosis was 7. In the patients with a final diagnosis of SS, the mean SGUS score was significantly higher (p < 0.001) than that of the non-SS patients (3.73 vs. 1.32 for the SGUS-global sum). A significant correlation was demonstrated between the SGUS scores and final SS diagnosis (p < 0.001), biopsy positivity (p < 0.001), ANA positivity (p = 0.016), Ro-SSA positivity (p = 0.01), and gland fibrosis (p = 0.02). (4) Conclusions: SGUS, using the OMERACT scoring system, has moderate sensitivity and high specificity for the diagnosis of SS. The scoring showed a strong and direct correlation with all the clinical hallmarks of SS diagnosis, such as the positivity of a labial salivary gland biopsy, ANA and Ro-SSA statuses, and salivary gland fibrosis. Because of its high specificity, a SGUS-global score > 6 could be therefore employed for the diagnosis of SS in the case of ANA negativity or the unavailability of a biopsy.","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"15 4","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139445735","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}