Tomography最新文献

{"title":"Ultra-High Contrast MRI: The Whiteout Sign Shown with Divided Subtracted Inversion Recovery (dSIR) Sequences in Post-Insult Leukoencephalopathy Syndromes (PILS).","authors":"Paul Condron, Daniel M Cornfeld, Miriam Scadeng, Tracy R Melzer, Gil Newburn, Mark Bydder, Eryn E Kwon, Joshua P McGeown, Geoffrey G Handsfield, Taylor Emsden, Maryam Tayebi, Samantha J Holdsworth, Graeme M Bydder","doi":"10.3390/tomography10070074","DOIUrl":"10.3390/tomography10070074","url":null,"abstract":"<p><p>Ultra-high contrast (UHC) MRI describes forms of MRI in which little or no contrast is seen on conventional MRI images but very high contrast is seen with UHC techniques. One of these techniques uses the divided subtracted inversion recovery (dSIR) sequence, which, in modelling studies, can produce ten times the contrast of conventional inversion recovery (IR) sequences. When used in cases of mild traumatic brain injury (mTBI), the dSIR sequence frequently shows extensive abnormalities in white matter that appears normal when imaged with conventional T₂-fluid-attenuated IR (T₂-FLAIR) sequences. The changes are bilateral and symmetrical in white matter of the cerebral and cerebellar hemispheres. They partially spare the anterior and posterior central corpus callosum and peripheral white matter of the cerebral hemispheres and are described as the whiteout sign. In addition to mTBI, the whiteout sign has also been seen in methamphetamine use disorder and Grinker's myelinopathy (delayed post-hypoxic leukoencephalopathy) in the absence of abnormalities on T₂-FLAIR images, and is a central component of post-insult leukoencephalopathy syndromes. This paper describes the concept of ultra-high contrast MRI, the whiteout sign, the theory underlying the use of dSIR sequences and post-insult leukoencephalopathy syndromes.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 7","pages":"983-1013"},"PeriodicalIF":2.2,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11280826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141762516","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":"Application of Diffusion Kurtosis Imaging and Blood Oxygen Level-Dependent Magnetic Resonance Imaging in Kidney Injury Associated with ANCA-Associated Vasculitis.","authors":"Wenhui Yu, Weijie Yan, Jing Yi, Lu Cheng, Peiyi Luo, Jiayu Sun, Shenju Gou, Ping Fu","doi":"10.3390/tomography10070073","DOIUrl":"10.3390/tomography10070073","url":null,"abstract":"<p><strong>Objective: </strong>Functional magnetic resonance imaging (fMRI) has been applied to assess the microstructure of the kidney. However, it is not clear whether fMRI could be used in the field of kidney injury in patients with Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV).</p><p><strong>Methods: </strong>This study included 20 patients with AAV. Diffusion kurtosis imaging (DKI) and blood oxygen level-dependent (BOLD) scanning of the kidneys were performed in AAV patients and healthy controls. The mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) parameters of DKI, the R2* parameter of BOLD, and clinical data were further analyzed.</p><p><strong>Results: </strong>In AAV patients, the cortex exhibited lower MD but higher R2* values compared to the healthy controls. Medullary MK values were elevated in AAV patients. Renal medullary MK values showed a positive correlation with serum creatinine levels and negative correlations with hemoglobin levels and estimated glomerular filtration rate. To assess renal injury in AAV patients, AUC values for MK, MD, FA, and R2* in the cortex were 0.66, 0.67, 0.57, and 0.55, respectively, and those in the medulla were 0.81, 0.77, 0.61, and 0.53, respectively.</p><p><strong>Conclusions: </strong>Significant differences in DKI and BOLD MRI parameters were observed between AAV patients with kidney injuries and the healthy controls. The medullary MK value in DKI may be a noninvasive marker for assessing the severity of kidney injury in AAV patients.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 7","pages":"970-982"},"PeriodicalIF":2.2,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11280752/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141762511","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":"Quantitative and Compositional MRI of the Articular Cartilage: A Narrative Review.","authors":"Domenico Albano, Umberto Viglino, Francesco Esposito, Aldo Rizzo, Carmelo Messina, Salvatore Gitto, Stefano Fusco, Francesca Serpi, Benedikt Kamp, Anja Müller-Lutz, Riccardo D'Ambrosi, Luca Maria Sconfienza, Philipp Sewerin","doi":"10.3390/tomography10070072","DOIUrl":"10.3390/tomography10070072","url":null,"abstract":"<p><p>This review examines the latest advancements in compositional and quantitative cartilage MRI techniques, addressing both their potential and challenges. The integration of these advancements promises to improve disease detection, treatment monitoring, and overall patient care. We want to highlight the pivotal task of translating these techniques into widespread clinical use, the transition of cartilage MRI from technical validation to clinical application, emphasizing its critical role in identifying early signs of degenerative and inflammatory joint diseases. Recognizing these changes early may enable informed treatment decisions, thereby facilitating personalized medicine approaches. The evolving landscape of cartilage MRI underscores its increasing importance in clinical practice, offering valuable insights for patient management and therapeutic interventions. This review aims to discuss the old evidence and new insights about the evaluation of articular cartilage through MRI, with an update on the most recent literature published on novel quantitative sequences.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 7","pages":"949-969"},"PeriodicalIF":2.2,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11280587/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141762514","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":"A Literature Review on the Relative Diagnostic Accuracy of Chest CT Scans versus RT-PCR Testing for COVID-19 Diagnosis.","authors":"Hafez Al-Momani","doi":"10.3390/tomography10060071","DOIUrl":"10.3390/tomography10060071","url":null,"abstract":"<p><strong>Background: </strong>Reverse transcription polymerase chain reaction (RT-PCR) is the main technique used to identify COVID-19 from respiratory samples. It has been suggested in several articles that chest CTs could offer a possible alternate diagnostic tool for COVID-19; however, no professional medical body recommends using chest CTs as an early COVID-19 detection modality. This literature review examines the use of CT scans as a diagnostic tool for COVID-19.</p><p><strong>Method: </strong>A comprehensive search of research works published in peer-reviewed journals was carried out utilizing precisely stated criteria. The search was limited to English-language publications, and studies of COVID-19-positive patients diagnosed using both chest CT scans and RT-PCR tests were sought. For this review, four databases were consulted: these were the Cochrane and ScienceDirect catalogs, and the CINAHL and Medline databases made available by EBSCOhost.</p><p><strong>Findings: </strong>In total, 285 possibly pertinent studies were found during an initial search. After applying inclusion and exclusion criteria, six studies remained for analysis. According to the included studies, chest CT scans were shown to have a 44 to 98% sensitivity and 25 to 96% specificity in terms of COVID-19 diagnosis. However, methodological limitations were identified in all studies included in this review.</p><p><strong>Conclusion: </strong>RT-PCR is still the suggested first-line diagnostic technique for COVID-19; while chest CT is adequate for use in symptomatic patients, it is not a sufficiently robust diagnostic tool for the primary screening of COVID-19.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 6","pages":"935-948"},"PeriodicalIF":2.2,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11209112/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141452075","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":"Digital Breast Tomosynthesis for Upgraded BIRADS Scoring towards the True Pathology of Lesions Detected by Contrast-Enhanced Mammography.","authors":"Ahuva Grubstein, Tal Friehmann, Marva Dahan, Chen Abitbol, Ithai Gadiel, Dario M Schejtman, Tzippy Shochat, Eli Atar, Shlomit Tamir","doi":"10.3390/tomography10050061","DOIUrl":"10.3390/tomography10050061","url":null,"abstract":"<p><strong>Objective: </strong>To determine the added value of digital breast tomosynthesis (DBT) in the assessment of lesions detected by contrast-enhanced mammography (CEM).</p><p><strong>Material and methods: </strong>A retrospective study was conducted in a tertiary university medical center. All CEM studies including DBT performed between January 2016 and December 2020 were included. Lesions were categorized and scored by four dedicated breast radiologists according to the recent CEM and DBT supplements to the Breast Imaging Reporting and Data System (BIRADS) lexicon. Changes in the BIRADS score of CEM-detected lesions with the addition of DBT were evaluated according to the pathology results and 1-year follow-up imaging study.</p><p><strong>Results: </strong>BIRADS scores of CEM-detected lesions were upgraded toward the lesion's pathology with the addition of DBT (<i>p</i> > 0.0001), overall and for each reader. The difference in BIRADS scores before and after the addition of DBT was more significant for readers who were less experienced. The reason for changes in the BIRADS score was better lesion margin visibility. The main BIRADS descriptors applied in the malignant lesions were spiculations, calcifications, architectural distortion, and sharp or obscured margins.</p><p><strong>Conclusions: </strong>The addition of DBT to CEM provides valuable information on the enhancing lesion, leading to a more accurate BIRADS score.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 5","pages":"806-815"},"PeriodicalIF":1.9,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11125662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141088215","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":"Relationship between Femoral Proximal Bone Quality Assessment by MRI IDEAL-IQ Sequence and Body Mass Index in Elderly Men.","authors":"Kashia Goto, Daisuke Watanabe, Norikazu Kawae, Takahiro Nakamura, Kazuki Yanagida, Takahiro Yoshida, Hajime Kajihara, Akio Mizushima","doi":"10.3390/tomography10050062","DOIUrl":"10.3390/tomography10050062","url":null,"abstract":"<p><strong>Background: </strong>Bone assessment using the MRI DEAL-IQ sequence may have the potential to serve as a substitute for evaluating bone strength by quantifying the bone marrow hematopoietic region (R2*) and marrow adiposity (proton density fat fraction: PDFF). Higher body mass index (BMI) is associated with increased bone mineral density (BMD) in the proximal femur; however, the relationship between BMI and R2* or PDFF remains unclear. Herein, we investigated the correlation between BMI and MRI IDEAL-IQ based R2* or PDFF of the proximal femur.</p><p><strong>Methods: </strong>A retrospective single-cohort study was conducted on 217 patients diagnosed with non-metastatic prostate cancer between September 2019 and December 2022 who underwent MRI. The correlation between BMI and R2* or PDFF of the proximal femur was analyzed using Spearman's rank correlation test.</p><p><strong>Results: </strong>Among 217 patients (median age, 74 years; median BMI, 23.8 kg/m²), there was a significant positive correlation between BMI and R2* at the right and left proximal femur (r = 0.2686, <i>p</i> < 0.0001; r = 0.2755, <i>p</i> < 0.0001, respectively). Furthermore, BMI and PDFF showed a significant negative correlation (r = -0.239, <i>p</i> = 0.0004; r = -0.2212, <i>p</i> = 0.001, respectively).</p><p><strong>Conclusion: </strong>In elderly men, the increased loading on the proximal femur due to elevated BMI was observed to promote a decrease in bone marrow adiposity in the proximal femur, causing a tendency for a transition from fatty marrow to red marrow with hematopoietic activity. These results indicate that the MRI IDEAL-IQ sequence may be valuable for assessing bone quality deterioration in the proximal femur.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 5","pages":"816-825"},"PeriodicalIF":1.9,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11125441/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141088389","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":"Breast Glandular and Ductal Volume Changes during the Menstrual Cycle: A Study in 48 Breasts Using Ultralow-Frequency Transmitted Ultrasound Tomography/Volography.","authors":"James Wiskin, John Klock, Susan Love","doi":"10.3390/tomography10050060","DOIUrl":"10.3390/tomography10050060","url":null,"abstract":"<p><p>The aim of this study was to show for the first time that low-frequency 3D-transmitted ultrasound tomography (3D UT, volography) can differentiate breast tissue types using tissue properties, accurately measure glandular and ductal volumes in vivo, and measure variation over time. Data were collected for 400 QT breast scans on 24 women (ages 18-71), including four (4) postmenopausal subjects, 6-10 times over 2+ months of observation. The date of onset of menopause was noted, and the cases were further subdivided into three (3) classes: pre-, post-, and peri-menopausal. The ducts and glands were segmented using breast speed of sound, attenuation, and reflectivity images and followed over several menstrual cycles. The coefficient of variation (CoV) for <i>glandular tissue</i> in premenopausal women was significantly larger than for postmenopausal women, whereas this is not true for the <i>ductal</i> CoV. The glandular standard deviation (SD) is significantly larger in premenopausal women vs. postmenopausal women, whereas this is not true for ductal tissue. We conclude that ducts do not appreciably change over the menstrual cycle in either pre- or post-menopausal subjects, whereas glands change significantly over the cycle in pre-menopausal women, and 3D UT can differentiate ducts from glands in vivo.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 5","pages":"789-805"},"PeriodicalIF":1.9,"publicationDate":"2024-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11125938/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141088098","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":"Arterial Input Function (AIF) Correction Using AIF Plus Tissue Inputs with a Bi-LSTM Network.","authors":"Qi Huang, Johnathan Le, Sarang Joshi, Jason Mendes, Ganesh Adluru, Edward DiBella","doi":"10.3390/tomography10050051","DOIUrl":"10.3390/tomography10050051","url":null,"abstract":"<p><p><b>Background:</b> The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time-concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. <b>Purpose:</b> When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training. <b>Methods</b>: Simulated data were generated using a 12-parameter AIF mathematical model for the AIF. Tissue curves were created from true AIFs combined with compartment-model parameters from a random distribution. Using Bloch simulations, a dictionary was constructed for a saturation-recovery 3D radial stack-of-stars sequence, accounting for deviations such as flip angle, T2* effects, and residual longitudinal magnetization after the saturation. A preliminary simulation study established the optimal tissue curve number using a bidirectional long short-term memory (Bi-LSTM) network with just AIF loss. Further optimization of the loss function involves comparing just AIF loss, AIF with compartment-model-based parameter loss, and AIF with compartment-model tissue loss. The optimized network was examined with both simulation and hybrid data, which included in vivo 3D stack-of-star datasets for testing. The AIF peak value accuracy and ktrans results were assessed. <b>Results</b>: Increasing the number of tissue curves can be beneficial when added tissue curves can provide extra information. Using just the AIF loss outperforms the other two proposed losses, including adding either a compartment-model-based tissue loss or a compartment-model parameter loss to the AIF loss. With the simulated data, the Bi-LSTM network reduced the AIF peak error from -23.6 ± 24.4% of the AIF using the dictionary method to 0.2 ± 7.2% (AIF input only) and 0.3 ± 2.5% (AIF + ten tissue curve inputs) of the network AIF. The corresponding ktrans error was reduced from -13.5 ± 8.8% to -0.6 ± 6.6% and 0.3 ± 2.1%. With the hybrid data (simulated data for training; in vivo data for testing), the AIF peak error was 15.0 ± 5.3% and the corresponding ktrans error was 20.7 ± 11.6% for the AIF using the dictionary method. The hybrid data revealed that using the AIF + tissue inputs reduced errors, with peak error (1.3 ± 11.1%) and ktrans error (-2.4 ± 6.7%). <b>Conclusions</b>: Integrating tissue curves with AIF curves into network inputs improves the precision of AI-driven AIF corrections. This result was seen both with simulated data and with applying the network trained only on simulated data to a limited in vivo test dataset.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 5","pages":"660-673"},"PeriodicalIF":1.9,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11126045/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141088018","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":"Advanced Imaging of Shunt Valves in Cranial CT Scans with Photon-Counting Scanner.","authors":"Anna Klempka, Eduardo Ackermann, Stefanie Brehmer, Sven Clausen, Christoph Groden","doi":"10.3390/tomography10050050","DOIUrl":"10.3390/tomography10050050","url":null,"abstract":"<p><p>This brief report aimed to show the utility of photon-counting technology alongside standard cranial imaging protocols for visualizing shunt valves in a patient's cranial computed tomography scan. Photon-counting CT scans with cranial protocols were retrospectively surveyed and four types of shunt valves were encountered: proGAV 2.0^®, M.blue^®, Codman Certas^®, and proSA^®. These scans were compared with those obtained from non-photon-counting scanners at different time points for the same patients. The analysis of these findings demonstrated the usefulness of photon-counting technology for the clear and precise visualization of shunt valves without any additional radiation or special reconstruction patterns. The enhanced utility of photon-counting is highlighted by providing superior spatial resolution compared to other CT detectors. This technology facilitates a more accurate characterization of shunt valves and may support the detection of subtle abnormalities and a precise assessment of shunt valves.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 5","pages":"654-659"},"PeriodicalIF":1.9,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11125980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141087845","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":"Optimizing CT Abdomen-Pelvis Scan Radiation Dose: Examining the Role of Body Metrics (Waist Circumference, Hip Circumference, Abdominal Fat, and Body Mass Index) in Dose Efficiency.","authors":"Huda I Almohammed, Wiam Elshami, Zuhal Y Hamd, Mohamed Abuzaid","doi":"10.3390/tomography10050049","DOIUrl":"10.3390/tomography10050049","url":null,"abstract":"<p><p><b>Objective</b>: This study investigates the correlation between patient body metrics and radiation dose in abdominopelvic CT scans, aiming to identify significant predictors of radiation exposure. <b>Methods:</b> Employing a cross-sectional analysis of patient data, including BMI, abdominal fat, waist, abdomen, and hip circumference, we analyzed their relationship with the following dose metrics: the CTDI_vol, DLP, and SSDE. <b>Results:</b> Results from the analysis of various body measurements revealed that BMI, abdominal fat, and waist circumference are strongly correlated with increased radiation doses. Notably, the SSDE, as a more patient-centric dose metric, showed significant positive correlations, especially with waist circumference, suggesting its potential as a key predictor for optimizing radiation doses. <b>Conclusions:</b> The findings suggest that incorporating patient-specific body metrics into CT dosimetry could enhance personalized care and radiation safety. Conclusively, this study highlights the necessity for tailored imaging protocols based on individual body metrics to optimize radiation exposure, encouraging further research into predictive models and the integration of these metrics into clinical practice for improved patient management.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"10 5","pages":"643-653"},"PeriodicalIF":1.9,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11126040/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141088266","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}