Multi-vessel coronary artery disease (MVCD) is a severe type of coronary artery disease (CAD) with high risk of major adverse cardiovascular events (MACEs). At present, the accurate identification and risk stratification of patients with MVCD is to be solved imminently. The aim of this study was to preliminarily explore the potential risk factors of the patients with MVCD and construct a classification model with logistic regression and machine learning (ML) algorithms. The 1708 hospitalized CAD patients who underwent percutaneous coronary intervention (PCI) in Shandong Provincial Hospital were recruited in this retrospective analysis. According to the results of coronary angiography, they were divided into single-vessel disease group and multi-vessel disease group (≥ 2 major coronary arteries have more than 50

Carotid atherosclerotic plaques are a leading cause of ischemic stroke and present a major challenge for early atherosclerosis intervention. Here we engineer a biomimetic delivery platform, such as the Trojan Horse system, composed of platelet membrane and extracellularvesicles (EVs) derived from M2-like macrophages. The resulting vesicles, called platelet-extracellular vesicles (P-EVs), selectively accumulate at injured endothelium and atherosclerotic plaques and enable the co-delivery of PIM1 siRNA and Max-40279. This strategy suppresses endothelial-mesenchymal transition, reduces macrophage foam cell formation, and attenuates inflammatory responses in lesions. In mouse models of atherosclerosis, treatment with P-EVs significantly limits plaque progression. These results establish P-EVs as a targeted approach for modulating vascular inflammation and provide a potential strategy for slowing atherosclerotic plaque development.

Cardiovascular disease (CVD) retains a substantial residual burden despite control of conventional risk factors, indicating contributions from additional metabolic, inflammatory and host–microbial pathways. The gut microbiota–bile acid axis links diet and environmental exposures to microbial metabolism, enterohepatic signalling and cardiovascular homeostasis. However, current evidence is commonly organised around isolated diseases or molecular mechanisms, with limited attention to when this axis becomes detectable, how it should be clinically interpreted and whether it can guide individualised prevention. In this review, we propose a spatiotemporal framework for the gut microbiota–bile acid axis across the health–suboptimal health–disease continuum within predictive, preventive and personalised medicine (PPPM/3PM). Mechanistic evidence is most developed for atherosclerosis and atherothrombosis, whereas evidence for atrial fibrillation, heart failure, pulmonary hypertension and cerebrovascular outcomes is more heterogeneous and less mature. Microbial bile salt hydrolase activity and downstream bile acid transformations reshape compartment-specific bile acid pools, with potential effects on cholesterol catabolism, inflammatory and barrier responses, vascular homeostasis, platelet activation and myocardial stress. For 3PM, molecular profiles should be interpreted together with multidomain functional phenotypes, including bowel function and gastrointestinal symptoms, hepatobiliary status, metabolic–inflammatory context, and diet and medication exposure. Microbiota-directed interventions should be function-informed rather than selected by taxonomy alone. Translation requires longitudinal multi-omics, standardised multi-compartment bile acid profiling, causal validation in human-relevant models and prospective studies determining whether phenotype-guided strategies add predictive or preventive value beyond established cardiovascular care.

To develop and validate a nomogram that integrates clinical factors and multiparametric MRI-based radiomics features for the preoperative prediction of lymph node metastasis (LNM) in non-small cell lung cancer (NSCLC). This retrospective diagnostic accuracy study enrolled 220 patients with pathologically confirmed NSCLC (142 males; 60.77 ± 8.70 years) between September 2021 and October 2024. Patients were randomly divided into training and validation sets. A clinical model was constructed using independent predictors identified by univariable and multivariable logistic regression analysis. A radiomics signature was developed from T1WI, T2WI, and T1 mapping sequences using the least absolute shrinkage and selection operator logistic regression algorithm. A nomogram was developed by integrating the clinical model and the radiomics signature. Diagnostic performance was assessed by receiver operating characteristic analysis, calibration, and decision curve analysis. Two radiologists independently assessed LNM status in the validation set for comparison. Tumor maximum diameter and carcinoembryonic antigen level were identified as independent predictors for the clinical model. In the validation set, the nomogram achieved an area under the curve (AUC) of 0.847, significantly greater than the clinical model (AUC = 0.710, p = 0.033) and the radiomics signature alone (AUC = 0.802, p = 0.033). The AUC of the nomogram was significantly higher than two radiologists (0.847 vs. 0.682, p = 0.022; 0.847 vs. 0.698, p = 0.041, respectively). The nomogram could serve as a noninvasive tool for preoperative prediction of LNM in NSCLC, thereby aiding in clinical decision-making.

Objective To evaluate and compare the efficacy and safety of endovascular treatment alone versus hybrid operation in the treatment of symptomatic chronic internal carotid artery occlusion (CICAO). Methods A total of 103 patients with symptomatic CICAO who underwent hybrid operation (n = 60) or endovascular treatment alone (n = 43) in Qilu Hospital of Shandong University from May 2016 to March 2025 were included. All cases were classified into 4 types, namely type A, type B, type C and type D by preoperative DSA examination combined with Hasan classification. The vascular recanalization success rate, as well as the incidence of complications during the perioperative period, follow-up period and in the vascular recanalization cases were recorded. Results The vascular recanalization success rate of the hybrid operation group was higher than that of the endovascular treatment alone group (χ2 = 10.885, P = 0.001). Analysis by Hasan classification showed that Hasan type C had more advantages with hybrid operation (Fisher's exact probability: P = 0.024). There was no statistically significant difference in the incidence of perioperative complications between the hybrid operation group and the endovascular treatment alone group (χ2 = 0.008, P = 0.928). The median follow-up time of the hybrid operation group was 33.00 (11.25, 52.75) months, and the median follow-up time of the endovascular treatment alone group was 24 (15, 30) months. During the follow-up period, there were no statistically significant differences in mortality (Fisher's exact probability: P = 1.000), the incidence of new transient ischemic attack/ischemic stroke (Fisher's exact probability: P = 0.251), and the incidence of restenosis/reocclusion of the affected internal carotid artery in vascular success recanalization cases (Fisher's exact probability: P = 0.210). Conclusions For patients with CICAO, hybrid operation achieves a higher vascular recanalization success rate. This surgical approach is both safe and feasible, and may be particularly beneficial for patients with more complex anatomical features (Hasan type C). There were no significant differences between hybrid operation and endovascular treatment alone in terms of safety and the incidence of postoperative restenosis/reocclusion of affected internal carotid artery.

Percutaneous coronary intervention (PCI) is a practical and effective method for treating coronary heart disease (CHD). This study aims to explore the influencing factors of major cardiovascular events (MACEs) and hospital readmission risk within one year following PCI treatment. Additionally, it seeks to assess the clinical value of Apolipoprotein B/Apolipoprotein A-I (ApoB/ApoA-I) in predicting the risk of one-year MACEs and readmission post-PCI. A retrospective study included 1938 patients who underwent PCI treatment from January 2010 to December 2018 at Shandong Provincial Hospital affiliated with Shandong First Medical University. Patient demographics, medications, and biochemical indicators were recorded upon admission, with one-year follow-up post-operation. Univariate and multivariate Cox proportional hazards regression models were utilized to establish the relationship between ApoB/ApoA-I levels and MACEs/readmission. Predictive nomograms were constructed to forecast MACEs and readmission, with the accuracy of the nomograms assessed using the concordance index. Subgroup analyses were conducted to explore the occurrence of MACEs and readmission. We observed a correlation between ApoB/ApoA-I and other lipid indices, including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) (P < 0.001). Univariate and multivariate Cox regression analyses demonstrated that ApoB/ApoA-I is an independent risk factor for MACEs in post-PCI patients (P = 0.038). Within one year, the incidence of MACEs significantly increased in the high-level ApoB/ApoA-I group (ApoB/ApoA-I ratio ≥ 0.824) (P = 0.038), while the increase in readmission incidence within one year was not statistically significant. Furthermore, a nomogram predicting one-year MACEs was established (Concordance Index: 0.668). Subgroup analysis revealed that ApoB/ApoA-I was associated with the occurrence of both MACEs and readmission in male patients, those using CCB/ARB/ACEI, those without multivessel diseases, or those with LDL-C < 2.6 mmol/L. The ApoB/ApoA-I ratio serves as an independent risk factor for one-year MACEs in post-PCI patients and correlates closely with other blood lipid indicators. ApoB/ApoA-I demonstrates significant predictive value for the occurrence of MACEs within one year. Trial registration Chinese clinical trial registry: No.ChiCTR22000597-23.

Background: The link between lymph node (LN) function and atherosclerosis is unclear, especially at the single-cell level. This study explores the relationship between pericarotid LNs and plaque stability using single-cell transcriptome analysis. Methods: We enrolled 106 patients with severe internal carotid artery stenosis undergoing carotid endarterectomy. We recorded baseline clinical data and pericarotid LN size, and analyzed plaque composition to assess its association with enlarged LNs. Single-cell transcriptome and T/B-cell receptor sequencing were used to profile pericarotid LNs. Results: Patients with symptomatic carotid atherosclerosis had more enlarged pericarotid LNs (P<0.001), indicating plaque instability. This was characterized by increased inflammation, greater CD68(+) macrophage infiltration (P<0.001), and reduced fibrous content (P<0.001). Single-cell analysis identified 3 main cellular compartments: lymphocytes, myeloid cells, and stromal cells. Enlarged LNs had significantly more naive B and T cells (P<0.001), suggesting heightened immune response. Macrophages and neutrophils may help in cholesterol transport and degradation, while stromal cells may regulate the immune microenvironment by influencing T-cell tolerance and lymphocyte trafficking. Conclusions: Enlarged pericarotid LNs are potential biomarkers for plaque instability and recent ischemic events. This study provides a comprehensive single-cell transcriptomic landscape of human LNs in atherosclerosis.

BACKGROUND:This study aims to explore the value of habitat-based magnetic resonance imaging (MRI) radiomics for predicting the origin of brain metastasis (BM). PURPOSE:To investigate whether habitat-based radiomics can identify the metastatic tumor type of BM and whether an imaging-based model that integrates the volume of peritumoral edema (VPE) can enhance predictive performance. METHODS:A primary cohort was developed with 384 patients from two centers, which comprises 734 BM lesions. An independent cohort was developed with 28 patients from a third center, which comprises 70 BM lesions. All patients underwent T1-weighted contrast-enhanced (T1CE) and T2-weighted (T2W) MRI scans before treatment. Radiomics features were extracted from tumor active area (TAA) and peritumoral edema area (PEA) selected using the least absolute shrinkage and selection operator (LASSO) to construct radiomics signatures (Rads). The Rads were further integrated with VPE to build combined models for predicting the metastatic type of BM. Performance of the models were assessed through receiver operating characteristic (ROC) curve analysis. RESULTS:Rads derived from TAA and PEA both showed predictive power for identifying the origin of BM. The developed combined models generated the best performance in the training (AUCs, lung cancer [LC]/non-lung cancer [NLC] vs. small cell lung cancer [SCLC]/non-small cell lung cancer [NSCLC] vs. breast cancer [BC]/gastrointestinal cancer [GIC], 0.870 vs. 0.946 vs. 0.886), internal validation (area under the receiver operating characteristic curves [AUCs], LC/NLC vs. SCLC/NSCLC vs. BC/GIC, 0.786 vs. 0.863 vs. 0.836) and external validation (AUCs, LC /NLC vs. SCLC/NSCLC vs. BC/GIC, 0.805 vs. 0.877 vs. 0.774) cohort. CONCLUSIONS:The developed habitat-based radiomics models can effectively identify the metastatic tumor type of BM and may be considered as a potential preoperative basis for timely treatment planning.

Proliferation activity mapping is crucial for the guidance of first biopsy and treatment evaluation of gliomas due to the highly heterogenous nature of glioma tumor. Here we propose and demonstrate an ease-of-use way of in vivo spatiotemporal mapping of proliferation activity by simply tracking transmembrane water dynamics with magnetic resonance imaging (MRI). Specifically, we demonstrated that proliferation activity can accelerate the transmembrane water transport in glioma cells. Method: The transmembrane water-efflux rate (k io) measured by water-exchange dynamic contrast-enhanced (DCE) MRI. Immunofluorescence, immunohistochemistry, and immunocytochemistry staining were used to validate results obtained from the in vivo imaging studies. Results: In glioma cell cultures, k io precisely followed the dynamic changes of proliferation activity in growth cycles and response to temozolomide (TMZ) treatment. In both animal glioma model and human glioma, k io linearly and strongly correlated with the spatial heterogeneity of intra-tumoral proliferation activity. More importantly, proliferation activity predicted by the single MRI parameter k io is much more accurate than those predicted by state-of-the-art methods using multimodal standard MRIs and advanced machine learning. Upregulated aquaporin 4 (AQP4) expression were observed in most proliferating glioma cells and the knockout of AQP4 could largely slow down proliferation activity, suggesting AQP4 is the potential molecule connecting MRI-k io with proliferation activity. Conclusion: This study provides an ease-of-use, accurate, and non-invasive imaging method for the spatiotemporal monitoring of proliferation activity in glioma.

BACKGROUND: The microbiota has been reported to play an important role in the occurrence of brain aneurysms (CA). However, no microbiota or metabolite has been used for diagnosis or therapy of CA till now. METHODS: The microbial DNA was extracted from the stool samples of the CA and healthy volunteer groups. The 16S rDNA gene was sequenced on a MiSeq system. R software package was used to analyze the sequence, and the variations in microbial composition was obtained. The correlation analysis of the differential intestinal bacteria, metabolites and blood parameters was explored based on a logistic regression model. A random forest algorithm was used to predict the classification of samples for further exploring the relationship between fecal microbiota and CA. RESULTS: The α-diversity indexes demonstrated an altered within-sample microbial diversities between patients and healthy people. The subsequent beta diversity results indicated that shift in the between-sample microbial diversities of the intestinal microbiota was associated with the occurrence of cerebral aneurysm. Specifically, the abundance of some gut bacterial genera, such as Blautia and Faecalibacterium, changed significantly after CA. Intestinal metabolite enrichment results highlight the role of carbohydrate metabolic pathways in CA, including sedoheptulose 7-phosphate (S-7-P). The correlation analysis of the differential intestinal bacteria, metabolites and blood parameters indicated that intestinal bacteria and metabolites were related to host blood parameters. Then, the predictive models were employed to test the significance of the combination of differential bacteria, metabolites and blood parameters in CA diagnosis and prognosis. The predictive model built by Faecalibacterium and s7p obtained an area under ROC curve (AUC) of 99.7%, and Faecalibacterium and s-7-p were also associated with some metabolite that have significance in post-surgery prognosis of CA. Conclusions: The gut microbiota and metabolites profiles of patients with CA were significantly altered. Bacterial genus Faecalibacterium and metabolite s-7-p could serve as potential biomarkers in CA prediction and post-surgery prognosis. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research was sponsored by ?Design and development of a smart department management platform based on big data? (Shandong University No.6010122150). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was reviewed and approved by the Ethic Committee of School of Basic Medical Science, Shandong University (Jinan, Shandong Province, China), the approval number is ECSBMSSDU2023-1-82. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Availability of data and material http://www.ncbi.nlm.nih.gov/bioproject/1053898 Supplemental files: meta\_intensity\_class\_neg and meta\_intensity\_class\_pos

Multi-vessel coronary disease (MVCD) is a severe form of coronary artery disease (CAD) that significantly increases the risk of acute coronary syndrome (ACS) and heart attacks. The triglyceride glucose (TyG) index is a reliable and convenient marker for insulin resistance (IR). Recent studies have demonstrated its predictive value for CAD in patients with MVCD. This review aims to explore the application of the TyG index in managing MVCD and its underlying pathogenesis to enhance risk stratification and improve therapeutic decision-making.

Objective:Angina, a prevalent manifestation of coronary artery disease, is primarily associated with inflammation, an established contributor to the pathogenesis of atherosclerosis and acute coronary syndromes (ACS). Various inflammatory markers are employed in clinical practice to predict patient prognosis and optimize clinical decision-making in the management of ACS. This study investigated the prognostic significance of integrating commonly used, easily repeatable inflammatory biomarkers within a multimodal preoperative prediction model in patients presenting with unstable Angina Pectoris (UAP) and intermediate coronary lesions. Methods:This retrospective analysis included patients diagnosed with UAP and intermediate coronary lesions (50%-70% stenosis) who underwent coronary angiography at our hospital between January 2019 and June 2021. The assessed outcome was the occurrence of major adverse cardiac and cerebrovascular events (MACCEs). The Boruta algorithm was applied to identify potential risk factors and develop a prognostic multimodal model. Results:A total of 773 patients were enrolled and divided into a training cohort (n=463) and validation cohort (n=310). A nomogram was constructed to predict the probability of MACCE-free survival based on five clinical features: diabetes mellitus, current smoking, history of myocardial infarction, neutrophil-to-lymphocyte ratio, and fasting blood glucose. In the training cohort, the area under the curve values for the nomogram at 24, 32, and 40 months were 0.669, 0.707, and 0.718, respectively, while those in the validation cohort were 0.613, 0.612 and 0.630, respectively. The model demonstrated good calibration in both cohorts with predicted outcomes aligning well with actual results at all time points up to 40 months. Furthermore, decision curve analysis showed significant clinical utility of the model across the specified time intervals. Conclusion:The developed preoperative prognostic model visually illustrates the association among inflammation, blood glucose level, established risk factors, and long-term MACCEs in UAP patients with intermediate coronary lesions.

Background and purpose: Studies on changes in the distal internal carotid artery based on high resolution magnetic resonance imaging (HRMRI) are scarce. Herein, we propose a histological classification system for patients with carotid artery pseudo-occlusion or occlusion based on preoperative HRMRI, for which we evaluated the feasibility and clinical implications. Materials and methods: From January 2017 to June 2021, 40 patients with Doppler ultrasound, CTA or MRA suggesting carotid artery occlusion were enrolled in this study. A new classification system based on HRMRI was established and subsequently verified by postoperative specimens. We recorded and analyzed patient characteristics, HRMRI data, recanalization rate, requirements of additional endovascular procedures, complications, and outcomes. Results: Four histological classifications (type I -IV) were identified. According to our classification system, 20 patients (50.00%) were type I, nine (22.50%) were type II, 7 (17.50%) were type III, and four (10.00%) were type IV. The success rate of recanalization was 88.89% (32/36) in type I -III patients. Four (44.44%) type II patients and five (71.43%) type III patients suffered from intraoperative dissection. Conclusion: Patients identified as types I (pseudo-occlusion) and II (thrombotic-occlusion) were able to be treated via hybrid revascularization with relatively low risk, while patients identified as type III (fibrous-occlusion) required more careful treatment. Recanalization is not suitable for patients identified as type IV. Our proposed classification system based on HRMRI data can be used as an adjunctive guide to predict the technical feasibility and success of revascularization via a hybrid technique.

Biofluid biomarkers, as objective predictors of traumatic brain injury (TBI) pathobiological processes, play an important role in the early detection of TBI. However, the lack of sensitive and rapid detection assays to detect biomarker levels has been an urgent problem. In this study, we devised a novel surface-enhanced Raman scattering (SERS)-based paper lateral flow strip (PLFS) based on gold nanorods (AuNRs) with controlled aspect ratios for the screening and diagnosis of TBI. To improve the sensitivity of the designed device, AuNRs, as the key component of SERS probes, were optimized by controlling the particle morphology, showing great local plasma enhancement. Furthermore, using thionin acetate (THI) as a Raman reporter, the detection performance of PLFS was further improved due to the unique molecular structure of THI. Thus, the constructed PLFS has been demonstrated to be ultrasensitive, with a limit of detection (LOD) reaching similar to 10(-1) pgmL(-1). Fo r real-world measurements of glial fibrillary acidic protein (GFAP) and myelin basic protein (MBP) in blood samples, the results monitored by the SERS assay were exactly consistent with those obtained through the traditional enzyme-linked immunosorbent assay (ELISA). The above result demonstrated that the developed SERS-PFLS has extensive application prospects in the screening and diagnosis of TBI in the emergency department as point-of-care testing (POCT) and may further shift the paradigm of TBI patient management and clinical outcome in emergency departments.

目的 探讨ZOOMit IVIM和T1 mapping的定量参数在鉴别肺良恶性病变中的作用并评估它们的诊断效能.方法 选取76例诊断为"肺占位性病变"的患者行肺MRI检查,良性11例(良性组),肺癌65例(肺癌组),测量ADC、D、D*、f和T1等参数,对这些参数进行分析,并使用受试者工作特征曲线评估诊断效能.结果 良性组与肺癌组之间对比分析,良性组的ADC值、D值、f值和T1值均大于肺癌组(ADC值P＜0.001;D值P＜0.001;f值P=0.004;T1值P=0.026).ROC曲线分析结果显示ADC值的AUC最大,诊断效能最好(ADC值AUC=0.9552;D值AUC=0.9483;f值AUC=0.7769;T1值AUC=0.710).而D*值在两组之间差异无统计学意义(P=0.430).结论 ADC、D、f和T1有助于鉴别肺的良恶性病变,ADC值的诊断效能最高.

目的 利用MRI探讨宫内正常胎儿第一腰椎(L1)椎体骨化中心的动态发育规律.方法 利用MRI对94例23～38孕周宫内胎儿行全脊柱SWI扫描,测量不同孕周胎儿L1椎体骨化中心生长参数(高度、前后径、左右径、正中矢状位面积)并进行统计学分析,获取其动态生长发育曲线.结果 MRI获取的胎儿脊柱参数在不同性别中差异无统计学意义(P＞0.05);胎儿脊柱L1椎体骨化中心高度随孕周增长的变化曲线为:y=-0.018+0.528×ln孕周(R2=0.716,P＜0.05);前后径随孕周增长的变化曲线为:y=-0.292+0.03 x孕周(R2=0.709,P＜0.05);左右径随孕周增长的变化曲线为:y=-0.277+0.036×ln孕周(R2=0.780,P＜0.05);矢状位面积随孕周增长的变化曲线为:y=-0.461+0.027×孕周(R2=0.817,P＜0.05).结论 孕中晚期胎儿L1椎体骨化中心高度、左右径随孕周增长呈对数增长,前后径及正中矢状位面积随孕周增长呈线性增长,该观察结果对于丰富胎儿脊柱发育影像学资料以及评估发育状况提供了客观影像学指标.

BACKGROUND Lipoprotein(a) [Lp(a)], which is predictive of coronary heart disease (CHD), plays an important role in the pathogenesis of atherosclerosis. This study aimed to evaluate the association of Lp(a) with major adverse cardiovascular events (MACEs) and readmission in individuals who had undergone a percutaneous coronary intervention (PCI). METHODS A total of 1,938 patients with CHD who had undergone a PCI from January 2010 to December 2018 were assigned to three groups based on Lp(a) level. Follow-up was performed to assess the 1-year occurrence of MACEs and readmission. RESULTS Kaplan-Meier survival curves showed that the cumulative hazard incidence rate of MACEs and repeat PCI (re-PCI) significantly increased with Lp(a) level. Multivariate Cox proportional hazards regression analysis further confirmed Lp(a) as a significant independent predictor of MACEs. The area under the curve of the complex index risk score was significantly larger than those of other independent indicators. In individuals with low-density lipoprotein-cholesterol (LDL-C) levels either below 70 mg/dL or between 70 mg/dL and 100 mg/dL, Lp(a) was associated with increased rates of MACEs and readmission. In addition, a nomogram was constructed to predict 1-year MACE. CONCLUSIONS High Lp(a) levels may be a residual risk factor for MACEs in individuals with LDL-C levels under 100 mg/dL. Additionally, the built nomogram could predict 1-year MACEs with high accuracy. Lp(a) independently predicts 1-year MACEs, indicating its importance in risk assessment and the selection of clinical strategies in patients who have undergone a PCI.

Objective:To evaluate the feasibility of quantitative parameters based on T1 mapping sequence in predicting the pathological types of lung cancer.Materials and Methods:A total of 117 lung cancer patients,including 62 cases of adenocarcinoma,26 cases of squamous cell carcinoma,29 cases of small cell lung cancer(SCLC),were enrolled in this study.Prior routine sequence scans,then the B1 field corrected variable flip angle VIBE sequence was used to acquire T1 mapping images.Afterwards,Gd-DTPA was used for dynamic enhanced scanning.T1 mapping images were collected 5 minutes before and after enhancement.Measure tumor size,T1 value before enhancement(T1pre),T1 value after enhancement(T1post),and calculate ΔT1,ΔT1%.SPSS and MedCalc software were used for analysis the differential diagnostic value of each quantitative parameter in each group,logistic regression combined with area under the curve(AUC)was constructed to evaluate the diagnostic value of each quantitative parameter and multi-parameter combination.Results:There were statistically significant differences in ΔT1,ΔT1%and T1post among adenocarcinoma,squamous cell carcinoma and SCLC(P＜0.05),but no difference in T1pre(P=0.506).The AUCs of T1post,ΔT1,and ΔT1%values to differentiate SCLC and non-small cell lung cancer(NSCLC)were 0.856,0.805 and 0.864,combination of the three parameters can improve the diagnostic accuracy of differentiating SCLC and NSCLC(AUC=0.870,P＜0.05).The AUCs of ΔT1 and ΔT1%values to differentiate adenocarcinoma and squamous cell carcinoma were 0.755 and 0.767,combination of the two could slightly improve the diagnostic accuracy(AUC=0.771,P＞0.05).The AUCs of ΔT1%,T1post values to differentiate squamous cell carcinoma and SCLC were 0.788 and 0.818,combination of the two could improve the diagnostic accuracy(AUC=0.831,P＞0.05).The AUCs of ΔT1%,T1post values to differentiate adenocarcinoma and SCLC is 0.895 and 0.873,combination of the two could improve the diagnostic accuracy(AUC=0.898,P＞0.05).Conclusions:T1 mapping can non-invasively and quantitatively obtain the T1 value of adenocarcinoma,squamous cell carcinoma and small cell lung cancer,and can be used to distinguish SCLC from NSCLC,as well as squamous cell carcinoma and adenocarcinoma,provide more accurate histological correlations and prognostic value in lung cancer.

BackgroundThe bioinformatics analysis on glioma has been a hot point recently. The purpose of this study was to provide an overview of the research in this field using a bibliometric method.MethodsThe Web of Science Core Collection (WOSCC) database was used to search for literature related to the bioinformatics analysis of gliomas. Countries, institutions, authors, references, and keywords were analyzed using VOSviewer, CiteSpace, and Microsoft Excel software.ResultChina was the most productive country, while the USA was the most cited. Capital Medical University had the largest number of publications and citations. Institutions tend to collaborate more with other institutions in their countries rather than foreign ones. The most productive and most cited author was Jiang Tao. Two citation paths were identified, with literature in basic research journals often cited in clinical journals. Immune-related vocabularies appeared frequently in recent studies.ConclusionGlioma bioinformatics analyses spanned a wide range of fields. The international communication in this field urgently needs to be strengthened. Glioma bioinformatics approaches are developing from basic research to clinical applications. Recently, immune-related research has become a focus.

目的 探讨宫内胎儿T12椎体骨化中心大小随孕周的变化关系,绘制其生长曲线.方法 选取23～38孕周82例宫内胎儿行全脊柱SWI扫描,测量T12椎体骨化中心的高度、前后径、左右径及正中矢状位面积,建立相关线性回归方程.结果 胎儿T12椎体骨化中心高度、前后径、左右径及正中矢状位面积与孕周的线性回归方程分别为:T12椎体骨化中心高度(cm)=-0.143+0.020×孕周(R2=0.923,P＜0.05)、前后径(cm)=-0.421+0.031×孕周(R2=0.926,P＜0.05)、左右径(cm)=-0.464+0.039×孕周(R2=0.925,P＜0.05)、正中矢状位面积(cm2)=-0.509+0.022×孕周(R2=0.944,P＜0.05).T12椎体骨化中心发育不存在性别差异.结论 孕中晚期宫内胎儿T12椎体骨化中心高度、前后径、左右径及正中矢状位面积与孕周呈高度线性相关,是评估胎儿脊柱发育的可靠指标.