Background: Pentraxin 3 (PTX3) is a well-established inflammatory biomarker with significant implications in the pathogenesis and prognostic assessment of cardiovascular diseases. This study aimed to investigate the potential value of serum PTX3 as a circulating biomarker when combined with the high-resolution magnetic resonance vessel wall imaging (HR-VWI) for identifying carotid vulnerable plaque (CVP) and its specific vulnerable features. Methods: This prospective cross-sectional study enrolled 86 patients with carotid atherosclerosis who underwent HR-VWI. Patients were classified into CVP and non-carotid vulnerable plaque (NCVP) groups, and CVP was divided into unilateral carotid vulnerable plaque (UCVP) and bilateral carotid vulnerable plaque (BCVP). CVP was defined as meeting ≥ 1 major criteria: lipid-rich necrotic core (LRNC) maximum area percentage > 40% combined with thin fibrous cap (FC), intraplaque hemorrhage (IPH), FC discontinuity, and focal inflammation. Multivariate logistic regression analysis identified factors influencing CVP and the formation of specific vulnerable features. Results: Serum PTX3 levels progressively increased across the NCVP, UCVP, and BCVP groups (median 638.23, 858.52, 1113.62 pg/mL; p < 0.001). PTX3 independently predicted the presence of CVP (OR = 2.88; 95% CI: 1.16-8.91; p = 0.039) and specific vulnerable features, including FC discontinuity (OR = 2.47; 95% CI: 1.32-4.63; p = 0.005) and focal inflammation (OR = 2.25; 95% CI: 1.18-4.32; p = 0.014) with high diagnostic performance for these conditions. PTX3 levels exhibited a moderate positive correlation with the number of vulnerable features (r = 0.610, p < 0.01). Conclusions: Elevated serum PTX3 levels were significantly associated with HR-VWI-defined carotid plaque vulnerability and its severity, serving as a reliable circulating biomarker for identifying FC discontinuity and focal inflammation.

PURPOSE:To evaluate the prognostic value of carotid plaque features derived from high-spatial-resolution vessel-wall MRI (HR-MRI) for long-term major adverse cardiovascular events (MACE) after carotid revascularization. METHODS:Consecutive patients undergoing carotid revascularization between April 2017 and April 2024 with preoperative carotid HR-MRI were included. Ipsilateral intraplaque hemorrhage (IPH) was identified as a hyperintense plaque component on SNAP images and manually segmented on each relevant slice using Vessel Explorer 2.0 software. IPH volume was calculated as the sum of the segmented IPH areas multiplied by slice thickness. MACE comprised cardiovascular death, nonfatal myocardial infarction, coronary revascularization, and stroke. Associations were assessed using Cox regression and Kaplan-Meier analysis. Prediction models were evaluated using the concordance index (C-index), calibration, and decision curve analysis (DCA). RESULTS:Among 296 patients (mean age [65.04 ± 9.47] years; 244 [82.4%] men), 154 underwent carotid endarterectomy (CEA) and 142 underwent carotid artery stenting (CAS). During a median follow-up of 4.5 years, ipsilateral IPH volume was an independent predictor of MACE in the overall cohort (hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.34-1.66; P < .001), as well as in the CEA subgroup (HR, 1.31; 95% CI, 1.11-1.55; P = .001) and CAS subgroup (HR, 1.21; 95% CI, 1.05-1.40; P = .007). Contralateral IPH was also independently associated with higher event risk in the overall cohort (HR, 2.37; 95% CI, 1.34-4.19; P = .003) and in both procedural subgroups (CEA: HR, 2.79; 95% CI, 1.16-6.67; P = .022; CAS: HR, 2.47; 95% CI, 1.22-5.00; P = .012). Kaplan-Meier analysis showed significantly lower event-free survival in patients with ipsilateral or contralateral IPH. Prediction models demonstrated acceptable discrimination (C-index: overall, 0.725; CEA, 0.755; CAS, 0.711), good calibration, and consistent clinical net benefit. CONCLUSIONS:Among HR-MRI-derived carotid plaque features, ipsilateral IPH volume and the presence of contralateral IPH were independently associated with long-term cardiovascular events after carotid revascularization. These findings support carotid IPH as an imaging marker of systemic atherosclerotic vulnerability and may improve individualized risk stratification after revascularization.

BackgroundArtificial intelligence (AI), particularly deep learning, has shown promise in enhancing medical image interpretation and improving radiologists’ efficiency. In China, growing imaging demand and workforce shortages have placed increasing pressure on radiology services. However, evidence on the operational impact of AI on reporting efficiency remains limited. ObjectiveThis study aimed to evaluate the effect of an AI system on radiologists’ reporting efficiency by examining changes in report-drafting time for lung nodule diagnosis in chest computed tomography (CT) images. MethodsWe analyzed 185,044 chest CT reports from Beijing Anzhen and Tsinghua Changgung Hospitals (2018-2023) using a difference-in-differences design with nonequivalent comparison groups. Report-drafting time before, immediately after, and up to 2 years following AI implementation was compared, adjusting for radiologist gender, seniority, and years of working experience. ResultsThe pooled analysis showed a modest overall increase of 0.86 minutes (95% CI 0.14 to 1.57). However, this masked substantial heterogeneity between hospitals due to differing implementation timelines. In the first year after AI deployment, Tsinghua Changgung Hospital experienced a nonsignificant increase of 0.90 minutes (95% CI –0.28 to 2.08). In contrast, at Beijing Anzhen Hospital, the AI-assisted group exhibited an absolute reduction of 0.76 minutes by the first year and a further 1.83-minute reduction by the second year (an approximate 28% time saved vs baseline), while the control group remained stable over time. Using a difference-in-differences framework, this corresponded to a 2.66-minute relative improvement compared with the counterfactual trend (P<.001). ConclusionsAI-assisted lung nodule diagnosis may initially increase report-drafting time due to adaptation and workflow adjustment. Sustained, meaningful efficiency gains were heterogeneous and observed at only 1 of the 2 study sites, indicating that long-term impacts are strongly contingent on site-specific implementation dynamics, learning curves, and local context.

ObjectivesIt is well established that calcified plaques are highly likely to lead to residual stenosis after stenting; however, the specific characteristics responsible for this effect remain unknown. This study aimed to identify both qualitative and quantitative imaging risk factors for residual stenosis using computed tomography angiography.MethodsWe retrospectively enrolled 233 patients with carotid artery stenosis. Patients were categorized into two groups based on the presence or absence of postoperative residual stenosis. Carotid computed tomography angiography evaluated plaque characteristics both qualitatively and quantitatively. Logistic regression analysis identified independent risk factors for residual stenosis. We evaluated the predictive model’s discriminative ability by calculating the area under the receiver operating characteristic (ROC) curve.ResultsUnivariate analysis indicated a statistical difference in age, creatinine, total plaque volume, percentage of total calcified plaque, percentage of total soft plaque, maximum slice attenuation value, maximum thickness, total length, and a circumferential calcification score ≥2 points (p < 0.05). Multivariable logistic regression identified creatinine (OR = 1. 020; 95%CI: 1.005–1.035; p = 0.010), maximum slice attenuation value(Z-score; OR = 1.627; 95%CI: 1.024–2.585; p = 0.039), percentage of calcified plaque volume(Z-score; OR = 1.872; 95%CI: 1.137–3.082; p = 0.014) and circumferential calcification score ≥2 (OR = 3.257; 95%CI: 1.620–6.548; p < 0.001) as independent factors associated with residual stenosis. Furthermore, receiver operating characteristic curve analysis revealed that the area under the curve for the combined model in diagnosing residual stenosis was 0.784.ConclusionIn conclusion, preoperative CTA-based assessment of specific plaque characteristics, such as calcified plaque volume percentage, circumferential calcium score, and the maximum slice attenuation value of calcification are related to residual stenosis.

OBJECTIVE:To evaluate the additive value of two-way fluid-structure interaction (twFSI)-derived biomechanical metrics for artery-level discrimination of symptomatic carotid disease. METHODS:This single-center retrospective study included 97 patients (125 carotid arteries) who underwent high-resolution vessel wall imaging (HR-VWI). Three-dimensional lumen, vessel wall, and plaque were reconstructed, followed by twFSI simulations to derive hemodynamic and structural indices. Slice-wise morphological descriptors and twFSI-derived biomechanical candidate features were aggregated to the artery level using an attention-based multiple-instance learning framework. Performance was assessed with patient-wise five-fold cross-validation using area under the receiver operating characteristic curve (AUC), accuracy, and macro-averaged F1 score (macro-F1). RESULTS:Symptomatic arteries tended to show lower shear-related exposure and a more disturbed low-shear environment, whereas solid-domain descriptors showed more heterogeneous between-group behavior. A clinical-morphology model (CM) achieved an AUC of 0.716. Incorporating twFSI-derived biomechanical features (CM-BM) improved discrimination (AUC = 0.821), with accuracy increasing from 0.668 to 0.710 and macro-F1 from 0.720 to 0.761. The final CM-BM model retained a concise set of morphological and biomechanical descriptors, including plaque type, plaque angle range, maximum plaque area, maximum total deformation, maximum normalized WSS, and maximum ECAP. CONCLUSIONS:In this single-center cohort, twFSI-derived biomechanical metrics provided incremental discriminative value beyond clinical and morphological variables alone. Attention-based MIL further offered a slice-weighting mechanism that may aid interpretability at the artery level. These findings support the potential of combined structural-dynamic phenotyping for symptom-oriented carotid assessment, while warranting prospective multicenter external validation.

Background/Objectives: Patients undergoing carotid revascularization may show distinct patterns of bilateral carotid vulnerability and clinical risk. This study used latent class analysis (LCA) to identify high-resolution magnetic resonance imaging (HR-MRI)-based clinical-radiological phenotypes and evaluate their association with long-term major adverse cardiovascular events (MACE). Methods: This retrospective cohort included 289 patients who underwent carotid endarterectomy (CEA) or carotid artery stenting (CAS) between April 2017 and April 2024 and had preoperative carotid HR-MRI within 90 days. Ipsilateral and contralateral plaque features were assessed on multi-contrast vessel-wall HR-MRI. LCA included five indicators: ipsilateral intraplaque hemorrhage, ipsilateral lipid-rich necrotic core, contralateral intraplaque hemorrhage, cardiovascular disease history, and symptomatic status. MACE comprised cardiovascular death, nonfatal myocardial infarction, coronary revascularization, or stroke. Outcomes were assessed using Kaplan-Meier analysis and multivariable Cox regression. Results: Among 289 patients undergoing carotid revascularization, the mean age was 65.12 ± 9.46 years, and 237 (82.0%) patients were men. LCA identified three phenotypes: Systemic High-Risk (n = 128), Silent High-Risk (n = 37), and Stable/Moderate (n = 124). The Systemic High-Risk phenotype showed high probabilities of symptomatic presentation, cardiovascular disease history, and bilateral carotid vulnerability, whereas the Silent High-Risk phenotype showed marked ipsilateral plaque vulnerability despite lower clinical risk. During a median follow-up of 4.4 years, MACE-free survival differed significantly across phenotypes (log-rank p = 0.043). Compared with the Stable/Moderate phenotype, the Systemic High-Risk and Silent High-Risk phenotypes were both associated with increased MACE risk (HR 1.65, 95% CI 1.15-2.37, p = 0.039; HR 1.43, 95% CI 1.12-2.15, p = 0.034). Conclusions: HR-MRI-based LCA identified clinically meaningful carotid vulnerability phenotypes associated with long-term MACE after carotid revascularization. These findings support integrated assessment of bilateral plaque vulnerability and clinical risk for postoperative cardiovascular risk stratification.

Background: Left ventricular hemodynamic forces (LV HDFs) are altered in myocardial dysfunction. While infarct location and size influence post-ST-segment elevation myocardial infarction (STEMI) remodeling, their specific effects on HDFs remain unclear. This study investigated how infarct location and size impact left ventricular HDFs and assessed HDFs’ prognostic value for predicting subsequent heart failure (HF) in STEMI patients. Methods: In this retrospective study, 275 STEMI patients underwent cardiac magnetic resonance (CMR) 3–7 days after primary percutaneous coronary intervention. HDFs were derived from routine CMR cine images. Patients were stratified by infarct location (anterior vs. non-anterior) and median infarct size (IS). Key parameters—apical–basal (A-B) and lateral-septal (L-S) forces, their ratio, force direction angle (φ), and force reversal during systolic–diastolic transition—were compared. The primary endpoint was new-onset congestive HF during follow-up. Results: Compared to non-anterior STEMI, anterior STEMI showed significantly impaired A-B and L-S HDFs throughout the cardiac cycle (all p < 0.05) and was independently associated with force reversal (OR 2.31, 95% CI: 1.05–5.07). Larger IS correlated with reduced A-B HDFs and altered force distribution (increased L-S/A-B ratio, decreased φ). Force reversal predicted HF (HR: 2.10, 95% CI: 1.22–3.62) and provided incremental prognostic value beyond left ventricular ejection fraction (LVEF) alone (C-statistic: LVEF 0.680 vs. LVEF + force reversal 0.770, p = 0.034). Conclusions: Anterior infarction causes global HDF impairment and force reversal, while larger IS primarily reduces longitudinal forces and disrupts force distribution. Force reversal predicts subsequent HF and enhances prognostic value beyond LVEF.

To develop a DeepSurv model for predicting survival in pancreatic adenocarcinoma patients, evaluating the benefit of surgical versus non-surgical treatment across different stages, including stage IV subcategories. Clinical data were extracted from the SEER database (2000-2020). Patients were randomly divided into a model-building group and an experimental group. The DeepSurv model was trained and hyperparameter-optimized. Simulated paired data were created by switching treatment status. Predicted survival rates were compared using generalized estimating equations. SHAP values analyzed variable importance.The study included 16,068 patients. The final model achieved a C-index of 0.85. Surgical treatment yielded higher survival rates than non-surgical across all stages (p<0.001), though the benefit diminished in advanced stages. For stage IV, surgery improved survival in T1-3 and N0 stages (p<0.001) but not in T4 and N1. SHAP analysis ranked M stage as the most significant predictor of mortality, followed by T stage, overall stage, and surgical status. M1 metastasis was associated with a 14% increased mortality risk, while surgery reduced risk by 11%.Surgery reduces mortality across stages, with declining efficacy in advanced disease. For stage IV patients, surgery is beneficial except for those with T4 or N1 disease. Combining DeepSurv with SHAP analysis facilitates individualized prediction of surgical survival benefits.

OBJECTIVE:To investigate the association between obstructive sleep apnea (OSA) and coronary inflammation measured by fat attenuation index (FAI), and to examine potential gender differences in this relationship. METHODS:We consecutively enrolled patients who underwent both sleep study and coronary computed tomography angiography (CTA). Multivariable linear regression models were constructed to assess the relationship between objective OSA severity metrics- including moderate-to-severe OSA, apnea-hypopnea index (AHI), and oxygen desaturation indices- and coronary FAI. Stratified analyses by sex were performed to evaluate potential gender-specific differences in this association. Additionally, we explored whether moderate-to-severe OSA correlated with elevated coronary inflammation (FAI > -70.1 Hounsfield units). RESULTS:A total of 526 patients (72.1 % male; mean age 54.7 ± 11.2 years) were finally analyzed. Of these, 307 (58.4 %) patients had moderate-to-severe OSA. Compared to patients with no or mild OSA, those with moderate-to-severe OSA exhibited significantly elevated FAI value in the right coronary artery (RCA) (P < 0.001). In contrast, no differences were observed in the left anterior descending artery (LAD) (P = 0.523) or left circumflex artery (LCX) (P = 0.379). The association between moderate-to-severe OSA and FAI in the RCA remained significant after multivariable adjustment (Model 1: β ± SE = 5.940 ± 0.680, P < 0.001; Model 2: β ± SE = 5.941 ± 0.694, P < 0.001). Furthermore, FAI_RCA showed significant correlations with AHI (P < 0.001), ODI (P < 0.001), and lowest SpO2 (P < 0.001), but not T90 (P = 0.429), consistently across gender subgroups. Moderate-to-severe OSA was correlated with 5.33-fold increased odds of high FAI_RCA (95 % CI: 2.05-13.86, P = 0.001). CONCLUSION:OSA severity was significantly associated with FAI around the RCA distribution, suggesting increased risk of coronary inflammation.

BackgroundUncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accuracy of AI systems in identifying and measuring lung nodules on chest computed tomography (CT) scans remains unclear, which requires further evaluation. ObjectiveThis study aimed to evaluate the impact of an AI-assisted diagnostic system on the diagnostic efficiency of radiologists. It specifically examined the report modification rates and missed and misdiagnosed rates of junior radiologists with and without AI assistance. MethodsWe obtained effective data from 12,889 patients in 2 tertiary hospitals in Beijing before and after the implementation of the AI system, covering the period from April 2018 to March 2022. Diagnostic reports written by both junior and senior radiologists were included in each case. Using reports by senior radiologists as a reference, we compared the modification rates of reports written by junior radiologists with and without AI assistance. We further evaluated alterations in lung nodule detection capability over 3 years after the integration of the AI system. Evaluation metrics of this study include lung nodule detection rate, accuracy, false negative rate, false positive rate, and positive predictive value. The statistical analyses included descriptive statistics and chi-square, Cochran-Armitage, and Mann-Kendall tests. ResultsThe AI system was implemented in Beijing Anzhen Hospital (Hospital A) in January 2019 and Tsinghua Changgung Hospital (Hospital C) in June 2021. The modification rate of diagnostic reports in the detection of lung nodules increased from 4.73% to 7.23% (χ21=12.15; P<.001) at Hospital A. In terms of lung nodule detection rates postimplementation, Hospital C increased from 46.19% to 53.45% (χ21=25.48; P<.001) and Hospital A increased from 39.29% to 55.22% (χ21=122.55; P<.001). At Hospital A, the false negative rate decreased from 8.4% to 5.16% (χ21=9.85; P=.002), while the false positive rate increased from 2.36% to 9.77% (χ21=53.48; P<.001). The detection accuracy demonstrated a decrease from 93.33% to 92.23% for Hospital A and from 95.27% to 92.77% for Hospital C. Regarding the changes in lung nodule detection capability over a 3-year period following the integration of the AI system, the detection rates for lung nodules exhibited a modest increase from 54.6% to 55.84%, while the overall accuracy demonstrated a slight improvement from 92.79% to 93.92%. ConclusionsThe AI system enhanced lung nodule detection, offering the possibility of earlier disease identification and timely intervention. Nevertheless, the initial reduction in accuracy underscores the need for standardized diagnostic criteria and comprehensive training for radiologists to maximize the effectiveness of AI-enabled diagnostic systems.

BACKGROUND:To evaluate the associations of three atherosclerosis indexes with stroke in a population aged 65 years and older. METHODS:A sample was obtained from wave 2011 to wave 2015 of the China Health and Retirement Longitudinal Study. Multivariate logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (CIs) for stroke in the quartiles of three atherosclerosis indexes, and restricted cubic splines were constructed. RESULTS:Four hundred and fifty-four of the 21,913 eligible participants had stroke. After multivariate adjustments and with respect to the lowest quartiles, the ORs (95% CIs) of stroke in the highest quartiles of the atherogenic index of plasma (AIP), the Castelli risk index I (CRI-I), and the Castelli risk index II (CRI-II) were 1.35 (0.99-1.83), 1.52 (1.13-2.06), and 1.40 (1.05-1.86), respectively. When assessed as a continuous exposure, per-unit increases in the AIP, CRI-I, and CRI-II were independently associated with a 49% (OR: 1.49, 95% CI: 1.07-2.08), 6% (OR: 1.06, 95% CI: 1.02-1.11), and 14% (OR: 1.14, 95% CI: 1.03-1.27) increase in the risk of stroke, respectively. CONCLUSION:The three atherosclerosis indexes studied-the AIP, CRI-I, and CRI-II-were found to be predictors of stroke in a Chinese population.

RATIONALE AND OBJECTIVES:This study aims to determine the long-term prognostic value of coronary hyper-intensity plaques and left ventricular (LV) myocardial strain for major adverse cardiac events (MACEs). MATERIALS AND METHODS:The study prospectively recruited 71 patients with acute coronary syndrome (ACS). All patients underwent CMR before PCI to determine the plaque-to-myocardium signal intensity ratio and LV strains. The MACEs included all-cause death, reinfarction, and new congestive heart failure. Mann-Whitney U test and chi-square test to compare patients with and without MACE, Kaplan-Meier survival analysis, Cox proportional hazards regression and C-statistics to assess prognosis, Receiver-operating characteristic (ROC) curve analysis to define the cutoff value. A P value of < 0.05 was considered statistically significant. RESULTS:Cox proportional hazard analysis showed that plaque-to-myocardium signal intensity ratio and global longitudinal strain (GLS) were independently associated with MACEs (plaque-to-myocardium signal intensity ratio: hazard ratio (HR) 2.80, 95% CI, 1.25-6.26, P = 0.01; GLS: HR1.21, 95% CI, 1.07-1.38, P＜0.01). ROC showed that a plaque-to-myocardium signal intensity ratio of 1.65 and a GLS of -10% were the best cutoff values for MACEs. The C-statistic values for plaque-to-myocardium signal intensity ratio, GLS, and plaque-to-myocardium signal intensity ratio+GLS for MACEs were 0.691, 0.792, and 0.825, respectively. Compared to GLS alone, the addition of plaque-to-myocardium signal intensity ratio to GLS increased the net reclassification index by 0.664 (P = 0.017). CONCLUSION:Plaque-to-myocardium signal intensity ratio and GLS were significantly associated with MACEs. Adding plaque-to-myocardium signal intensity ratio to GLS substantially improved the prediction for MACEs. Our findings indicate that plaque-to-myocardium signal intensity ratio combined with GLS provides incremental prognostic value for MACEs.

Inflammation induced by activated macrophages within vulnerable atherosclerotic plaques (VAPs) constitutes a significant risk factor for plaque rupture. Translocator protein (TSPO) is highly expressed in activated macrophages. This study investigated the effectiveness of TSPO radiotracers, 18F-FDPA, in detecting VAPs and quantifying plaque inflammation in rabbits. 18 New Zealand rabbits were divided into 3 groups: sham group A, VAP model group B, and evolocumab treatment group C. 18F-FDPA PET/CTA imaging was performed at 12, 16, and 24 weeks in all groups. Optical coherence tomography (OCT) was performed on the abdominal aorta at 24 weeks. The VAP was defined through OCT images, and ex vivo aorta PET imaging was also performed at 24 weeks. The SUVmax and SUVmean of 18F-FDPA were measured on the target organ, and the target-to-background ratio (TBRmax) was calculated as SUVmax/SUVblood pool. The arterial sections of the isolated abdominal aorta were analyzed by HE staining, CD68 and TSPO immunofluorescence staining, and TSPO Western blot. The results showed that at 24 weeks, the plaque TBRmax of 18F-FDPA in group B was significantly higher than in groups A and C. Immunofluorescence staining of CD68 and TSPO, as well as Western blot, confirmed the increased expression of macrophages and TSPO in the corresponding regions of group B. HE staining revealed an increased presence of the lipid core, multiple foam cells, and inflammatory cell infiltration in the area with high 18F-FDPA uptake. This indicates a correlation between 18F-FDPA uptake, inflammation severity, and VAPs. The TSPO-targeted tracer 18F-FDPA shows specific uptake in macrophage-rich regions of atherosclerotic plaques, making it a valuable tool for assessing inflammation in VAPs.

Objectives:This study assesses the perceptions and attitudes of Chinese radiologists concerning the application of artificial intelligence (AI) in the diagnosis of lung nodules. Material and Methods:An anonymous questionnaire, consisting of 26 questions addressing the usability of AI systems and comprehensive evaluation of AI technology, was distributed to all radiologists affiliated with Beijing Anzhen Hospital and Beijing Tsinghua Changgung Hospital. The data collection was conducted between July 19, and 21, 2023. Results:Of the 90 respondents, the majority favored the AI system's convenience and usability, reflected in "good" system usability scale (SUS) scores (Mean ± standard deviation [SD]: 74.3 ± 11.9). General usability was similarly well-received (Mean ± SD: 76.0 ± 11.5), while learnability was rated as "acceptable" (Mean ± SD: 67.5 ± 26.4). Most radiologists noted increased work efficiency (Mean Likert scale score: 4.6 ± 0.6) and diagnostic accuracy (Mean Likert scale score: 4.2 ± 0.8) with the AI system. Views on AI's future impact on radiology careers varied (Mean ± SD: 3.2 ± 1.4), with a consensus that AI is unlikely to replace radiologists entirely in the foreseeable future (Mean ± SD: 2.5 ± 1.1). Conclusion:Radiologists at two leading Beijing hospitals generally perceive the AI-assisted lung nodule diagnostic system positively, citing its user-friendliness and effectiveness. However, the system's learnability requires enhancement. While AI is seen as beneficial for work efficiency and diagnostic accuracy, its long-term career implications remain a topic of debate.

Background: The gut and biliary microbiota are important components of the complex microecology system in the human body. However, it is often difficult to obtain bile in clinical practice to manage gallstone diseases, warranting further microbiota research to evaluate the relationship between biliary microbiota and gallstone formation. Aims: We aimed to characterize the diversity and alterations of biliary and gut microbiota in patients with gallstones and analyze their possible correlations to gallstone formation. Methods: We collected gallstones, bile, gallbladder mucosa, and feces from 21 patients with gallstone disease during operation and fecal samples from 20 healthy subjects without gallstones. We performed high-throughput sequencing of the V3-V4 regions of the 16S rRNA gene in the gallstone and control groups and analyzed the final optimization sequence. Results: We identified a total of 23,427 operational taxonomic units. Achromobacter (P = 0.010), Faecalibacterium (P = 0.042), and Lachnospira (P = 0.011) were significantly reduced, while Enterococcus (P = 0.001) was increased in the gallstone group. The diversity and composition between the biliary and gut microbiota in gallstone patients had statistical differences. The diversity of gut microbiota was significantly higher than that of biliary microbiota (P < 0.05). In addition, linear discriminant analysis (LDA) >4 indicated that the characteristic flora was specific to five samples. Prevotella and Proteobacteria had LDA values >4 in the feces and both bile and gallbladder mucosa, respectively, of patients with gallstones. Conclusion: The biliary and gut microbiota of patients with gallstones displayed bacterial heterogeneity. Prevotella and Proteobacteria may serve as biomarkers for dysbacteriosis in patients with gallstones, suggesting that alterations of biliary and gut microbiota are involved in the formation of gallstones. This study highlights the potential application of fecal microbiota transplantation technology in the treatment of gallstone diseases. Relevance for Patients: Microecology of the digestive tract is closely related to the formation of gallstones, providing new ideas for the prevention and treatment of patients with gallstones.

Background:Obstructive severe acute biliary pancreatitis (SABP) is a clinical emergency with a high rate of mortality that can be alleviated by endoscopic retrograde cholangiopancreatography (ERCP) and percutaneous transhepatic cholangial drainage (PTCD) selectively. However, the optimal timing of ERCP and PTCD requires elucidation.Aim:The aim of this study was to evaluate outcome parameters in patients with SABP subjected to ERCP and PTCD compared to SABP patients who were not subjected to any form of invasive intervention.Methods:A total of 62 patients with obstructive SABP who had been treated from July 2013 to July 2019 were included in this retrospective case-control study and stratified into a PTCD group (N = 22), ERCP group (N = 24), and conservative treatment group (N = 16, control). Patients in the PTCD and ERCP groups were substratified into early (≤72 h) and delayed (>72 h) treatment groups based on the timing of the intervention after diagnosis. Clinical chemistry, hospitalization days, liver function, abdominal pain, and complications were determined to assess the treatment efficacy and safety of each modality and to establish the optimal timing for PTCD and ERCP.Results:The average hospitalization time, time to abdominal pain relief, and time to normalization of hematological and clinical chemistry parameters (leukocyte count, amylase, alanine transaminase [ALT], and total bilirubin [TBiL]) were shorter in the PTCD and ERCP groups compared to the conservative treatment group (p < 0.05). The average hospitalization time in the ERCP group (16.7 ± 4.0 d) was shorter compared to the PTCD group (19.6 ± 4.3 d) (p < 0.05). Compared to the conservative treatment group (62.5%), there were more complications in patients treated with ERCP and PTCD (p < 0.05). In the early ERCP group, the average hospitalization time (13.9 ± 3.3 d) and the time to normalization of leukocyte count (6.3 ± 0.9 d) and TBiL (9.1 ± 2.0 d) were lower than in the delayed ERCP group (18.6 ± 4.1 d, 9.9 ± 2.4 d, 11.8 ± 2.9 d, respectively) and early PTCD group (16.4 ± 3.7 d, 8.5 ± 2.1 d, 10.9 ± 3.1 d, respectively) (p < 0.05). In the delayed ERCP group, the average hospitalization time (18.6 ± 4.1 d) and ALT recovery time (12.2 ± 2.6 d) were lower than in the delayed PTCD group (21.9 ± 4.3 d and 14.9 ± 3.9 d, respectively) (p < 0.05).Conclusions:ERCP and PTCD effectively relieve SABP-associated biliary obstruction with comparable overall incidence of complications. It is recommended that ERCP is performed within 72 h after diagnosis; and PTCD drainage may be considered an alternative approach in cases where patients are unable or unwilling to undergo ERCP, or when ERCP is unsuccessful.Relevance for Patients:ERCP and PTCD in patients with obstructive SABP can resolve biliary obstruction and delay progression of the disease. Performing ERCP and PTCD within 72 h (i.e., optimal treatment time window) can be beneficial to patients, especially in terms of post-operative recovery. Visual biliary endoscopy (oral or percutaneous transhepatic) may be used for concomitant therapeutic interventions in the biliary system.

Background: The plaque imaging findings associated with the stent expansion rate (SER) of the carotid artery are not well known. The purpose of this study was to investigate the imaging findings associated with SER. Methods: It was a retrospective investigation. Based on the kind of carotid stents used, retrospective data from 89 patients who had carotid artery stenting (CAS) for atherosclerotic carotid stenosis were gathered and divided into two groups: open-cell stents and closed-cell stents. Patients underwent preoperative carotid high-resolution magnetic resonance vessel wall imaging (HR-VWI). Use HR-VWI to quantitatively evaluate carotid wall thickness and plaque components. Calculate SER using digital subtraction angiography (DSA). All patients' baseline and HR-VWI imaging features were retrospectively analyzed. Simple and multivariable linear regression analysis was used to determine the imaging findings associated with SER of open-cell and closed-cell stents. Results: A total of 89 patients (mean age, 70±8 years; 69 men) were included in the final analysis. Among 89 patients, 35 patients were treated with open-cell stents. Fifty-four patients were treated with closed-cell stents. In the open-cell stents group, the Maximum single-slice calcification circumference score, maximum wall thickness (WTmax), and total calcification location score with P<0.10 in the simple linear regression analysis were included in the multivariable linear regression analysis. The results of the multivariable linear regression revealed that only the Maximum single-slice calcification circumference score (β=−9.35; 95% CI: −18.15 to −0.56; P=0.03) was associated with SER of open-cell stents. In the closed-cell stents group, the Maximum single-slice calcification circumference score, WTmax, maximum area percentage of calcification, calcification volume, and total calcification location score with P<0.10 in the simple linear regression analysis were included in the multivariable linear regression analysis. The results of the multivariable linear regression revealed that the Maximum area percentage of calcification (β=−0.67; 95% CI: −1.29 to −0.05; P=0.03), Maximum single-slice calcification circumference score (β=−8.43; 95% CI: −13.36 to −3.49; P=0.001) and total calcification location score (β=−0.37; 95% CI: −1.08 to 0.09; P=0.02) were associated with SER of closed-cell stents. Conclusions: Calcified plaques are associated with SER of the carotid artery. Calcification circumference correlates with SER of open-cell stents. Calcification circumference, calcification area, and calcification location are related to SER of closed-cell stents, which may provide a new consideration for clinicians when choosing carotid artery stents.