Predicting major adverse cardiovascular events within 3 years by optimization of radiomics model derived from pericoronary adipose tissue on coronary computed tomography angiography: a case-control study.

BACKGROUND: Coronary inflammation induces changes in pericoronary adipose tissue (PCAT) can be detected by coronary computed tomography angiography (CCTA). Our aim was to investigate whether different PCAT radiomics model based on CCTA could improve the prediction of major adverse cardiovascular events (MACE) within 3 years. METHODS: This retrospective study included 141 consecutive patients with MACE and matched to patients with non-MACE (n = 141). Patients were randomly assigned into training and test datasets at a ratio of 8:2. After the robust radiomics features were selected by using the Spearman correlation analysis and the least absolute shrinkage and selection operator, radiomics models were built based on different machine learning algorithms. The clinical model was then calculated according to independent clinical risk factors. Finally, an overall model was established using the radiomics features and the clinical factors. Performance of the models was evaluated for discrimination degree, calibration degree, and clinical usefulness. RESULTS: The diagnostic performance of the PCAT model was superior to that of the RCA-model, LAD-model, and LCX-model alone, with AUCs of 0.723, 0.675, 0.664, and 0.623, respectively. The overall model showed superior diagnostic performance than that of the PCAT-model and Cli-model, with AUCs of 0.797, 0.723, and 0.706, respectively. Calibration curve showed good fitness of the overall model, and decision curve analyze demonstrated that the model provides greater clinical benefit. CONCLUSION: The CCTA-based PCAT radiomics features of three major coronary arteries have the potential to be used as a predictor for MACE. The overall model incorporating the radiomics features and clinical factors offered significantly higher discrimination ability for MACE than using radiomics or clinical factors alone.

Coronary artery segmentation in CCTA images based on multi-scale feature learning.

BACKGROUND: Coronary artery segmentation is a prerequisite in computer-aided diagnosis of Coronary Artery Disease (CAD). However, segmentation of coronary arteries in Coronary Computed Tomography Angiography (CCTA) images faces several challenges. The current segmentation approaches are unable to effectively address these challenges and existing problems such as the need for manual interaction or low segmentation accuracy. OBJECTIVE: A Multi-scale Feature Learning and Rectification (MFLR) network is proposed to tackle the challenges and achieve automatic and accurate segmentation of coronary arteries. METHODS: The MFLR network introduces a multi-scale feature extraction module in the encoder to effectively capture contextual information under different receptive fields. In the decoder, a feature correction and fusion module is proposed, which employs high-level features containing multi-scale information to correct and guide low-level features, achieving fusion between the two-level features to further improve segmentation performance. RESULTS: The MFLR network achieved the best performance on the dice similarity coefficient, Jaccard index, Recall, F1-score, and 95% Hausdorff distance, for both in-house and public datasets. CONCLUSION: Experimental results demonstrate the superiority and good generalization ability of the MFLR approach. This study contributes to the accurate diagnosis and treatment of CAD, and it also informs other segmentation applications in medicine.

Vulnerable plaque of the petrous internal carotid artery in embolic stroke of undetermined source.

BACKGROUND AND PURPOSE: The association between nonstenotic plaque at the petrous internal carotid artery (ICA) and embolic stroke of undetermined source (ESUS) remains unknown. We aimed to test the hypothesis that the presence of a larger build-up of petrous plaque is more prevalent in the ipsilateral versus the contralateral side among ESUS patients without plaque in the intracranial and proximal ICA. METHODS: From a total of 243 patients with ESUS and 160 patients with small-vessel disease (SVD) without proximal ICA plaque, we enrolled 88 ESUS and 103 SVD patients without ipsilateral nonstenotic intracranial and proximal ICA plaque in the present study. Targeting the petrous segment of the ICA on two sides, plaque burden including plaque thickness, lumen area, vessel area, wall area, and percentage of luminal stenosis, and composition features (presence/absence of the ruptured fibrous cap, ulcer plaque, thrombus, discontinuity of plaque surface [DPS], intraplaque hemorrhage and complicated plaque) were assessed by high-resolution magnetic resonance imaging. RESULTS: We found a higher prevalence of petrous plaque thickness ≥3.5 mm ipsilateral versus contralateral to the stroke (25/88 [28.4%] vs. 12/88 [13.6%], odds ratio [OR] 3.60, 95% confidence interval [CI] 1.34-9.70), but this imbalance was not seen in SVD. In patients with plaque thickness ≥3.5 mm, the presence of DPS (OR 4.05, 95% CI 1.11-14.78) and complicated plaque (OR 5.00, 95% CI 1.10-22.82) was more closely related to an index ESUS, a finding that was not evident in the subgroup with petrous plaque <3.5 mm (p for interaction = 0.027). CONCLUSIONS: The present study provided the first evidence supporting a potential etiological role of vulnerable petrous plaque in ESUS.

A Comparative Study of Clinical and Aortic Morphological Characteristics between Bovine Aortic Arch and Normal Aortic Arch in Patients with Acute Type B Aortic Dissection.

INTRODUCTION: The purpose of this study was to analyze the difference in clinical and aortic morphological features between the bovine aortic arch and normal aortic arch in patients with acute type B aortic dissection (aTBAD). METHODS: A total of 133 patients diagnosed with aTBAD were retrospectively collected. Based on aortic arch morphology, they were divided into the bovine aortic arch group (n = 20) and the normal aortic arch group (n = 113). Aortic morphological features were assessed on computed tomographic angiography. Clinical and aortic morphological features were then compared between the bovine aortic arch and normal aortic arch groups. RESULTS: Patients in the bovine aortic arch group were significantly younger and with higher weight and BMI than the normal aortic arch group (p < 0.001, p = 0.045, and p = 0.016, respectively). The total aortic length in the bovine aortic arch group was significantly shorter than that in the normal aortic arch group (p = 0.039). The tortuosity of descending thoracic aorta, the tortuosity of descending aorta, and the angulation of aortic arch were significantly lower in the bovine aortic arch group (p = 0.004, p = 0.015, and p = 0.023, respectively). The width of descending aorta, the height of aorta arch, and the angle of ascending aorta were significantly smaller in the bovine aortic arch group (p = 0.045, p = 0.044, and p = 0.042, respectively). CONCLUSION: When the aTBAD occurred, patients with bovine aortic arch were prone to be younger and with higher BMI than those with normal aortic arch. The aortic curvature and the total aortic length were lower in patients with bovine aortic arch.

Relationship between quantitative epicardial adipose tissue based on coronary computed tomography angiography and coronary slow flow.

BACKGROUND: The purpose of this study was to explore the relationship between quantitative epicardial adipose tissue (EAT) based on coronary computed tomography angiography (CCTA) and coronary slow flow (CSF). METHODS: A total of 85 patients with < 40% coronary stenosis on diagnostic coronary angiography were included in this retrospective study between January 2020 and December 2021. A semi-automatic method was developed for EAT quantification on CCTA images. According to the thrombolysis in myocardial infarction flow grade, the patients were divided into CSF group (n = 39) and normal coronary flow group (n = 46). Multivariate logistic regression was used to explore the relationship between EAT and CSF. Receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic value of EAT in CSF. RESULTS: EAT volume in the CSF group was significantly higher than that of the normal coronary flow group (128.83± 21.59 mL vs. 101.87± 18.56 mL, P < 0.001). There was no significant difference in epicardial fat attenuation index between the two groups (P > 0.05). Multivariate logistic regression analysis showed that EAT volume was independently related to CSF [odds ratio (OR) = 4.82, 95% confidence interval (CI): 3.06-7.27, P < 0.001]. The area under ROC curve for EAT volume in identifying CSF was 0.86 (95% CI: 0.77-0.95). The optimal cutoff value of 118.46 mL yielded a sensitivity of 0.80 and a specificity of 0.94. CONCLUSIONS: Increased EAT volume based on CCTA is strongly associated with CSF. This preliminary finding paves the way for future and larger studies aimed to definitively recognize the diagnostic value of EAT in CSF.

The characteristics of intracranial plaques of unilateral, anterior circulation embolic stroke of undetermined source: An analysis of different subtypes based on high-resolution imaging.

BACKGROUND AND PURPOSE: The aim was to investigate the characteristics of non-stenotic intracranial plaque (NSIP) in embolic stroke of undetermined source (ESUS) subtypes by high-resolution magnetic resonance imaging. METHODS: Consecutive patients with ESUS who were mandatory for high-resolution magnetic resonance imaging were retrospectively enrolled. Based on the location and arterial supply of the infarct, the ESUS were categorized into three types: cortical ESUS, subcortical ESUS and mixed ESUS. The NSIP parameters including plaque location, morphology (plaque distribution, remodeling index and plaque burden) and composition (thick fibrous cap, discontinuity of plaque surface, intraplaque hemorrhage and complicated plaque) were evaluated amongst the subtypes. RESULTS: Of 243 patients, there were 87 (35.8%) cortical ESUS, 127 (52.3%) subcortical ESUS and 29 (11.9%) mixed ESUS. Significant differences were found in plaque location (p < 0.001), plaque quadrant (p < 0.001), remodeling index (p < 0.001), plaque burden (p < 0.001), discontinuity of plaque surface (p < 0.001), intraplaque hemorrhage (p = 0.001) and complicated plaque (p < 0.001) of ipsilateral NISP amongst the different ESUS subtypes, except for fibrous cap (p = 0.135). However, no differences were found amongst contralateral NISP. In addition, the clinical characteristics of the differences between ESUS subtypes were striking, including age (p = 0.004), initial National Institutes of Health Stroke Scale (p < 0.001), coronary artery disease (p = 0.039), serum urea (p = 0.011) and creatinine (p = 0.002). CONCLUSION: This is the first report of significantly heterogeneous characteristics of ipsilateral NSIP and clinical findings amongst ESUS subtypes, which may suggest their different underlying mechanisms.

Relationship between epicardial fat volume on cardiac CT and atherosclerosis severity in three-vessel coronary artery disease: a single-center cross-sectional study.

BACKGROUND: The ideal treatment strategy for stable three-vessel coronary artery disease (CAD) patients are difficult to determine and for patients undergoing conservative treatment, imaging evidence of coronary atherosclerotic severity progression remains limited. Epicardial fat volume (EFV) on coronary CT angiography (CCTA) has been considered to be associated with coronary atherosclerosis. Therefore, this study aims to evaluate the relationship between EFV level and coronary atherosclerosis severity in three-vessel CAD. METHODS: This retrospective study enrolled 252 consecutive patients with three-vessel CAD and 252 normal control group participants who underwent CCTA between January 2018 and December 2019. A semi-automatic method was developed for EFV quantification on CCTA images, standardized by body surface area. Coronary atherosclerosis severity was evaluated and scored by the number of coronary arteries with ≥ 50% stenosis on coronary angiography. Patients were subdivided into groups on the basis of lesion severity: mild (score = 3 vessels, n = 85), moderate (3.5 vessels ≤ score < 4 vessels, n = 82), and severe (4 vessels ≤ score ≤ 7 vessels, n = 85). The independent sample t-test, analysis of variance, and logistic regression analysis were used to evaluate the associations between EFV level and severity of coronary atherosclerosis. RESULTS: Compared with normal controls, three-vessel CAD patients had significantly higher EFV level (65 ± 22 mL/m2 vs. 48 ± 19 mL/m2; P < 0.001). In patients with three-vessel CAD, there was a progressive decline in EFV level as the score of coronary atherosclerosis severity increased, especially in those patients with a body mass index (BMI) ≥ 25 kg/m2 (75 ± 21 mL/m2 vs. 72 ± 22 mL/m2 vs. 62 ± 17 mL/m2; P < 0.05). Multivariable regression analysis showed that both BMI (OR 3.40, 95% CI 2.00-5.78, P < 0.001) and the score of coronary atherosclerosis severity (OR 0.49, 95% CI 0.26-0.93, P < 0.05) were independently related to the change of EFV level. CONCLUSION: Three-vessel CAD patients do have higher EFV level than the normal controls. While, there may be an inverse relationship between EFV level and the severity of coronary atherosclerosis in patients with three-vessel CAD.

Hyperdense middle cerebral artery sign predicts favorable outcome after decompressive craniectomy in patients with malignant middle cerebral artery infarction.

BACKGROUND: Malignant middle cerebral artery infarction (MMI) is a life-threatening cerebral vascular event. Early decompressive craniectomy (DC) has proven to be an effective treatment strategy. However, the ideal candidate for DC continues to be debated. PURPOSE: To investigate whether a hyperdense middle cerebral artery sign (HMCAS) provides prognostic value after DC in patients with MMI. MATERIAL AND METHODS: We reviewed clinical information and radiological parameters on computed tomography of 42 patients with MMI who underwent DC. Functional outcome was assessed according to the modified Rankin scale (mRS) at three months as follows: favorable outcome (mRS ≤ 4) versus unfavorable outcome (mRS > 4). Logistic regression analysis was used to identify predictors of functional outcome after DC in patients with MMI. RESULTS: Age (odds ratio [OR] = 0.87; 95% confidence interval [CI] = 0.78-0.97; P = 0.014) and HMCAS (OR = 7.40; 95% CI = 1.35-40.48; P = 0.021) were associated with functional outcome. The area under the receiver operating characteristic curve for predicting favorable outcome using the combination of age and HMCAS was 0.882, and the sensitivity and specificity were 0.947 and 0.696, respectively. CONCLUSION: Patients with MMI with HMCAS, as well as younger patients, often showed a favorable outcome after DC in this study.

Prominent deep medullary veins: a predictive biomarker for stroke risk from transient ischemic attack?

Background Deep medullary veins (DMVs) are a biomarker of severity and prognosis in patients with acute cerebral infarction. However, their clinical significance remains unclear in patients with transient ischemic attack (TIA). Purpose To determine whether prominent deep medullary veins (PDMVs) are a predictive biomarker for stroke risk after TIA. Material and Methods Clinical and imaging data of 49 patients with TIA and 49 sex- and age-matched controls were studied. PDMVs were defined as DMVs with a score of 3 (TDMVs) or asymmetric DMVs (ADMVs), and the relationship between PDMVs and clinical features was analyzed. The DMV score based on susceptibility weighted imaging (SWI) ranged from 0 (not visible) to 3 (very prominent) and was calculated for both hemispheres separately. A different score in each hemisphere was defined as ADMVs and an equal score was defined as symmetric DMVs. The asymmetry and score of DMVs were compared between the two groups and with respect to the time from TIA onset to imaging analysis. Results Agreement between neuroradiologists for the DMV asymmetry/score on SWI was excellent. The frequency of ADMVs and TDMVs was significantly higher in patients with TIA than controls ( P < 0.05). The patients showed no correlation between the time from TIA onset to imaging and the DMV asymmetry/score ( P > 0.05); PDMVs were not correlated with age, blood pressure, or diabetes. However, PDMVs were associated with the ABCD2 score (≥4), clinical symptoms, and duration of TIA (≥10 min). Conclusion Prominent deep medullary veins is a predictive biomarker for the risk of stroke in many patients having suffered from TIA.

Safety of gadobutrol in over 23,000 patients: the GARDIAN study, a global multicentre, prospective, non-interventional study.

OBJECTIVES: To investigate the safety and tolerability of gadobutrol at the recommended dose in patients requiring contrast-enhanced magnetic resonance imaging/angiography (MRI/MRA) in the routine setting. METHODS: GARDIAN prospectively enrolled 23,708 patients undergoing routine gadobutrol-enhanced MRI/MRA for approved indications at 272 study centres in Europe, Asia, North America, and Africa and monitored for adverse events. RESULTS: Median gadobutrol dose was 0.11 mmol/kg body weight. The overall incidence of adverse drug reactions (ADRs) was 0.7 % (n = 170 patients), with similar incidences in patients with renal impairment or cardiac disease, from different geographic regions and in different gadobutrol dose groups. Patients at risk for contrast media reaction had an ADR incidence of 2.5 %. Five patients (0.02 %) experienced serious adverse events, four were drug-related. One patient experienced a fatal anaphylactoid shock, assessed to be related to injection of gadobutrol. The contrast quality of gadobutrol-enhanced images was rated by treating physicians as good or excellent in 97 % cases, with similar ratings in all patient subgroups and indications. CONCLUSIONS: The GARDIAN study shows that gadobutrol at the recommended dose is well tolerated across a large, diverse patient population. KEY POINTS: • Gadobutrol at recommended dose shows low rates of adverse drug reactions • Gadobutrol demonstrates a uniform safety profile across diverse patient groups • Gadobutrol provides excellent contrast quality in routine practice.

Prognostic value of microRNA-100 in esophageal squamous cell carcinoma.

BACKGROUND: MicroRNA-100 (miR-100) has been demonstrated to be implicated in tumorigenesis and tumor progression of human esophageal squamous cell carcinoma (ESCC). However, its expression patterns in ESCC are controversial and its prognostic value in this malignancy has not been fully elucidated. The aim of this study was to investigate the expression and clinical significance of miR-100 in ESCC. MATERIALS AND METHODS: Real-time quantitative reverse transcription polymerase chain reaction (RT-PCR) was performed to detect expression levels of miR-100 in 120 self-paired specimens of ESCC and adjacent normal esophageal tissues. The associations of miR-100 expression with clinicopathologic features, locoregional progression-free survival (LPFS), distant progression-free survival (DPFS), and overall survival (OS) of patients with ESCC were statistically analyzed. RESULTS: Compared with adjacent normal esophageal tissues, the expression levels of miR-100 in ESCC were significantly decreased (normal versus ESCC: 3.53 ± 1.22 versus 1.89 ± 0.38, P <0.001). Additionally, low miR-100 expression in ESCC tissues was significantly associated with the advanced clinical stage (P = 0.008), the presence of distant metastasis (P = 0.008), and the great depth of invasion (P = 0.02). Moreover, univariate analysis revealed that low miR-100 expression was associated with poor LPFS, DPFS, and OS. In multivariate analysis, miR-100 expression was identified as an independent prognostic factor for all LPFS, DPFS, and OS. CONCLUSIONS: These findings show the reduced expression of miR-100 in human ESCC tissues and suggest a crucial role of its downregulation in ESCC progression and prognosis. More interestingly, the detection of miR-100 expression may be used to efficiently screen those ESCC patients who would benefit from radiotherapy.

Papillary Muscle Infarction by Cardiac MRI in Patients With Mitral Regurgitation.

BACKGROUND: Papillary muscle (PM) infarction (PMI) detected by cardiac magnetic resonance imaging (CMR) is associated with poor outcomes. Whether PM parameters provide more value for mitral regurgitation (MR) management currently remains unclear. Therefore, we examined the prognostic value of PMI using CMR in patients with MR. METHODS: Between March 2018 and July 2023, we retrospectively enrolled 397 patients with MR undergoing CMR. CMR was used to detect PMI qualitatively and quantitively. We also collected baseline clinical, echocardiography, and follow-up data. RESULTS: Of the 397 patients with MR (52.4 ± 13.9 years), 117 (29.5%) were assigned to the PMI group, with 280 (70.5%) in the non-PMI group. PMI was demonstrated more in the posteromedial PM (PM-PM, 98/117) than in the anterolateral PM (AL-PM, 45/117). Compared with patients without PMI, patients with PMI had a decreased AL-PM (41.5 ± 5.4 vs. 45.6 ± 5.3)/PM-PM diastolic length (35.0 ± 5.2 vs. 37.9 ± 4.0), PM-longitudinal strain (LS, 20.4 ± 6.1 vs. 24.9 ± 4.6), AL-PM-LS (19.7 ± 6.8 vs. 24.7 ± 5.6)/PM-PM-LS (21.2 ± 7.9 vs. 25.2 ± 6.0), and increased inter-PM distance (25.7 ± 8.0 vs. 22.7 ± 6.2, all p < 0.001). Multiple logistic regression analyses identified male sex (odds ratio [OR] = 3.65, 95% confidence interval = 1.881-7.081, p < 0.001) diabetes mellitus (OR/95% CI/p = 2.534/1.13-5.68/0.024), AL-PM diastolic length (OR/95% CI/p = 0.841/0.77-0.92/< 0.001), PM-PM diastolic length (OR/95% CI/p = 0.873/0.79-0.964/0.007), inter-PM distance (OR/95% CI/p = 1.087/1.028-1.15/0.003), AL-PM-LS (OR/95% CI/p = 0.892/0.843-0.94/< 0.001), and PM-PM-LS (OR/95% CI/p = 0.95/0.9-0.992/0.021) as independently associated with PMI. Over a 769 ± 367-day follow-up, 100 (25.2%) patients had arrhythmia. Cox regression analyses indicated that PMI (hazard ratio [HR]/95% CI/p = 1.644/1.062-2.547/0.026), AL-PM-LS (HR/95% CI/p = 0.937/0.903-0.973/0.001), and PM-PM-LS (HR/95% CI/p = 0.933/0.902-0.965/< 0.001) remained independently associated with MR. CONCLUSIONS: The CMR-derived PMI and LS parameters improve the evaluation of PM dysfunction, indicating a high risk for arrhythmia, and provide additive risk stratification for patients with MR.

A U-Shaped Network Based on Multi-level Feature and Dual-Attention Coordination Mechanism for Coronary Artery Segmentation of CCTA Images.

PURPOSE: Computed tomography coronary angiography (CCTA) images provide optimal visualization of coronary arteries to aid in diagnosing coronary heart disease (CHD). With the deep convolutional neural network, this work aims to develop an intelligent and lightweight coronary artery segmentation algorithm that can be deployed in hospital systems to assist clinicians in quantitatively analyzing CHD. METHODS: With the multi-level feature fusion, we proposed Dual-Attention Coordination U-Net (DAC-UNet) that achieves automated coronary artery segmentation in 2D CCTA images. The coronary artery occupies a small region, and the foreground and background are extremely unbalanced. For this reason, the more original information can be retained by fusing related features between adjacent layers, which is conducive to recovering the small coronary artery area. The dual-attention coordination mechanism can select valid information and filter redundant information. Moreover, the complementation and coordination of double attention factors can enhance the integrity of features of coronary arteries, reduce the interference of non-coronary arteries, and prevent over-learning. With gradual learning, the balanced character of double attention factors promotes the generalization ability of the model to enhance coronary artery localization and contour detail segmentation. RESULTS: Compared with existing related segmentation methods, our method achieves a certain degree of improvement in 2D CCTA images for the segmentation accuracy of coronary arteries with a mean Dice index of 0.7920. Furthermore, the method can obtain relatively accurate results even in a small sample dataset and is easy to implement and deploy, which is promising. The code is available at: https://github.com/windfly666/Segmentation . CONCLUSION: Our method can capture the coronary artery structure end-to-end, which can be used as a fundamental means for automatic detection of coronary artery stenosis, blood flow reserve fraction analysis, and assisting clinicians in diagnosing CHD.

Pulmonary arteries segmentation from CT images using PA-Net with attention module and contour loss.

BACKGROUND: Pulmonary embolism is a kind of cardiovascular disease that threatens human life and health. Since pulmonary embolism exists in the pulmonary artery, improving the segmentation accuracy of pulmonary artery is the key to the diagnosis of pulmonary embolism. Traditional medical image segmentation methods have limited effectiveness in pulmonary artery segmentation. In recent years, deep learning methods have been gradually adopted to solve complex problems in the field of medical image segmentation. PURPOSE: Due to the irregular shape of the pulmonary artery and the adjacent-complex tissues, the accuracy of the existing pulmonary artery segmentation methods based on deep learning needs to be improved. Therefore, the purpose of this paper is to develop a segmentation network, which can obtain higher segmentation accuracy and further improve the diagnosis effect. METHODS: In this study, the pulmonary artery segmentation performance from the network model and loss function is improved, proposing a pulmonary artery segmentation network (PA-Net) to segment the pulmonary artery region from 2D CT images. Reverse Attention and edge attention are used to enhance the expression ability of the boundary. In addition, to better use feature information, the channel attention module is introduced in the decoder to highlight the important channel features and suppress the unimportant channels. Due to blurred boundaries, pixels near the boundaries of the pulmonary artery may be difficult to segment. Therefore, a new contour loss function based on the active contour model is proposed in this study to segment the target region by assigning dynamic weights to false positive and false negative regions and accurately predict the boundary structure. RESULTS: The experimental results show that the segmentation accuracy of this proposed method is significantly improved in comparison with state-of-the-art segmentation methods, and the Dice coefficient is 0.938 ± 0.035, which is also confirmed from the 3D reconstruction results. CONCLUSIONS: Our proposed method can accurately segment pulmonary artery structure. This new development will provide the possibility for further rapid diagnosis of pulmonary artery diseases such as pulmonary embolism. Code is available at https://github.com/Yuanyan19/PA-Net.

Low (0-5) Alberta Stroke Program Early Computed Tomography Score on admission predictive of worse functional outcome after mechanical thrombectomy for anterior circulation large vessel occlusion.

BACKGROUND AND PURPOSE: We examined functional outcomes of mechanical thrombectomy (MT) procedures following anterior circulation large vessel occlusion (ACLVO)-related acute ischemic strokes (AIS). Results were based on admission non-contrast computed tomography (NCCT) studies, using the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) as standard metric. METHODS: Qualifying subjects were consecutive patients (N = 343) at a single center undergoing MT for ACLVO-related AIS. Each was grouped according to ASPECTS status on admission, determined from NCCT images by two physicians. Primary clinical endpoint was functional independence, assessed via modified Rankin Scale (mRS) at 90 days. Secondary endpoints were vessel recanalization (i.e., modified Thrombolysis in Cerebral Infarction [mTICI] score), symptomatic intracranial hemorrhage (sICH), and mortality. RESULTS: In this study population (mean age, 63.6 ± 12.6 years; women, 30.3%; median baseline National Institute of Health Stroke Scale [NIHSS] score, 15.2 ± 4.5), patients were stratified by ASPECTS tier at presentation, either 0-5 (n = 50) or 6-10 (n = 293). Multivariate logistic regression showed a relation between ASPECTS values ≤ 5 and lesser chance of 90-day functional improvement (OR = 2.309, 95% confidence interval [CI] 1.012-5.271; p = 0.047), once adjusted for age, baseline NIHSS score, diabetes mellitus, HbA1c concentration, D-dimer level, occlusive location, numbers of device passes, and successful recanalization. CONCLUSIONS: ASPECTS values ≤ 5 correspond with worse long-term functional improvement (mRS scores > 2) in patients undergoing MT for ACLVO-related AIS. Other independent determinants of functional outcomes after MT are age, baseline NIHSS score, HbA1c concentration, and successful recanalization.

Coronary slow flow research: a bibliometric analysis.

BACKGROUND: Studies on coronary slow flow are receiving increasing attention, but objective evaluations are still lacking. The purpose of this study was to visualize the current status and research hotspots of coronary slow flow through bibliometric analysis. METHODS: All relevant publications on coronary slow flow from 2003 to 2022 were extracted from the Web of Science Core Collection database and analyzed by VOSviewer and CiteSpace visualization software. Year of publication, journal, country/region, institution, and first author of each paper, as well as research hotspots were identified. RESULTS: A total of 913 publications were retrieved. The journal with the most publications was Coronary Artery Disease. The country/region with the most publications was Turkey, followed by China and the United States. The institution with the largest publication volume was Turkey Specialized Higher Education Research Hospital. The author with the largest publication volume was Chun-Yan Ma from China. Keyword analysis indicated that "treatment and prognosis", "pathogenesis and risk factors" and "diagnosis" were the clustering centers of coronary slow flow, and the research hotspots gradually changed with time, from pathogenesis to treatment and prognosis. CONCLUSION: Future research will focus on the search for effective and non-invasive detection indicators and treatments of coronary slow flow. Collaboration needs to be enhanced between different institutions or countries/regions, which would improve clinical outcomes for patients with coronary slow flow.

Noncontrast cardiac computed tomography-derived mitral annular calcification scores in mitral valve disease.

BACKGROUND AND AIMS: Mitral annular calcification (MAC) by computed tomography (CT) is reported as an independent predictor of poor outcomes. However, it currently remains unclear if quantitative MAC parameters provide more value for mitral valve disease (MVD) management, therefore, we examined the prognostic value of MAC scores using noncontrast cardiac-CT in MVD patients. METHODS: Between January 2020 and December 2021, we prospectively enrolled 300 consecutive patients with MVD (MAC-present = 80 and MAC-absent = 220) undergoing preoperative cardiac-CT and mitral valve (MV) surgery. Noncontrast cardiac-CT images were used to qualitatively detect MAC (present or absent) and evaluate MAC scores. For analyses, we also collected baseline clinical data, intraoperative conversion (from MV repair to MV replacement), and follow-up arrhythmia data. RESULTS: Compared with the MAC-absent group, MAC-present patients were older (62 ± 7 vs. 58 ± 9 years, p < .001), mostly women (55% vs. 39.5%, p = .017), and also had aortic valve calcification (57.5% vs. 23.2%, p < .001), mitral stenosis (82.5% vs. 61.8%, p < .001), atrial fibrillation (30% vs. 11.8%, p < .001), and larger left atrial end-diastolic dimension (LADD, 49 [44-56] versus 46 [41-50], p = .001]. Furthermore, MAC-present patients underwent more MV replacements (61.8% vs. 82.5%, p = .001) and experienced a higher intraoperative conversion prevalence (11.8% vs. 61.3%, p < .001). Multiple logistic regression analyses showed that the female gender (odds ratio [OR]/95% confidence interval [CI]/p = 2.001/1.042-3.841/0.037) and MAC scores (OR/95% CI/p = 10.153/4.434-23.253/p < .001) were independent predictors of intraoperative conversion. During a follow-up of 263 ± 134 days, MAC-present patients had more arrhythmias (42.5% vs. 9.5%, p < .001). Also, MAC-scores (hazard ratio [HR]/95% CI/p = 6.841/3.322-14.089/p < .001) and LADD (HR/95% CI/p = 1.039/1.018-1.060/p < .001) were independently associated with arrhythmias by Cox regression analyses. CONCLUSIONS: Noncontrast cardiac CT-derived MAC-scores showed a high risk for intraoperative conversion and follow-up arrhythmias in MVD-patients.

Automatic coronary artery segmentation of CCTA images using UNet with a local contextual transformer.

Coronary artery segmentation is an essential procedure in the computer-aided diagnosis of coronary artery disease. It aims to identify and segment the regions of interest in the coronary circulation for further processing and diagnosis. Currently, automatic segmentation of coronary arteries is often unreliable because of their small size and poor distribution of contrast medium, as well as the problems that lead to over-segmentation or omission. To improve the performance of convolutional-neural-network (CNN) based coronary artery segmentation, we propose a novel automatic method, DR-LCT-UNet, with two innovative components: the Dense Residual (DR) module and the Local Contextual Transformer (LCT) module. The DR module aims to preserve unobtrusive features through dense residual connections, while the LCT module is an improved Transformer that focuses on local contextual information, so that coronary artery-related information can be better exploited. The LCT and DR modules are effectively integrated into the skip connections and encoder-decoder of the 3D segmentation network, respectively. Experiments on our CorArtTS2020 dataset show that the dice similarity coefficient (DSC), Recall, and Precision of the proposed method reached 85.8%, 86.3% and 85.8%, respectively, outperforming 3D-UNet (taken as the reference among the 6 other chosen comparison methods), by 2.1%, 1.9%, and 2.1%.

Multi-constraint point set registration with redundant point removal for the registration of coronary arteries.

BACKGROUND: Coronary artery disease (CAD) is the leading cause of death worldwide. The registration of the coronary artery at different phases can help radiologists explore the motion patterns of the coronary artery and assist in the diagnosis of CAD. However, there is no automatic and easy-to-execute method to solve the missing data problem that occurs at the endpoints of the coronary artery tree. This paper proposed a non-rigid multi-constraint point set registration with redundant point removal (MPSR-RPR) algorithm to tackle this challenge. METHODS: Firstly, the MPSR-RPR algorithm roughly registered two coronary artery point sets with the pre-set smoothness regularization parameter and Gaussian filter width value. The moving coherent, local feature, and the corresponding relationship between bifurcation point pairs were exploited as the constraints. Next, the spatial geometry information of the coronary artery was utilized to automatically recognize the vessel endpoints and to delete the redundant points of the coronary artery. Finally, the algorithm continued carrying out the multi-constraint registration with another group of the pre-set parameters to improve the alignment performance. RESULTS: The experimental results demonstrated that the MPSR-RPR algorithm achieved a significantly lower mean value of the modified Hausdorff distance (MHD) compared to the other state-of-the-art methods for addressing the serious missing data in the left and right coronary arteries. CONCLUSION: This study demonstrated the effectiveness of the proposed algorithm in aligning coronary arteries, providing significant value in assisting in the diagnosis of coronary artery and myocardial lesions.