Carotid artery stenting vs. endarterectomy

Randomized clinical trials have demonstrated that carotid endarterectomy (CEA) is superior to medical management for stroke prevention in patients with symptomatic and, to a lesser degree, asymptomatic internal carotid artery stenosis. However, large-scale registries have shown that the adverse event rates following CEA are commonly higher than observed in the trials. In the last decade, carotid artery stenting (CAS) has emerged as a less invasive alternative to surgery. In order to address the efficacy of CAS, we performed a meta-analysis of 10 randomized trials comparing CAS with CEA in 4648 mainly symptomatic patients. The analysis showed that CAS was associated with a statistically significant increased death or stroke rate at 30 days compared with CEA (odds ratio 1.60, 95% confidence interval 1.26-2.02). However, most of the trials had inadequate requirements in terms of endovascular expertise and did not mandate the use of emboli protection devices. Beyond 30 days, long-term follow-up of the trials previously reported suggest that both revascularization techniques are equivalent in terms of stroke prevention. Conversely, large-scale high-quality CAS registries—mostly with independent neurological assessment and clinical event committee adjudication—have reported results in the range of current recommendation for CEA in over 20 000 patients, despite the fact that the majority of patients were at high risk for surgery. Until further data become available, the performance of CAS should be limited to protocols or centres of excellence and targeted especially to patients at high risk for surger

Feasibility Test Verification Method For Nonsymmetric Release Time Task Scheduling

This paper discusses problems associated with scheduling periodic task on a uniprocessor in a hard, real-time processing environment using a static-priority, preemptive-resume operating system. Task sets containing a single periodic task with two Ned release periocis of unequal length are examined. Ihe nonsymmetric scheduling algorithm is based on the rate monotonic scheduling algorithm which assigns higher task priorities to tasks with shorter release periods. me effects on processor utilization using two dirkrent priority assignment schemes are examined; one with task priorities sorted by the average release periods and the other with priorities sorted using the short nonsymmetric task period with the average period lengths for the remaining task. Results indicate that the second scheme had higher breakdown utilizations than the first one, and that the second scheme, for task sets with a low utilization nonsymmetric task, results in little or no loss in the overall task set utilization

Automated Measurement of Vascular Calcification in Femoral Endarterectomy Patients Using Deep Learning

Atherosclerosis, a chronic inflammatory disease affecting the large arteries, presents a global health risk. Accurate analysis of diagnostic images, like computed tomographic angiograms (CTAs), is essential for staging and monitoring the progression of atherosclerosis-related conditions, including peripheral arterial disease (PAD). However, manual analysis of CTA images is time-consuming and tedious. To address this limitation, we employed a deep learning model to segment the vascular system in CTA images of PAD patients undergoing femoral endarterectomy surgery and to measure vascular calcification from the left renal artery to the patella. Utilizing proprietary CTA images of 27 patients undergoing femoral endarterectomy surgery provided by Prisma Health Midlands, we developed a Deep Neural Network (DNN) model to first segment the arterial system, starting from the descending aorta to the patella, and second, to provide a metric of arterial calcification. Our designed DNN achieved 83.4% average Dice accuracy in segmenting arteries from aorta to patella, advancing the state-of-the-art by 0.8%. Furthermore, our work is the first to present a robust statistical analysis of automated calcification measurement in the lower extremities using deep learning, attaining a Mean Absolute Percentage Error (MAPE) of 9.5% and a correlation coefficient of 0.978 between automated and manual calcification scores. These findings underscore the potential of deep learning techniques as a rapid and accurate tool for medical professionals to assess calcification in the abdominal aorta and its branches above the patella. The developed DNN model and related documentation in this project are available at GitHub page at https://github.com/pip-alireza/DeepCalcScoring.Comment: Published in MDPI Diagnostic journal, the code can be accessed via the GitHub link in the pape

TransONet: Automatic Segmentation of Vasculature in Computed Tomographic Angiograms Using Deep Learning

Pathological alterations in the human vascular system underlie many chronic diseases, such as atherosclerosis and aneurysms. However, manually analyzing diagnostic images of the vascular system, such as computed tomographic angiograms (CTAs) is a time-consuming and tedious process. To address this issue, we propose a deep learning model to segment the vascular system in CTA images of patients undergoing surgery for peripheral arterial disease (PAD). Our study focused on accurately segmenting the vascular system (1) from the descending thoracic aorta to the iliac bifurcation and (2) from the descending thoracic aorta to the knees in CTA images using deep learning techniques. Our approach achieved average Dice accuracies of 93.5% and 80.64% in test dataset for (1) and (2), respectively, highlighting its high accuracy and potential clinical utility. These findings demonstrate the use of deep learning techniques as a valuable tool for medical professionals to analyze the health of the vascular system efficiently and accurately. Please visit the GitHub page for this paper at https://github.com/pip-alireza/TransOnet.Comment: Accepted for the 2023 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, US

Safety of paclitaxel-coated balloon angioplasty for femoropopliteal peripheral artery disease

OBJECTIVES: The aim of this study was to assess safety outcomes of femoropopliteal drug-coated balloon (DCB) angioplasty using patient-level data from the Lutonix clinical program. BACKGROUND: A recent systematic review and meta-analysis of heterogenous trials and summary-level data identified increased long-term mortality in patients treated with paclitaxel-coated balloons and stents. METHODS: We evaluated DCB angioplasty (n = 1,093) and uncoated balloon angioplasty (percutaneous transluminal angioplasty [PTA]) (n = 250) outcomes in LEVANT 1 (The Lutonix Paclitaxel-Coated Balloon for the Prevention of Femoropopliteal Restenosis), LEVANT 2 (Moxy Drug Coated Balloon vs. Standard Balloon Angioplasty for the Treatment of Femoropopliteal Arteries), and the LEVANT Japan Clinical Trial. Hazard ratios (HRs) were calculated with Cox proportional hazards modeling. RESULTS: There were no significant differences in mortality rates between DCB angioplasty and PTA. The 5-year HR was 1.01 (95% confidence interval [CI]: 0.68 to 1.52) in the aggregated LEVANT trials. The 2-year HR after DCB angioplasty was 0.99 (95% CI: 0.25 to 3.95) in LEVANT 1, 1.40 (95% CI: 0.62 to 3.14) in LEVANT 2, and 0.32 (95% CI: 0.05 to 1.92) in the LEVANT Japan Clinical Trial. The 5-year HR was 1.60 (95% CI: 0.94 to 2.72) in LEVANT 2. Adverse events and causes of death were balanced, without clustering between DCB angioplasty and PTA. Patients who underwent paclitaxel or nonpaclitaxel reinterventions had higher survival rates than those who did not undergo reinterventions. Baseline covariates predicting mortality included, among others, age (HR: 1.03 per year; p \u3c 0.0001), prior treatment of target lesion (HR: 1.67; p = 0.022), arrhythmia (HR: 1.65; p = 0.031), and diabetes (HR: 1.18; p = 0.047), without differences between the 2 arms. No dose-response relationship was identified when adjusted for key predictors of mortality. CONCLUSIONS: Analyses of patient-level data identified no mortality differences between DCB angioplasty and PTA. Furthermore, the lack of dose-response relationships or clustering of causes of death argues against a causal relationship between paclitaxel and mortality. (LEVANT 1, The Lutonix Paclitaxel-Coated Balloon for the Prevention of Femoropopliteal Restenosis [LEVANT 1], NCT00930813; Moxy Drug Coated Balloon vs. Standard Balloon Angioplasty for the Treatment of Femoropopliteal Arteries [LEVANT 2], NCT01412541; LEVANT 2 Continued Access Registry, NCT01628159; LEVANT Japan Clinical Trial, NCT01816412)