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OBJECTIVES: While the link between carotid plaque composition and cerebrovascular vascular (CVE) events is recognized, the role of calcium configuration remains unclear. This study aimed to develop and validate a CT angiography (CTA)-based machine learning (ML) model that uses carotid plaques 6-type calcium grading, and clinical parameters to identify CVE patients with bilateral plaques. MATERIAL AND METHODS: We conducted a multicenter, retrospective diagnostic study (March 2013-May 2020) approved by the institutional review board. We included adults (18 +) with bilateral carotid artery plaques, symptomatic patients having recently experienced a carotid territory ischemic event, and asymptomatic patients either after 3 months from symptom onset or with no such event. Four ML models (clinical factors, calcium configurations, and both with and without plaque grading [ML-All-G and ML-All-NG]) and logistic regression on all variables identified symptomatic patients. Internal validation assessed discrimination and calibration. External validation was also performed, and identified important variables and causes of misclassifications. RESULTS: We included 790 patients (median age 72, IQR [61-80], 42% male, 64% symptomatic) for training and internal validation, and 159 patients (age 68 [63-76], 36% male, 39% symptomatic) for external testing. The ML-All-G model achieved an area-under-ROC curve of 0.71 (95% CI 0.58-0.78; p < .001) and sensitivity 80% (79-81). Performance was comparable on external testing. Calcified plaque, especially the positive rim sign on the right artery in older and hyperlipidemic patients, had a major impact on identifying symptomatic patients. CONCLUSION: The developed model can identify symptomatic patients using plaques calcium configuration data and clinical information with reasonable diagnostic accuracy. CLINICAL RELEVANCE: The analysis of the type of calcium configuration in carotid plaques into 6 classes, combined with clinical variables, allows for an effective identification of symptomatic patients. KEY POINTS: ⢠While the association between carotid plaques composition and cerebrovascular events is recognized, the role of calcium configuration remains unclear. ⢠Machine learning of 6-type plaque grading can identify symptomatic patients. Calcified plaques on the right artery, advanced age, and hyperlipidemia were the most important predictors. ⢠Fast acquisition of CTA enables rapid grading of plaques upon the patient's arrival at the hospital, which streamlines the diagnosis of symptoms using ML.
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OBJECTIVES: The objective is to assess the performance of the Eluvia polymer coated drug eluting stent (DES) compared to a bare metal stent (BMS) platform in patients with femoropopliteal arterial disease. METHODS: This is a retrospective, single-center analysis. Patients treated with the Eluvia DES (group Eluvia) or the EverFlex BMS (group BMS) for femoropopliteal disease between January 2013 and December 2019 were included. Primary measure outcome of this analysis was the overall mortality. The PTX specific mortality, the primary patency, the amputation free survival (AFS), and the target lesion revascularization (TLR) rates were additionally evaluated. RESULTS: A total of 124 patients were treated by BMS deployment, while the Eluvia platform was preferred in 75 subjects. In both groups the majority presented with lifestyle limiting claudication (BMS: 84% vs Eluvia: 73%, p = 0.73). Chronic total occlusions were more frequent in patients treated by BMS (BMS: 71% vs Eluvia: 84%, p = 0.027), whereas the calcification burden (BMS: 81% vs Eluvia: 76%, p = 0.43) and the median lesion length (in mm, IQR) (BMS: 160 (100 to 240) vs Eluvia: 140 (80 to 229), p = 0.17) were comparable. At 24 months, the overall survival (BMS: 93% vs Eluvia: 89%, hazard ratio (HR): 1.20, 95% confidence interval (CI): 0.55 to 2.64, p = 0.64) and the PTX specific survival (BMS: 95% vs Eluvia: 95%, HR: 1.28, 95% CI: 0.41 to 4.02, p = 0.67) did not differ significantly between the two platforms. No significant difference was observed regarding the 24 months primary patency rate (BMS: 66% vs Eluvia: 78%, HR: 0.65, 95% CI: 0.37 to 1.15, p = 0.18), the freedom from TLR (BMS: 83% vs Eluvia: 89%, HR: 0.81, 95% CI: 0.39 to 1.68, p = 0.572), and the AFS (BMS: 93 vs Eluvia: 89%, HR: 1.20, 95% CI: 0.55 to 2.64). The Cox regression analysis revealed a higher mortality risk among patients with chronic limb-threatening ischemia (CLTI) (HR: 3.14, 95% CI: 1.61 to 6.14, p = 0.008), chronic obstructive pulmonary disease (COPD) (HR: 4.65, 95% CI: 2.14 to 10.09, p = 0.001), in octagenerians (HR: 4.40, 95% CI: 1.92 to 10.44, p = 0.005), and in patients not on statins at baseline (HR: 2.44, 95% CI: 1.19 to 4.99, p=0.014). CONCLUSIONS: In this cohort, the use of the Eluvia DES did not increase the risk for mortality compared to BMS deployment. CLTI, COPD, advanced age, and the lack of statin therapy at baseline were associated with a higher risk for death.