Machine learning detects symptomatic patients with carotid plaques based on 6-type calcium configuration classification on CT angiography.

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.

Efficacy analysis following polymer coated drug eluting stent and bare metal stent deployment for femoropopliteal arterial disease.

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.