Anatomical classification of chronic total occlusions in coronary bifurcations.
Juan Luis Gutiérrez-ChicoJuan Luis Gutiérrez-ChicoNiels Ramsing HolmEvald Høj ChristiansenMaciej LesiakBernward LauerSylvia OttoFrancesco LavarraViktor SasiYiannis S ChatzizisisSudhir RathoreFranz-Josef NeumannPublished in: Cardiology journal (2022)
Percutaneous coronary intervention (PCI) of chronic total occlusions (CTO) in coronary bifurcation lesions (CBL) is undergoing substantial technical progress and standardization, paralleling the evolution of dedicated devices, tools, and techniques. A standard consensus to classify CTO-CBL might be instrumental to homogenize data collection and description of procedures for scientific and educational purposes. The Medina-CTO classification replicates the classical three digits in Medina classification for bifurcations, representing the proximal main vessel, distal main vessel, and side branch, respectively. Each digit can take a value of 1 if it concerns atherosclerosis and is anatomically stenosed, or 0 if it is not. In addition, the occluded segment(s) of the bifurcation are noted by a subscript, which describes key interventional features of the cap: t (tapered), b (blunt), or a (ambiguous). This approach results in 56 basic categories that can be grouped by means of different elements, depending on the specific needs of each study. Medina-CTO classification, consisting of adding a subscript describing the basic cap characteristics to the totally occluded segment(s) of the standard Medina triplet, might be a useful methodological tool to standardize percutaneous intervention of bifurcational CTO lesions, with interesting scientific and educational applications.
Keyphrases
- deep learning
- machine learning
- coronary artery disease
- percutaneous coronary intervention
- coronary artery
- acute myocardial infarction
- acute coronary syndrome
- st segment elevation myocardial infarction
- randomized controlled trial
- minimally invasive
- st elevation myocardial infarction
- antiplatelet therapy
- coronary artery bypass grafting
- cardiovascular disease
- big data
- artificial intelligence
- electronic health record
- heart failure
- type diabetes
- left ventricular
- aortic stenosis
- ultrasound guided
- ejection fraction