Cardiac lesions classification
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Cardiac Lesions Classification: Key Systems and Approaches
Coronary Artery Lesion Classification: ACC/AHA and Lesion Severity
The American College of Cardiology/American Heart Association (ACC/AHA) classification is a widely used system for categorizing coronary artery lesions. It divides lesions into types A, B1, B2, and C, based on complexity and likelihood of procedural success during interventions like percutaneous coronary intervention (PCI). Studies confirm that as lesion complexity increases (especially type C), procedural success rates decrease and the risk of adverse events rises, even with modern PCI techniques. This validates the ACC/AHA system as a reliable predictor of PCI outcomes and complications, making it a valuable tool in clinical practice for risk stratification and procedural planning .
Functional Patterns of Coronary Disease: Focal, Serial, and Diffuse Lesions
Coronary lesions can also be classified by their physiological patterns: focal (single, localized narrowing), serial (multiple, sequential narrowings), and diffuse (widespread narrowing along the vessel). These patterns influence the accuracy of diagnostic tools and the outcomes of interventions. Identifying the specific pattern is important for tailoring management strategies and optimizing procedural planning, as diffuse disease in particular can complicate both diagnosis and treatment .
Imaging and Deep Learning in Lesion Classification
Advances in imaging and artificial intelligence have improved lesion classification. Deep learning models trained on invasive coronary angiography (ICA) images can distinguish between lesion and non-lesion areas and assess lesion severity. However, classification accuracy can be affected by the degree of the lesion, with lower accuracy observed when less severe lesions are included. Despite this, high F-measure and AUC values have been achieved, demonstrating the potential of these technologies to support clinical decision-making . Additionally, radiomics features extracted from cardiac computed tomography angiography (CCTA) can be used to noninvasively classify lesion-specific myocardial ischemia, offering promising accuracy and potential to reduce reliance on invasive procedures .
Cardiac Tumor and Mass Lesion Classification: WHO and Clinical Systems
Cardiac lesions also include tumors and tumor-like masses. The World Health Organization (WHO) classification system divides cardiac tumors into benign, malignant, and intermediate categories, with further subtypes based on tissue origin and molecular characteristics. Most primary cardiac tumors are benign (such as myxomas and papillary fibroelastomas), while malignant tumors are less common but have worse outcomes. Secondary (metastatic) tumors are much more frequent than primary cardiac tumors Basso2016Amano2013Simonavičius2023+2 MORE.
Clinical classification systems for cardiac tumors consider origin (primary vs. secondary), tissue type, and malignancy. These systems guide diagnostic and treatment strategies, as management differs significantly between benign and malignant lesions. Imaging (ultrasound, CT, MRI) and blood tests are essential for diagnosis, and treatment may involve surgery, chemotherapy, or radiotherapy depending on the tumor type Simonavičius2023Maleszewski2017Burke2016.
Congenital Cardiac Lesion Classification: Standardized Nomenclature
For congenital cardiac lesions, standardized nomenclature systems like the International Paediatric and Congenital Cardiac Code (IPCCC) and the World Health Organization’s ICD-11 are used. These systems enable consistent data entry, research, and risk stratification across centers, supporting better outcomes and multicenter studies .
Conclusion
Cardiac lesion classification encompasses a range of systems tailored to different lesion types, including coronary artery disease, cardiac tumors, and congenital defects. The ACC/AHA system and functional pattern classification are central for coronary lesions, while the WHO and clinical systems are key for cardiac tumors. Advances in imaging and artificial intelligence are enhancing lesion detection and classification, supporting more precise diagnosis and treatment planning. Standardized nomenclature remains essential for congenital lesions, ensuring consistency in research and clinical care.
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Most relevant research papers on this topic
Coronary Artery Disease Classification With Different Lesion Degree Ranges Based on Deep Learning
Deep learning methods can accurately classify coronary artery disease with 92.7% and 98.1% accuracy, but performance is significantly affected by the degree of the lesion.
Cardiac masses and tumours
Cardiac masses include benign and malignant tumors, with the most common being myxomas and papillary fibroelastomas, and their diagnosis and management require a clinical setting and a multidisciplinary approach.
Clinical classification of cardiovascular tumors and tumor-like lesions, and its incidences
A new classification of cardiovascular tumors reveals that metastatic tumors are more common than heart and great vessel tumors, with cardiac myxoma being the most frequent type in all cardiac tumors.
Functional Patterns of Coronary Disease: Diffuse, Focal, and Serial Lesions.
This review provides clear definitions of physiological patterns of coronary artery disease, aiding in tailored management and percutaneous coronary intervention planning.
The 2015 WHO Classification of Tumors of the Heart and Pericardium.
The 4th edition of the WHO Classification of Heart and Pericardium Tumors introduces new classifications, focusing on benign, malignant, and intermediate tumors of uncertain behavior, and highlights the importance of genetic changes in cardiac myxomas.
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Classification of lesion specific myocardial ischemia using cardiac computed tomography radiomics
The study shows that radiomic features from noninvasive coronary computed tomography angiograms can accurately classify lesion-specific myocardial ischemia with high accuracy.
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