Accuracy of Artificial Intelligence-Based Automated Quantitative Coronary Angiography Compared to Intravascular Ultrasound: Retrospective Cohort Study. (Preprint)

Artificial Intelligence in Coronary Artery Interventions: Preprocedural Planning and Procedural Assistance

Artificial intelligence (AI) has profoundly influenced the field of cardiovascular interventions and coronary artery procedures in particular. AI has enhanced diagnostic accuracy in coronary artery disease through advanced invasive and noninvasive imaging modalities, facilitating more precise diagnosis and personalized interventional strategies. AI integration in coronary interventions has streamlined diagnostic and procedural workflows, improved procedural accuracy, increased clinician efficiency, and enhanced patient safety and outcomes. Despite its potential, AI still faces significant challenges, including concerns regarding algorithmic biases, lack of transparency in AI-driven decision making, and ethical challenges. This review explores the latest advancements of AI applications in coronary artery interventions, focusing on preprocedural planning and real-time procedural guidance. It also addresses the major limitations and obstacles that hinder the widespread clinical adoption of AI technologies in this field.

An Introductory Guide to Artificial Intelligence in Interventional Radiology: Part 1 Foundational Knowledge

Artificial intelligence (AI) is rapidly evolving and has transformative potential for interventional radiology (IR) clinical practice. However, formal training in AI may be limited for many clinicians and therefore presents a challenge for initial implementation and trust in AI. An understanding of the foundational concepts in AI may help familiarize the interventional radiologist with the field of AI, thus facilitating understanding and participation in the development and deployment of AI. A pragmatic classification system of AI based on the complexity of the model may guide clinicians in the assessment of AI. Finally, the current state of AI in IR and the patterns of implementation are explored (pre-procedural, intra-procedural, and post-procedural).

Quantitative Angiography: The Dawn of a New Era in Cardiovascular Medicine

This comprehensive review explores the transformative role of quantitative angiography in the landscape of cardiovascular medicine. Tracing the historical evolution of cardiovascular diagnostics, we emphasize the significance of angiography in diagnosis and treatment. The primary focus on quantitative angiography reveals its capacity to move beyond qualitative assessments, providing clinicians with precise measurements and objective parameters. This paradigm shift enhances diagnostic accuracy, promising far-reaching implications for the future of cardiovascular medicine. The ability to tailor interventions based on meticulous measurements optimizes therapeutic strategies and positions the field on the brink of a new era where personalized approaches become the norm. However, challenges such as image quality, radiation exposure, and interpretation variability persist, necessitating a collective call to action for continued research and development. As we confront these issues, collaborative efforts across disciplines are essential to refine existing technologies and usher in innovative solutions. This review concludes with a resounding call for ongoing research initiatives, large-scale clinical studies, and collective commitment to propel quantitative angiography into a universally accepted standard, ensuring its full realization in enhancing patient care and outcomes in cardiovascular medicine.

Validation of artificial intelligence-based quantitative coronary angiography

Background

Coronary angiography is fundamental for the diagnosis and treatment of coronary artery disease. Manual quantitative coronary angiography (QCA) is accurate and reproducible; however, it is time-consuming and labor-intensive. However, recent advancements in artificial intelligence (AI) have enabled automated and rapid analysis of medical images, addressing the need for real-time quantitative coronary analysis.

Aims

This study aimed to evaluate the accuracy of AI-based QCA (AI-QCA) compared with that via manual QCA and clinician acceptance.

Methods

This retrospective, single-center study was conducted in two phases. Phase 1 was a pilot study comparing AI-QCA with manual QCA and visual estimation. It involved 15 patients who underwent coronary angiography at Seoul National University Bundang Hospital between September 2011 and July 2021. Phase 2 included a larger cohort of 762 patients, with 1002 coronary angiograms analyzed between May 2020 and April 2021.

Results

In phase 1, AI-QCA and manual QCA consistency varied among the observers, with AI-QCA showing superior consistency compared with visual estimation. However, a strong correlation between AI-QCA and manual-QCA was found in phase 2. AI-QCA accurately identified and quantitatively analyzed multiple lesions in the major vessels, providing results comparable with those of manual QCA.

Conclusions

AI-QCA demonstrated high concordance with manual QCA, offering real-time analysis and reduced workload. Therefore, AI-QCA has the potential to be a valuable tool for diagnosing and treating coronary artery disease, necessitating further studies for clinical validation.

State-of-art review: intravascular imaging in percutaneous coronary interventions

The history of intravascular ultrasound (IVUS) and optical coherence tomography (OCT) reflects the relentless pursuit of innovation in interventional cardiology. These intravascular imaging technologies have played a pivotal role in our understanding of coronary atherosclerosis, vascular pathology, and the interaction of coronary stents with the vessel wall. Two decades of clinical investigations demonstrating the clinical efficacy and safety of intravascular imaging modalities have established these technologies as staples in the contemporary cardiac catheterization lab's toolbox and earning their place in revascularization clinical practice guidelines. In this comprehensive review, we will delve into the historical evolution, mechanisms, and technical aspects of IVUS and OCT. We will discuss the expanding evidence supporting their use in complex percutaneous coronary interventions, emphasizing their crucial roles in optimizing patient outcomes and ensuring procedural success. Furthermore, we will explore the substantial advances that have propelled these imaging modalities to the forefront of contemporary interventional cardiology. Finally, we will survey the latest developments in the field and explore the promising future directions that have the potential to further revolutionize coronary interventions.