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New Developments in Coronary Interventional Therapy

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Cardiology".

Deadline for manuscript submissions: closed (31 October 2025) | Viewed by 1227

Special Issue Editor


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Guest Editor
Division of Cardiology, Wayne State University/Detroit Medical Center, Detroit, MI 48201, USA
Interests: complex coronary interventions; mechanical circulatory support; large bore vascular access; medical education; social media as learning tools for physicians
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Special Issue Information

Dear Colleagues,

Coronary interventional therapies have undergone significant advancements in recent years, revolutionizing the management of coronary artery disease (CAD). As the leading cause of morbidity and mortality worldwide, CAD necessitates continuous innovation to improve patient outcomes. This Special Issue highlights the latest breakthroughs in coronary interventions with a focus on collecting articles that explore the most recent advancements in percutaneous coronary interventions (PCI), stent technology, as well as approaches to bifurcation lesions, chronic total occlusions (CTOs), left main disease, in-stent restenosis (ISR), stent thrombosis, and multivessel interventions with a focus on enhancing precision, safety, and efficacy. Additionally, we want to highlight the emerging trends in the usage of personalized medicine, bioabsorbable vascular scaffolds, and innovative imaging techniques such as optical coherence tomography (OCT) and intravascular imaging (IVUS) that may affect optimal treatment planning. Furthermore, the influence of operator experience, family presence during PCI, and the role of fasting protocols in improving procedural outcomes will be examined. Particular emphasis will be placed on the role of multimodal risk assessment and the application of artificial intelligence in decision-making.

This issue aims to provide clinicians with a comprehensive overview of the current landscape and future directions in coronary interventional therapies and will additionally give them insights and guidance to improve patient outcomes in interventional cardiovascular care.

Dr. Chadi Alraies
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • high risk PCI
  • optical coherence tomography
  • chronic total occlusions
  • bifurcation lesions
  • left main stem disease
  • multivessel coronary artery disease

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Published Papers (2 papers)

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Research

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14 pages, 3059 KB  
Article
Automated Artificial Intelligence Mapping of Coronary Plaque Calcification: A Comparison with Manual Intravascular Image Analysis
by Killian J. McCarthy, Emily A. Larnard, Christina K. Anderson, Mohsin Chowdhury, Ronny Shalev, Diaa A. Hakim, Kevin J. Croce and Eric A. Osborn
J. Clin. Med. 2025, 14(22), 8166; https://doi.org/10.3390/jcm14228166 - 18 Nov 2025
Viewed by 437
Abstract
Background/Aims: Intravascular imaging during percutaneous coronary intervention (PCI) improves clinical outcomes; however, is dependent on accurate and rapid interpretation of the images generated. This study aimed to compare coronary artery calcification assessment using a novel automated artificial intelligence (AI) software algorithm with manual [...] Read more.
Background/Aims: Intravascular imaging during percutaneous coronary intervention (PCI) improves clinical outcomes; however, is dependent on accurate and rapid interpretation of the images generated. This study aimed to compare coronary artery calcification assessment using a novel automated artificial intelligence (AI) software algorithm with manual optical coherence tomography (OCT) image analysis. Methods and Results: A deep neural network based on a UNet-like architecture was developed and trained to identify calcified atherosclerotic plaque from an independent dataset of expert-annotated clinical intravascular OCT pullbacks. The AI network was subsequently validated on previously unseen clinical OCT pullbacks that were manually annotated for plaque calcium and used to quantify clinically relevant calcified plaque characteristics. Correlation and agreement between the expert-annotated images and the model predictions were evaluated. In total, 8259 cross-sectional images comprised the training and internal validation dataset. Pixel-based classification by the AI model performed best to identify calcified plaque (AUC = 0.96), with an overall diagnostic accuracy of 73.3%. During independent external validation, the model correctly identified 934 of the 1248 calcified plaques, corresponding to a diagnostic accuracy of 74.8%. The AI model performed well in assessing the calculated OCT-calcium score (ρ = 0.84; 95% confidence interval [CI], 0.81–0.87, p ≤ 0.001). Conclusions: Implementation of an automated AI software algorithm provides a rapid and efficient method to comprehensively map coronary calcium in intravascular OCT images. With further training and refinement, it is anticipated that the AI machine learning software will continue to improve, enabling new robust tools for clinical OCT calcium detection to better guide PCI procedures. Full article
(This article belongs to the Special Issue New Developments in Coronary Interventional Therapy)
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Review

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27 pages, 2319 KB  
Review
Modern Imaging Techniques for Percutaneous Coronary Intervention Guidance: A Focus on Intravascular Ultrasound and Optical Coherence Tomography
by Lorenzo Scalia, Mattia Squillace, Antonio Popolo Rubbio, Enrico Poletti, Federica Agnello, Antonio Sisinni, Francesco Bedogni, Marco Barbanti and Luca Testa
J. Clin. Med. 2025, 14(24), 8627; https://doi.org/10.3390/jcm14248627 - 5 Dec 2025
Viewed by 477
Abstract
The use of imaging during percutaneous coronary intervention (PCI) can improve the outcomes by giving key information in every phase of the procedure. It can improve the knowledge of plaque composition thus helping the subsequent technical strategy; it can precisely define the measure [...] Read more.
The use of imaging during percutaneous coronary intervention (PCI) can improve the outcomes by giving key information in every phase of the procedure. It can improve the knowledge of plaque composition thus helping the subsequent technical strategy; it can precisely define the measure of the stent to implant; it can assess in detail the correct positioning of the stent (apposition, expansion, and full coverage of the atherosclerotic plaque); it helps in recognizing the complications that may occur after stenting (e.g., edge dissection or tissue/thrombus protrusion in the stent area). Further, it could help evaluation for both diagnostic and therapeutic purposes of angiographic unknown or questionable findings [e.g., spontaneous coronary artery dissection (SCAD), characterization of mycotic aneurysm and pseudoaneurysm]. In the follow up phase, the use of intracoronary imaging may significantly improve the understanding of the mechanisms leading to the procedural failure. What this review adds is to describe the similarities and differences between intravascular ultrasound (IVUS) and optical coherence tomography (OCT) technologies, to highlight the evidence supporting their utility to improve PCI outcomes, to give practical advice and tools on daily interventional routine, to show a point of view on future perspectives and integration with artificial intelligence (AI). Full article
(This article belongs to the Special Issue New Developments in Coronary Interventional Therapy)
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