Myocarditis is an inflammatory disease of the heart characterized by a complex interplay between innate and adaptive immune responses. The innate immune system provides first-line defense and includes soluble molecules, including macrophages, neutrophils, dendritic cells, and molecular mediators, but lacks immunological memory. In contrast, the adaptive immune system, via T and B lymphocytes, offers high specificity and long-term memory, which can sometimes target myocardial tissue, causing autoimmune injury. Particularly, acute myocarditis is characterized by dysregulated immune signaling, with cytokines (IL-2, IFN-γ, IL-12, IL-4, IL-10) and chemokines (MCP-1, CXCL4, CXCL10) driving disease progression, while adhesion molecules (ICAM-1, VCAM-1, VAP-1) promote leukocyte trafficking and cardiac inflammation. The balance between pro-inflammatory and regulatory responses determines disease outcomes, ranging from resolution with recovery to fulminant myocarditis or progression to dilated cardiomyopathy. Emerging therapeutic approaches targeting cytokines, chemokines, and adhesion molecules, along with established immunosuppressive treatments, underline the potential for modulating immune responses in myocarditis and, thereby, improving patient outcomes.

Introduction: Artificial intelligence (AI) tools have emerged in cardiovascular clinical practice. Regarding transcatheter aortic valve replacement/implantation (TAVR/TAVI) procedures, their utilization optimizes procedural planning, aids physicians with decision making, and predicts possible post-procedural complications. Moreover, machine-learning (ML) models, compared with traditional mortality risk scores, show promising results considering predicted mortality in TAVI patients. However, further validation is required. As the implementation of cardiovascular procedures can be challenging, AI technology broadens the armamentarium of tools that a clinician is able to use for a more comprehensive evaluation of patients, minimizing complications and resulting in optimum clinical outcomes. Methods: A comprehensive literature search was conducted through the PubMed and Google Scholar databases from inception to 20 September 2025, to identify relevant studies. The search strategy included the following keywords: [“TAVI” OR “TAVR”] AND [“AI”, Artificial Intelligence]. Results: According to our database research, 7177 articles were initially screened, and 2145 duplicate articles were excluded. Eventually, 189 articles were evaluated by our reviewers and 51 articles of studies published between 2014 and 2025 were included in our review. Conclusions: AI algorithms could revolutionize the Heart Team decision making process, being not only a tool for patient evaluation but an active member of the team with applications to analyze and optimize all stages of the TAVI procedure, guide decision making and predict outcomes, and, with the contribution and evaluation of information from all human members of the team, enhance even more the patient-mediated medicine/interventions.

Angiography remains the standard imaging modality during cardiac catheterization; however, this technique provides only a two-dimensional representation of the coronary lumen, which limits the assessment of vessel wall pathology. In comparison, intravascular imaging techniques, such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT), provide high-resolution cross-sectional and two-dimensional reconstructions of the coronary arteries. Thus, these modalities complement angiographic findings, enable detailed evaluation of underlying pathology, and facilitate precise procedural guidance. Advancements in imaging technologies, including near-infrared spectroscopy and virtual histology intravascular ultrasound, further enhance lesion characterization and procedural planning. An increasing body of evidence from registries, randomized controlled trials, and meta-analyses supports the use of intravascular imaging-guided percutaneous coronary interventions, demonstrating improved procedural success rates and superior long-term clinical outcomes. In the context of acute coronary syndromes (ACS), OCT offers critical diagnostic insights that enhance accuracy and inform optimal treatment strategies. This review highlights the evolving role of OCT in the management of ACS and the favorable impact of this technique on patient outcomes.

Coronary artery disease (CAD) is the leading cause of mortality, with percutaneous coronary intervention (PCI) constituting the gold standard treatment. However, in an important proportion of the cases, lesion severity is debatable since conventional angiography provides only a two-dimensional representation of the vessel lumen and fails to quantify ischemic significance or plaque morphology. In these cases, several adjunctive tools considering physiology and imaging guidance may assist in quantifying the severity of the disease. Imaging modalities such as intravascular ultrasonography (IVUS) and optical coherence tomography (OCT), as well as physiology such as fractional flow reserve (FFR) and instantaneous wave-free (iFR), revolutionized revascularization strategy by linking anatomical stenosis to its functional consequence on myocardial perfusion. The present review summarizes and contrasts the available evidence for physiology and imaging guidance, considering the assessment of intermediate lesions during PCI and providing insights for their use in specific lesion subsets.