Although coronary computed tomographic angiography (CTA) is widely used for anatomical evaluation, its advanced analyses, including plaque characterization, computed tomography-derived fractional flow reserve (CT-FFR), and radiomics signature extraction, hold promise for improved prediction of major adverse cardiovascular events (MACE). The aim of this meta-analysis was to assess the added prognostic value of advanced coronary CTA-based analyses in predicting MACE. A systematic search of PubMed, Embase, and CENTRAL identified studies reporting coronary CTA-based advanced analyses predicting MACE. The pooled HR of advanced coronary CTA-based analyses for the prediction of MACE was the primary outcome measure. The secondary endpoint included the mean difference in C index (ΔC index) between advanced coronary CTA-based predictive models and conventional models. MACE were defined according to study-level definitions. The protocol was registered in the International Prospective Register of Systematic Reviews (CRD42024606545). Of 75 studies, 52 were included in the primary analysis of HRs (n = 58,123) and 32 in the secondary analysis of ΔC index. The median follow-up time was 36 months (Q1-Q3: 24-57 months). Most advanced coronary CTA-based analyses, including CT-FFR, high-risk plaque, fat attenuation index, total plaque volume or low-attenuation plaque volume, and radiomics-derived scores, demonstrated a significant and consistent association with MACE, observed across both pooled unadjusted and adjusted HRs. In particular, CT-FFR (HR: 6.14 [95% CI: 3.75-10.05]; P < 0.01) and high-risk plaque (HR: 4.05 [95% CI: 3.16-5.18]; P < 0.01) showed the strongest associations with MACE despite a moderate to severe between-studies heterogeneity for most of the pooled analyses. Advanced coronary CTA-based analyses show consistent association to the occurrence of MACE, suggesting their potential for refining cardiovascular risk stratification on top of conventional clinical risk assessment. Given the heterogeneity of advanced imaging analyses by coronary CTA and their varying pathophysiological targets, future comparative studies are needed to evaluate their implementation in different clinical scenarios.

The classical concept of plaque vulnerability, centred on specific morphological features, has failed to deliver reliable risk prediction in clinical practice. Recent evidence highlights the need to redefine coronary vulnerability as a dynamic, patient-specific phenotype shaped by plaque biology, systemic inflammation, and haemodynamic forces. Advanced imaging modalities, artificial intelligence, and circulating biomarkers now enable a multidimensional assessment of this complex phenotype. This integrative approach may offer a more precise framework for risk stratification and personalised prevention in coronary artery disease.

Optical Coherence Tomography (OCT) is a further light-based intravascular imaging modality and provides a high-resolution, cross-sectional view of coronary arteries. It has a useful anatomic and increasingly physiological evaluation in light of coronary artery disease (CAD). This review provides a critical examination of the increased application of the OCT in assessing coronary artery physiology, beyond its initial mainstay application in anatomical imaging. OCT provides precise information on plaque morphology, which can help identify vulnerable plaques, and is most important in informing percutaneous coronary interventions (PCIs), including implanting a stent and optimizing it. The combination of OCT and functional measurements, such as optical flow ratio and OCT-based fractional flow reserve (OCT-FFR), permits a more complete assessment of coronary stenoses, which may provide increased diagnostic accuracy and better revascularization decision-making. The recent developments in OCT technology have also enhanced the accuracy in the measurement of coronary functions. The innovations may support the optimal treatment of patients as they provide more personalized and individualized treatment options; however, it is critical to recognize the limitations of OCT and distinguish between the hypothetical advantages and empirical outcomes. This review evaluates the existing uses, technological solutions, and future trends in OCT-based physiological imaging and evaluation, and explains how such an advancement will be beneficial in the treatment of CAD and gives a fair representation concerning other imaging applications.

Percutaneous coronary intervention outcomes rely heavily on accurate lesion assessment and procedural planning. Invasive tools, such as fractional flow reserve, nonhyperemic pressure ratios, intravascular ultrasound, and optical coherence tomography, provide essential physiological and anatomic insights but are resource-intensive, prolong procedures, and increase contrast and radiation exposure. Coronary computed tomography (CT) angiography has emerged as a noninvasive modality with high diagnostic accuracy for coronary artery disease, capable of detailing plaque composition, lesion length, and vessel geometry. With the integration of CT-derived fractional flow reserve and CT myocardial perfusion imaging, coronary CT angiography now offers both anatomic and functional evaluation, bridging diagnostic and interventional decision-making. Despite guideline endorsement for coronary artery disease diagnosis, its role in guiding percutaneous coronary intervention strategies remains underutilized and absent from revascularization recommendations. This review outlines a practical, step-by-step framework for integrating coronary CT angiography into contemporary percutaneous coronary intervention planning, covering acquisition protocols, software platforms, lesion assessment, and stent strategy optimization. It also explores emerging intraprocedural applications, including fusion imaging, augmented and virtual reality, and holographic visualization. By synthesizing current evidence and identifying gaps, this review positions coronary CT angiography as a promising adjunct in precision-based percutaneous coronary intervention.