In recent years, pericoronary fat radiomics on coronary CT angiography has emerged as an innovative method for assessing cardiovascular risk. Furthermore, this technique captures subtle tissue heterogeneity and vascular inflammation beyond standard plaque metrics. Consequently, clinicians can better evaluate local coronary inflammation to predict major adverse cardiac events in susceptible patients.
Diagnostic Value of Pericoronary Fat Radiomics
Specifically, a systematic review evaluated ten retrospective studies to quantify the diagnostic performance of these advanced models. However, radiomics-only models showed moderate predictive capacity with an area under the curve of 0.78. In addition, combining radiomics features with clinical variables improved discrimination to an area under the curve of 0.80.
Incremental Value of Multimodal Integration
Moreover, integrating imaging features with radiomics yielded substantial diagnostic improvements, reaching a sensitivity of 0.89. Most importantly, triple-combination models integrating radiomics, clinical data, and imaging markers achieved the highest performance with an area under the curve of 0.87. Therefore, combining pericoronary fat radiomics with routine diagnostic tools provides incremental predictive value over traditional risk assessment methods.
Clinical Implications and Future Directions
Overall, the current evidence demonstrates moderate certainty and highlights the promising role of quantitative adipose tissue analysis. Nevertheless, clinicians must acknowledge that standardized pipelines and prospective multicenter trials are necessary before routine clinical implementation. As a result, ongoing research aims to refine these diagnostic algorithms for personalized patient management.
Frequently Asked Questions
Q1: What is pericoronary fat radiomics?
Pericoronary fat radiomics is an advanced imaging analysis technique that extracts quantitative features from pericoronary adipose tissue on coronary CT angiography to assess local inflammation and cardiovascular risk.
Q2: How does pericoronary fat radiomics improve MACE prediction?
It captures subtle tissue heterogeneity beyond conventional anatomical metrics. Consequently, when combined with clinical and imaging parameters, it achieves higher predictive accuracy for major adverse cardiac events.
Q3: Is pericoronary fat radiomics currently ready for routine clinical use?
Not yet. Although initial studies demonstrate clear incremental value, standardized image processing pipelines and prospective validation studies are needed before routine adoption.
References
- Mirzohreh ST et al. Pericoronary fat radiomics on coronary CT angiography for predicting major adverse cardiac events: a systematic review and meta-analysis. Eur Radiol. 2026 Jul 28. doi: 10.1007/s00330-026-12778-z. PMID: 42521849.
- Oikonomou EK et al. Non-invasive detection of coronary inflammation using computed tomography. Lancet. 2018;392(10151):929-939.