Perivascular adipose tissue (PVAT) is a metabolically active tissue that influences vascular function through paracrine signaling of adipokines. Pathologically altered PVAT is associated with proinflammatory, pro-oxidative, and proatherogenic signaling in coronary vessels, and consequently contributes to the pathophysiological mechanisms underlying atherosclerosis. Bidirectional cross talk from inflamed vasculature can also induce phenotypic changes in the PVAT that can be detected noninvasively with cross-sectional imaging. Imaging modalities like computed tomography are readily available in clinical settings, and PVAT characterization with Fat Attenuation Index has emerged as a valuable prognostic tool that quantifies coronary inflammation. This article reviews the imaging, quantification, and novel radiotranscriptomic analysis of PVAT. We also describe how these could integrate into artificial intelligence-enabled risk-prediction models for personalizing medical therapy guided by an individual's inflammatory risk, and how this approach already changes clinical management in healthcare systems where it has been adopted.