Purpose of the review: The purpose of this review is to evaluate the current state of knowledge regarding the technical challenges associated with the Post-Acquisition Fat Attenuation Index (PFAI). By examining the limitations and gaps in the current methodologies, this review aims to provide a comprehensive understanding of how various factors impact the accuracy and reliability of PFAI measurements.
Recent findings: PFAI correlates with plaque instability, as inflammation in coronary plaque alters surrounding adipose tissue composition, increasing its water content and reducing lipid content, which is detectable via cardiac CT as increased attenuation. Recent studies have demonstrated PFA's prognostic value, with elevated levels linked to higher risks of cardiac events and plaque instability. A 2022 meta-analysis confirmed its association with major adverse cardiac events. Machine learning algorithms incorporating PFA and additional imaging features have further enhanced risk prediction beyond traditional metrics. Pericoronary fat attenuation is a promising marker for assessing coronary inflammation and could be useful in predicting plaque development, rupture, and monitoring treatment response, though further prospective studies and technical standardization are needed to fully establish its clinical benefits.
Keywords: Cardiac computed tomography angiography (CCTA); Inflammation; Machine learning; Major adverse cardiac events; Pericoronary fat attenuation index (pFAI); Plaque instability.
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