Predicting Plaque Regression Based on Plaque Characteristics Identified by Optical Coherence Tomography: A Retrospective Study.

Background: Atherosclerosis is a lipid-driven, systemic immune-inflammatory disease characterized by the accumulation of plaque within the arterial walls. Plaque regression can occur following appropriate treatment interventions. Optical coherence tomography (OCT), a high-resolution imaging modality, is frequently employed to assess plaque morphology. This study aims to explore the correlation between plaque characteristics identified using OCT, particularly macrophage infiltration, and subsequent plaque regression.

Methods: In this retrospective study, data from 112 individuals with coronary artery plaques, who underwent OCT imaging at our hospital, between June 2019 and June 2024, were evaluated. Plaques were classified as lipid-rich, fibrous, or calcified based on the initial OCT findings. Macrophage infiltration levels within each plaque type were quantified. After one year of follow-up, repeat OCT imaging was performed to evaluate plaque regression. Statistical analyses were conducted to assess the relationship between initial plaque characteristics and regression outcomes.

Results: Plaques that underwent regression were more commonly lipid-rich and exhibited higher levels of macrophage infiltration compared to those without regression. Multivariate analysis identified the histological inflammation score (HIS) as an independent factor influencing plaque regression.

Conclusion: Macrophage-rich plaques, as detected by OCT, are significant predictors of plaque regression. The identification of vulnerable plaque features through OCT can enhance the early diagnosis and treatment strategies for atherosclerotic cardiovascular disease.