Plaque characteristics derived from intravascular optical coherence tomography that predict major adverse cardiovascular events

BackgroundWith its near histological resolution and its optical contrast, intravascular optical coherence tomography (IVOCT) is the only imaging modality that allows a unique assessment of microscopic plaque characteristics. This study aimed to investigate whether plaque characteristics derived from IVOCT could predict a long-term major adverse cardiovascular event (MACE). MethodsThis study was a single-center, retrospective study on 104 patients who had undergone IVOCT-guided percutaneous coronary intervention. Plaque characterization was performed using OCTOPUS software developed by our group. A total of 31 plaque features, including lesion length, lumen, calcium, fibrous cap (FC), and vulnerable plaque features (e.g., microchannel and cholesterol crystal), were computed from the baseline IVOCT images (obtained before stenting). For IVOCT plaque features, the discriminatory power for predicting MACE was determined using univariate/multivariate logistic regression as assessed by area under the receiver operating characteristic curve (AUC). ResultsOf 104 patients, MACE was identified in 24 patients (23.1%). Univariate logistic regression revealed that lesion length, maximum calcium angle, maximum calcium thickness, maximum FC angle, maximum FC area, and FC surface area were significantly associated with MACE (p<0.05). Additionally, cholesterol crystal and layered plaque showed a strong association with MACE (p<0.05). In the multivariate logistic analysis, only the FC surface area (OR 2.38, CI 0.98-5.83, p<0.05) was identified as a significant determinant for MACE, highlighting the importance of the 3D lesion analysis. The AUC of FC surface area for predicting MACE was 0.851 (95% CI 0.800-0.927, p<0.05). Luminal stenosis was not a strong predictor of the risk of MACE. ConclusionsPatients with MACE had distinct plaque characteristics in IVOCT. In particular, large FC surface areas were a risk factor. Interestingly, cap thickness, a commonly highlighted feature for lesion vulnerability, was less predictive than cap area. Studies such as this one might someday lead to recommendations for pharmaceutical and interventional approaches.