Optical coherence tomography features of angiographic complex and smooth lesions in acute coronary syndromes

Comparison of adverse cardiovascular event endpoints between patients with diabetes and patients without diabetes based on coronary artery plaques: a systematic review and meta-analysis

BACKGROUND

The classification of major adverse cardiovascular event (MACE) endpoints in patients with type 2 diabetes mellitus (T2DM) and either confirmed coronary artery disease (CAD) or high CAD risk, as well as the extent of the association between T2DM and coronary plaque characteristics, remains uncertain.

PURPOSE

This meta-analysis aims to compare MACE endpoints between patients with diabetes and patients without diabetes based on coronary artery plaques.

METHODS

We searched studies from Web of Science, PubMed, Embase, and the Cochrane Library up until September 1, 2023. Two independent researchers evaluated the quality and bias of the included studies. We used odds ratio (OR) and standardized mean difference (SMD) with 95% confidence interval (CI) to assess the effect of individual lesion parameters and coronary artery plaque characteristics on MACE endpoints.

RESULTS

Seven studies covered 1218 patients with diabetes and 3038 patients without diabetes. The follow-up time ranged from 2 to 5.4 years. The pooled results indicated that in all CAD lesions, DM was more strongly associated with MACE, myocardial infarction (MI), revascularization, and rehospitalization for unstable or progressive angina. The pooled OR was 1.82 (95% CI: 1.42 to 2.33, I2 = 0%, P < 0.00001) for MACE, 2.36 (95% CI: 1.47 to 3.79, I2 = 0%, P = 0.0004) for MI, 1.83 (95% CI: 1.33 to 2.53, I2 = 0%, P = 0.0002) for revascularization, and 1.65 (95% CI: 1.20 to 2.27, I2 = 0%, P = 0.002) for rehospitalization respectively. Subgroup analysis of culprit lesions (CLs) revealed significant differences between DM and non-DM for MACE, MI, revascularization, and stent thrombosis. While non-culprit lesions (NCLs) showed differences for MACE, MI, revascularization, and rehospitalization between the two groups.

CONCLUSION

The rates of MACE, MI, and revascularization are greater in DM than in non-DM patients in terms of all lesions, CLs, and NCLs. Except for CLs, the readmission rate is greater for unstable or progressive angina. Plaque characteristics are similar between patients with and without diabetes. Prospero registration number CRD42023474226.

Heterogeneous plaque-lumen geometry is associated with major adverse cardiovascular events

Aims

Prospective studies show that only a minority of plaques with higher risk features develop future major adverse cardiovascular events (MACE), indicating the need for more predictive markers. Biomechanical estimates such as plaque structural stress (PSS) improve risk prediction but require expert analysis. In contrast, complex and asymmetric coronary geometry is associated with both unstable presentation and high PSS, and can be estimated quickly from imaging. We examined whether plaque-lumen geometric heterogeneity evaluated from intravascular ultrasound affects MACE and incorporating geometric parameters enhances plaque risk stratification.

Methods and results

We examined plaque-lumen curvature, irregularity, lumen aspect ratio (LAR), roughness, PSS, and their heterogeneity indices (HIs) in 44 non-culprit lesions (NCLs) associated with MACE and 84 propensity-matched no-MACE-NCLs from the PROSPECT study. Plaque geometry HI were increased in MACE-NCLs vs. no-MACE-NCLs across whole plaque and peri-minimal luminal area (MLA) segments (HI curvature: adjusted P = 0.024; HI irregularity: adjusted P = 0.002; HI LAR: adjusted P = 0.002; HI roughness: adjusted P = 0.004). Peri-MLA HI roughness was an independent predictor of MACE (hazard ratio: 3.21, P < 0.001). Inclusion of HI roughness significantly improved the identification of MACE-NCLs in thin-cap fibroatheromas (TCFA, P < 0.001), or with MLA ≤ 4 mm2 (P < 0.001), or plaque burden (PB) ≥ 70% (P < 0.001), and further improved the ability of PSS to identify MACE-NCLs in TCFA (P = 0.008), or with MLA ≤ 4 mm2 (P = 0.047), and PB ≥ 70% (P = 0.003) lesions.

Conclusion

Plaque-lumen geometric heterogeneity is increased in MACE vs. no-MACE-NCLs, and inclusion of geometric heterogeneity improves the ability of imaging to predict MACE. Assessment of geometric parameters may provide a simple method of plaque risk stratification.

OCT utilization: Summary statistics from the LightLab clinical initiative

OBJECTIVES

The study describes the evolution of optical coherence tomography (OCT) adoption and performance during percutaneous coronary intervention (PCI) following implementation of a standardized LightLab (LL) workflow.

BACKGROUND

The purpose of the LL Clinical Initiative was to evaluate the impact of a standardized workflow on physician efficiency, decision making, and image quality.

METHODS

The LL Clinical Initiative is a multicenter, prospective, observational clinical program. Data were collected from 48 physicians at 17 U.S. centers from 01/21/19 to 06/08/21. The study included 401 OCT-guided PCIs during the baseline phase and 1898 during the LL workflow phases. The baseline phase consisted of physicians utilizing OCT at their discretion. After completing the baseline phase, the workflow progressed through multiple phases culminating in the expansion phase, which focused on addressing greater procedural complexity. The LL workflow utilized OCT to assess plaque Morphology, lesion Length, and vessel Diameter before PCI, and optimized results by treating Medial edge dissection, stent mal-Apposition, and stent under-eXpansion (MLD MAX). High-level summary statistics were generated to elucidate trends.

RESULTS

After program implementation, there was a rise in the number of PCIs where the LL workflow was utilized compared to the baseline phase (68% during the expansion phase vs. 41% at baseline; p for trend <0.0001). Adoption of the LL workflow was associated with progressively greater procedural and lesion complexity when OCT was performed pre- and post-PCI (87% vs. 52%, p < 0.0001; 55% vs. 37%, p < 0.0001, respectively). In addition, the quality of OCT imaging obtained improved after LL workflow introduction, with over 95% of pre- and post-PCI pullback quality considered usable during the expansion phase. Finally, there was a reduction in time spent on OCT interpretation, both pre-PCI (4.6 min vs. 7.5 min, p < 0.0001) and post-PCI (2.9 min vs. 5.3 min, p < 0.0001).

CONCLUSIONS

After completion of the standardized OCT-guided workflow, there was greater uptake of OCT imaging, incorporation in more complex procedures, procedural efficiency, and image quality.

Novel predictors and adverse long-term outcomes of No-reflow phenomenon in patients with acute ST elevation myocardial infarction undergoing primary percutaneous coronary intervention

Objectives

The no-reflow phenomenon occurs in 25% of patients with ST elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI), and may be associated with adverse outcomes. The aim of our study was to detect novel predictors of no-reflow phenomenon and the resulting adverse long term outcomes.

Methods

We enrolled 400 STEMI patients undergoing primary PCI; 228 patients had TIMI flow 3 after PCI (57%) and the remaining 172 patients had TIMI flow <3 (43%). Fibrinogen to albumin ratio (FAR), high sensitive C-reactive protein to albumin ratio (CAR), and atherogenic index of plasma (AIP) were calculated. Long term mortality and morbidity during 6 months follow up were recorded. These data were compared among both groups.

Results

In multivariate regression analysis, old age (OR = 1.115, 95% CI: 1.032–1.205, P = 0.006), higher troponin level >5.6 ng/mL (OR = 1.040, 95% CI: 1.001–1.080, P = 0.04), diabetes mellitus (OR = 4.401, 95% CI: 1.081–17.923, P = 0.04) and heavy thrombus burden (OR = 16.915, 95% CI: 5.055–56.602, P < 0.001) could be considered as predictors for the development of no-reflow. Interestingly, CAR >0.21, FAR >11.56, and AIP >0.52 could be considered as novel powerful independent predictors (OR = 3.357, 95% CI: 2.288–4.927, P < 0.001, OR = 4.187, 95% CI: 2.761–6.349, P < 0.001, OR = 16.794, 95% CI: 1.018–277.01, P = 0.04, respectively). Higher long term mortality (P < 0.001) and heart failure (P < 0.001) was also strongly related to incidence of no-reflow.

Conclusion

No-reflow could be attributed to novel predictors as CAR, FAR, and AIP. This phenomenon was associated with long term adverse events as higher mortality and pump failure.

Low Plasma Adiponectin Levels Are Associated With Vulnerable Plaque Features in Patients With Acute Coronary Syndrome: An Optical Coherence Tomography Study

BACKGROUND

Vulnerable plaques are the primary cause of acute coronary syndrome (ACS). The association between in-vivo plaque vulnerability and adiponectin levels in ACS still remains to be determined.

OBJECTIVE

The purpose of this study was to investigate the correlation between adiponectin levels and vulnerable plaque features in ACS patients.

METHODS

We enrolled 107 ACS patients admitted to our institution; 83 with Non-ST elevation ACS (NSTE-ACS) and 24 with ST-elevation myocardial infarction (STEMI). Adiponectin levels were measured in these patients. Coronary angiography and subsequent optical coherence tomography (OCT) analysis of culprit lesions were performed.

RESULTS

Adiponectin level was lower in patients with complex angiographic lesions, compared to those with non-complex lesions (7.13 ± 3.04 vs. 8.94 ± 2.84 μg/ml, P = 0.002). Adiponectin level was lower in patients with plaque rupture (PR), micro-thrombi, and thin cap fibroatheroma (TCFA), compared to those with non-vulnerable features (7.19 ± 2.95 vs 8.79 ± 3.02 μg/ml, P = 0.007 & 7.29 ± 2.97 vs 8.44 ± 3.09 μg/ml, P = 0.04 and 4.76 ± 0.65 vs 9.74 ± 2.35 μg/ml, P < 0.001 μg/ml respectively). There was a significant negative correlation between adiponectin levels and lipid rich plaque extent and maximum lipid arc (r = -0.05, P < 0.001 & r = -0.03, P = 0.03, respectively). However, a significant positive correlation was observed between adiponectin levels and fibrous cap thickness (r = 0.95, P < 0.001).

CONCLUSION

Low adiponectin levels were associated with complex angiographic lesions and vulnerable plaque features in ACS patients, where there was a significant correlation between it and PR, TCFA, and lipid rich plaque.

Automatic Plaque Segmentation in Coronary Optical Coherence Tomography Images

Coronary optical coherence tomography (OCT) is a new high-resolution intravascular imaging technology that clearly depicts coronary artery stenosis and plaque information. Study of coronary OCT images is of significance in the diagnosis of coronary atherosclerotic heart disease (CAD). We introduce a new method based on the convolutional neural network (CNN) and an improved random walk (RW) algorithm for the recognition and segmentation of calcified, lipid and fibrotic plaque in coronary OCT images. First, we design CNN with three different depths (2, 4 or 6 convolutional layers) to perform the automatic recognition and select the optimal CNN model. Then, we device an improved RW algorithm. According to the gray-level distribution characteristics of coronary OCT images, the weights of intensity and texture term in the weight function of RW algorithm are adjusted by an adaptive weight. Finally, we apply mathematical morphology in combination with two RWs to accurately segment the plaque area. Compared with the ground truth of clinical segmentation results, the Jaccard similarity coefficient (JSC) of calcified and lipid plaque segmentation results is 0.864, the average symmetric contour distance (ASCD) is 0.375[Formula: see text]mm, the JSC and ASCD reliabilities are 88.33% and 92.50% respectively. The JSC of fibrotic plaque is 0.876, the ASCD is 0.349[Formula: see text]mm, the JSC and ASCD reliabilities are 90.83% and 95.83% respectively. In addition, the average segmentation time (AST) does not exceed 5 s. Reliable and significantly improved results have been achieved in this study. Compared with the CNN, traditional RW algorithm and other methods. The proposed method has the advantages of fast segmentation, high accuracy and reliability, and holds promise as an aid to doctors in the diagnosis of CAD.

Presence of multiple coronary angiographic characteristics for the diagnosis of acute coronary thrombus

BACKGROUND

Coronary angiography is frequently employed to aid in the diagnosis of acute coronary thrombosis, but there is limited data to support its efficacy. The aim of the study was to evaluate sensitivity and specificity of five commonly used angiographic characteristics for diagnosis of acute coronary thrombosis: Ambrose complex lesion morphology; spherical, ovoid, or irregular filling defect; abrupt vessel cutoff; intraluminal staining; and any coronary filling defect.

METHODS

Coronary angiography of 80 acute myocardial infarction or stable coronary artery disease subjects were assessed in blinded fashion, for the presence or absence of five angiographic characteristics. Only lesions of ≥ 10% stenosis were included in the analysis. Presence or absence of each angiographic characteristic was compared between lesions with or without the following study defined outcomes: 1) histologically confirmed thrombus, 2) highly probable thrombus, and 3) highly unlikely thrombus.

RESULTS

A total of 323 lesions were evaluated. All studied angiographic characteristics were associated with histologically confirmed and highly probable thrombotic lesions vs. lesions not meeting criteria for these outcomes (p < 0.03), except for complex Ambrose morphology which was not associated with any of the study outcomes (p > 0.05). Specificity for identifying histologically confirmed or highly probable thrombotic lesion was high (92-100%), especially for spherical, ovoid, or irregular filling defect (99-100%) and intraluminal staining (99%). Sensitivity for identification of histologically confirmed or highly probable thrombotic lesions was low for all tested angiographic characteristics (17-60%).

CONCLUSIONS

The presence of spherical, ovoid, or irregular filling defect or intraluminal staining was highly suggestive of coronary thrombus. However, none of the evaluated angiographic characteristics were useful for ruling out the presence of coronary thrombus. If confirmed in an independent cohort, these angiographic characteristic will be of significant value in confirming the diagnosis of acute coronary thrombosis.

Prevalence and predictors of culprit plaque rupture at OCT in patients with coronary artery disease: a meta-analysis

AIMS

The prevalence of plaque rupture at the culprit lesion identified by optical coherence tomography (OCT) in different clinical subset of patients undergoing coronary angiography and its clinical predictors remain to be defined.

METHODS

All studies including patients with OCT evaluation of the culprit coronary plaque were included. The prevalence of culprit plaque rupture (CPR) and thin-cap fibro-atheroma (TCFA) were the primary endpoints. The factors associated with these findings were studied in a subset of patients with different clinical presentations [ST-elevation myocardial (STEMI) vs. nonST-elevation myocardial infarction (NSTEMI) vs. unstable angina (UA) vs. stable angina pectoris (SAP)].

RESULTS

One hundred and fifty citations were initially appraised at the abstract level and 23 full-text studies were assessed. The mean prevalence of CPR and TCFA was 48.1% (40.5-55.8) and 48.7% (37.4-60.1), respectively. The prevalence of CPR and TCFA were higher in STEMI (70.4 and 76.6%) than in NSTEMI (55.6 and 56.3%) and UA (39.1 and 52.9%) or SAP (6.2 and 22.8%). In the overall population at meta-regression analysis, TCFA and current smoking were the only predictors of CPR (B 3.6:2.0-5.1, P < 0.001 and 0.06:0.02-0.1, P = 0.002, respectively). The factors associated with CPR were different depending on clinical presentation. Hypertension was the only clinical predictor for STEMI (B 3.3: 1.2.-5.3 P = 0.001), while advanced age (B 0.12: 0.02-0.22, P = 0.021), diabetes mellitus (B 0.04: 0.01-0.08, P = 0.012), and hyperlipidaemia (B 0.07:0.02-0.11, P = 0.005) were the predictors in NSTEMI and UA. No clinical predictor was found in SA.

CONCLUSIONS

Our analysis showed high rates of CPR and TCFA detected by OCT in CAD patients, especially in those with ACS, although their prevalence is not negligible in stable patients. TCFA seems to be a strong predictor of CPR in all the ACS scenarios.