Quantitative plaque characterization, pericoronary fat attenuation index, and fractional flow reserve: a novel method for differentiating between stable and unstable angina pectoris in a case-control study.

Accurate diagnosis of coronary artery disease is essential for preventing serious cardiovascular events. Although coronary computed tomography angiography (CCTA) is widely used in the clinic, it is limited because it only provides anatomical information, which makes differentiating in-depth between subtypes of noncalcified plaques and assessing the inflammatory state of coronary vessels difficult. Fractional flow reserve with computed tomography (FFR-CT) can be combined with CCTA to form a hybrid anatomic-physiologic diagnostic strategy. This study aimed to improve the recognition of stable and unstable angina with quantitative plaque characteristics, fat attenuation index (FAI), and fractional flow reserve with FFR-CT using a coronary artificial intelligence (AI)-assisted diagnostic system. In this retrospective case-control study, 215 and 202 patients with stable and unstable angina pectoris, respectively, who were treated at our hospital between January 2015 and August 2023, were enrolled. Propensity score matching was used to reduce clinical baseline data bias. Binary logistic regression was used to determine the risk factors for unstable angina pectoris. The diagnostic efficacy of quantitative plaque characteristics, pericoronary FAI, FFR-CT, and their combined models in differentiating stable and unstable angina pectoris was determined using the area under the receiver operating characteristic (ROC) curve. This study included 168 pairs of patients with stable or unstable angina. Patients with unstable angina had a significantly greater pericoronary FAI volume and percentage of, lipid, and fibrolipid components within the total plaque (all P<0.001) and a significantly smaller percentage of calcification components (P<0.001), FFR-CT (P=0.003), and lumen area at the narrowest point of the stenosis(P=0.003) than those with stable angina. Independent risk factors for unstable angina were FAI >-82 Hounsfield units (HU) and total intraplaque lipid component percentage >1.2% (P=0.003 and 0.009, respectively). The area under the curve (AUC) of the ROC regarding pericoronary FAI differentiating between stable and unstable angina was 0.631 (P<0.001). In contrast, the AUC of the combined model of FFR-CT, plaque characteristics, and pericoronary FAI was 0.698 (P<0.001). The AUC value of the combined model was significantly higher than that of the diagnostic model using a single index (all, P<0.001). AI-assisted diagnostic systems could provide new methods to differentiate between stable and unstable angina. Patients with FAI >-82 HU and total intraplaque lipid component percentage >1.2% had a significantly increased risk of unstable angina, a finding that may be informative for clinical decision-making.

Li D ，Guan H ，Wang Y ，Zhu T ... -  《-》

Quantitative plaque characteristics and pericoronary fat attenuation index enhance risk prediction of unstable angina in nonobstructive lesions.

The role of quantitative plaque characterization and pericoronary fat attenuation index (FAI) in nonobstructive lesions is uncertain. Hence, this study aimed to investigate artificial intelligence (AI)-based plaque characterization and pericoronary FAI in patients with nonobstructive lesions to enhance risk prediction of unstable angina. This study was conducted using the clinical data of 408 patients with cardiovascular disease diagnosed with angina pectoris. A coronary computed tomography angiography examination was performed, and quantitative plaque characteristics and pericoronary FAI were analyzed. Of the 408 patients with angina, 130 had nonobstructive lesions and 278 had obstructive ones. No significant difference in pericoronary FAI was observed between patients with nonobstructive and obstructive lesions. In patients with nonobstructive lesions, the plaque length and pericoronary FAI were significantly higher in patients with unstable angina than in those with stable angina. In patients with obstructive lesions, the plaque fibrolipid volume and percentage were significantly higher in patients with unstable angina than in those with stable angina, and the narrowest lumen area was significantly smaller. Left anterior descending peripheral (peri-LAD) FAI > -83 HU or total plaque length >20.17 mm were independent predictors of unstable angina in patients with nonobstructive lesions. In patients with obstructive lesions, peri-LAD FAI > -77 HU, total lipid volume >12.6 mm3, and narrowest lumen area ≤2.25 mm2 were independent predictors of unstable angina. Pericoronary FAI and total plaque length may be suitable imaging biomarkers for AI-based prediction of the occurrence of unstable angina in patients with nonobstructive lesions.

Li D ，Li H ，Wang Y ，Zhu T ... -  《-》

Correlation between hemodynamics assessed by FAI combined with CT-FFR and plaque characteristics in coronary artery stenosis.

While both CT-FFR and FAI are found to be associated with the development of CAD, their relationship with hemodynamics and plaque characteristics remains unclear. The present study aims to investigate the relationship between hemodynamics assessed by FAI combined with CT-FFR and plaque characteristics in functionally significant coronary artery stenosis. This retrospective study included 130 patients with suspected coronary heart disease, who were admitted to the Department of Cardiology of our hospital and underwent coronary computed tomography angiography (CCTA) from January 2022 to December 2023. Clinical baseline data and relevant auxiliary examination results were collected, and CCTA, FAI, and CT-FFR data were analyzed to investigate the relationship between these imaging parameters and both the hemodynamics and plaque characteristics of coronary artery lesions. From 130 patients, a total of 207 diseased vessels were analyzed and classified based on CAD-RADS grading: 128 vessels exhibited stenosis of less than 50%, and 79 exhibited stenosis exceeding 50%. Patients with more than one lesion of > 50% stenosis were classified into the myocardial ischemia group (44 cases), and the rest were categorized as the non-myocardial ischemia group (86 cases). Compared to the non-myocardial ischemia group, patients in the myocardial ischemia group were significantly older (p < 0.001). No significant difference was found between the two groups in sex, cardiovascular risk factors, or the indicator of stenotic vessel distribution. The minimum CT-FFR in vessels with < 50% stenosis was higher than in vessels with > 50% stenosis, ΔCT-FFR was lower in vessels with < 50% stenosis than in vessels with > 50% stenosis, and the median CT-FFR was significantly lower in vessels with > 50% stenosis than in vessels with < 50% stenosis (p < 0.001). Additionally, FAI-LAD, FAI-LCX, FAI-RCA, and FAI-Mean were found to be significantly higher in vessels with > 50% stenosis compared to vessels with < 50% stenosis (p < 0.05). A negative correlation was observed between the minimum CT-FFR among three main coronary arteries (LAD, LCX, RCA) and CAD-RADS classification, while both ΔCT-FFR and FAI were positively correlated with CAD-RADS classification (p < 0.05). Non-calcified plaques were more prevalent in the vessels with > 50% stenosis, primarily located in the LAD, while calcified plaques were predominantly observed in vessels with < 50% stenosis (p < 0.001). In addition, in vessels with > 50% stenosis, plaques were longer, the degree of luminal stenosis was greater, and both the total volume and burden of plaques were significantly greater than in vessels with < 50% stenosis (p < 0.001). Lastly, the FAIlesion value in the vessels with > 50% stenosis was higher than in vessels with < 50% stenosis (p < 0.001). FAI is associated with coronary artery stenosis and myocardial ischemia, and may serve as a novel indicator for identifying myocardial ischemia. Both FAI and CT-FFR demonstrated strong predictive abilities in significant coronary stenosis.

Duan B ，Deng S ，Xu R ，Wang Y ，He K ... -  《BMC MEDICAL IMAGING》

The predictive value of lesion-specific pericoronary fat attenuation index for major adverse cardiovascular events in patients with type 2 diabetes.

The purpose of this study was to explore the prognostic significance of the lesion-specific pericoronary fat attenuation index (FAI) in forecasting major adverse cardiovascular events (MACE) among patients with type 2 diabetes mellitus (T2DM). This study conducted a retrospective analysis of 304 patients diagnosed with T2DM who underwent coronary computed tomography angiography (CCTA) in our hospital from December 2011 to October 2021. All participants were followed for a period exceeding three years. Detailed clinical data and CCTA imaging features were carefully recorded, encompassing lesion-specific pericoronary FAI, FAI of the three prime coronary arteries, features of high-risk plaques, and the coronary artery calcium score (CACS). The MACE included in the study comprised cardiac death, acute coronary syndrome (which encompasses unstable angina pectoris and myocardial infarction), late-phase coronary revascularization procedures, and hospital admissions prompted by heart failure. Within the three-year follow-up, 76 patients with T2DM suffered from MACE. The lesion-specific pericoronary FAI in patients who experienced MACE was notably higher compared to those without MACE (-84.87 ± 11.36 Hounsfield Units (HU) vs. -88.65 ± 11.89 HU, p = 0.016). Multivariate Cox regression analysis revealed that CACS ≥ 100 (hazard ratio [HR] = 4.071, 95% confidence interval [CI] 2.157-7.683, p < 0.001) and lesion-specific pericoronary FAI higher than - 83.5 HU (HR = 2.400, 95% CI 1.399-4.120, p = 0.001) were independently associated with heightened risk of MACE in patients with T2DM over a three-year period. Kaplan-Meier analysis showed that patients with higher lesion-specific pericoronary FAI were more likely to develop MACE (p = 0.0023). Additionally, lesions characterized by higher lesion-specific pericoronary FAI values were found to have a greater proportion of high-risk plaques (p = 0.015). Subgroup analysis indicated that lesion-specific pericoronary FAI higher than - 83.5 HU (HR = 2.017, 95% CI 1.143-3.559, p = 0.015) was independently correlated with MACE in patients with T2DM who have moderate to severe coronary calcification. Moreover, the combination of CACS ≥ 100 and lesion-specific pericoronary FAI>-83.5 HU significantly enhanced the predictive value of MACE in patients with T2DM within 3 years. The elevated lesion-specific pericoronary FAI emerged as an independent prognostic factor for MACE in patients with T2DM, inclusive of those with moderate to severe coronary artery calcification. Incorporating lesion-specific pericoronary FAI with the CACS provided incremental predictive power for MACE in patients with T2DM.

Liu M ，Zhen Y ，Shang J ，Dang Y ，Zhang Q ，Ni W ，Qiao Y ，Hou Y ... -  《Cardiovascular Diabetology》

Prognostic value of computed tomography-derived fractional flow reserve in patients with diabetes mellitus and unstable angina.

Coronary artery calcification is commonly found in patients with type 2 diabetes mellitus (T2DM), which may compromise the diagnostic accuracy of coronary computed tomography angiography (CTA). Computed tomography-derived fractional flow reserve (CT-FFR), which integrates coronary anatomy with functional assessment, holds the potential to become a powerful diagnostic tool for evaluating calcified lesions. We aim to assess the prognostic value of CT-FFR for calcific lesions in patients with T2DM and unstable angina (UA). We conducted a retrospective study involving 3,392 patients who were diagnosed with T2DM and UA who underwent coronary CTA, with at least one visible calcification site. Of those, 1,091 patients and 1,372 vessels were recommended by cardiovascular specialists and completed invasive coronary angiography (ICA) and invasive fractional flow reserve (FFR) measurements. Simultaneously, those patients also underwent CT-FFR measurements and were divided into two groups based on CT-FFR values: one group with CT-FFR > 0.80 and the other with CT-FFR ≤ 0.80. Demographics, clinical data, the diagnostic performance of CT-FFR, analysis of calcified lesions on CTA, and major adverse events during follow-up were recorded. The diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the curve (AUC) of CT-FFR were 84.8%, 84.6%, 85.1%, 84.7%, 85.0%, and 84.8%, respectively, per patient, and 82.2%, 80.3.2%, 81.8%, 79.7%, 81.1%, and 82.9% respectively, per vessel. For lesion and calcification characteristics, the degree of stenosis, lesion length, rate of bifurcation lesions, diffusive lesions, occlusion, calcium volume, and coronary artery calcification score (CACS) were significantly higher in the CT-FFR ≤ 0.8 group compared to the CT-FFR > 0.8 group. In contrast, the minimum cross-sectional area was smaller in the CT-FFR ≤ 0.8 group than in the CT-FFR > 0.8 group. Major adverse cardiovascular and cerebrovascular events (MACCE) at the 3-year follow-up was significantly higher in the CT-FFR ≤ 0.8 group compared to the CT-FFR > 0.8 group. The CT-FFR value is an independent predictor of MACCE at the 3-year follow-up. CT-FFR demonstrated significant diagnostic performance using invasive FFR as the reference standard and proved to be an important predictive tool for assessing prognosis not only in calcified lesions but also in lesions with a CACS score of zero in patients with T2DM and UA. CT-FFR may serve as a valuable tool for guiding treatment decisions in these patients.

Zhao Q ，Liu L ，Xian H ，Luo X ，Zhang D ，Hou S ，Qu C ，Zhang R ，Qu X ... -  《Cardiovascular Diabetology》