Diagnostic Performance of On-Site Automatic Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve.

BACKGROUND AND OBJECTIVES: Fractional flow reserve (FFR) is an invasive standard method to identify ischemia-causing coronary artery disease (CAD). With the advancement of technology, FFR can be noninvasively computed from coronary computed tomography angiography (CCTA). Recently, a novel simpler method has been developed to calculate on-site CCTA-derived FFR (CT-FFR) with a commercially available workstation. METHODS: A total of 319 CAD patients who underwent CCTA, invasive coronary angiography, and FFR measurement were included. The primary outcome was the accuracy of CT-FFR for defining myocardial ischemia evaluated with an invasive FFR as a reference. The presence of ischemia was defined as FFR ≤0.80. Anatomical obstructive stenosis was defined as diameter stenosis on CCTA ≥50%, and the diagnostic performance of CT-FFR and CCTA stenosis for ischemia was compared. RESULTS: Among participants (mean age 64.7±9.4 years, male 77.7%), mean FFR was 0.82±0.10, and 126 (39.5%) patients had an invasive FFR value of ≤0.80. The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CT-FFR were 80.6% (95% confidence interval [CI], 80.5-80.7%), 88.1% (95% CI, 82.4-93.7%), 75.6% (95% CI, 69.6-81.7%), 70.3% (95% CI, 63.1-77.4%), and 90.7% (95% CI, 86.2-95.2%), respectively. CT-FFR had higher diagnostic accuracy (80.6% vs. 59.1%, p<0.001) and discriminant ability (area under the curve from receiver operating characteristic curve 0.86 vs. 0.64, p<0.001), compared with anatomical obstructive stenosis on CCTA. CONCLUSIONS: This novel CT-FFR obtained from an on-site workstation demonstrated clinically acceptable diagnostic performance and provided better diagnostic accuracy and discriminant ability for identifying hemodynamically significant lesions than CCTA alone.

Artificial Intelligence-Enabled Quantitative Coronary Plaque and Hemodynamic Analysis for Predicting Acute Coronary Syndrome.

BACKGROUND: A lesion-level risk prediction for acute coronary syndrome (ACS) needs better characterization. OBJECTIVES: This study sought to investigate the additive value of artificial intelligence-enabled quantitative coronary plaque and hemodynamic analysis (AI-QCPHA). METHODS: Among ACS patients who underwent coronary computed tomography angiography (CTA) from 1 month to 3 years before the ACS event, culprit and nonculprit lesions on coronary CTA were adjudicated based on invasive coronary angiography. The primary endpoint was the predictability of the risk models for ACS culprit lesions. The reference model included the Coronary Artery Disease Reporting and Data System, a standardized classification for stenosis severity, and high-risk plaque, defined as lesions with ≥2 adverse plaque characteristics. The new prediction model was the reference model plus AI-QCPHA features, selected by hierarchical clustering and information gain in the derivation cohort. The model performance was assessed in the validation cohort. RESULTS: Among 351 patients (age: 65.9 ± 11.7 years) with 2,088 nonculprit and 363 culprit lesions, the median interval from coronary CTA to ACS event was 375 days (Q1-Q3: 95-645 days), and 223 patients (63.5%) presented with myocardial infarction. In the derivation cohort (n = 243), the best AI-QCPHA features were fractional flow reserve across the lesion, plaque burden, total plaque volume, low-attenuation plaque volume, and averaged percent total myocardial blood flow. The addition of AI-QCPHA features showed higher predictability than the reference model in the validation cohort (n = 108) (AUC: 0.84 vs 0.78; P < 0.001). The additive value of AI-QCPHA features was consistent across different timepoints from coronary CTA. CONCLUSIONS: AI-enabled plaque and hemodynamic quantification enhanced the predictability for ACS culprit lesions over the conventional coronary CTA analysis. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary Computed Tomography Angiography and Computational Fluid Dynamics II [EMERALD-II]; NCT03591328).

Association of epicardial adipose tissue with metabolic risk factors on cardiovascular outcomes: serial coronary computed tomography angiography study.

BACKGROUND/AIMS: Epicardial adipose tissue (EAT) shares pathophysiological properties with other visceral fats and potentially triggers local inflammation. However, the association of EAT with cardiovascular disease (CVD) is still debatable. The study aimed to observe the changes and associations in EAT and risk factors over time, as well as to investigate whether EAT was associated with CVD. METHODS: A total of 762 participants from Seoul National University Hospital (SNUH) and SNUH Gangnam Center were included in this study. EAT was measured using coronary computed tomography angiography. RESULTS: Baseline EAT level was positively associated with body mass index (BMI), calcium score, atherosclerotic cardiovascular disease (ASCVD) 10-year risk score, glucose, triglycerides (TG)/high-density lipoprotein (HDL), but not with total cholesterol, low-density lipoprotein (LDL). At follow-up, EAT levels increased in all groups, with low EAT groups demonstrating a significant increase in EAT per year. Change in EAT was associated with a change in BMI, TG/HDL, and glucose, while changes in LDL, calcium score, and ASCVD 10-year risk score were not associated. Although calcium score and ASCVD 10-year risk score were associated with CVD events, baseline information of EAT, baseline EAT/body surface area, or EAT change was not available. CONCLUSION: Metabolic risks, e.g., BMI, TG/HDL, and glucose, were associated with EAT change per year, whereas classical CVD risks, e.g., LDL, calcium score, and ASCVD 10-year risk score, were not. The actual CVD event was not associated with EAT volume, warranting future studies combining qualitative assessments with quantitative ones.

Prediction of the development of new coronary atherosclerotic plaques with radiomics.

BACKGROUND: Radiomics is expected to identify imaging features beyond the human eye. We investigated whether radiomics can identify coronary segments that will develop new atherosclerotic plaques on coronary computed tomography angiography (CCTA). METHODS: From a prospective multinational registry of patients with serial CCTA studies at ≥ 2-year intervals, segments without identifiable coronary plaque at baseline were selected and radiomic features were extracted. Cox models using clinical risk factors (Model 1), radiomic features (Model 2) and both clinical risk factors and radiomic features (Model 3) were constructed to predict the development of a coronary plaque, defined as total PV â€‹≥ â€‹1 â€‹mm3, at follow-up CCTA in each segment. RESULTS: In total, 9583 normal coronary segments were identified from 1162 patients (60.3 â€‹± â€‹9.2 years, 55.7% male) and divided 8:2 into training and test sets. At follow-up CCTA, 9.8% of the segments developed new coronary plaque. The predictive power of Models 1 and 2 was not different in both the training and test sets (C-index [95% confidence interval (CI)] of Model 1 vs. Model 2: 0.701 [0.690-0.712] vs. 0.699 [0.0.688-0.710] and 0.696 [0.671-0.725] vs. 0.0.691 [0.667-0.715], respectively, all p â€‹> â€‹0.05). The addition of radiomic features to clinical risk factors improved the predictive power of the Cox model in both the training and test sets (C-index [95% CI] of Model 3: 0.772 [0.762-0.781] and 0.767 [0.751-0.787], respectively, all p â€‹< â€‹00.0001 compared to Models 1 and 2). CONCLUSION: Radiomic features can improve the identification of segments that would develop new coronary atherosclerotic plaque. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT0280341.

Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry.

OBJECTIVES: No clear recommendations are endorsed by the different scientific societies on the clinical use of repeat coronary computed tomography angiography (CCTA) in patients with non-obstructive coronary artery disease (CAD). This study aimed to develop and validate a practical CCTA risk score to predict medium-term disease progression in patients at a low-to-intermediate probability of CAD. METHODS: Patients were part of the Progression of AtheRosclerotic PlAque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry. Specifically, 370 (derivation cohort) and 219 (validation cohort) patients with two repeat, clinically indicated CCTA scans, non-obstructive CAD, and absence of high-risk plaque (≥ 2 high-risk features) at baseline CCTA were included. Disease progression was defined as the new occurrence of ≥ 50% stenosis and/or high-risk plaque at follow-up CCTA. RESULTS: In the derivation cohort, 104 (28%) patients experienced disease progression. The median time interval between the two CCTAs was 3.3 years (2.7-4.8). Odds ratios for disease progression derived from multivariable logistic regression were as follows: 4.59 (95% confidence interval: 1.69-12.48) for the number of plaques with spotty calcification, 3.73 (1.46-9.52) for the number of plaques with low attenuation component, 2.71 (1.62-4.50) for 25-49% stenosis severity, 1.47 (1.17-1.84) for the number of bifurcation plaques, and 1.21 (1.02-1.42) for the time between the two CCTAs. The C-statistics of the model were 0.732 (0.676-0.788) and 0.668 (0.583-0.752) in the derivation and validation cohorts, respectively. CONCLUSIONS: The new CCTA-based risk score is a simple and practical tool that can predict mid-term CAD progression in patients with known non-obstructive CAD. CLINICAL RELEVANCE STATEMENT: The clinical implementation of this new CCTA-based risk score can help promote the management of patients with non-obstructive coronary disease in terms of timing of imaging follow-up and therapeutic strategies. KEY POINTS: • No recommendations are available on the use of repeat CCTA in patients with non-obstructive CAD. • This new CCTA score predicts mid-term CAD progression in patients with non-obstructive stenosis at baseline. • This new CCTA score can help guide the clinical management of patients with non-obstructive CAD.

Identification of Mitral Valve Prolapse on Non-electrocardiography-gated Enhanced Chest Computed Tomography.

PURPOSE: The primary imaging modality for the diagnosis of mitral valve prolapse (MVP) is echocardiography supplemented by electrocardiography (ECG)-gated cardiac computed tomography (CT) angiography. However, we have recently encountered patients with MVP who were initially identified on non-ECG-gated enhanced chest CT. The purpose of this study is to evaluate the diagnostic accuracy of non-ECG-gated enhanced chest CT to predict the presence of MVP. PATIENTS AND METHODS: Of 92 patients (surgically confirmed MVP who underwent non-ECG-gated chest CT), 27 patients were excluded for motion artifact or insufficient surgical correlation, and 65 patients were ultimately included. As a control, 65 patients with dyspnea and without MVP (non-ECG-gated chest CT and echocardiography were performed within 1 month) were randomly selected. We retrospectively analyzed an asymmetric double line sign on axial CT images for the presence of MVP. The asymmetric double line sign was defined as the presence of a linear structure, not located in the plane traversing the mitral annulus. RESULTS: Use of the asymmetric double line sign to predict MVP on non-ECG-gated CT showed modest sensitivity, high specificity, modest negative predictive value, and high positive predictive value of 59% (38/65), 99% (64/65), 70% (64/91), and 97% (38/39), respectively. CONCLUSION: The asymmetric double line sign on non-ECG-gated enhanced chest CT may be a valuable finding to predict the presence of MVP. Familiarity with this CT finding may lead to prompt diagnosis and proper management of MVP.

How early can atherosclerosis be detected by coronary CT angiography? Insights from quantitative CT analysis of serial scans in the PARADIGM trial.

BACKGROUND: Non-obstructing small coronary plaques may not be well recognized by expert readers during coronary computed tomography angiography (CCTA) evaluation. Recent developments in atherosclerosis imaging quantitative computed tomography (AI-QCT) enabled by machine learning allow for whole-heart coronary phenotyping of atherosclerosis, but its diagnostic role for detection of small plaques on CCTA is unknown. METHODS: We performed AI-QCT in patients who underwent serial CCTA in the multinational PARADIGM study. AI-QCT results were verified by a level III experienced reader, who was blinded to baseline and follow-up status of CCTA. This retrospective analysis aimed to characterize small plaques on baseline CCTA and evaluate their serial changes on follow-up imaging. Small plaques were defined as a total plaque volume <50 â€‹mm3. RESULTS: A total of 99 patients with 502 small plaques were included. The median total plaque volume was 6.8 â€‹mm3 (IQR 3.5-13.9 â€‹mm3), most of which was non-calcified (median 6.2 â€‹mm3; 2.9-12.3 â€‹mm3). The median age at the time of baseline CCTA was 61 years old and 63% were male. The mean interscan period was 3.8 â€‹± â€‹1.6 years. On follow-up CCTA, 437 (87%) plaques were present at the same location as small plaques on baseline CCTA; 72% were larger and 15% decreased in volume. The median total plaque volume and non-calcified plaque volume increased to 18.9 â€‹mm3 (IQR 8.3-45.2 â€‹mm3) and 13.8 â€‹mm3 (IQR 5.7-33.4 â€‹mm3), respectively, among plaques that persisted on follow-up CCTA. Small plaques no longer visualized on follow-up CCTA were significantly more likely to be of lower volume, shorter in length, non-calcified, and more distal in the coronary artery, as compared with plaques that persisted at follow-up. CONCLUSION: In this retrospective analysis from the PARADIGM study, small plaques (<50 â€‹mm3) identified by AI-QCT persisted at the same location and were often larger on follow-up CCTA.

Differential predictability for high-risk plaque characteristics between fractional flow reserve and instantaneous wave-free ratio.

To evaluate the differential associations of high-risk plaque characteristics (HRPC) with resting or hyperemic physiologic indexes (instantaneous wave-free ratio [iFR] or fractional flow reserve [FFR]), a total of 214 vessels from 127 patients with stable angina or acute coronary syndrome who underwent coronary computed tomography angiography (CCTA) and invasive physiologic assessment were investigated. HPRC were classified into quantitative (minimal luminal area < 4 mm2 or plaque burden ≥ 70%) and qualitative features (low attenuation plaque, positive remodeling, napkin ring sign, or spotty calcification). Vessels with FFR ≤ 0.80 or iFR ≤ 0.89 had significantly higher proportions of HRPC than those with FFR > 0.80 or iFR > 0.89, respectively. FFR was independently associated with both quantitative and qualitative HRPC, but iFR was only associated with quantitative HRPC. Both FFR and iFR were significantly associated with the presence of ≥ 3 HRPC, and FFR demonstrated higher discrimination ability than iFR (AUC 0.703 vs. 0.648, P = 0.045), which was predominantly driven by greater discriminating ability of FFR for quantitative HRPC (AUC 0.832 vs. 0.744, P = 0.005). In conclusion, both FFR and iFR were significantly associated with CCTA-derived HRPC. Compared with iFR, however, FFR was independently associated with the presence of qualitative HRPC and showed a higher predictive ability for the presence of ≥ 3 HRPC.

Effects of renin-angiotensin-aldosterone-system inhibitors on coronary atherosclerotic plaques: The PARADIGM registry.

BACKGROUND AND AIMS: Inhibition of Renin-Angiotensin-Aldosterone-System (RAAS) has been hypothesized to improve endothelial function and reduce plaque inflammation, however, their impact on the progression of coronary atherosclerosis is unclear. We aim to study the effects of RAAS inhibitor on plaque progression and composition assessed by serial coronary CT angiography (CCTA). METHODS: We performed a prospective, multinational study consisting of a registry of patients without history of CAD, who underwent serial CCTAs. Patients using RAAS inhibitors were propensity matched to RAAS inhibitor naïve patients based on clinical and CCTA characteristics at baseline. Atherosclerotic plaques in CCTAs were quantitatively analyzed for percent atheroma volume (PAV) according to plaque composition. Interactions between RAAS inhibitor use and baseline PAV on plaque progression were assessed in the unmatched cohort using a multivariate linear regression model. RESULTS: Of 1248 patients from the registry, 299 RAAS inhibitor taking patients were matched to 299 RAAS inhibitor naïve patients. Over a mean interval of 3.9 years, there was no significant difference in annual progression of total PAV between RAAS inhibitor naïve vs taking patients (0.75 vs 0.79%/year, p = 0.66). With interaction testing in the unmatched cohort, however, RAAS inhibitor use was significantly associated with lower non-calcified plaque progression (Beta coefficient -0.100, adjusted p = 0.038) with higher levels of baseline PAV. CONCLUSIONS: The use of RAAS inhibitors over a period of nearly 4 years did not significantly impact on total atherosclerotic plaque progression or various plaque components. However, interaction testing to assess the differential effect of RAAS inhibition based on baseline PAV suggested a significant decrease in progression of non-calcified plaque in patients with a higher burden of baseline atherosclerosis, which should be considered hypothesis generating.

The effect of non-optimal lipids on the progression of coronary artery calcification in statin-naïve young adults: results from KOICA registry.

Background: Despite the importance of attaining optimal lipid levels from a young age to secure long-term cardiovascular health, the detailed impact of non-optimal lipid levels in young adults on coronary artery calcification (CAC) is not fully explored. We sought to investigate the risk of CAC progression as per lipid profiles and to demonstrate lipid optimality in young adults. Methods: From the KOrea Initiative on Coronary Artery calcification (KOICA) registry that was established in six large volume healthcare centers in Korea, 2,940 statin-naïve participants aged 20-45 years who underwent serial coronary calcium scans for routine health check-ups between 2002 and 2017 were included. The study outcome was CAC progression, which was assessed by the square root method. The risk of CAC progression was analyzed according to the lipid optimality and each lipid parameter. Results: In this retrospective cohort (mean age, 41.3 years; men 82.4%), 477 participants (16.2%) had an optimal lipid profile, defined as triglycerides <150 mg/dl, LDL cholesterol <100 mg/dl, and HDL cholesterol >60 mg/dl. During follow-up (median, 39.7 months), CAC progression was observed in 434 participants (14.8%), and more frequent in the non-optimal lipid group (16.5% vs. 5.7%; p < 0.001). Non-optimal lipids independently increased the risk of CAC progression [adjusted hazard ratio (aHR), 1.97; p = 0.025], in a dose-dependent manner. Even in relatively low-risk participants with an initial calcium score of zero (aHR, 2.13; p = 0.014), in their 20 s or 30 s (aHR 2.15; p = 0.041), and without other risk factors (aHR 1.45; p = 0.038), similar results were demonstrable. High triglycerides had the greatest impact on CAC progression in this young adult population. Conclusion: Non-optimal lipid levels were significantly associated with the risk of CAC progression in young adults, even at low-risk. Screening and intervention for non-optimal lipid levels, particularly triglycerides, from an early age might be of clinical value.

Performance of a Novel CT-Derived Fractional Flow Reserve Measurement to Detect Hemodynamically Significant Coronary Stenosis.

BACKGROUND: Fractional flow reserve (FFR) based on computed tomography (CT) has been shown to better identify ischemia-causing coronary stenosis. However, this current technology requires high computational power, which inhibits its widespread implementation in clinical practice. This prospective, multicenter study aimed at validating the diagnostic performance of a novel simple CT based fractional flow reserve (CT-FFR) calculation method in patients with coronary artery disease. METHODS: Patients who underwent coronary CT angiography (CCTA) within 90 days and invasive coronary angiography (ICA) were prospectively enrolled. A hemodynamically significant lesion was defined as an FFR ≤ 0.80, and the area under the receiver operating characteristic curve (AUC) was the primary measure. After the planned analysis for the initial algorithm A, we performed another set of exploratory analyses for an improved algorithm B. RESULTS: Of 184 patients who agreed to participate in the study, 151 were finally analyzed. Hemodynamically significant lesions were observed in 79 patients (52.3%). The AUC was 0.71 (95% confidence interval [CI], 0.63-0.80) for CCTA, 0.65 (95% CI, 0.56-0.74) for CT-FFR algorithm A (P = 0.866), and 0.78 (95% CI, 0.70-0.86) for algorithm B (P = 0.112). Diagnostic accuracy was 0.63 (0.55-0.71) for CCTA alone, 0.66 (0.58-0.74) for algorithm A, and 0.76 (0.68-0.82) for algorithm B. CONCLUSION: This study suggests the feasibility of automated CT-FFR, which can be performed on-site within several hours. However, the diagnostic performance of the current algorithm does not meet the a priori criteria for superiority. Future research is required to improve the accuracy.

Endocardial versus whole-myocardial tracking global longitudinal strain analysis in patients with hypertrophic cardiomyopathy: A preliminary comparative study.

BACKGROUND AND OBJECTIVES: We investigated whether the feasibility of left ventricular (LV) global longitudinal strain (GLS) in hypertrophic cardiomyopathy (HCM) varies according to the methodology (e.g. endocardial vs. whole myocardial tracking techniques). METHODS: We retrospectively analyzed 111 consecutive patients with HCM (median age, 58 years; male, 68.5%) who underwent both transthoracic echocardiography (TTE) and cardiac magnetic resonance imaging (apical 29.7%, septal 33.3%, and diffuse or mixed 37.0%). TTE-whole myocardial and TTE-endocardial GLS were measured and compared in terms of association with late gadolinium enhancement (LGE) extent and discrimination performance for extensive LGE (>15% of the LV myocardium). RESULTS: Although TTE-whole myocardial and TTE-endocardial GLS were significantly correlated, absolute TTE-endocardial GLS values (19.3 [16.2-21.9] %) were higher than TTE-whole myocardial GLS values (13.3[10.9-15.6] %, p<0.001). Both TTE-derived GLS parameters were significantly correlated with the LGE extent and independently associated with extensive LGE (odds ratio [OR] 1.30, p = 0.022; and OR 1.24, p = 0.013, respectively). Discrimination performance for extensive LGE was comparable between TTE-whole myocardial and TTE-endocardial GLS (area under the curve [AUC], 0.747 and 0.754, respectively, pdifference = 0.610). However, among patients with higher LV mass index (>70 g/m2), only TTE-whole myocardial GLS correlated with LGE extent and was independently associated with extensive LGE (OR 1.35, p = 0.042), while TTE-endocardial GLS did not. Additionally, TTE-whole myocardial GLS had better discrimination performance for extensive LGE than TTE-endocardial GLS (AUC, 0.705 and 0.668, respectively, pdifference = 0.006). CONCLUSION: TTE-derived GLS using either the endocardial or whole myocardial tracking technique is feasible in patients with HCM. However, in those with severe hypertrophy, TTE-whole myocardial GLS is better than TTE-endocardial GLS.

Assessment of Normal Systolic Blood Pressure Maintenance with the Risk of Coronary Artery Calcification Progression in Asymptomatic Metabolically Healthy Korean Adults with Normal Weight, Overweight, and Obesity.

Metabolically healthy obesity (MHO) is known to have a close association with subclinical coronary atherosclerosis. Despite recent data on the benefit of intensive systolic blood pressure (SBP) control in diverse clinical conditions, little is known regarding the association of normal SBP maintenance (SBPmaintain) with coronary artery calcification (CAC) progression in MHO. This study included 2724 asymptomatic adults (48.8 ± 7.8 years; 77.9% men) who had no metabolic abnormalities except overweight and obesity. Participants with normal weight (44.2%), overweight (31.6%), and obesity (24.2%) were divided into two groups: normal SBPmaintain (follow-up SBP < 120 mm Hg) and ≥elevated SBPmaintain (follow-up SBP ≥ 120 mm Hg). CAC progression was defined using the SQRT method, a difference of ≥2.5 between the square root (√) of the baseline and follow-up coronary artery calcium score. During a mean follow-up of 3.4 years, the proportion of normal SBPmaintain (76.2%, 65.2%, and 59.1%) and the incidence of CAC progression (15.0%, 21.3%, and 23.5%) was different in participants with normal weight, overweight, and obesity (all p < 0.05, respectively). The incidence of CAC progression was lower in the normal SBPmaintain group than in the ≥elevated SBPmaintain group in only participants with obesity (20.8% vs. 27.4%, p = 0.048). In multiple logistic models, compared to participants with normal weight, those with obesity had a higher risk of CAC progression. Normal SBPmaintain was independently associated with the decreased risk of CAC progression in participants with obesity. MHO had a significant association with CAC progression. Normal SBPmaintain reduced the risk of CAC progression in asymptomatic adults with MHO.

Impact of statins based on high-risk plaque features on coronary plaque progression in mild stenosis lesions: results from the PARADIGM study.

AIMS: To investigate the impact of statins on plaque progression according to high-risk coronary atherosclerotic plaque (HRP) features and to identify predictive factors for rapid plaque progression in mild coronary artery disease (CAD) using serial coronary computed tomography angiography (CCTA). METHODS AND RESULTS: We analyzed mild stenosis (25-49%) CAD, totaling 1432 lesions from 613 patients (mean age, 62.2 years, 63.9% male) and who underwent serial CCTA at a ≥2 year inter-scan interval using the Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging (NCT02803411) registry. The median inter-scan period was 3.5 ± 1.4 years; plaques were quantitatively assessed for annualized percent atheroma volume (PAV) and compositional plaque volume changes according to HRP features, and the rapid plaque progression was defined by the ≥90th percentile annual PAV. In mild stenotic lesions with ≥2 HRPs, statin therapy showed a 37% reduction in annual PAV (0.97 ± 2.02 vs. 1.55 ± 2.22, P = 0.038) with decreased necrotic core volume and increased dense calcium volume compared to non-statin recipient mild lesions. The key factors for rapid plaque progression were ≥2 HRPs [hazard ratio (HR), 1.89; 95% confidence interval (CI), 1.02-3.49; P = 0.042], current smoking (HR, 1.69; 95% CI 1.09-2.57; P = 0.017), and diabetes (HR, 1.55; 95% CI, 1.07-2.22; P = 0.020). CONCLUSION: In mild CAD, statin treatment reduced plaque progression, particularly in lesions with a higher number of HRP features, which was also a strong predictor of rapid plaque progression. Therefore, aggressive statin therapy might be needed even in mild CAD with higher HRPs. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT02803411.

Long-term prognostic implications of hemodynamic and plaque assessment using coronary CT angiography.

BACKGROUND AND AIMS: Hemodynamic and plaque characteristics can be analyzed using coronary CT angiography (CTA). We aimed to explore long-term prognostic implications of hemodynamic and plaque characteristics using coronary CT angiography (CTA). METHODS: Invasive fractional flow reserve (FFR) and CTA-derived FFR (FFRCT) were undertaken for 136 lesions in 78 vessels and followed-up to 10 years until December 2020. FFRCT, wall shear stress (WSS), change in FFRCT across the lesion (ΔFFRCT), total plaque volume (TPV), percent atheroma volume (PAV), and low-attenuation plaque volume (LAPV) for target lesions [L] and vessels [V] were obtained by independent core laboratories. Their collective influence was evaluated for the clinical endpoints of target vessel failure (TVF) and target lesion failure (TLF). RESULTS: During a median follow-up of 10.1 years, PAV[V] (per 10% increase, HR 2.32 [95% CI 1.11-4.86], p = 0.025), and FFRCT[V] (per 0.1 increase, HR 0.56 [95% CI 0.37-0.84], p = 0.006) were independent predictors of TVF for the per-vessel analysis, and WSS[L] (per 100 dyne/cm2 increase, HR 1.43 [1.09-1.88], p = 0.010), LAPV[L] (per 10 mm3 increase, HR 3.81 [1.16-12.5], p = 0.028), and ΔFFRCT[L] (per 0.1 increase, HR 1.39 [1.02-1.90], p = 0.040) were independent predictors of TLF for the per-lesion analysis after adjustment for clinical and lesion characteristics. The addition of both plaque and hemodynamic predictors improved the predictability for 10-year TVF and TLF of clinical and lesion characteristics (all p < 0.05). CONCLUSIONS: Vessel- and lesion-level hemodynamic characteristics, and vessel-level plaque quantity, and lesion-level plaque compositional characteristics assessed by CTA offer independent and additive long-term prognostic value.

Centerline depth world for left atrial appendage orifice localization using reinforcement learning.

Left atrial appendage (LAA) occlusion (LAAO) is a minimally invasive implant-based method to prevent cardiovascular stroke in patients with non-valvular atrial fibrillation. Assessing the LAA orifice in preoperative CT angiography plays a crucial role in choosing an appropriate LAAO implant size and a proper C-arm angulation. However, accurate orifice localization is hard because of the high anatomic variation of LAA, and unclear position and orientation of the orifice in available CT views. With the major research focus being on LAA segmentation, the only existing computational method for orifice localization utilized a rule-based decision. Nonetheless, using such a fixed rule may yield high localization error due to the varied anatomy of LAA. While deep learning-based models usually show improvements under such variation, learning an effective localization model is difficult because of the tiny orifice structure compared to the vast search space of CT volume. In this paper, we propose a centerline depth-based reinforcement learning (RL) world for effective orifice localization in a small search space. In our scheme, an RL agent observes the centerline-to-surface distance and navigates through the LAA centerline to localize the orifice. Thus, the search space is significantly reduced facilitating improved localization. The proposed formulation could result in high localization accuracy compared to the expert annotations. Moreover, the localization process takes about 7.3 s which is 18 times more efficient than the existing method. Therefore, this can be a useful aid to physicians during the preprocedural planning of LAAO.

Clinical and Coronary Plaque Predictors of Atherosclerotic Nonresponse to Statin Therapy.

BACKGROUND: Statins reduce the incidence of major cardiovascular events, but residual risk remains. The study examined the determinants of atherosclerotic statin nonresponse. OBJECTIVES: This study aimed to investigate factors associated with statin nonresponse-defined atherosclerosis progression in patients treated with statins. METHODS: The multicenter PARADIGM (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging) registry included patients who underwent serial coronary computed tomography angiography ≥2 years apart, with whole-heart coronary tree quantification of vessel, lumen, and plaque, and matching of baseline and follow-up coronary segments and lesions. Patients with statin use at baseline and follow-up coronary computed tomography angiography were included. Atherosclerotic statin nonresponse was defined as an absolute increase in percent atheroma volume (PAV) of 1.0% or more per year. Furthermore, a secondary endpoint was defined by the additional requirement of progression of low-attenuation plaque or fibro-fatty plaque. RESULTS: The authors included 649 patients (age 62.0 ± 9.0 years, 63.5% male) on statin therapy and 205 (31.5%) experienced atherosclerotic statin nonresponse. Age, diabetes, hypertension, and all atherosclerotic plaque features measured at baseline scan (high-risk plaque [HRP] features, calcified and noncalcified PAV, and lumen volume) were significantly different between patients with and without atherosclerotic statin nonresponse, whereas only diabetes, number of HRP features, and noncalcified and calcified PAV were independently associated with atherosclerotic statin nonresponse (odds ratio [OR]: 1.41 [95% CI: 0.95-2.11], OR: 1.15 [95% CI: 1.09-1.21], OR: 1.06 [95% CI: 1.02-1.10], OR: 1.07 [95% CI: 1.03-1.12], respectively). For the secondary endpoint (N = 125, 19.2%), only noncalcified PAV and number of HRP features were the independent determinants (OR: 1.08 [95% CI: 1.03-1.13] and OR: 1.21 [95% CI: 1.06-1.21], respectively). CONCLUSIONS: In patients treated with statins, baseline plaque characterization by plaque burden and HRP is associated with atherosclerotic statin nonresponse. Patients with the highest plaque burden including HRP were at highest risk for plaque progression, despite statin therapy. These patients may need additional therapies for further risk reduction.

Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry.

BACKGROUND AND HYPOTHESIS: The recently introduced Bayesian quantile regression (BQR) machine-learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coronary artery disease (CAD) using the BQR model in a vessel-specific manner. METHODS: From the data of 1,463 patients obtained from the PARADIGM (NCT02803411) registry, we analyzed the lumen diameter stenosis (DS) of the three vessels: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). Two models for predicting DS and DS changes were developed. Baseline CV risk factors, symptoms, and laboratory test results were used as the inputs. The conditional 10%, 25%, 50%, 75%, and 90% quantile functions of the maximum DS and DS change of the three vessels were estimated using the BQR model. RESULTS: The 90th percentiles of the DS of the three vessels and their maximum DS change were 41%-50% and 5.6%-7.3%, respectively. Typical anginal symptoms were associated with the highest quantile (90%) of DS in the LAD; diabetes with higher quantiles (75% and 90%) of DS in the LCx; dyslipidemia with the highest quantile (90%) of DS in the RCA; and shortness of breath showed some association with the LCx and RCA. Interestingly, High-density lipoprotein cholesterol showed a dynamic association along DS change in the per-patient analysis. CONCLUSIONS: This study demonstrates the clinical utility of the BQR model for evaluating the comprehensive relationship between risk factors and baseline-grade CAD and its progression.

Longitudinal Quantitative Assessment of Coronary Atherosclerotic Plaque Burden Related to Serum Hemoglobin Levels.

Background: Despite a potential role of hemoglobin in atherosclerosis, data on coronary plaque volume changes (PVC) related to serum hemoglobin levels are limited. Objectives: The authors sought to evaluate coronary atherosclerotic plaque burden changes related to serum hemoglobin levels using serial coronary computed tomographic angiography (CCTA). Methods: A total of 830 subjects (age 61 ± 10 years, 51.9% male) who underwent serial CCTA were analyzed. The median interscan period was 3.2 (IQR: 2.5-4.4) years. Quantitative assessment of coronary plaques was performed at both scans. All participants were stratified into 4 groups based on the quartile of baseline hemoglobin levels. Annualized total PVC (mm3/year) was defined as total PVC divided by the interscan period. Results: Baseline total plaque volume (mm3) was not different among all groups (group I [lowest]: 34.1 [IQR: 0.0-127.4] vs group II: 28.8 [IQR: 0.0-123.0] vs group III: 49.9 [IQR: 5.6-135.0] vs group IV [highest]: 34.3 [IQR: 0.0-130.7]; P = 0.235). During follow-up, serum hemoglobin level changes (Δ hemoglobin; per 1 g/dL) was related to annualized total PVC (ß = -0.114) in overall participants (P < 0.05). After adjusting for age, sex, traditional risk factors, baseline hemoglobin and creatinine levels, baseline total plaque volume, and the use of aspirin, beta-blocker, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, and statin, Δ hemoglobin significantly affected annualized total PVC in only the composite of groups I and II (ß = -2.401; P = 0.004). Conclusions: Serial CCTA findings suggest that Δ hemoglobin has an independent effect on coronary atherosclerosis. This effect might be influenced by baseline hemoglobin levels. (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging [PARADIGM]; NCT02803411).