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).

Interaction of AI-Enabled Quantitative Coronary Plaque Volumes on Coronary CT Angiography, FFRCT, and Clinical Outcomes: A Retrospective Analysis of the ADVANCE Registry.

BACKGROUND: Luminal stenosis, computed tomography-derived fractional-flow reserve (FFRCT), and high-risk plaque features on coronary computed tomography angiography are all known to be associated with adverse clinical outcomes. The interactions between these variables, patient outcomes, and quantitative plaque volumes have not been previously described. METHODS: Patients with coronary computed tomography angiography (n=4430) and one-year outcome data from the international ADVANCE (Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care) registry underwent artificial intelligence-enabled quantitative coronary plaque analysis. Optimal cutoffs for coronary total plaque volume and each plaque subtype were derived using receiver-operator characteristic curve analysis. The resulting plaque volumes were adjusted for age, sex, hypertension, smoking status, type 2 diabetes, hyperlipidemia, luminal stenosis, distal FFRCT, and translesional delta-FFRCT. Median plaque volumes and optimal cutoffs for these adjusted variables were compared with major adverse cardiac events, late revascularization, a composite of the two, and cardiovascular death and myocardial infarction. RESULTS: At one year, 55 patients (1.2%) had experienced major adverse cardiac events, and 123 (2.8%) had undergone late revascularization (>90 days). Following adjustment for age, sex, risk factors, stenosis, and FFRCT, total plaque volume above the receiver-operator characteristic curve-derived optimal cutoff (total plaque volume >564 mm3) was associated with the major adverse cardiac event/late revascularization composite (adjusted hazard ratio, 1.515 [95% CI, 1.093-2.099]; P=0.0126), and both components. Total percent atheroma volume greater than the optimal cutoff was associated with both major adverse cardiac event/late revascularization (total percent atheroma volume >24.4%; hazard ratio, 2.046 [95% CI, 1.474-2.839]; P<0.0001) and cardiovascular death/myocardial infarction (total percent atheroma volume >37.17%, hazard ratio, 4.53 [95% CI, 1.943-10.576]; P=0.0005). Calcified, noncalcified, and low-attenuation percentage atheroma volumes above the optimal cutoff were associated with all adverse outcomes, although this relationship was not maintained for cardiovascular death/myocardial infarction in analyses stratified by median plaque volumes. CONCLUSIONS: Analysis of the ADVANCE registry using artificial intelligence-enabled quantitative plaque analysis shows that total plaque volume is associated with one-year adverse clinical events, with incremental predictive value over luminal stenosis or abnormal physiology by FFRCT. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02499679.

Impact of Smoking on Coronary Volume-to-Myocardial Mass Ratio: An ADVANCE Registry Substudy.

Purpose To examine the relationship between smoking status and coronary volume-to-myocardial mass ratio (V/M) among individuals with coronary artery disease (CAD) undergoing CT fractional flow reserve (CT-FFR) analysis. Materials and Methods In this secondary analysis, participants from the ADVANCE registry evaluated for suspected CAD from July 15, 2015, to October 20, 2017, who were found to have coronary stenosis of 30% or greater at coronary CT angiography (CCTA) were included if they had known smoking status and underwent CT-FFR and V/M analysis. CCTA images were segmented to calculate coronary volume and myocardial mass. V/M was compared between smoking groups, and predictors of low V/M were determined. Results The sample for analysis included 503 current smokers, 1060 former smokers, and 1311 never-smokers (2874 participants; 1906 male participants). After adjustment for demographic and clinical factors, former smokers had greater coronary volume than never-smokers (former smokers, 3021.7 mm3 ± 934.0 [SD]; never-smokers, 2967.6 mm3 ± 978.0; P = .002), while current smokers had increased myocardial mass compared with never-smokers (current smokers, 127.8 g ± 32.9; never-smokers, 118.0 g ± 32.5; P = .02). However, both current and former smokers had lower V/M than never-smokers (current smokers, 24.1 mm3/g ± 7.9; former smokers, 24.9 mm3/g ± 7.1; never-smokers, 25.8 mm3/g ± 7.4; P < .001 [unadjusted] and P = .002 [unadjusted], respectively). Current smoking status (odds ratio [OR], 0.74 [95% CI: 0.59, 0.93]; P = .009), former smoking status (OR, 0.81 [95% CI: 0.68, 0.97]; P = .02), stenosis of 50% or greater (OR, 0.62 [95% CI: 0.52, 0.74]; P < .001), and diabetes (OR, 0.67 [95% CI: 0.56, 0.82]; P < .001) were independent predictors of low V/M. Conclusion Both current and former smoking status were independently associated with low V/M. Keywords: CT Angiography, Cardiac, Heart, Ischemia/Infarction Clinical trial registration no. NCT02499679 Supplemental material is available for this article. © RSNA, 2024.

Intravascular Imaging Findings After PCI in Patients With Focal and Diffuse Coronary Artery Disease.

BACKGROUND: Following percutaneous coronary intervention (PCI), optical coherence tomography provides prognosis information. The pullback pressure gradient is a novel index that discriminates focal from diffuse coronary artery disease based on fractional flow reserve pullbacks. We sought to investigate the association between coronary artery disease patterns, defined by coronary physiology, and optical coherence tomography after stent implantation in stable patients undergoing PCI. METHODS AND RESULTS: This multicenter, prospective, single-arm study was conducted in 5 countries (NCT03782688). Subjects underwent motorized fractional flow reserve pullbacks evaluation followed by optical coherence tomography-guided PCI. Post-PCI optical coherence tomography minimum stent area, stent expansion, and the presence of suboptimal findings such as incomplete stent apposition, stent edge dissection, and irregular tissue protrusion were compared between patients with focal versus diffuse disease. Overall, 102 patients (105 vessels) were included. Fractional flow reserve before PCI was 0.65±0.14, pullback pressure gradient was 0.66±0.14, and post-PCI fractional flow reserve was 0.88±0.06. The mean minimum stent area was 5.69±1.99 mm2 and was significantly larger in vessels with focal disease (6.18±2.12 mm2 versus 5.19±1.72 mm2, P=0.01). After PCI, incomplete stent apposition, stent edge dissection, and irregular tissue protrusion were observed in 27.6%, 10.5%, and 51.4% of the cases, respectively. Vessels with focal disease at baseline had a lower prevalence of incomplete stent apposition (11.3% versus 44.2%, P=0.002) and more irregular tissue protrusion (69.8% versus 32.7%, P<0.001). CONCLUSIONS: Baseline coronary pathophysiological patterns are associated with suboptimal imaging findings after PCI. Patients with focal disease had larger minimum stent area and a higher incidence of tissue protrusion, whereas stent malapposition was more frequent in patients with diffuse disease.

Impact of coronary CT image quality on the accuracy of the FFRCT Planner.

OBJECTIVE: To assess the accuracy of a virtual stenting tool based on coronary CT angiography (CCTA) and fractional flow reserve (FFR) derived from CCTA (FFRCT Planner) across different levels of image quality. MATERIALS AND METHODS: Prospective, multicenter, single-arm study of patients with chronic coronary syndromes and lesions with FFR ≤ 0.80. All patients underwent CCTA performed with recent-generation scanners. CCTA image quality was adjudicated using the four-point Likert scale at a per-vessel level by an independent committee blinded to the FFRCT Planner. Patient- and technical-related factors that could affect the FFRCT Planner accuracy were evaluated. The FFRCT Planner was applied mirroring percutaneous coronary intervention (PCI) to determine the agreement with invasively measured post-PCI FFR. RESULTS: Overall, 120 patients (123 vessels) were included. Invasive post-PCI FFR was 0.88 ± 0.06 and Planner FFRCT was 0.86 ± 0.06 (mean difference 0.02 FFR units, the lower limit of agreement (LLA) - 0.12, upper limit of agreement (ULA) 0.15). CCTA image quality was assessed as excellent (Likert score 4) in 48.3%, good (Likert score 3) in 45%, and sufficient (Likert score 2) in 6.7% of patients. The FFRCT Planner was accurate across different levels of image quality with a mean difference between FFRCT Planner and invasive post-PCI FFR of 0.02 ± 0.07 in Likert score 4, 0.02 ± 0.07 in Likert score 3 and 0.03 ± 0.08 in Likert score 2, p = 0.695. Nitrate dose ≥ 0.8mg was the only independent factor associated with the accuracy of the FFRCT Planner (95%CI - 0.06 to - 0.001, p = 0.040). CONCLUSION: The FFRCT Planner was accurate in predicting post-PCI FFR independent of CCTA image quality. CLINICAL RELEVANCE STATEMENT: Being accurate in predicting post-PCI FFR across a wide spectrum of CT image quality, the FFRCT Planner could potentially enhance and guide the invasive treatment. Adequate vasodilation during CT acquisition is relevant to improve the accuracy of the FFRCT Planner. KEY POINTS: • The fractional flow reserve derived from coronary CT angiography (FFRCT) Planner is a novel tool able to accurately predict fractional flow reserve after percutaneous coronary intervention. • The accuracy of the FFRCT Planner was confirmed across a wide spectrum of CT image quality. Nitrates dose at CT acquisition was the only independent predictor of its accuracy. • The FFRCT Planner could potentially enhance and guide the invasive treatment.

Combination of computed tomography angiography with coronary artery calcium score for improved diagnosis of coronary artery disease: a collaborative meta-analysis of stable chest pain patients referred for invasive coronary angiography.

OBJECTIVES: Coronary computed tomography angiography (CCTA) has higher diagnostic accuracy than coronary artery calcium (CAC) score for detecting obstructive coronary artery disease (CAD) in patients with stable chest pain, while the added diagnostic value of combining CCTA with CAC is unknown. We investigated whether combining coronary CCTA with CAC score can improve the diagnosis of obstructive CAD compared with CCTA alone. METHODS: A total of 2315 patients (858 women, 37%) aged 61.1 ± 10.2 from 29 original studies were included to build two CAD prediction models based on either CCTA alone or CCTA combined with the CAC score. CAD was defined as at least 50% coronary diameter stenosis on invasive coronary angiography. Models were built by using generalized linear mixed-effects models with a random intercept set for the original study. The two CAD prediction models were compared by the likelihood ratio test, while their diagnostic performance was compared using the area under the receiver-operating-characteristic curve (AUC). Net benefit (benefit of true positive versus harm of false positive) was assessed by decision curve analysis. RESULTS: CAD prevalence was 43.5% (1007/2315). Combining CCTA with CAC improved CAD diagnosis compared with CCTA alone (AUC: 87% [95% CI: 86 to 89%] vs. 80% [95% CI: 78 to 82%]; p < 0.001), likelihood ratio test 236.3, df: 1, p < 0.001, showing a higher net benefit across almost all threshold probabilities. CONCLUSION: Adding the CAC score to CCTA findings in patients with stable chest pain improves the diagnostic performance in detecting CAD and the net benefit compared with CCTA alone. CLINICAL RELEVANCE STATEMENT: CAC scoring CT performed before coronary CTA and included in the diagnostic model can improve obstructive CAD diagnosis, especially when CCTA is non-diagnostic. KEY POINTS: • The combination of coronary artery calcium with coronary computed tomography angiography showed significantly higher AUC (87%, 95% confidence interval [CI]: 86 to 89%) for diagnosis of coronary artery disease compared to coronary computed tomography angiography alone (80%, 95% CI: 78 to 82%, p < 0.001). • Diagnostic improvement was mostly seen in patients with non-diagnostic C. • The improvement in diagnostic performance and the net benefit was consistent across age groups, chest pain types, and genders.

Impact of Coronary CT Angiography-derived Fractional Flow Reserve on Downstream Management and Clinical Outcomes in Individuals with and without Diabetes.

Purpose: To compare the clinical use of coronary CT angiography (CCTA)-derived fractional flow reserve (FFR) in individuals with and without diabetes mellitus (DM). Materials and Methods: This secondary analysis included participants (enrolled July 2015 to October 2017) from the prospective, multicenter, international The Assessing Diagnostic Value of Noninvasive CT-FFR in Coronary Care (ADVANCE) registry (ClinicalTrials.gov identifier, NCT02499679) who were evaluated for suspected coronary artery disease (CAD), with one or more coronary stenosis ≥30% on CCTA images, using CT-FFR. CCTA and CT-FFR findings, treatment strategies at 90 days, and clinical outcomes at 1-year follow-up were compared in participants with and without DM. Results: The study included 4290 participants (mean age, 66 years ± 10 [SD]; 66% male participants; 22% participants with DM). Participants with DM had more obstructive CAD (one or more coronary stenosis ≥50%; 78.8% vs 70.6%, P < .001), multivessel CAD (three-vessel obstructive CAD; 18.9% vs 11.2%, P < .001), and proportionally more vessels with CT-FFR ≤ 0.8 (74.3% vs 64.6%, P < .001). Treatment reclassification by CT-FFR occurred in two-thirds of participants which was consistent regardless of the presence of DM. There was a similar graded increase in coronary revascularization with declining CT-FFR in both groups. At 1 year, presence of DM was associated with higher rates of major adverse cardiovascular events (hazard ratio, 2.2; 95% CI: 1.2, 4.1; P = .01). However, no between group differences were observed when stratified by stenosis severity (<50% or ≥50%) or CT-FFR positivity. Conclusion: Both anatomic CCTA findings and CT-FFR demonstrated a more complex pattern of CAD in participants with versus without DM. Rates of treatment reclassification were similar regardless of the presence of DM, and DM was not an adverse prognostic indicator when adjusted for diameter stenosis and CT-FFR.Clinical trial registration no. NCT 02499679Keywords: Fractional Flow Reserve, CT Angiography, Diabetes Mellitus, Coronary Artery Disease Supplemental material is available for this article. See also the commentary by Ghoshhajra in this issue.© RSNA, 2023.

Prognostic Value of Coronary CT Angiography-derived Fractional Flow Reserve on 3-year Outcomes in Patients with Stable Angina.

Background The prognostic value of coronary CT angiography (CTA)-derived fractional flow reserve (FFR) beyond 1-year outcomes and in patients with high levels of coronary artery calcium (CAC) is uncertain. Purpose To assess the prognostic value of coronary CTA-derived FFR test results on 3-year clinical outcomes in patients with coronary stenosis and among a subgroup of patients with high levels of CAC. Materials and Methods This study represents a 3-year follow-up of patients with new-onset stable angina pectoris who were consecutively enrolled in the Assessing Diagnostic Value of Noninvasive CT-FFR in Coronary Care, known as ADVANCE (ClinicalTrials.gov: NCT02499679) registry, between December 2015 and October 2017 at three Danish sites. A high CAC was defined as an Agatston score of at least 400. A lesion-specific coronary CTA-derived FFR value of 2 cm with distal-to-stenosis value at or below 0.80 represented an abnormal test result. The primary end point was a composite of all-cause death and nonfatal spontaneous myocardial infarction. Event rates were estimated using the one-sample binomial model, and relative risk was compared between participants stratified by results of coronary CTA-derived FFR. Results This study included 900 participants: 523 participants with normal results (mean age, 64 years ± 9.6 [SD]; 318 male participants) and 377 with abnormal results from coronary CTA-derived FFR (mean age, 65 years ± 9.6; 264 male participants). The primary end point occurred in 11 of 523 (2.1%) and 25 of 377 (6.6%) participants with normal and abnormal coronary CTA-derived FFR results, respectively (relative risk, 3.1; 95% CI: 1.6, 6.3; P < .001). In participants with high CAC, the primary end point occurred in four of 182 (2.2%) and 19 of 212 (9.0%) participants with normal and abnormal coronary CTA-derived FFR results, respectively (relative risk, 4.1; 95% CI: 1.4, 11.8; P = .001). Conclusion In individuals with stable angina, a normal coronary CTA-derived FFR test result identified participants with a low 3-year risk of all-cause death or nonfatal spontaneous myocardial infarction, both in the overall cohort and in participants with high CAC scores. Clinical trial registration no. NCT02499679 Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Sinitsyn in this issue.

Coronary Atherosclerosis Phenotypes in Focal and Diffuse Disease.

BACKGROUND: The interplay between coronary hemodynamics and plaque characteristics remains poorly understood. OBJECTIVES: The aim of this study was to compare atherosclerotic plaque phenotypes between focal and diffuse coronary artery disease (CAD) defined by coronary hemodynamics. METHODS: This multicenter, prospective, single-arm study was conducted in 5 countries. Patients with functionally significant lesions based on an invasive fractional flow reserve ≤0.80 were included. Plaque analysis was performed by using coronary computed tomography angiography and optical coherence tomography. CAD patterns were assessed using motorized fractional flow reserve pullbacks and quantified by pullback pressure gradient (PPG). Focal and diffuse CAD was defined according to the median PPG value. RESULTS: A total of 117 patients (120 vessels) were included. The median PPG was 0.66 (IQR: 0.54-0.75). According to coronary computed tomography angiography analysis, plaque burden was higher in patients with focal CAD (87% ± 8% focal vs 82% ± 10% diffuse; P = 0.003). Calcifications were significantly more prevalent in patients with diffuse CAD (Agatston score per vessel: 51 [IQR: 11-204] focal vs 158 [IQR: 52-341] diffuse; P = 0.024). According to optical coherence tomography analysis, patients with focal CAD had a significantly higher prevalence of circumferential lipid-rich plaque (37% focal vs 4% diffuse; P = 0.001) and thin-cap fibroatheroma (TCFA) (47% focal vs 10% diffuse; P = 0.002). Focal disease defined by PPG predicted the presence of TCFA with an area under the curve of 0.73 (95% CI: 0.58-0.87). CONCLUSIONS: Atherosclerotic plaque phenotypes associate with intracoronary hemodynamics. Focal CAD had a higher plaque burden and was predominantly lipid-rich with a high prevalence of TCFA, whereas calcifications were more prevalent in diffuse CAD. (Precise Percutaneous Coronary Intervention Plan [P3]; NCT03782688).

Influence of Obesity on Coronary Artery Disease and Clinical Outcomes in the ADVANCE Registry.

BACKGROUND: The relationship between body size and cardiovascular events is complex. This study utilized the ADVANCE (Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care) Registry to investigate the association between body mass index (BMI), coronary artery disease (CAD), and clinical outcomes. METHODS: The ADVANCE registry enrolled patients undergoing evaluation for clinically suspected CAD who had >30% stenosis on cardiac computed tomography angiography. Patients were stratified by BMI: normal <25 kg/m2, overweight 25-29.9 kg/m2, and obese ≥30 kg/m2. Baseline characteristics, cardiac computed tomography angiography and computed tomography fractional flow reserve (FFRCT), were compared across BMI groups. Adjusted Cox proportional hazards models assessed the association between BMI and outcomes. RESULTS: Among 5014 patients, 2166 (43.2%) had a normal BMI, 1883 (37.6%) were overweight, and 965 (19.2%) were obese. Patients with obesity were younger and more likely to have comorbidities, including diabetes and hypertension (all P<0.001), but were less likely to have obstructive coronary stenosis (65.2% obese, 72.2% overweight, and 73.2% normal BMI; P<0.001). However, the rate of hemodynamic significance, as indicated by a positive FFRCT, was similar across BMI categories (63.4% obese, 66.1% overweight, and 67.8% normal BMI; P=0.07). Additionally, patients with obesity had a lower coronary volume-to-myocardial mass ratio compared with patients who were overweight or had normal BMI (obese BMI, 23.7; overweight BMI, 24.8; and normal BMI, 26.3; P<0.001). After adjustment, the risk of major adverse cardiovascular events was similar regardless of BMI (all P>0.05). CONCLUSIONS: Patients with obesity in the ADVANCE registry were less likely to have anatomically obstructive CAD by cardiac computed tomography angiography but had a similar degree of physiologically significant CAD by FFRCT and similar rates of adverse events. An exclusively anatomic assessment of CAD in patients with obesity may underestimate the burden of physiologically significant disease that is potentially due to a significantly lower volume-to-myocardial mass ratio.

Computed tomographic angiography in coronary artery disease.

Coronary computed tomographic angiography (CCTA) is becoming the first-line investigation for establishing the presence of coronary artery disease and, with fractional flow reserve (FFRCT), its haemodynamic significance. In patients without significant epicardial obstruction, its role is either to rule out atherosclerosis or to detect subclinical plaque that should be monitored for plaque progression/regression following prevention therapy and provide risk classification. Ischaemic non-obstructive coronary arteries are also expected to be assessed by non-invasive imaging, including CCTA. In patients with significant epicardial obstruction, CCTA can assist in planning revascularisation by determining the disease complexity, vessel size, lesion length and tissue composition of the atherosclerotic plaque, as well as the best fluoroscopic viewing angle; it may also help in selecting adjunctive percutaneous devices (e.g., rotational atherectomy) and in determining the best landing zone for stents or bypass grafts.

Relationship between coronary volume, myocardial mass, and post-PCI fractional flow reserve.

BACKGROUND: Fractional flow reserve (FFR) measured after percutaneous coronary intervention (PCI) carries prognostic information. Yet, myocardial mass subtended by a stenosis influences FFR. We hypothesized that a smaller coronary lumen volume and a large myocardial mass might be associated with lower post-PCI FFR. AIM: We sought to assess the relationship between vessel volume, myocardial mass, and post-PCI FFR. METHODS: This was a subanalysis with an international prospective study of patients with significant lesions (FFR ≤ 0.80) undergoing PCI. Territory-specific myocardial mass was calculated from coronary computed tomography angiography (CCTA) using the Voronoi's algorithm. Vessel volume was extracted from quantitative CCTA analysis. Resting full-cycle ratio (RFR) and FFR were measured before and after PCI. We assessed the association between coronary lumen volume (V) and its related myocardial mass (M), and the percent of total myocardial mass (%M) with post-PCI FFR. RESULTS: We studied 120 patients (123 vessels: 94 left anterior descending arteries, 13 left Circumflex arteries, 16 right coronary arteries). Mean vessel-specific mass was 61 ± 23.1 g (%M 39.6 ± 11.7%). The mean post-PCI FFR was 0.88 ± 0.06 FFR units. Post-PCI FFR values were lower in vessels subtending higher mass (0.87 ± 0.05 vs. 0.89 ± 0.07, p = 0.047), and with lower V/M ratio (0.87 ± 0.06 vs. 0.89 ± 0.07, p = 0.02). V/M ratio correlated significantly with post-PCI RFR and FFR (RFR r = 0.37, 95% CI: 0.21-0.52, p < 0.001 and FFR r = 0.41, 95% CI: 0.26-0.55, p < 0.001). CONCLUSION: Post-PCI RFR and FFR are associated with the subtended myocardial mass and the coronary volume to mass ratio. Vessels with higher mass and lower V/M ratio have lower post-PCI RFR and FFR.

Procedural Outcomes After Percutaneous Coronary Interventions in Focal and Diffuse Coronary Artery Disease.

Background Coronary artery disease (CAD) patterns play an essential role in the decision-making process about revascularization. The pullback pressure gradient (PPG) quantifies CAD patterns as either focal or diffuse based on fractional flow reserve (FFR) pullbacks. The objective of this study was to evaluate the impact of CAD patterns on acute percutaneous coronary intervention (PCI) results considered surrogates of clinical outcomes. Methods and Results This was a prospective, multicenter study of patients with hemodynamically significant CAD undergoing PCI. Motorized FFR pullbacks and optical coherence tomography (OCT) were performed before and after PCI. Post-PCI FFR >0.90 was considered an optimal result. Focal disease was defined as PPG >0.73 (highest PPG tertile). Overall, 113 patients (116 vessels) were included. Patients with focal disease were younger than those with diffuse CAD (61.4±9.9 versus 65.1±8.7 years, P=0.042). PCI in vessels with high PPG (focal CAD) resulted in higher post-PCI FFR (0.91±0.07 in the focal group versus 0.86±0.05 in the diffuse group, P<0.001) and larger minimal stent area (6.3±2.3 mm2 in focal versus 5.3±1.8 mm2 in diffuse CAD, P=0.015) compared withvessels with low PPG (diffuse CAD). The PPG was associated with the change in FFR after PCI (R2=0.51, P<0.001). The PPG significantly improved the capacity to predict optimal PCI results compared with an angiographic assessment of CAD patterns (area under the curvePPG 0.81 [95% CI, 0.73-0.88] versus area under the curveangio 0.51 [95% CI, 0.42-0.60]; P<0.001). Conclusions PCI in vessels with focal disease defined by the PPG resulted in greater improvement in epicardial conductance and larger minimal stent area compared with diffuse disease. PPG, but not angiographically defined CAD patterns, distinguished patients attaining superior procedural outcomes. Registration URL: https://clinicaltrials.gov/ct2/show/NCT03782688.

Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow.

BACKGROUND: A pathophysiological interplay exists between plaque morphology and coronary physiology. Machine learning (ML) is increasingly being applied to coronary computed tomography angiography (CCTA) for cardiovascular risk stratification. We sought to assess the performance of a ML score integrating CCTA-based quantitative plaque features for predicting vessel-specific ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by positron emission tomography (PET). METHODS: This post-hoc analysis of the PACIFIC trial (Prospective Comparison of Cardiac Positron Emission Tomography/Computed Tomography [CT]' Single Photon Emission Computed Tomography/CT Perfusion Imaging and CT Coronary Angiography with Invasive Coronary Angiography) included 208 patients with suspected coronary artery disease who prospectively underwent CCTA' [15O]H2O PET, and invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. An ML algorithm trained on the prospective NXT trial (484 vessels) was used to develop a ML score for the prediction of ischemia (FFR≤0.80), which was then evaluated in 581 vessels from the PACIFIC trial. Thereafter, the ML score was applied for predicting impaired hyperemic MBF (≤2.30 mL/min per g) from corresponding PET scans. The performance of the ML score was compared with CCTA reads and noninvasive FFR derived from CCTA (FFRCT). RESULTS: One hundred thirty-nine (23.9%) vessels had FFR-defined ischemia, and 195 (33.6%) vessels had impaired hyperemic MBF. For the prediction of FFR-defined ischemia, the ML score yielded an area under the receiver-operating characteristic curve of 0.92, which was significantly higher than that of visual stenosis grade (0.84; P<0.001) and comparable with that of FFRCT (0.93; P=0.34). Quantitative percent diameter stenosis and low-density noncalcified plaque volume had the greatest ML feature importance for predicting FFR-defined ischemia. When applied for impaired MBF prediction, the ML score exhibited an area under the receiver-operating characteristic curve of 0.80; significantly higher than visual stenosis grade (area under the receiver-operating characteristic curve 0.74; P=0.02) and comparable with FFRCT (area under the receiver-operating characteristic curve 0.77; P=0.16). CONCLUSIONS: An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and impaired MBF by PET, performing superiorly to standard CCTA stenosis evaluation and comparably to FFRCT.

Influence of intensive lipid-lowering on CT derived fractional flow reserve in patients with stable chest pain: Rationale and design of the FLOWPROMOTE study.

INTRODUCTION: Coronary CT angiography (CTA) derived fractional flow reserve (FFRCT ) shows high diagnostic performance when compared to invasively measured FFR. Presence and extent of low attenuation plaque density have been shown to be associated with abnormal physiology by measured FFR. Moreover, it is well established that statin therapy reduces the rate of plaque progression and results in morphology alterations underlying atherosclerosis. However, the interplay between lipid lowering treatment, plaque regression, and the coronary physiology has not previously been investigated. AIM: To test whether lipid lowering therapy is associated with significant improvement in FFRCT , and whether there is a dose-response relationship between lipid lowering intensity, plaque regression, and coronary flow recovery. METHODS: Investigator driven, prospective, multicenter, randomized study of patients with stable angina, coronary stenosis ≥50% determined by clinically indicated first-line CTA, and FFRCT ≤ 0.80 in whom coronary revascularization was deferred. Patients are randomized to standard (atorvastatin 40 mg daily) or intensive (rosuvastatin 40 mg + ezetimibe 10 mg daily) lipid lowering therapy for 18 months. Coronary CTA scans with blinded coronary plaque and FFRCT analyses will be repeated after 9 and 18 months. The primary endpoint is the 18-month difference in FFRCT using (1) the FFRCT value 2 cm distal to stenosis and (2) the lowest distal value in the vessel of interest. A total of 104 patients will be included in the study. CONCLUSION: The results of this study will provide novel insights into the interplay between lipid lowering, and the pathophysiology in coronary artery disease.

Prediction of Cardiac Resynchronization Therapy Response Using a Lead Placement Score Derived From 4-Dimensional Computed Tomography.

BACKGROUND: Cardiac resynchronization therapy (CRT) is an effective treatment for patients with heart failure; however, 30% of patients do not respond to the treatment. We sought to derive patient-specific left ventricle maps of lead placement scores (LPS) that highlight target pacing lead sites for achieving a higher probability of CRT response. METHODS: Eighty-two subjects recruited for the ImagingCRT trial (Empiric Versus Imaging Guided Left Ventricular Lead Placement in Cardiac Resynchronization Therapy) were retrospectively analyzed. All 82 subjects had 2 contrast-enhanced full cardiac cycle 4-dimensional computed tomography scans: a baseline and a 6-month follow-up scan. CRT response was defined as a reduction in computed tomography-derived end-systolic volume ≥15%. Eight left ventricle features derived from the baseline scans were used to train a support vector machine via a bagging approach. An LPS map over the left ventricle was created for each subject as a linear combination of the support vector machine feature weights and the subject's own feature vector. Performance for distinguishing responders was performed on the original 82 subjects. RESULTS: Fifty-two (63%) subjects were responders. Subjects with an LPS≤Q1 (lower-quartile) had a posttest probability of responding of 14% (3/21), while subjects with an LPS≥ Q3 (upper-quartile) had a posttest probability of responding of 90% (19/21). Subjects with Q1

Clinical Validation of a Virtual Planner for Coronary Interventions Based on Coronary CT Angiography.

BACKGROUND: Low fractional flow reserve (FFR) values after percutaneous coronary intervention (PCI) carry a worse prognosis than high post-PCI FFR values. Therefore, the ability to predict post-PCI FFR might play an important role in procedural planning. Post-PCI FFR values can now be computed from pre-PCI coronary computed tomography angiography (CTA) using the fractional flow reserve derived from coronary computed tomography angiography revascularization planner (FFRCT Planner). OBJECTIVES: The aim of this study was to validate the accuracy of the FFRCT Planner. METHODS: In this multicenter, investigator-initiated, prospective study, patients with chronic coronary syndromes and significant lesions based on invasive FFR ≤0.80 were recruited. The FFRCT Planner was applied to the fractional flow reserve derived from coronary computed tomography angiography (FFRCT) model, simulating PCI. The primary objective was the agreement between the predicted post-PCI FFR by the FFRCT Planner and measured post-PCI FFR. Accuracy of the FFRCT Planner's luminal dimensions was assessed by using post-PCI optical coherence tomography as the reference. RESULTS: Overall, 259 patients were screened, with 120 patients (123 vessels) included in the final analysis. The mean patient age was 64 ± 9 years, and 24% had diabetes. Measured FFR post-PCI was 0.88 ± 0.06, and the FFRCT Planner FFR was 0.86 ± 0.06 (mean difference: 0.02 ± 0.07 FFR unit; limits of agreement: -0.12 to 0.15). Optical coherence tomography minimal stent area was 5.60 ± 2.01 mm2, and FFRCT Planner minimal stent area was 5.0 ± 2.2 mm2 (mean difference: 0.66 ± 1.21 mm2; limits of agreement: -1.7 to 3.0). The accuracy and precision of the FFRCT Planner remained high in cases with focal and diffuse disease and with low and high calcium burden. CONCLUSIONS: The FFRCT-based technology was accurate and precise for predicting FFR after PCI. (Precise Percutaneous Coronary Intervention Plan Study [P3]; NCT03782688).