Personalized coronary and myocardial blood flow models incorporating CT perfusion imaging and synthetic vascular trees.

Computational simulations of coronary artery blood flow, using anatomical models based on clinical imaging, are an emerging non-invasive tool for personalized treatment planning. However, current simulations contend with two related challenges - incomplete anatomies in image-based models due to the exclusion of arteries smaller than the imaging resolution, and the lack of personalized flow distributions informed by patient-specific imaging. We introduce a data-enabled, personalized and multi-scale flow simulation framework spanning large coronary arteries to myocardial microvasculature. It includes image-based coronary anatomies combined with synthetic vasculature for arteries below the imaging resolution, myocardial blood flow simulated using Darcy models, and systemic circulation represented as lumped-parameter networks. We propose an optimization-based method to personalize multiscale coronary flow simulations by assimilating clinical CT myocardial perfusion imaging and cardiac function measurements to yield patient-specific flow distributions and model parameters. Using this proof-of-concept study on a cohort of six patients, we reveal substantial differences in flow distributions and clinical diagnosis metrics between the proposed personalized framework and empirical methods based purely on anatomy; these errors cannot be predicted a priori. This suggests virtual treatment planning tools would benefit from increased personalization informed by emerging imaging methods.

Quantification and Visualization of CT Myocardial Perfusion Imaging to Detect Ischemia-Causing Coronary Arteries.

Coronary computed tomography angiography (cCTA) has poor specificity to identify coronary stenosis that limit blood flow to the myocardial tissue. Integration of dynamic CT myocardial perfusion imaging (CT-MPI) can potentially improve the diagnostic accuracy. We propose a method that integrates cCTA and CT-MPI to identify culprit coronary lesions that limit blood flow to the myocardium. Coronary arteries and left ventricle surfaces were segmented from cCTA and registered to CT-MPI. Myocardial blood flow (MBF) was derived from CT-MPI. A ray-casting approach was developed to project volumetric MBF onto the left ventricle surface. MBF volume were divided into coronary-specific territories based on proximity to the nearest coronary artery. MBF and normalized MBF were computed for the myocardium and each of the coronary artery. Projection of MBF onto cCTA allowed for direct visualization of perfusion defects. Normalized MBF had higher correlation with ischemic myocardial territory compared to MBF (MBF: R2=0.81 and Index MBF: R2=0.90). There were 18 vessels that showed angiographic disease (stenosis >50%); however, normalized MBF demonstrated only 5 coronary territories to be ischemic. These findings demonstrate that cCTA and CT-MPI can be integrated to visualize myocardial defects and detect culprit coronary arteries responsible for perfusion defects. These methods can allow for non-invasive detection of ischemia-causing coronary lesions and ultimately help guide clinicians to deliver more targeted coronary interventions.

Atherosclerosis evaluation and cardiovascular risk estimation using coronary computed tomography angiography.

Clinical risk scores based on traditional risk factors of atherosclerosis correlate imprecisely to an individual's complex pathophysiological predisposition to atherosclerosis and provide limited accuracy for predicting major adverse cardiovascular events (MACE). Over the past two decades, computed tomography scanners and techniques for coronary computed tomography angiography (CCTA) analysis have substantially improved, enabling more precise atherosclerotic plaque quantification and characterization. The accuracy of CCTA for quantifying stenosis and atherosclerosis has been validated in numerous multicentre studies and has shown consistent incremental prognostic value for MACE over the clinical risk spectrum in different populations. Serial CCTA studies have advanced our understanding of vascular biology and atherosclerotic disease progression. The direct disease visualization of CCTA has the potential to be used synergistically with indirect markers of risk to significantly improve prevention of MACE, pending large-scale randomized evaluation.

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.

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.

Coronary computed tomography angiography derived fractional flow reserve and risk of recurrent angina: A 3-year follow-up study.

BACKGROUND: The association between coronary computed tomography angiography (CTA) derived fractional flow reserve (FFRCT) and risk of recurrent angina in patients with new onset stable angina pectoris (SAP) and stenosis by CTA is uncertain. METHODS: Multicenter 3-year follow-up study of patients presenting with symptoms suggestive of new onset SAP who underwent first-line CTA evaluation and subsequent standard-of-care treatment. All patients had at least one ≥30 â€‹% coronary stenosis. A per-patient lowest FFRCT-value ≤0.80 represented an abnormal test result. Patients with FFRCT ≤0.80 who underwent revascularization were categorized according to completeness of revascularization: 1) Completely revascularized (CR-FFRCT), all vessels with FFRCT ≤0.80 revascularized; or 2) incompletely revascularized (IR-FFRCT) ≥1 vessels with FFRCT ≤0.80 non-revascularized. Recurrent angina was evaluated using the Seattle Angina Questionnaire. RESULTS: Amongst 769 patients (619 [80 â€‹%] stenosis ≥50 â€‹%, 510 [66 â€‹%] FFRCT ≤0.80), 174 (23 â€‹%) reported recurrent angina at follow-up. An FFRCT ≤0.80 vs â€‹> â€‹0.80 associated to increased risk of recurrent angina, relative risk (RR): 1.82; 95 â€‹% CI: 1.31-2.52, p â€‹< â€‹0.001. Risk of recurrent angina in CR-FFRCT (n â€‹= â€‹135) was similar to patients with FFRCT >0.80, 13 â€‹% vs 15 â€‹%, RR: 0.93; 95 â€‹% CI: 0.62-1.40, p â€‹= â€‹0.72, while IR-FFRCT (n â€‹= â€‹90) and non-revascularized patients with FFRCT ≤0.80 (n â€‹= â€‹285) had increased risk, 37 â€‹% vs 15 â€‹% RR: 2.50; 95 â€‹% CI: 1.68-3.73, p â€‹< â€‹0.001 and 30 â€‹% vs 15 â€‹%, RR: 2.03; 95 â€‹% CI: 1.44-2.87, p â€‹< â€‹0.001, respectively. Use of antianginal medication was similar across study groups. CONCLUSION: In patients with SAP and coronary stenosis by CTA undergoing standard-of-care guided treatment, FFRCT provides information regarding risk of recurrent angina.

Exercise electrocardiography for pre-test assessment of the likelihood of coronary artery disease.

OBJECTIVES: To develop a tool including exercise electrocardiography (ExECG) for patient-specific clinical likelihood estimation of patients with suspected obstructive coronary artery disease (CAD). METHODS: An ExECG-weighted clinical likelihood (ExECG-CL) model was developed in a training cohort of patients with suspected obstructive CAD undergoing ExECG. Next, the ExECG-CL model was applied in a CAD validation cohort undergoing ExECG and clinically driven invasive coronary angiography and a prognosis validation cohort and compared with the risk factor-weighted clinical likelihood (RF-CL) model for obstructive CAD discrimination and prognostication, respectively.In the CAD validation cohort, obstructive CAD was defined as >50% diameter stenosis on invasive coronary angiography. For prognosis, the endpoint was non-fatal myocardial infarction and death. RESULTS: The training cohort consisted of 1214 patients (mean age 57 years, 57% males). In the CAD (N=408; mean age 55 years, 53% males) and prognosis validation (N=3283; mean age 57 years, 57% males) cohorts, 11.8% patients had obstructive CAD and 4.4% met the endpoint. In the CAD validation cohort, discrimination of obstructive CAD was similar between the ExECG-CL and RF-CL models: area under the receiver-operating characteristic curves 83.1% (95% CIs 77.5% to 88.7%) versus 80.7% (95% CI 74.6% to 86.8%), p=0.14. In the ExECG-CL model, more patients had very low (≤5%) clinical likelihood of obstructive CAD compared with the RF-CL (42.2% vs 36.0%, p<0.01) where obstructive CAD prevalence and event risk remained low. CONCLUSIONS: ExECG incorporated into a clinical likelihood model improves reclassification of patients to a very low clinical likelihood group with very low prevalence of obstructive CAD and favourable prognosis.

Quantitative metrics of the LV trabeculated layer by cardiac CT and cardiac MRI in patients with suspected noncompaction cardiomyopathy.

OBJECTIVES: To compare cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) for the quantitative assessment of the left ventricular (LV) trabeculated layer in patients with suspected noncompaction cardiomyopathy (NCCM). MATERIALS AND METHODS: Subjects with LV excessive trabeculation who underwent both CMR and CCT imaging as part of the prospective international multicenter NONCOMPACT clinical study were included. For each subject, short-axis CCT and CMR slices were matched. Four quantitative metrics were estimated: 1D noncompacted-to-compacted ratio (NCC), trabecular-to-myocardial area ratio (TMA), trabecular-to-endocardial cavity area ratio (TCA), and trabecular-to-myocardial volume ratio (TMV). In 20 subjects, end-diastolic and mid-diastolic CCT images were compared for the quantification of the trabeculated layer. Relationships between the metrics were investigated using linear regression models and Bland-Altman analyses. RESULTS: Forty-eight subjects (49.9 ± 12.8 years; 28 female) were included in this study. NCC was moderately correlated (r = 0.62), TMA and TMV were strongly correlated (r = 0.78 and 0.78), and TCA had excellent correlation (r = 0.92) between CMR and CCT, with an underestimation bias from CCT of 0.3 units, and 5.1, 4.8, and 5.4 percent-points for the 4 metrics, respectively. TMA, TCA, and TMV had excellent correlations (r = 0.93, 0.96, 0.94) and low biases (- 3.8, 0.8, - 3.8 percent-points) between the end-diastolic and mid-diastolic CCT images. CONCLUSIONS: TMA, TCA, and TMV metrics of the LV trabeculated layer in patients with suspected NCCM demonstrated high concordance between CCT and CMR images. TMA and TCA were highly reproducible and demonstrated minimal differences between mid-diastolic and end-diastolic CCT images. CLINICAL RELEVANCE STATEMENT: The results indicate similarity of CCT to CMR for quantifying the LV trabeculated layer, and the small differences in quantification between end-diastole and mid-diastole demonstrate the potential for quantifying the LV trabeculated layer from clinically performed coronary CT angiograms. KEY POINTS: • Data on cardiac CT for quantifying the left ventricular trabeculated layer are limited. • Cardiac CT yielded highly reproducible metrics of the left ventricular trabeculated layer that correlated well with metrics defined by cardiac MR. • Cardiac CT appears to be equivalent to cardiac MR for the quantification of the left ventricular trabeculated layer.

Deep Learning-based Prediction of Percutaneous Recanalization in Chronic Total Occlusion Using Coronary CT Angiography.

Background CT is helpful in guiding the revascularization of chronic total occlusion (CTO), but manual prediction scores of percutaneous coronary intervention (PCI) success have challenges. Deep learning (DL) is expected to predict success of PCI for CTO lesions more efficiently. Purpose To develop a DL model to predict guidewire crossing and PCI outcomes for CTO using coronary CT angiography (CCTA) and evaluate its performance compared with manual prediction scores. MATERIALS AND METHODS: Participants with CTO lesions were prospectively identified from one tertiary hospital between January 2018 and December 2021 as the training set to develop the DL prediction model for PCI of CTO, with fivefold cross validation. The algorithm was tested using an external test set prospectively enrolled from three tertiary hospitals between January 2021 and June 2022 with the same eligibility criteria. All participants underwent preprocedural CCTA within 1 month before PCI. The end points were guidewire crossing within 30 minutes and PCI success of CTO.Results A total of 534 participants (mean age, 57.7 years ± 10.8 [SD]; 417 [78.1%] men) with 565 CTO lesions were included. In the external test set (186 participants with 189 CTOs), the DL model saved 85.0% of the reconstruction and analysis time of manual scores (mean, 73.7 seconds vs 418.2-466.9 seconds) and had higher accuracy than manual scores in predicting guidewire crossing within 30 minutes (DL, 91.0%; CT Registry of Chronic Total Occlusion Revascularization, 61.9%; Korean Multicenter CTO CT Registry [KCCT], 68.3%; CCTA-derived Multicenter CTO Registry of Japan (J-CTO), 68.8%; P < .05) and PCI success (DL, 93.7%; KCCT, 74.6%; J-CTO, 75.1%; P < .05). For DL, the area under the receiver operating characteristic curve was 0.97 (95% CI: 0.89, 0.99) for the training test set and 0.96 (95% CI: 0.90, 0.98) for the external test set. Conclusion The DL prediction model accurately predicted the percutaneous recanalization outcomes of CTO lesions and increased the efficiency of noninvasively grading the difficulty of PCI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Pundziute-do Prado in this issue.

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.

Personalized coronary and myocardial blood flow models incorporating CT perfusion imaging and synthetic vascular trees.

Computational simulations of coronary artery blood flow, using anatomical models based on clinical imaging, are an emerging non-invasive tool for personalized treatment planning. However, current simulations contend with two related challenges - incomplete anatomies in image-based models due to the exclusion of arteries smaller than the imaging resolution, and the lack of personalized flow distributions informed by patient-specific imaging. We introduce a data-enabled, personalized and multi-scale flow simulation framework spanning large coronary arteries to myocardial microvasculature. It includes image-based coronary models combined with synthetic vasculature for arteries below the imaging resolution, myocardial blood flow simulated using Darcy models, and systemic circulation represented as lumped-parameter networks. Personalized flow distributions and model parameters are informed by clinical CT myocardial perfusion imaging and cardiac function using surrogate-based optimization. We reveal substantial differences in flow distributions and clinical diagnosis metrics between the proposed personalized framework and empirical methods based on anatomy; these errors cannot be predicted a priori. This suggests virtual treatment planning tools would benefit from increased personalization informed by emerging imaging methods.

Coronary Volume to Left Ventricular Mass Ratio in Patients With Hypertension.

The coronary vascular volume to left ventricular mass (V/M) ratio assessed by coronary computed tomography angiography (CCTA) is a promising new parameter to investigate the relation of coronary vasculature to the myocardium supplied. It is hypothesized that hypertension decreases the ratio between coronary volume and myocardial mass by way of myocardial hypertrophy, which could explain the detected abnormal myocardial perfusion reserve reported in patients with hypertension. Individuals enrolled in the multicenter ADVANCE (Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care) registry who underwent clinically indicated CCTA for analysis of suspected coronary artery disease with known hypertension status were included in current analysis. The V/M ratio was calculated from CCTA by segmenting the coronary artery luminal volume and left ventricular myocardial mass. In total, 2,378 subjects were included in this study, of whom 1,346 (56%) had hypertension. Left ventricular myocardial mass and coronary volume were higher in subjects with hypertension than normotensive patients (122.7 ± 32.8 g vs 120.0 ± 30.5 g, p = 0.039, and 3,105.0 ± 992.0 mm3 vs 2,965.6 ± 943.7 mm3, p <0.001, respectively). Subsequently, the V/M ratio was higher in patients with hypertension than those without (26.0 ± 7.6 mm3/g vs 25.3 ± 7.3 mm3/g, p = 0.024). After correcting for potential confounding factors, the coronary volume and ventricular mass remained higher in patients with hypertension (least square) mean difference estimate: 196.3 (95% confidence intervals [CI] 119.9 to 272.7) mm3, p <0.001, and 5.60 (95% CI 3.42 to 7.78) g, p <0.001, respectively), but the V/M ratio was not significantly different (least square mean difference estimate: 0.48 (95% CI -0.12 to 1.08) mm3/g, p = 0.116). In conclusion, our findings do not support the hypothesis that the abnormal perfusion reserve would be caused by reduced V/M ratio in patients with hypertension.

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.

Prediction of Coronary Artery Calcium Using Deep Learning of Echocardiograms.

BACKGROUND: Coronary artery calcification (CAC), often assessed by computed tomography (CT), is a powerful marker of coronary artery disease that can guide preventive therapies. Computed tomographies, however, are not always accessible or serially obtainable. It remains unclear whether other widespread tests such as transthoracic echocardiograms (TTEs) can be used to predict CAC. METHODS: Using a data set of 2,881 TTE videos paired with coronary calcium CTs, we trained a video-based artificial intelligence convolutional neural network to predict CAC scores from parasternal long-axis views. We evaluated the model's ability to classify patients from a held-out sample as well as an external site sample into zero CAC and high CAC (CAC ≥ 400 Agatston units) groups by receiver operating characteristic and precision-recall curves. We also investigated whether such classifications prognosticated significant differences in 1-year mortality rates by the log-rank test of Kaplan-Meier curves. RESULTS: Transthoracic echocardiogram artificial intelligence models had high discriminatory abilities in predicting zero CAC (receiver operating characteristic area under the curve [AUC] = 0.81 [95% CI, 0.74-0.88], F1 score = 0.95) and high CAC (AUC = 0.74 [0.68-0.8], F1 score = 0.74). This performance was confirmed in an external test data set of 92 TTEs (AUC = 0.75 [0.65-0.85], F1 score = 0.77; and AUC = 0.85 [0.76-0.93], F1 score = 0.59, respectively). Risk stratification by TTE-predicted CAC performed similarly to CT CAC scores in prognosticating significant differences in 1-year survival in high-CAC patients (CT CAC ≥ 400 vs CT CAC < 400, P = .03; TTE-predicted CAC ≥ 400 vs TTE-predicted CAC < 400, P = .02). CONCLUSIONS: A video-based deep learning model successfully used TTE videos to predict zero CAC and high CAC with high accuracy. Transthoracic echocardiography-predicted CAC prognosticated differences in 1-year survival similar to CT CAC. Deep learning of TTEs holds promise for future adjunctive coronary artery disease risk stratification to guide preventive therapies.

Role of cardiac imaging in acute chest pain.

Chest pain is the second most common complaint in the emergency department. The need to diagnose the cause of chest pain in a timely manner and appropriately direct care is crucial. This article discusses the role of imaging in acute chest pain, after first differentiating chest pain into cardiac and non-cardiac causes with upfront clinical and biochemical assessment. The role of non-invasive imaging including point-of-care ultrasound, echocardiography, myocardial perfusion imaging, cardiac MRI, coronary computed tomography angiography and novel cardiac CT applications are discussed. Updates in the literature regarding the role of coronary plaque imaging in acute chest pain are reviewed, as are ongoing challenges and future directions. This includes a discussion on the yield of diagnostic testing in low-risk acute chest pain cohorts vs intermediate-high risk cohorts. The incremental value of further testing in the former is low, which is reflected in contemporary guidelines that discourage the use of costly diagnostic tests in these cohorts. In the latter cohort, emerging evidence has shown specifically the role coronary computed tomography angiography could play in reducing the need for invasive coronary angiography in selective patients where the true probability of acute coronary syndrome is thought to be low. Real-world considerations such as accessibility and affordability are also discussed in the paper because while guidelines offer clinicians the flexibility of evidence-based choice, physician decision must necessarily be made in consideration of real-world constraints.