Coronary CTA With AI-QCT Interpretation: Comparison With Myocardial Perfusion Imaging for Detection of Obstructive Stenosis Using Invasive Angiography as Reference Standard.

BACKGROUND. Deep learning frameworks have been applied to interpretation of coronary CTA performed for coronary artery disease (CAD) evaluation. OBJECTIVE. The purpose of our study was to compare the diagnostic performance of myocardial perfusion imaging (MPI) and coronary CTA with artificial intelligence quantitative CT (AI-QCT) interpretation for detection of obstructive CAD on invasive angiography and to assess the downstream impact of including coronary CTA with AI-QCT in diagnostic algorithms. METHODS. This study entailed a retrospective post hoc analysis of the derivation cohort of the prospective 23-center Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) trial. The study included 301 patients (88 women and 213 men; mean age, 64.4 ± 10.2 [SD] years) recruited from May 2014 to May 2017 with stable symptoms of myocardial ischemia referred for nonemergent invasive angiography. Patients underwent coronary CTA and MPI before angiography with quantitative coronary angiography (QCA) measurements and fractional flow reserve (FFR). CTA examinations were analyzed using an FDA-cleared cloud-based software platform that performs AI-QCT for stenosis determination. Diagnostic performance was evaluated. Diagnostic algorithms were compared. RESULTS. Among 102 patients with no ischemia on MPI, AI-QCT identified obstructive (≥ 50%) stenosis in 54% of patients, including severe (≥ 70%) stenosis in 20%. Among 199 patients with ischemia on MPI, AI-QCT identified nonobstructive (1-49%) stenosis in 23%. AI-QCT had significantly higher AUC (all p < .001) than MPI for predicting ≥ 50% stenosis by QCA (0.88 vs 0.66), ≥ 70% stenosis by QCA (0.92 vs 0.81), and FFR < 0.80 (0.90 vs 0.71). An AI-QCT result of ≥ 50% stenosis and ischemia on stress MPI had sensitivity of 95% versus 74% and specificity of 63% versus 43% for detecting ≥ 50% stenosis by QCA measurement. Compared with performing MPI in all patients and those showing ischemia undergoing invasive angiography, a scenario of performing coronary CTA with AIQCT in all patients and those showing ≥ 70% stenosis undergoing invasive angiography would reduce invasive angiography utilization by 39%; a scenario of performing MPI in all patients and those showing ischemia undergoing coronary CTA with AI-QCT and those with ≥ 70% stenosis on AI-QCT undergoing invasive angiography would reduce invasive angiography utilization by 49%. CONCLUSION. Coronary CTA with AI-QCT had higher diagnostic performance than MPI for detecting obstructive CAD. CLINICAL IMPACT. A diagnostic algorithm incorporating AI-QCT could substantially reduce unnecessary downstream invasive testing and costs. TRIAL REGISTRATION. Clinicaltrials.gov NCT02173275.

AI Evaluation of Stenosis on Coronary CTA, Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve: A CREDENCE Trial Substudy.

BACKGROUND: Clinical reads of coronary computed tomography angiography (CTA), especially by less experienced readers, may result in overestimation of coronary artery disease stenosis severity compared with expert interpretation. Artificial intelligence (AI)-based solutions applied to coronary CTA may overcome these limitations. OBJECTIVES: This study compared the performance for detection and grading of coronary stenoses using artificial intelligence-enabled quantitative coronary computed tomography (AI-QCT) angiography analyses to core lab-interpreted coronary CTA, core lab quantitative coronary angiography (QCA), and invasive fractional flow reserve (FFR). METHODS: Coronary CTA, FFR, and QCA data from 303 stable patients (64 ± 10 years of age, 71% male) from the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia) trial were retrospectively analyzed using an Food and Drug Administration-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. RESULTS: Disease prevalence was high, with 32.0%, 35.0%, 21.0%, and 13.0% demonstrating ≥50% stenosis in 0, 1, 2, and 3 coronary vessel territories, respectively. Average AI-QCT analysis time was 10.3 ± 2.7 minutes. AI-QCT evaluation demonstrated per-patient sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 94%, 68%, 81%, 90%, and 84%, respectively, for ≥50% stenosis, and of 94%, 82%, 69%, 97%, and 86%, respectively, for detection of ≥70% stenosis. There was high correlation between stenosis detected on AI-QCT evaluation vs QCA on a per-vessel and per-patient basis (intraclass correlation coefficient = 0.73 and 0.73, respectively; P < 0.001 for both). False positive AI-QCT findings were noted in in 62 of 848 (7.3%) vessels (stenosis of ≥70% by AI-QCT and QCA of <70%); however, 41 (66.1%) of these had an FFR of <0.8. CONCLUSIONS: A novel AI-based evaluation of coronary CTA enables rapid and accurate identification and exclusion of high-grade stenosis and with close agreement to blinded, core lab-interpreted quantitative coronary angiography. (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia [CREDENCE]; NCT02173275).

Relation of Gender to Atherosclerotic Plaque Characteristics by Differing Angiographic Stenosis Severity.

It is unknown whether gender influences the atherosclerotic plaque characteristics (APCs) of lesions of varying angiographic stenosis severity. This study evaluated the imaging data of 303 symptomatic patients from the derivation arm of the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial, all of whom underwent coronary computed tomographic angiography and clinically indicated nonemergent invasive coronary angiography upon study enrollment. Index tests were interpreted by 2 blinded core laboratories, one of which performed quantitative coronary computed tomographic angiography using an artificial intelligence application to characterize and quantify APCs, including percent atheroma volume (PAV), low-density noncalcified plaque (LD-NCP), noncalcified plaque (NCP), calcified plaque (CP), lesion length, positive arterial remodeling, and high-risk plaque (a combination of LD-NCP and positive remodeling ≥1.10); the other classified lesions as obstructive (≥50% diameter stenosis) or nonobstructive (<50% diameter stenosis) based on quantitative invasive coronary angiography. The relation between APCs and angiographic stenosis was further examined by gender. The mean age of the study cohort was 64.4 ± 10.2 years (29.0% female). In patients with obstructive disease, men had more LD-NCP PAV (0.5 ± 0.4 vs 0.3 ± 0.8, p = 0.03) and women had more CP PAV (11.7 ± 1.6 vs 8.0 ± 0.8, p = 0.04). Obstructive lesions had more NCP PAV compared with their nonobstructive lesions in both genders, however, obstructive lesions in women also demonstrated greater LD-NCP PAV (0.4 ± 0.5 vs 1.0 ± 1.8, p = 0.03), and CP PAV (17.4 ± 16.5 vs 25.9 ± 18.7, p = 0.03) than nonobstructive lesions. Comparing the composition of obstructive lesions by gender, women had more CP PAV (26.3 ± 3.4 vs 15.8 ± 1.5, p = 0.005) whereas men had more NCP PAV (33.0 ± 1.6 vs 26.7 ± 2.5, p = 0.04). Men had more LD-NCP PAV in nonobstructive lesions compared with women (1.2 ± 0.2 vs 0.6 ± 0.2, p = 0.02). In conclusion, there are gender-specific differences in plaque composition based on stenosis severity.

Diabetes, Atherosclerosis, and Stenosis by AI.

OBJECTIVE: This study evaluates the relationship between atherosclerotic plaque characteristics (APCs) and angiographic stenosis severity in patients with and without diabetes. Whether APCs differ based on lesion severity and diabetes status is unknown. RESEARCH DESIGN AND METHODS: We retrospectively evaluated 303 subjects from the Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia (CREDENCE) trial referred for invasive coronary angiography with coronary computed tomographic angiography (CCTA) and classified lesions as obstructive (≥50% stenosed) or nonobstructive using blinded core laboratory analysis of quantitative coronary angiography. CCTA quantified APCs, including plaque volume (PV), calcified plaque (CP), noncalcified plaque (NCP), low-density NCP (LD-NCP), lesion length, positive remodeling (PR), high-risk plaque (HRP), and percentage of atheroma volume (PAV; PV normalized for vessel volume). The relationship between APCs, stenosis severity, and diabetes status was assessed. RESULTS: Among the 303 patients, 95 (31.4%) had diabetes. There were 117 lesions in the cohort with diabetes, 58.1% of which were obstructive. Patients with diabetes had greater plaque burden (P = 0.004). Patients with diabetes and nonobstructive disease had greater PV (P = 0.02), PAV (P = 0.02), NCP (P = 0.03), PAV NCP (P = 0.02), diseased vessels (P = 0.03), and maximum stenosis (P = 0.02) than patients without diabetes with nonobstructive disease. APCs were similar between patients with diabetes with nonobstructive disease and patients without diabetes with obstructive disease. Diabetes status did not affect HRP or PR. Patients with diabetes had similar APCs in obstructive and nonobstructive lesions. CONCLUSIONS: Patients with diabetes and nonobstructive stenosis had an association to similar APCs as patients without diabetes who had obstructive stenosis. Among patients with nonobstructive disease, patients with diabetes had more total PV and NCP.

Valvular heart disease in patients exposed to pergolide: insights from the clinical presentation.

PURPOSE: The aim of this study was to determine whether the presence of symptoms would aid in the detection of valvular heart disease (VHD) in those exposed to pergolide. METHODS: Utilizing a prospective, cross-sectional study design, patients with an exposure to pergolide were asked regarding the presence or absence of chest pain, shortness of breath or lower extremity edema through a questionnaire. Echocardiograms were obtained on the same day as the questionnaire and were blinded to all staff involved in the study. The sensitivity, specificity, positive and negative predictive value of the reported symptoms towards the outcome moderate or severe valvular regurgitation were obtained. Using the area under the receiver-operating characteristic curve, we also ascertained whether a relationship existed between symptoms, pergolide dose and presence of VHD. To understand the associations between symptoms and echocardiographic covariates, a logistic regression analysis was performed adjusted for age and gender. RESULTS: The sensitivity, specificity, positive and negative predictive value of symptom presentation and total dose was sufficiently low that it did not aid in the determination whether significant valvular regurgitation was present. Multivariable analysis noted a significant association with indexed left atrial volume (p = 0.011), estimated pulmonary artery pressure (p = 0.047) and shortness of breath. CONCLUSIONS: The presence or absence of symptoms does not help guide whether valvular regurgitation is present or absent in individuals exposed to pergolide. Therefore, echocardiography is needed to confirm or refute pergolide-associated VHD.

Predictors of Left Main Coronary Artery Disease in the ISCHEMIA Trial.

BACKGROUND: Detection of ≥50% diameter stenosis left main coronary artery disease (LMD) has prognostic and therapeutic implications. Noninvasive stress imaging or an exercise tolerance test (ETT) are the most common methods to detect obstructive coronary artery disease, though stress test markers of LMD remain ill-defined. OBJECTIVES: The authors sought to identify markers of LMD as detected on coronary computed tomography angiography (CTA), using clinical and stress testing parameters. METHODS: This was a post hoc analysis of ISCHEMIA (International Study of Comparative Health Effectiveness With Medical and Invasive Approaches), including randomized and nonrandomized participants who had locally determined moderate or severe ischemia on nonimaging ETT, stress nuclear myocardial perfusion imaging, or stress echocardiography followed by CTA to exclude LMD. Stress tests were read by core laboratories. Prior coronary artery bypass grafting was an exclusion. In a stepped multivariate model, the authors identified predictors of LMD, first without and then with stress testing parameters. RESULTS: Among 5,146 participants (mean age 63 years, 74% male), 414 (8%) had LMD. Predictors of LMD were older age (P < 0.001), male sex (P < 0.01), absence of prior myocardial infarction (P < 0.009), transient ischemic dilation of the left ventricle on stress echocardiography (P = 0.05), magnitude of ST-segment depression on ETT (P = 0.004), and peak metabolic equivalents achieved on ETT (P = 0.001). The models were weakly predictive of LMD (C-index 0.643 and 0.684). CONCLUSIONS: In patients with moderate or severe ischemia, clinical and stress testing parameters were weakly predictive of LMD on CTA. For most patients with moderate or severe ischemia, anatomical imaging is needed to rule out LMD. (International Study of Comparative Health Effectiveness With Medical and Invasive Approaches [ISCHEMIA]; NCT01471522).

The effect of scan and patient parameters on the diagnostic performance of AI for detecting coronary stenosis on coronary CT angiography.

OBJECTIVES: To determine whether coronary computed tomography angiography (CCTA) scanning, scan preparation, contrast, and patient based parameters influence the diagnostic performance of an artificial intelligence (AI) based analysis software for identifying coronary lesions with ≥50% stenosis. BACKGROUND: CCTA is a noninvasive imaging modality that provides diagnostic and prognostic benefit to patients with coronary artery disease (CAD). The use of AI enabled quantitative CCTA (AI-QCT) analysis software enhances our diagnostic and prognostic ability, however, it is currently unclear whether software performance is influenced by CCTA scanning parameters. METHODS: CCTA and quantitative coronary CT (QCT) data from 303 stable patients (64 ± 10 years, 71% male) from the derivation arm of the CREDENCE Trial were retrospectively analyzed using an FDA-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. The algorithm's diagnostic performance measures (sensitivity, specificity, and accuracy) for detecting coronary lesions of ≥50% stenosis were determined based on concordance with QCA measurements and subsequently compared across scanning parameters (including scanner vendor, model, single vs dual source, tube voltage, dose length product, gating technique, timing method), scan preparation technique (use of beta blocker, use and dose of nitroglycerin), contrast administration parameters (contrast type, infusion rate, iodine concentration, contrast volume) and patient parameters (heart rate and BMI). RESULTS: Within the patient cohort, 13% demonstrated ≥50% stenosis in 3 vessel territories, 21% in 2 vessel territories, 35% in 1 vessel territory while 32% had <50% stenosis in all vessel territories evaluated by QCA. Average AI analysis time was 10.3 ± 2.7 min. On a per vessel basis, there were significant differences only in sensitivity for ≥50% stenosis based on contrast type (iso-osmolar 70.0% vs non isoosmolar 92.1% p = 0.0345) and iodine concentration (<350 mg/ml 70.0%, 350-369 mg/ml 90.0%, 370-400 mg/ml 90.0%, >400 mg/ml 95.2%; p = 0.0287) in the context of low injection flow rates. On a per patient basis there were no significant differences in AI diagnostic performance measures across all measured scanner, scan technique, patient preparation, contrast, and individual patient parameters. CONCLUSION: The diagnostic performance of AI-QCT analysis software for detecting moderate to high grade stenosis are unaffected by commonly used CCTA scanning parameters and across a range of common scanning, scanner, contrast and patient variables. CONDENSED ABSTRACT: An AI-enabled quantitative CCTA (AI-QCT) analysis software has been validated as an effective tool for the identification, quantification and characterization of coronary plaque and stenosis through comparison to blinded expert readers and quantitative coronary angiography. However, it is unclear whether CCTA screening parameters related to scanner parameters, scan technique, contrast volume and rate, radiation dose, or a patient's BMI or heart rate at time of scan affect the software's diagnostic measures for detection of moderate to high grade stenosis. AI performance measures were unaffected across a broad range of commonly encountered scanner, patient preparation, scan technique, intravenous contrast and patient parameters.

Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence.

OBJECTIVE: The study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT). METHODS: This is a post-hoc analysis of data from 303 subjects enrolled in the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial who were referred for invasive coronary angiography and subsequently underwent coronary computed tomographic angiography (CCTA). In this study, a blinded core laboratory analysing quantitative coronary angiography images classified lesions as obstructive (≥50%) or non-obstructive (<50%) while AI software quantified APCs including plaque volume (PV), low-density non-calcified plaque (LD-NCP), non-calcified plaque (NCP), calcified plaque (CP), lesion length on a per-patient and per-lesion basis based on CCTA imaging. Plaque measurements were normalised for vessel volume and reported as % percent atheroma volume (%PAV) for all relevant plaque components. Data were subsequently stratified by age <65 and ≥65 years. RESULTS: The cohort was 64.4±10.2 years and 29% women. Overall, patients >65 had more PV and CP than patients <65. On a lesion level, patients >65 had more CP than younger patients in both obstructive (29.2 mm3 vs 48.2 mm3; p<0.04) and non-obstructive lesions (22.1 mm3 vs 49.4 mm3; p<0.004) while younger patients had more %PAV (LD-NCP) (1.5% vs 0.7%; p<0.038). Younger patients had more PV, LD-NCP, NCP and lesion lengths in obstructive compared with non-obstructive lesions. There were no differences observed between lesion types in older patients. CONCLUSION: AI-QCT identifies a unique APC signature that differs by age and degree of stenosis and provides a foundation for AI-guided age-based approaches to atherosclerosis identification, prevention and treatment.

Stress Myocardial Perfusion Imaging vs Coronary Computed Tomographic Angiography for Diagnosis of Invasive Vessel-Specific Coronary Physiology: Predictive Modeling Results From the Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) Trial.

Importance: Stress imaging has been the standard for diagnosing functionally significant coronary artery disease. It is unknown whether novel, atherosclerotic plaque measures improve accuracy beyond coronary stenosis for diagnosing invasive fractional flow reserve (FFR) measurement. Objective: To compare the diagnostic accuracy of comprehensive anatomic (obstructive and nonobstructive atherosclerotic plaque) vs functional imaging measures for estimating vessel-specific FFR. Design, Setting, and Participants: Controlled clinical trial of diagnostic accuracy with a multicenter derivation-validation cohort of patients referred for nonemergent invasive coronary angiography. A total of 612 patients (64 [10] years; 30% women) with signs and symptoms suggestive of myocardial ischemia from 23 sites were included. Patients were recruited from 2014 to 2017. Data analysis began in August 2018. Interventions: Patients underwent invasive coronary angiography with measurement of invasive FFR, coronary computed tomographic angiography (CCTA) quantification of atherosclerotic plaque and FFR by CT (FFR-CT), and semiquantitative scoring of rest/stress myocardial perfusion imaging (by magnetic resonance, positron emission tomography, or single photon emission CT). Multivariable generalized linear mixed models were derived and validated calculating the area under the receiver operating characteristics curve. Main Outcomes and Measures: The primary end point was invasive FFR of 0.80 or less. Results: Of the 612 patients, the mean (SD) age was 64 (10) years, and 426 (69.9%) were men. An invasive FFR of 0.80 or less was measured in 26.5% of 1727 vessels. In the derivation cohort, CCTA vessel-specific factors associated with FFR 0.80 or less were stenosis severity, percentage of noncalcified atheroma volume, lumen volume, the number of lesions with high-risk plaque (≥2 of low attenuation plaque, positive remodeling, napkin ring sign, or spotty calcification), and the number of lesions with stenosis greater than 30%. Fractional flow reserve-CT was not additive to this model including stenosis and atherosclerotic plaque. Significant myocardial perfusion imaging predictors were the summed rest and difference scores. In the validation cohort, the areas under the receiver operating characteristic curve were 0.81 for CCTA vs 0.67 for myocardial perfusion imaging (P < .001). Conclusions and Relevance: A comprehensive anatomic interpretation with CCTA, including quantification of obstructive and nonobstructive atherosclerotic plaque, was superior to functional imaging in the diagnosis of invasive FFR. Comprehensive CCTA measures improve prediction of vessel-specific coronary physiology more so than stress-induced alterations in myocardial perfusion. Trial Registration: ClinicalTrials.gov Identifier: NCT02173275.

Predictive Model for High-Risk Coronary Artery Disease.

BACKGROUND: Patients with high-risk coronary artery disease (CAD) may be difficult to identify. METHODS: Using the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) cohort randomized to coronary computed tomographic angiography (n=4589), 2 predictive models were developed for high-risk CAD, defined as left main stenosis (≥50% stenosis) or either (1) ≥50% stenosis [50] or (2) ≥70% stenosis [70] of 3 vessels or 2-vessel CAD involving the proximal left anterior descending artery. Pretest predictors were examined using stepwise logistic regression and assessed for discrimination and calibration. RESULTS: High-risk CAD was identified in 6.6% [50] and 2.4% [70] of patients. Models developed to predict high-risk CAD discriminated well: [50], bias-corrected C statistic=0.73 (95% CI, 0.71-0.76); [70], bias-corrected C statistic=0.73 (95% CI, 0.68-0.77). Variables predictive of CAD in both models included family history of premature CAD, age, male sex, lower glomerular filtration rate, diabetes mellitus, elevated systolic blood pressure, and angina. Additionally, smoking history was predictive of [50] CAD and sedentary lifestyle of [70] CAD. Both models characterized high-risk CAD better than the Pooled Cohort Equation (area under the curve=0.70 and 0.71 for [50] and [70], respectively) and Diamond-Forrester risk scores (area under the curve=0.68 and 0.71, respectively). Both [50] and [70] CAD was associated with more frequent invasive interventions and adverse events than non-high-risk CAD (all P<0.0001). CONCLUSIONS: In contemporary practice, 2.4% to 6.6% of stable, symptomatic patients requiring noninvasive testing have high-risk CAD. A simple combination of pretest clinical variables improves prediction of high-risk CAD over traditional risk assessments. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT01174550.

Cardiac-Specific Conversion Factors to Estimate Radiation Effective Dose From Dose-Length Product in Computed Tomography.

OBJECTIVES: This study sought to determine updated conversion factors (k-factors) that would enable accurate estimation of radiation effective dose (ED) for coronary computed tomography angiography (CTA) and calcium scoring performed on 12 contemporary scanner models and current clinical cardiac protocols and to compare these methods to the standard chest k-factor of 0.014 mSv·mGy-1cm-1. BACKGROUND: Accurate estimation of ED from cardiac CT scans is essential to meaningfully compare the benefits and risks of different cardiac imaging strategies and optimize test and protocol selection. Presently, ED from cardiac CT is generally estimated by multiplying a scanner-reported parameter, the dose-length product, by a k-factor which was determined for noncardiac chest CT, using single-slice scanners and a superseded definition of ED. METHODS: Metal-oxide-semiconductor field-effect transistor radiation detectors were positioned in organs of anthropomorphic phantoms, which were scanned using all cardiac protocols, 120 clinical protocols in total, on 12 CT scanners representing the spectrum of scanners from 5 manufacturers (GE, Hitachi, Philips, Siemens, Toshiba). Organ doses were determined for each protocol, and ED was calculated as defined in International Commission on Radiological Protection Publication 103. Effective doses and scanner-reported dose-length products were used to determine k-factors for each scanner model and protocol. RESULTS: k-Factors averaged 0.026 mSv·mGy-1cm-1 (95% confidence interval: 0.0258 to 0.0266) and ranged between 0.020 and 0.035 mSv·mGy-1cm-1. The standard chest k-factor underestimates ED by an average of 46%, ranging from 30% to 60%, depending on scanner, mode, and tube potential. Factors were higher for prospective axial versus retrospective helical scan modes, calcium scoring versus coronary CTA, and higher (100 to 120 kV) versus lower (80 kV) tube potential and varied among scanner models (range of average k-factors: 0.0229 to 0.0277 mSv·mGy-1cm-1). CONCLUSIONS: Cardiac k-factors for all scanners and protocols are considerably higher than the k-factor currently used to estimate ED of cardiac CT studies, suggesting that radiation doses from cardiac CT have been significantly and systematically underestimated. Using cardiac-specific factors can more accurately inform the benefit-risk calculus of cardiac-imaging strategies.

A pilot study to assess the utility of five established variables to standardize exercise treadmill test reporting.

BACKGROUND: The prognostic utility of 5 established variables (functional capacity, Duke treadmill score, chronotropic response to exercise, heart rate recovery, and premature ventricular contractions) together after routine exercise treadmill testing (ETT) has not been determined. METHODS: We assessed the combined prognostic ability of 5 established variables for the primary outcome (myocardial infarction [MI], coronary revascularization [CR] or all-cause mortality) and the secondary outcome of unnecessary downstream testing (defined as receipt of further noninvasive imaging without CR, MI, or death) compared with standard methods. Using a retrospective study design, 1857 consecutive patients were enrolled in the year 2014 and followed until December 31, 2015. Optimal discrimination and global fit statistics were assessed from logistic regression models. Classification and regression tree (CART) methodology was used for the final model. RESULTS: The mean [SD] age was 56.0 [12.5]years; median comorbidities (2, IQR 2) with 26% having an equivocal report. Compared to other models, a model with age, sex, and the 5 established variables showed an improvement in discrimination for the primary [c-statistic 0.85 versus (0.69-0.79)] and secondary [c-statistic 0.73 versus (0.65-0.71)] outcomes with substantial improvement in global fit. The final, optimal, 10-fold cross-validated CART model had a c-statistic of 0.78. CONCLUSIONS: The utility of the 5-established variables, based on the current study, resides in its ability to decrease unnecessary downstream testing and improve cardiovascular event prognostication. This is accomplished by removing the subjective interpretation of currently used ETT variables that can lead to an equivocal report.

Effectiveness of Percutaneous Coronary Intervention Versus Coronary Artery Bypass Grafting in Patients With End-Stage Renal Disease.

The optimal coronary revascularization strategy (coronary artery bypass grafting [CABG] or percutaneous coronary intervention [PCI]) in patients with end-stage renal disease (ESRD) remains uncertain. We performed an updated systematic review and meta-analysis of observational studies comparing CABG and PCI in patients with ESRD using a random-effects model for the primary outcome of long-term all-cause mortality. Our review registered through PROSPERO included observational studies published after 2011 to ensure overlap with previous studies and identified 7 new studies for a total of 23. We found that the median sample size in the selected studies was 125 patients (25 to 15,784) with a large variation in the covariate risk adjustment and only 3 studies reporting the indications for the revascularization strategy. CABG was associated with a small reduction in mortality (relative risk 0.92, 95% CI 0.89 to 0.96) with significant heterogeneity demonstrated (p = 0.005, I(2) = 48.6%). Subgroup analysis by categorized "year of study initiation" (<1990, 1991 to 2003, >2004) further confirmed the summary estimate trending toward survival benefit of CABG along with a substantial decrease in heterogeneity after 2004 (p = 0.64, I(2) = 0%). In conclusion, our updated systematic review and meta-analysis demonstrated that in patients with ESRD referred for coronary revascularization, CABG was associated with a small decrease in the relative risk of long-term mortality compared with PCI. The generalizability of the finding to all patients with ESRD referred for coronary revascularization is limited because of a lack of known indications for coronary revascularization, substantial variation in covariate risk adjustment, and lack of randomized clinical trial data.

Developmental endothelial locus-1 (Del-1), a novel angiogenic protein: its role in ischemia.

BACKGROUND: Developmentally regulated endothelial locus-1 (Del-1) is an extracellular matrix protein that is expressed by endothelial cells during embryological vascular development. We speculated that Del-1 may be reexpressed in ischemia and may be involved in endogenous angiogenesis. METHODS AND RESULTS: Del-1 protein was detected by immunohistochemistry in murine ischemic hindlimb after femoral artery excision. To determine whether exogenous Del-1 would augment angiogenesis in vivo, Del-1 or vehicle was administered for 3 weeks by intramuscular injection of murine ischemic hindlimbs. Angiogenesis was quantified by gadolinium-MRI perfusion and capillary densitometry. We used a disc angiogenesis system (DAS) to characterize the angiogenic response to vehicle (PBS), Del-1, Del-1 mutant (altered RGD domain), Del-1 minor (truncated discoidin-I-like domain), or basic fibroblast growth factor. After 14 days, the discs were extracted and sectioned to quantify vascular growth by morphometry. Endogenous Del-1 protein expression was increased in ischemic hindlimbs. Administration of Del-1 increased hindlimb vascular flow index and capillary density. In the DAS, Del-1 doubled fibrovascular growth, as did basic fibroblast growth factor. However, angiogenesis was not enhanced by the Del-1 mutant or Del-1 minor proteins. CONCLUSIONS: Del-1 is expressed in ischemic tissue. Del-1 stimulates angiogenesis, an effect that is dependent on the RGD motif and a second signaling sequence in the discoidin-I-like domain. Exogenous intramuscular administration of Del-1 significantly enhances angiogenesis in the murine ischemic hindlimb. Del-1 may prove to be a novel therapeutic agent for patients with ischemia.

Coronary artery bypass grafting and percutaneous coronary intervention in patients with end-stage renal disease.

OBJECTIVES: To determine the relative risks of long-term mortality between coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) among patients with end-stage renal disease (ESRD). METHODS: We identified 1015 patients with ESRD who underwent coronary revascularization between 1996 and 2008 within Kaiser Permanente Northern California. We obtained clinical variables from health plan databases, state death certificates and social security administration files. Our primary and secondary outcomes, respectively, were all-cause mortality and repeat revascularization. Our primary predictor was CABG compared with PCI. We used a Cox proportional hazards model for multivariable analyses. RESULTS: The mean age of CABG and PCI patients was similar (64.7 ± 10.6 and 63.4 ± 9.3, respectively, P = 0.06). The CABG group had a higher proportion of diabetics (P = 0.045), and higher nitrate use (P = 0.01). Adjusted for age, gender, race, year of index revascularization, number of vessels intervened, duration of dialysis and baseline comorbidities, patients referred for CABG during the first year had a hazard ratio (HR) of 1.16 [95% confidence interval (CI), 0.80-1.67] for mortality compared with PCI. During Years 1-5, the HR was 0.91 (95% CI, 0.63-1.33) with an overall HR of 0.73 (95% CI, 0.43-1.22). The sub-HR as calculated by the Fine-Gray competing risk model was 0.51 (95% CI, 0.31-0.85). CONCLUSIONS: As there are no randomized clinical trials in this area, our observational study adds to the growing body of literature that suggests a significant decrease in repeat revascularization with CABG and at least equivalency in long-term mortality with CABG when compared with PCI in ESRD patients.

Discordance between echocardiography and MRI in the assessment of mitral regurgitation severity: a prospective multicenter trial.

BACKGROUND: The decision to undergo mitral valve surgery is often made on the basis of echocardiographic criteria and clinical assessment. Recent changes in treatment guidelines recommending surgery in asymptomatic patients make the accurate assessment of mitral regurgitation (MR) severity even more important. OBJECTIVES: The purpose of this study was to compare echocardiography and magnetic resonance imaging (MRI) in the assessment of MR severity using the degree of left ventricular (LV) remodeling after surgery as the reference standard. METHODS: In this prospective multicenter trial, MR severity was assessed in 103 patients using both echocardiography and MRI. Thirty-eight patients subsequently had isolated mitral valve surgery, and 26 of these had an additional MRI performed 5 to 7 months after surgery. The pre-surgical estimate of regurgitant severity was correlated with the postoperative decrease in LV end-diastolic volume. RESULTS: Agreement between MRI and echocardiographic estimates of MR severity was modest in the overall cohort (r = 0.6; p < 0.0001), and there was a poorer correlation in the subset of patients sent for surgery (r = 0.4; p = 0.01). There was a strong correlation between post-surgical LV remodeling and MR severity as assessed by MRI (r = 0.85; p < 0.0001), and no correlation between post-surgical LV remodeling and MR severity as assessed by echocardiography (r = 0.32; p = 0.1). CONCLUSIONS: The data suggest that MRI is more accurate than echocardiography in assessing the severity of MR. MRI should be considered in those patients when MR severity as assessed by echocardiography is influencing important clinical decisions, such as the decision to undergo MR surgery.

The association of gender to cardiovascular outcomes after coronary artery revascularization in patients with end-stage renal disease.

BACKGROUND: Inadequate recruitment of women and an exclusion of patients with end-stage renal disease (ESRD) in coronary revascularization trials have led to knowledge gaps of gender-based outcomes. HYPOTHESIS: Women have equivalent cardiovascular outcomes when compared to men. METHODS: We conducted a retrospective observational study utilizing Kaiser Permanente Northern California (KPNC) databases and identified 1015 adults with ESRD who underwent coronary revascularization between 1996 and 2008. We ascertained baseline characteristics, primary (mortality at 5 years) and secondary (myocardial infarction [MI] and repeat revascularization) outcomes from KPNC databases, state death certificates, and Social Security Administration files. A multivariable logistic regression was used to determine the association of gender to the prespecified outcomes. RESULTS: Men and women were similar in age (P = 0.23). The mean number of baseline comorbidities was higher in women (2.7, 95% confidence interval [CI]: 2.5-2.9) compared to men (2.3, 95% CI: 2.1-2.4, P = 0.0002). The risk-adjusted odds ratios (OR) of female gender to death at 5 years (OR: 1.12, 95% CI: 0.83-1.52), MI (OR: 1.19, 95% CI: 0.86-1.64), and repeat revascularization (OR: 1.01, 95% CI: 0.70-1.45) were similar to men. Age modified the effect of gender for the primary outcome death (Pinteraction < 0.048), with a trend toward worse outcomes in younger women and improved outcomes in older women. This effect was noted more in patients who underwent coronary artery bypass grafting. CONCLUSIONS: Although the overall relative risk of cardiovascular outcomes after coronary revascularization in ESRD was equivalent between men and women, age had a significant interaction with gender on overall mortality.

Predictive values of Framingham risk and coronary artery calcium scores in the detection of obstructive CAD in patients with normal SPECT.

A subgroup of patients with normal stress myocardial perfusion imaging (MPI) have obstructive coronary artery disease (CAD) on coronary computed tomographic angiography (CCTA). A retrospective study was performed to identify factors associated with obstructive CAD in patients with normal MPI. Bivariate differences between patients with obstructive (>50% stenosis) and nonobstructive (<50% stenosis) CAD were assessed. Of the 105 patients with normal MPI, 42 (40%) had obstructive CAD on CCTA. After a multivariable logistic regression analysis increased Framingham risk scores ([FRS] ≥10%) and coronary artery calcium scores ([CACS] >100 Agatston Units [AU]) were independently associated with obstructive CAD (P = .006 and P < .0001, respectively). Patients with normal MPI had 13 times and 98 times higher odds of having obstructive CAD if they had a FRS ≥10% versus <10% and CACS >100 AU versus ≤100 AU, respectively. Increased FRS and CACS may stratify patients who may benefit from further evaluation for significant CAD despite normal MPI.