Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories.

This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QCT) with qualitative approaches to atherosclerotic disease burden codified in the multisociety 2022 CAD-RADS 2.0 Expert Consensus. 105 patients who underwent cardiac computed tomography angiography (CCTA) for chest pain were evaluated by a blinded core laboratory through FDA-cleared software (Cleerly, Denver, CO) that performs AI-QCT through artificial intelligence, analyzing factors such as % stenosis, plaque volume, and plaque composition. AI-QCT plaque volume was then staged by recently validated prognostic thresholds, and compared with CAD-RADS 2.0 clinical methods of plaque evaluation (segment involvement score (SIS), coronary artery calcium score (CACS), visual assessment, and CAD-RADS percent (%) stenosis) by expert consensus blinded to the AI-QCT core lab reads. Average age of subjects were 59 ± 11 years; 44% women, with 50% of patients at CAD-RADS 1-2 and 21% at CAD-RADS 3 and above by expert consensus. AI-QCT quantitative plaque burden staging had excellent agreement of 93% (k = 0.87 95% CI: 0.79-0.96) with SIS. There was moderate agreement between AI-QCT quantitative plaque volume and categories of visual assessment (64.4%; k = 0.488 [0.38-0.60]), and CACS (66.3%; k = 0.488 [0.36-0.61]). Agreement between AI-QCT plaque volume stage and CAD-RADS % stenosis category was also moderate. There was discordance at small plaque volumes. With ongoing validation, these results demonstrate a potential for AI-QCT as a rapid, reproducible approach to quantify total plaque burden.

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).

Interobserver variability among expert readers quantifying plaque volume and plaque characteristics on coronary CT angiography: a CLARIFY trial sub-study.

BACKGROUND: The difference between expert level (L3) reader and artificial intelligence (AI) performance for quantifying coronary plaque and plaque components is unknown. OBJECTIVE: This study evaluates the interobserver variability among expert readers for quantifying the volume of coronary plaque and plaque components on coronary computed tomographic angiography (CCTA) using an artificial intelligence enabled quantitative CCTA analysis software as a reference (AI-QCT). METHODS: This study uses CCTA imaging obtained from 232 patients enrolled in the CLARIFY (CT EvaLuation by ARtificial Intelligence For Atherosclerosis, Stenosis and Vascular MorphologY) study. Readers quantified overall plaque volume and the % breakdown of noncalcified plaque (NCP) and calcified plaque (CP) on a per vessel basis. Readers categorized high risk plaque (HRP) based on the presence of low-attenuation-noncalcified plaque (LA-NCP) and positive remodeling (PR; ≥1.10). All CCTAs were analyzed by an FDA-cleared software service that performs AI-driven plaque characterization and quantification (AI-QCT) for comparison to L3 readers. Reader generated analyses were compared among readers and to AI-QCT generated analyses. RESULTS: When evaluating plaque volume on a per vessel basis, expert readers achieved moderate to high interobserver consistency with an intra-class correlation coefficient of 0.78 for a single reader score and 0.91 for mean scores. There was a moderate trend between readers 1, 2, and 3 and AI with spearman coefficients of 0.70, 0.68 and 0.74, respectively. There was high discordance between readers and AI plaque component analyses. When quantifying %NCP v. %CP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.23, 0.34 and 0.24, respectively, compared to AI with a spearman coefficient of 0.38, 0.51, and 0.60, respectively. The intra-class correlation coefficient among readers for plaque composition assessment was 0.68. With respect to HRP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.22, 0.26, and 0.17, respectively, and a spearman coefficient of 0.36, 0.35, and 0.44, respectively. CONCLUSION: Expert readers performed moderately well quantifying total plaque volumes with high consistency. However, there was both significant interobserver variability and high discordance with AI-QCT when quantifying plaque composition.

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.

CT ​Evaluation ​by ​Artificial ​Intelligence ​for ​Atherosclerosis, Stenosis and Vascular ​Morphology ​(CLARIFY): ​A ​Multi-center, international study.

BACKGROUND: Atherosclerosis evaluation by coronary computed tomography angiography (CCTA) is promising for coronary artery disease (CAD) risk stratification, but time consuming and requires high expertise. Artificial Intelligence (AI) applied to CCTA for comprehensive CAD assessment may overcome these limitations. We hypothesized AI aided analysis allows for rapid, accurate evaluation of vessel morphology and stenosis. METHODS: This was a multi-site study of 232 patients undergoing CCTA. Studies were analyzed by FDA-cleared software service that performs AI-driven coronary artery segmentation and labeling, lumen and vessel wall determination, plaque quantification and characterization with comparison to ground truth of consensus by three L3 readers. CCTAs were analyzed for: % maximal diameter stenosis, plaque volume and composition, presence of high-risk plaque and Coronary Artery Disease Reporting & Data System (CAD-RADS) category. RESULTS: AI performance was excellent for accuracy, sensitivity, specificity, positive predictive value and negative predictive value as follows: >70% stenosis: 99.7%, 90.9%, 99.8%, 93.3%, 99.9%, respectively; >50% stenosis: 94.8%, 80.0%, 97.0, 80.0%, 97.0%, respectively. Bland-Altman plots depict agreement between expert reader and AI determined maximal diameter stenosis for per-vessel (mean difference -0.8%; 95% CI 13.8% to -15.3%) and per-patient (mean difference -2.3%; 95% CI 15.8% to -20.4%). L3 and AI agreed within one CAD-RADS category in 228/232 (98.3%) exams per-patient and 923/924 (99.9%) vessels on a per-vessel basis. There was a wide range of atherosclerosis in the coronary artery territories assessed by AI when stratified by CAD-RADS distribution. CONCLUSIONS: AI-aided approach to CCTA interpretation determines coronary stenosis and CAD-RADS category in close agreement with consensus of L3 expert readers. There was a wide range of atherosclerosis identified through AI.

Perioperative Inotrope Therapy and Atrial Fibrillation Following Coronary Artery Bypass Graft Surgery: Evidence of a Racial Disparity.

BACKGROUND AND OBJECTIVE: Following coronary artery bypass graft (CABG) surgery, mortality rates are significantly higher among black patients who experience postoperative atrial fibrillation (POAF). Perioperative inotropic therapy (PINOT) was associated with POAF in previous reports, but the extent to which race influences this association is unknown. In the present study, the relationship between PINOT, race, and POAF was examined in patients undergoing CABG surgery. METHODS AND SETTING: Clinical records were examined from a prospectively maintained cohort of 11,855 patients (median age 64 yrs; 70% male; 16% black) undergoing primary isolated CABG at a large cardiovascular institute in the southeastern region of the United States. Relative risk (RR) and 95% confidence intervals (CIs) were computed using log-binomial regression. MAIN RESULTS: The association between PINOT and POAF was significantly increased among black patients (adjusted RR 1.7, CI 1.4-2.0) compared with white patients (adjusted RR 1.3, CI 1.2-1.4) (pinteraction  = 0.013). CONCLUSIONS: These findings suggest that PINOT may be disproportionately associated with POAF among black patients undergoing CABG surgery. Additional studies are needed to examine further the potential underlying mechanisms of this association.

Biomarkers and the prediction of atrial fibrillation: state of the art.

Atrial fibrillation (AF) is the most common sustained arrhythmia encountered in clinical practice, and it places a substantial burden on the health care system. Despite improvements in our understanding of AF pathophysiology, we have yet to develop targeted preventive therapies. Recently, numerous biological markers have been identified to aid in the prediction of future AF events. Subclinical markers of atrial stress, inflammation, endothelial dysfunction, kidney dysfunction, and atherosclerosis have been linked to AF. The connection between these markers and AF is the identification of subclinical states in which AF propagation is likely to occur, as these conditions are associated with abnormal atrial remodeling and fibrosis. Additionally, several risk scores have been developed to aid in the identification of at-risk patients. The practicing clinician should be aware of these subclinical markers, as several of these markers improve the predictive abilities of current AF risk scores. Knowledge of these subclinical markers also provides clinicians with a better understanding of AF risk factors, and the opportunity to reduce the occurrence of AF by incorporating well-known cardiovascular disease risk factor modification strategies. In this review, we highlight several novel biological markers that have improved our understanding of AF pathophysiology and appraise the utility of these markers to improve our ability to predict future AF events.

Comparison of Risk of Atrial Fibrillation in Black Versus White Patients After Coronary Artery Bypass Grafting.

Obesity has been identified as a risk factor for postoperative atrial fibrillation (POAF) after coronary artery bypass grafting (CABG). However, no studies have addressed the influence of race on this association. A total of 13,594 patients undergoing first-time, isolated CABG without preoperative AF between 1992 and 2011 were included in our study. The association between body mass index and POAF was compared by race. Relative risk and 95% CIs were computed using maximum likelihood log-binomial regression. Increasing levels of body mass index were associated with higher POAF risk after CABG in black but not white patients (pinteraction = 0.0009).

Peripheral arterial disease is associated with an increased risk of atrial fibrillation in the elderly.

AIMS: To examine the relationship between peripheral arterial disease (PAD) and atrial fibrillation (AF) in a population-based cohort study of older adults. METHODS AND RESULTS: We examined the relationship between PAD and AF in 5143 participants (85% white, 43% male) in the Cardiovascular Health Study (CHS), a longitudinal, observational study of adults aged 65 years and older. Peripheral arterial disease was defined by abnormal ankle-brachial index (ABI) values (<1.0 or >1.4). Incident AF events were ascertained by self-reported history, study electrocardiograms, and hospitalization discharge records. Cox regression was used to compute hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between PAD and AF. Over a median follow-up of 11.7 years, a total of 1521 participants developed AF. The incidence rate (per 1000 person-years) of AF was higher in those with PAD (incidence rate = 32.9, 95% CI = 29.5, 36.7) than those without PAD (incidence rate = 23.3, 95% CI = 22.0, 24.6). In a multivariate Cox regression analysis, PAD was associated with an increased risk for AF (HR = 1.52, 95% CI = 1.34, 1.72). Each 0.1 decrease in the ABI was associated with a 6% increase in the risk for AF (HR = 1.06, 95% CI = 1.02, 1.10). The associations of high (>1.4) and low (<1.0) ABI values with AF were examined separately and were in the same direction as the main result for PAD (ABI < 1.0: HR = 1.24, 95% CI = 1.08, 1.42; ABI > 1.4: HR = 1.33, 95% CI = 0.95, 1.86). CONCLUSION: The presence of PAD should alert practitioners to the increased risk of AF. Elderly patients with PAD possibly will benefit from routine electrocardiographic screening to identify AF events.

Conditional long-term survival following minimally invasive robotic mitral valve repair: a health services perspective.

BACKGROUND: Conditional survival is defined as the probability of surviving an additional number of years beyond that already survived. The aim of this study was to compute conditional survival in patients who received a robotically assisted, minimally invasive mitral valve repair procedure (RMVP). METHODS: Patients who received RMVP with annuloplasty band from May 2000 through April 2011 were included. A 5- and 10-year conditional survival model was computed using a multivariable product-limit method. RESULTS: Non-smoking men (≤65 years) who presented in sinus rhythm had a 96% probability of surviving at least 10 years if they survived their first year following surgery. In contrast, recent female smokers (>65 years) with preoperative atrial fibrillation only had an 11% probability of surviving beyond 10 years if alive after one year post-surgery. CONCLUSIONS: In the context of an increasingly managed healthcare environment, conditional survival provides useful information for patients needing to make important treatment decisions, physicians seeking to select patients most likely to benefit long-term following RMVP, and hospital administrators needing to comparatively assess the life-course economic value of high-tech surgical procedures.

Increased Long-Term Mortality among Black CABG Patients Receiving Preoperative Inotropic Agents.

The aim of this study was to examine racial differences in long-term mortality after coronary artery bypass grafting (CABG), stratified by preoperative use of inotropic agents. Black and white patients who required preoperative inotropic support prior to undergoing CABG procedures between 1992 and 2011 were compared. Mortality probabilities were computed using the Kaplan-Meier product-limit method. Hazard ratios (HR) and 95% confidence intervals (CI) were computed using a Cox regression model. A total of 15,765 patients underwent CABG, of whom 211 received preoperative inotropic agents within 48 hours of surgery. Long-term mortality differed by race (black versus white) among preoperative inotropic category (inotropes: adjusted HR = 1.6, 95% CI = 1.009-2.4; no inotropes: adjusted HR = 1.15, 95% CI = 1.08-1.2; P(interaction) < 0.0001). Our study identified an independent preoperative risk-factor for long-term mortality among blacks receiving CABG. This outcome provides information that may be useful for surgeons, primary care providers, and their patients.

Increased coronary artery disease severity in black women undergoing coronary bypass surgery.

Race and sex disparities are believed to play an important role in heart disease. The purpose of this study was to examine the association between race, sex, and number of diseased vessels at the time of coronary artery bypass grafting (CABG), and subsequent postoperative outcomes. The 13,774 patients undergoing first-time, isolated CABG between 1992 and 2011 were included. Trend in the number of diseased vessels between black and white patients, stratified by sex, were analyzed using a Cochran-Armitage trend test. Models were adjusted for age, procedural status (elective vs. nonelective), and payor type (private vs. nonprivate insurance). Black female CABG patients presented with an increasingly greater number of diseased vessels than white female CABG patients (adjusted P(trend) = 0.0021). A similar trend was not observed between black and white male CABG patients (adjusted P(trend) = 0.18). Black female CABG patients were also more likely to have longer intensive care unit and hospital lengths of stay than other race-sex groups.Our findings suggest that black female CABG patients have more advanced coronary artery disease than white female CABG patients. Further research is needed to determine the benefit of targeted preventive care and preoperative workup for this high-risk group.

Discharge ß-Blocker Use and Race after Coronary Artery Bypass Grafting.

INTRODUCTION: The use of discharge ß-blockers after cardiac surgery is associated with a long-term mortality benefit. ß-Blockers have been suggested to be less effective in black cardiovascular patients compared with whites. To date, racial differences in the long-term survival of coronary artery bypass grafting (CABG) patients who receive ß-blockers at discharge have not been examined. METHODS: A retrospective cohort study was conducted on patients undergoing CABG between 2002 and 2011. Long-term survival was compared in patients who were and who were not discharged with ß-blockers. Hazard ratios (HR) and 95% confidence intervals (CI) were computed using a Cox regression model. P-for-interaction between race and discharge ß-blocker use was computed using a likelihood ratio test. RESULTS: A total of 853 (88%) black (n = 970) and 3,038 (88%) white (n = 3,460) patients had a history of ß-blocker use at discharge (N = 4,430). Black patients who received ß-blockers survived longer than those not receiving ß-blockers and the survival advantage was comparable with white patients (black, adjusted HR = 0.33, 95% CI = 0.23-0.46; white, adjusted HR = 0.48, 95% CI = 0.39-0.58; p-for-interaction = 0.74). Among patients discharged on ß-blockers, we did not observe a long-term survival advantage for white compared with black patients (HR = 1.2, 95% CI = 0.95-1.5). CONCLUSION: ß-Blocker use at discharge was associated with a survival advantage among black patients after CABG and a similar association was observed in white patients.

Deletion of the EphA2 receptor exacerbates myocardial injury and the progression of ischemic cardiomyopathy.

EphrinA1-EphA-receptor signaling is protective during myocardial infarction (MI). The EphA2-receptor (EphA2-R) potentially mediates cardiomyocyte survival. To determine the role of the EphA2-R in acute non-reperfused myocardial injury in vivo, infarct size, inflammatory cell density, NF-κB, p-AKT/Akt, and MMP-2 protein levels, and changes in ephrinA1/EphA2-R gene expression profile were assessed 4 days post-MI in B6129 wild-type (WT) and EphA2-R-mutant (EphA2-R-M) mice lacking a functional EphA2-R. Fibrosis, capillary density, morphometry of left ventricular chamber and infarct dimensions, and cardiac function also were measured 4 weeks post-MI to determine the extent of ventricular remodeling. EphA2-R-M infarct size and area of residual necrosis were 31.7% and 113% greater than WT hearts, respectively. Neutrophil and macrophage infiltration were increased by 46% and 84% in EphA2-R-M hearts compared with WT, respectively. NF-κB protein expression was 1.9-fold greater in EphA2-R-M hearts at baseline and 56% less NF-κB after infarction compared with WT. EphA6 gene expression was 2.5-fold higher at baseline and increased 9.8-fold 4 days post-MI in EphA2-R-M hearts compared with WT. EphrinA1 gene expression in EphA2-R-M hearts was unchanged at baseline and decreased by 42% 4 days post-MI compared with WT hearts. EphA2-R-M hearts had 66.7% less expression of total Akt protein and 59% less p-Akt protein than WT hearts post-MI. EphA2-R-M hearts 4 weeks post-MI had increased chamber dilation and interstitial fibrosis and decreased MMP-2 expression and capillary density compared with WT. In conclusion, the EphA2-R is necessary to appropriately modulate the inflammatory response and severity of early injury during acute MI, thereby influencing the progression of ischemic cardiomyopathy.

Ephrin-Eph signaling as a potential therapeutic target for the treatment of myocardial infarction.

Although numerous strategies have been developed to reduce the initial ischemic insult and cellular injury that occurs during myocardial infarction (MI), few have progressed into the clinical arena. The epidemiologic and economic impact of MI necessitates the development of innovative therapies to rapidly and effectively reduce the initial injury and subsequent cardiac dysfunction. The Eph receptors and their cognate ligands, the ephrins, are the largest family of receptor tyrosine kinases, and their signaling has been shown to play a diverse role in various cellular processes. The recent advances in the study of ephrin-Eph signaling have shown promising progress in many fields of medicine. They have been implicated in the pathophysiology of various cancers and in the regulation of inflammation and apoptosis. Recent studies have shown that manipulation of ephrin-Eph cell signaling can favorably influence cardiomyocyte viability and ultimately preserve cardiac function post-MI. In this article, we explore the hypothesis that manipulation of ephrin-Eph signaling may potentially be a novel therapeutic target in the treatment of MI through alteration of the cellular processes that govern injury and wound healing.