Epicardial adipose tissue radiodensity is associated with all-cause mortality in patients undergoing hemodialysis

The radiodensity and volume of epicardial adipose tissue (EAT) on computed tomography angiography (CTA) may provide information regarding cardiovascular risk and long-term outcomes. EAT volume is associated with mortality in patients undergoing incident hemodialysis. However, the relationship between EAT radiodensity/volume and all-cause mortality in patients with end-stage renal disease (ESRD) undergoing maintenance hemodialysis remains elusive. In this retrospective study, EAT radiodensity (in Hounsfield units) and volume (in cm3) on coronary CTA were quantified for patients with ESRD using automatic, quantitative measurement software between January 2012 and December 2018. All-cause mortality data (up to December 2019) were obtained from the Korean National Statistical Office. The prognostic values of EAT radiodensity and volume for predicting long-term mortality were assessed using multivariable Cox regression models, which were adjusted for potential confounders. A total of 221 patients (mean age: 64.88 ± 11.09 years; 114 women and 107 men) with ESRD were included. The median follow-up duration (interquartile range) after coronary CTA was 29.63 (range 16.67–44.7) months. During follow-up, 82 (37.1%) deaths occurred. In the multivariable analysis, EAT radiodensity (hazard ratio [HR] 1.055; 95% confidence interval [CI] 1.015–1.095; p = 0.006) was an independent predictor of all-cause mortality in patients with ESRD. However, EAT volume was not associated with mortality. Higher EAT radiodensity on CTA is associated with higher long-term all-cause mortality in patients undergoing prevalent hemodialysis, highlighting its potential as a prognostic imaging biomarker in patients undergoing hemodialysis.

Two Cases of Anomalous Origin of Left Coronary Artery From The Pulmonary Artery

Coronary artery originating from pulmonary artery is a rare congenital vascular malformation, which generally presents corresponding clinical symptoms with the growth of patients' age. Coronary CTA and angiography are important methods for diagnosis of this disease, and provide evidence for treatment strategies of patients.

Prognostic value of CAD-RADS classification by coronary CTA in patients with suspected CAD

Background The study sought to compare Coronary Artery Disease Reporting and Data System (CAD-RADS) classification with traditional coronary artery disease (CAD) classifications and Duke Prognostic CAD Index for predicting the risk of all-cause mortality in patients with suspected CAD. Methods 9625 consecutive suspected CAD patients were assessed by coronary CTA for CAD-RADS classification, traditional CAD classifications and Duke Prognostic CAD Index. Kaplan–Meier and multivariable Cox models were used to estimate all-cause mortality. Discriminatory ability of classifications was assessed using time dependent receiver-operating characteristic (ROC) curves and The Hosmer–Lemeshow goodness-of-fit test was employed to evaluate calibration. Results A total of 540 patients died from all causes with a median follow-up of 4.3 ± 2.1 years. Kaplan–Meier survival curves showed the cumulative events increased significantly associated with CAD-RADS, three traditional CAD classifications and Duke Prognostic CAD Index. In multivariate Cox regressions, the risk for the all-cause death increased from HR 0.861 (95% CI 0.420–1.764) for CAD-RADS 1 to HR 2.761 (95% CI 1.961–3.887) for CAD-RADS 4B&5, using CAD-RADS 0 as the reference group. The relative HRs for all-cause death increased proportionally with the grades of the three traditional CAD classifications and Duke Prognostic CAD Index. The area under the time dependent ROC curve for prediction of all-cause death was 0.7917, 0.7805, 0.7991for CAD-RADS in 1 year, 3 year, 5 year, respectively, which was non-inferior to the traditional CAD classifications and Duke Prognostic CAD Index. Conclusions The CAD-RADS classification provided important prognostic information for patients with suspected CAD with noninvasive evaluation, which was non-inferior than Duke Prognostic CAD Index and traditional stenosis-based grading schemes in prognostic value of all-cause mortality. Traditional and simplest CAD classification should be preferable, given the more number of groups and complexity of CAD-RADS and Duke prognostic index, without using more time consuming classification.

Prognostic value of fractional flow reserve using computed tomography for predicting major adverse cardiac events and mortality in kidney transplant candidates

Background Coronary artery disease (CAD) is highly prevalent in patients with severe chronic kidney disease (CKD), it is the leading cause of mortality and morbidity in the short and long term among kidney transplant candidates, and the prevalence of CAD is high even after kidney transplantation. Most institutions recommend non-invasive cardiac tests prior to transplantation. Previous studies have indicated that cardiac screening by coronary computed tomography angiography (CTA) in kidney transplant candidates before transplantation yields both diagnostic and prognostic information. Additional analysis by CT-derived fractional flow reserve (FFRct) may improve diagnostic performance and have prognostic information. Purpose To establish the occurrence of major adverse cardiac events (MACE) and all-cause mortality in kidney transplantation candidates undergoing cardiac screening with coronary CTA with additional FFRct. Methods Coronary CTA scans from 340 consecutive kidney transplant candidates (CKD stage 4–5) undergoing cardiac evaluation with coronary CTA as part of the diagnostic work-up, between February 2011 and September 2019, were evaluated with subsequent FFRct analysis, the FFRct results were not clinically available. Patients were categorized into three groups based on distal FFRct; normal FFRct >0.80, moderate FFRct 0.80 to >0.75, low FFRct ≤0.75. Secondary analysis was performed using lesion specific (≥50% stenosis on coronary CTA) FFRct values, with normal FFRct >0.80 and abnormal ≤0.80. The primary end-point was MACE (cardiac death, cardiac arrest, myocardial infarction or revascularization unrelated to baseline work-up). The secondary end-point was all-cause mortality. End-point and baseline data were identified through patient files and registry data. Results Patients had a median age of 53 [45–63], 63% were men, 31% were on dialysis, the median follow-up time was 3.3 years [2.0–5.1]. During follow-up, MACE occurred in 28 patients (8.2%) and 28 patients (8.2%) died. When adjusting for risk factors and kidney transplantation during follow-up, the primary analysis identified increased risk of MACE in patients with lower distal FFRct compared to patients with FFRct >0.80; FFRct 0.80 to >0.75; Hazard ratio (HR): 1.63 (95% CI: 0.48–5.58; p=0.44), and FFRct with FFRct ≤0.75; HR: 3.27 (95% CI: 1.34–7.96; p<0.01). In the secondary analysis based on lesion-specific FFRct values, a FFRct ≤0.80 was associated with a higher risk of MACE compared to FFRct >0.80; HR 3.21 (95% CI 1.01–10.20, p<0.05). There were no significant differences in mortality between groups. Conclusions In kidney transplant candidates, a low FFRct ≤0.75 was predictive of MACE but not mortality. A lesion-specific approach found similar results with increased risk of MACE in patients with lesion-specific FFRct ≤0.80. Thus, FFRct adds prognostic information to the cardiac evaluation of these patients with severe CKD. FUNDunding Acknowledgement Type of funding sources: Private company. Main funding source(s): The Private Company, HeartFlow Inc, Redwood City, Califonia US- sponsored the fractional flow reserve using computed tomography scans, with no exchange of financial meansThe Public, Health Research Fund of the Central Denmark Region.- provided parts of the salary for two authors. FFRct distal values – MACE and Mortality FFRct lesion values – MACE and Mortality

Deep learning-based plaque quantification from coronary computed tomography angiography: external validation and comparison with intravascular ultrasound

Background Atherosclerotic plaque quantification from coronary computed tomography angiography (CTA) enables accurate assessment of coronary artery disease burden, progression, and prognosis. However, quantitative plaque analysis is time-consuming and requires high expertise. We sought to develop and externally validate an artificial intelligence (AI)-based deep learning (DL) approach for CTA-derived measures of plaque volume and stenosis severity. We compared the performance of DL to expert readers and the gold standard of intravascular ultrasound (IVUS). Methods This was a multicenter study of patients undergoing coronary CTA at 11 sites, with software-based quantitative plaque measurements performed at a per-lesion level by expert readers. AI-based plaque analysis was performed by a DL novel convolutional neural network which automatically segmented the coronary artery wall, lumen, and plaque for the computation of plaque volume and stenosis severity. Using expert measurements as ground truth, the DL algorithm was trained on 887 patients (4,686 lesions). Thereafter, the algorithm was applied to an independent test set of 221 patients (1,234 lesions), which included an external validation cohort of 171 patients from the SCOT-HEART (Scottish Computed Tomography of the Heart) trial as well as 50 patients who underwent IVUS within one month of CTA. We report the performance of AI-based plaque analysis in the independent test set. Results Within the external validation cohort, there was excellent agreement between DL and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0.876), noncalcified plaque volume (ICC 0.869), and percent diameter stenosis (ICC 0.850; all p<0.001). When compared with IVUS, there was excellent agreement for DL total plaque volume (ICC 0.945), total plaque burden (ICC 0.853), minimal luminal area (ICC 0.864), and percent area stenosis (ICC 0.805; all p<0.001); with strong correlation between DL and IVUS for total plaque volume (r=0.915; p<0.001; Figure). The average DL plaque analysis time was 20 seconds per patient, compared with 25–30 minutes taken by experts. Conclusions AI-based plaque quantification from coronary CTA using an externally validated DL approach enables rapid measurements of plaque volume and stenosis severity in close agreement with expert readers and IVUS. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute, United States

The atherosclerosis profile by coronary CTA compared to the coronary artery calcium score (CACS) in a young symptomatic high-risk population between 19 and 49 years

Background Whether the coronary artery calcium score (CACS) or coronary CTA should be used in young high-risk adults for screening of coronary artery disease (CAD), is an open debate and data sparse. Aims To evaluate the coronary atherosclerosis profile by coronary computed tomography angiography (CTA) in a young symptomatic high-risk population (age, 19–49 years) in comparison with the coronary artery calcium score (CACS). Methods and results 1137 symptomatic high-risk patients between 19–49 years (mean 42.4y; 33.2%females) with suspected CAD who underwent CTA and CACS were assigned into 6 age groups (19–30; 31–35; 36–40; 41–45; 46–47; 48–49y).CTA-analysis included stenosis severity (CADRADS) and high-risk-plaque (“HRP”) criteria. Atherosclerosis was more often detected by CTA than by CACS (45% vs. 27%; p<0.001), >50% stenosis in 13.6% and HRP in 17.7%. Prevalence of atherosclerosis was low and not different between CACS and CTA in the youngest (19–30y:5.2% and 6.4%; 30–35y:10.6% and 16%). Above >35 years, atherosclerosis detection by CTA increased (p=0.004, OR: 2.8, 95% CI: 1.45–5.89); and was higher by CTA as compared to CACS (34.9% vs 16.7%; p<0.001). CTA outperformed CACS among all higher age groups >35 years, with an increasing gap towards a superior performance of CTA along with age: Above 35 years, stenosis severity (CADRADS) (p=0.002) and >50% stenosis increased from 2.6% to 12.5% (p<0.001). The rate of HRP increased linearly with age from 6.4% to 26.5%.The distribution of HRP into CACS0 and CACS>0.1AU was similar among all age groups (CACS 0:45.1% had HRP), with an increasing proportion of HRP in CACS>0.1AU with age. 24.9% of CACS 0 patients had CAD by CTA, 4.4% >50% stenosis and 11.5% HRP. Conclusion Above 35 years of age, CTA outperforms CACS with an increasing power. Between 19 and 35 years, CACS 0 does not reliably rule out CAD and high-risk-plaque; hence for “noRISK100%safety”, CTA is superior.(#eachlifematters) FUNDunding Acknowledgement Type of funding sources: None. 30 YOM diabetic, CACS 0 and HRP by CTA Atherosclerosis vs age: CACS vs CTA