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Objectives: The main factors associated with coronavirus disease-19 (COVID-19) mortality are age, comorbidities, pattern of inflammatory response, and SARS-CoV-2 lineage involved in infection. However, the clinical course of the disease is extremely heterogeneous, and reliable biomarkers predicting adverse prognosis are lacking. Our aim was to elucidate the prognostic role of a novel marker of coronary artery disease inflammation, peri-coronary adipose tissue attenuation (PCAT), available from high-resolution chest computed tomography (HRCT) in COVID-19 patients with severe disease requiring hospitalization., Methods: Two distinct groups of patients were admitted to Parma University Hospital in Italy with COVID-19 in March 2020 and March 2021 (first- and third-wave peaks of the COVID-19 pandemic in Italy, with the prevalence of wild-type and B.1.1.7 SARS-CoV-2 lineage, respectively) were retrospectively enrolled. The primary endpoint was in-hospital mortality. Demographic, clinical, laboratory, HRCT data, and coronary artery HRCT features (coronary calcium score and PCAT attenuation) were collected to show which variables were associated with mortality., Results: Among the 769 patients enrolled, 555 (72%) were discharged alive, and 214 (28%) died. In multivariable logistic regression analysis age (p < 0.001), number of chronic illnesses (p < 0.001), smoking habit (p = 0.006), P/F ratio (p = 0.001), platelet count (p = 0.002), blood creatinine (p < 0.001), non-invasive mechanical ventilation (p < 0.001), HRCT visual score (p < 0.001), and PCAT (p < 0.001), but not the calcium score, were independently associated with in-hospital mortality., Conclusion: Coronary inflammation, measured with PCAT on non-triggered HRCT, appeared to be independently associated with higher mortality in patients with severe COVID-19, while the pre-existent coronary atherosclerotic burden was not associated with adverse outcomes after adjustment for covariates., Clinical Relevance Statement: The current study demonstrates that a relatively simple measurement, peri-coronary adipose tissue attenuation (PCAT), available ex-post from standard high-resolution computed tomography, is strongly and independently associated with in-hospital mortality., Key Points: • Coronary inflammation can be measured by the attenuation of peri-coronary adipose tissue (PCAT) on high-resolution CT (HRCT) without contrast media. • PCAT is strongly and independently associated with in-hospital mortality in SARS-CoV-2 patients. • PCAT might be considered an independent prognostic marker in COVID-19 patients if confirmed in other studies., (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

Aims: The atherosclerotic profile and advanced plaque subtype burden in symptomatic patients ≤45 years old have not been established. This study aimed to assess the prevalence and predictors of coronary artery calcium (CAC), plaque subtypes, and plaque burden by coronary computed tomography angiography (CCTA) in symptomatic young patients., Methods and Results: We included 907 symptomatic young patients (18-45 years) from Montefiore undergoing CCTA for chest pain evaluation. Prevalence and predictors of CAC, plaque subtypes, and burden were evaluated using semi-automated software. In the overall population (55% female and 44% Hispanic), 89% had CAC = 0. The likelihood of CAC or any plaque by CCTA increased with >3 risk factors {RFs, odds ratio [OR] 7.13 (2.14-23.7) and OR 10.26 (3.36-31.2), respectively}. Any plaque by CCTA was present in 137 (15%); the strongest independent predictors were age ≥35 years [OR 3.62 (2.05-6.41)] and family history of premature coronary artery disease (FHx) [OR 2.76 (1.67-4.58)]. Stenosis ≥50% was rare (1.8%), with 31% of those having CAC = 0. Significant non-calcified plaque (NCP, 37.2%) and low-attenuation plaque (LAP, 4.24%) burdens were seen, even in those with non-obstructive stenosis. Among patients with CAC = 0, 5% had plaque, and the only predictor of exclusively NCP was FHx [OR 2.29 (1.08-4.86)]., Conclusion: In symptomatic young patients undergoing CCTA, the prevalence of CAC or any coronary atherosclerosis was not negligible, and the likelihood increased with RF burden. The presence of coronary stenosis ≥50% was rare and most often accompanied by CAC >0, but there was a significant burden of NCP and LAP even within the non-obstructive group., Competing Interests: Conflict of interest: P.P., and D.L. are supported by grants from Amgen and Philips. A.L. is a consultant for and on the advisory board of Medtronic, Abbott, Boston Scientific, and Philips. R.B. has received consulting honoraria from Caristo, Novartis, Silence Therapeutic and grant/research support from Amgen and is a member of the board of directors for the American Society of Nuclear Cardiology and the Society of Cardiovascular Computed Tomography. M.J.B. has received grants from the National Institutes of Health, U.S. Food and Drug Administration, AHA, Amgen, Novo Nordisk, and Bayer and is on the advisory boards for Amgen, Sanofi, Regeneron, Novartis, Novo Nordisk, Bayer, 89Bio, Kaleido, Roche, Inozyme, emocha, VoxelCloud, and Kowa. D.S.B. and D.D. received software royalties from Cedars-Sinai Medical Center and hold a patent (US8885905B2 in the USA and World Intellectual Property Organization patent WO2011069120A1, ‘Method and System for Plaque Characterization’). S.S.V. has received honorarium from the American College of Cardiology (Associate Editor for Innovations, acc.org) and grant funding from the U.S. Department of Veterans Affairs, National Institutes of Health, World Heart Federation, and Tahir and Jooma Family. L.S. has received consulting honoraria from Amgen, Regeneron and Philips and research grants from Amgen and Philips. The remaining authors have nothing to disclose., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Aim: Recent studies suggest that the application of exercise activity questionnaires, including the use of a single-item exercise question, can be additive to the prognostic efficacy of imaging findings. This study aims to evaluate the prognostic efficacy of exercise activity in patients undergoing coronary computed tomography angiography (CCTA)., Methods and Results: We assessed 9772 patients who underwent CCTA at a single center between 2007 and 2020. Patients were divided into 4 groups of physical activity as no exercise (n ​= ​1643, 17%), mild exercise (n ​= ​3156, 32%), moderate exercise (n ​= ​3542, 36%), and high exercise (n ​= ​1431,15%), based on a single-item self-reported questionnaire. Coronary stenosis was categorized as no (0%), non-obstructive (1-49%), borderline (50-69%), and obstructive (≥70%). During a median follow-up of 4.64 (IQR 1.53-7.89) years, 490 (7.6%) died. There was a stepwise inverse relationship between exercise activity and mortality (p ​< ​0.001). Compared with the high activity group, the no activity group had a 3-fold higher mortality risk (HR: 3.3, 95%CI (1.94-5.63), p ​< ​0.001) after adjustment for age, clinical risk factors, symptoms, and statin use. For any level of CCTA stenosis, mortality rates were inversely associated with the degree of patients' exercise activity. The risk of all-cause mortality was similar among the patients with obstructive stenosis with high exercise versus those with no coronary stenosis but no exercise activity (p ​= ​0.912)., Conclusion: Physical activity as assessed by a single-item self-reported questionnaire is a strong stepwise inverse predictor of mortality risk among patients undergoing CCTA., Competing Interests: Declaration of competing interest All authors declare no conflict of interests, (Copyright © 2024. Published by Elsevier Inc.)

Background: Computed tomography attenuation correction (CTAC) improves perfusion quantification of hybrid myocardial perfusion imaging by correcting for attenuation artifacts. Artificial intelligence (AI) can automatically measure coronary artery calcium (CAC) from CTAC to improve risk prediction but could potentially derive additional anatomic features., Objectives: The authors evaluated AI-based derivation of cardiac anatomy from CTAC and assessed its added prognostic utility., Methods: The authors considered consecutive patients without known coronary artery disease who underwent single-photon emission computed tomography/computed tomography (CT) myocardial perfusion imaging at 3 separate centers. Previously validated AI models were used to segment CAC and cardiac structures (left atrium, left ventricle, right atrium, right ventricular volume, and left ventricular [LV] mass) from CTAC. They evaluated associations with major adverse cardiovascular events (MACEs), which included death, myocardial infarction, unstable angina, or revascularization., Results: In total, 7,613 patients were included with a median age of 64 years. During a median follow-up of 2.4 years (IQR: 1.3-3.4 years), MACEs occurred in 1,045 (13.7%) patients. Fully automated AI processing took an average of 6.2 ± 0.2 seconds for CAC and 15.8 ± 3.2 seconds for cardiac volumes and LV mass. Patients in the highest quartile of LV mass and left atrium, LV, right atrium, and right ventricular volume were at significantly increased risk of MACEs compared to patients in the lowest quartile, with HR ranging from 1.46 to 3.31. The addition of all CT-based volumes and CT-based LV mass improved the continuous net reclassification index by 23.1%., Conclusions: AI can automatically derive LV mass and cardiac chamber volumes from CT attenuation imaging, significantly improving cardiovascular risk assessment for hybrid perfusion imaging., Competing Interests: Funding Support and Author Disclosures This research was supported in part by the National Heart, Lung, and Blood Institute at the National Institutes of Health grant R35HL161195 (Principal Investigator: Dr Slomka). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Mr Kavanagh has received software royalties for QPS software at Cedars-Sinai Medical Center. Dr Miller has received consulting fees and research support from Pfizer; and has served as a consultant for GE Healthcare. Dr Newby is supported by the British Heart Foundation; is a recipient of a Wellcome Trust Senior Investigator Award (WT103782AIA); and has received honoraria for consultancy and lectures from AstraZeneca. Dr Berman has received software royalties for QPS software at Cedars-Sinai Medical Center; and has served as a consultant for GE Healthcare. Dr Slomka has received software royalties for QPS software at Cedars-Sina Medical Center, research grant support from Siemens Medical Systems, and consulting fees from Synektik., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Purpose of Review: Despite recent advances, coronary artery disease remains one of the leading causes of mortality worldwide. Noninvasive imaging allows atherosclerotic phenotyping by measurement of plaque burden, morphology, activity and inflammation, which has the potential to refine patient risk stratification and guide personalized therapy. This review describes the current and emerging roles of advanced noninvasive cardiovascular imaging methods for the assessment of coronary artery disease., Recent Findings: Cardiac computed tomography enables comprehensive, noninvasive imaging of the coronary vasculature, and is used to assess luminal stenoses, coronary calcifications, and distinct adverse plaque characteristics, helping to identify patients prone to future events. Novel software tools, implementing artificial intelligence solutions, can automatically quantify and characterize atherosclerotic plaque from standard computed tomography datasets. These quantitative imaging biomarkers have been shown to improve patient risk stratification beyond clinical risk scores and current clinical interpretation of cardiac computed tomography. In addition, noninvasive molecular imaging in higher risk patients can be used to assess plaque activity and plaque thrombosis. Noninvasive imaging allows unique insight into the burden, morphology and activity of atherosclerotic coronary plaques. Such phenotyping of atherosclerosis can potentially improve individual patient risk prediction, and in the near future has the potential for clinical implementation., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Positive remodeling is an integral part of the vascular adaptation process during the development of atherosclerosis, which can be detected by coronary computed tomography angiography (CTA)., Methods: A total of 426 patients who underwent both coronary CTA and optical coherence tomography (OCT) were included. Four machine learning (ML) models, gradient boosting machine (GBM), random forest (RF), deep learning (DL), and support vector machine (SVM), were employed to detect specific plaque features. A total of 15 plaque features assessed by OCT were analyzed. The variable importance ranking was used to identify the features most closely associated with positive remodeling., Results: In the variable importance ranking, lipid index and maximal calcification arc were consistently ranked high across all four ML models. Lipid index and maximal calcification arc were correlated with positive remodeling, showing pronounced influence at the lower range and diminishing influence at the higher range. Patients with more plaques with positive remodeling throughout their entire coronary trees had higher low-density lipoprotein cholesterol levels and were associated with a higher incidence of cardiovascular events during 5-year follow-up (Hazard ratio 2.10 [1.26-3.48], P ​= ​0.004)., Conclusion: Greater lipid accumulation and less calcium burden were important features associated with positive remodeling in the coronary arteries. The number of coronary plaques with positive remodeling was associated with a higher incidence of cardiovascular events., Competing Interests: Declaration of competing interest Dr. Jang reports receiving educational grants from Abbott Vascular and consulting fees from Svelte Medical Systems, Inc. Dr. Ferencik has received consulting fees from Siemens Healthineers, HeartFlow, and Elucid. All other authors have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

Aims: Variation in diagnostic performance of single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has been observed, yet the impact of cardiac size has not been well characterized. We assessed whether low left ventricular volume influences SPECT MPI's ability to detect obstructive coronary artery disease (CAD) and its interaction with age and sex., Methods and Results: A total of 2066 patients without known CAD (67% male, 64.7 ± 11.2 years) across nine institutions underwent SPECT MPI with solid-state scanners followed by coronary angiography as part of the REgistry of Fast Myocardial Perfusion Imaging with NExt Generation SPECT. Area under receiver-operating characteristic curve (AUC) analyses evaluated the performance of quantitative and visual assessments according to cardiac size [end-diastolic volume (EDV); <20th vs. ≥20th population or sex-specific percentiles], age (<75 vs. ≥75 years), and sex. Significantly decreased performance was observed in patients with low EDV compared with those without (AUC: population 0.72 vs. 0.78, P = 0.03; sex-specific 0.72 vs. 0.79, P = 0.01) and elderly patients compared with younger patients (AUC 0.72 vs. 0.78, P = 0.03), whereas males and females demonstrated similar AUC (0.77 vs. 0.76, P = 0.67). The reduction in accuracy attributed to lower volumes was primarily observed in males (sex-specific threshold: EDV 0.69 vs. 0.79, P = 0.01). Accordingly, a significant decrease in AUC, sensitivity, specificity, and negative predictive value for quantitative and visual assessments was noted in patients with at least two characteristics of low EDV, elderly age, or male sex., Conclusion: Detection of CAD with SPECT MPI is negatively impacted by small cardiac size, most notably in elderly and male patients., Competing Interests: Conflict of interest: D.S.B. and P.J.S. participated in software royalties for QPS software at Cedars-Sinai Medical Center. P.J.S. has received research grant support from Siemens Medical Systems. D.S.B., S.D., A.J.E., and E.J.M. are consultants for GE Healthcare. S.D. is a consultant for Bracco Diagnostics and has received a grant through her institution from Astellas. M.D.C. has received research grant support from Spectrum Dynamics; and he is a consultant for Sanof and GE Healthcare. D.S.B.’s institution has received grant support from HeartFlow. E.J.M. has served as a consultant for Bracco Inc, and he and his institution have received grant support from Bracco Inc. T.D.R. has received research grant support from GE Healthcare and Advanced Accelerator Applications. A.J.E. reports receiving a speaker's fee from Ionetix, consulting fees from W. L. Gore & Associates, authorship fees from Wolters Kluwer Healthcare—UpToDate, and serving on a scientific advisory board for Canon America Medical Systems USA; his institution has grants/grants pending from Attralus, BridgeBio Pharma, Canon Medical Systems USA, GE Healthcare, Intellia Therapeutics, Ionis Pharmaceuticals, Neovasc, Pfizer, Roche Medical Systems, and W. L. Gore & Associates. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Aims: To assess pericoronary adipose tissue (PCAT) density on coronary computed tomography angiography (CCTA) as a marker of inflammatory disease activity in coronary allograft vasculopathy (CAV)., Methods and Results: PCAT density, lesion volumes, and total vessel volume-to-myocardial mass ratio (V/M) were retrospectively measured in 126 CCTAs from 94 heart transplant patients [mean age 49 (SD 14.5) years, 40% female] who underwent imaging between 2010 and 2021; age- and sex-matched controls; and patients with atherosclerosis. PCAT density was higher in transplant patients with CAV [n = 40; -73.0 HU (SD 9.3)] than without CAV [n = 86; -77.9 HU (SD 8.2)], and controls [n = 12; -86.2 HU (SD 5.4)], P < 0.01 for both. Unlike patients with atherosclerotic coronary artery disease (n = 32), CAV lesions were predominantly non-calcified and comprised of mostly fibrous or fibrofatty tissue. V/M was lower in patients with CAV than without [32.4 mm3/g (SD 9.7) vs. 41.4 mm3/g (SD 12.3), P < 0.0001]. PCAT density and V/M improved the ability to predict CAV from area under the receiver operating characteristic curve (AUC) 0.75-0.85 when added to donor age and donor hypertension status (P < 0.0001). PCAT density above -66 HU was associated with a greater incidence of all-cause mortality {odds ratio [OR] 18.0 [95% confidence interval (CI) 3.25-99.6], P < 0.01} and the composite endpoint of death, CAV progression, acute rejection, and coronary revascularization [OR 7.47 (95% CI 1.8-31.6), P = 0.01] over 5.3 (SD 2.1) years., Conclusion: Heart transplant patients with CAV have higher PCAT density and lower V/M than those without. Increased PCAT density is associated with adverse clinical outcomes. These CCTA metrics could be useful for the diagnosis and monitoring of CAV severity., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Aims: Vessel-specific coronary artery calcification (CAC) is additive to global CAC for prognostic assessment. We assessed accuracy and prognostic implications of vessel-specific automated deep learning (DL) CAC analysis on electrocardiogram (ECG) gated and attenuation correction (AC) computed tomography (CT) in a large multi-centre registry., Methods and Results: Vessel-specific CAC was assessed in the left main/left anterior descending (LM/LAD), left circumflex (LCX), and right coronary artery (RCA) using a DL model trained on 3000 gated CT and tested on 2094 gated CT and 5969 non-gated AC CT. Vessel-specific agreement was assessed with linear weighted Cohen's Kappa for CAC zero, 1-100, 101-400, and >400 Agatston units (AU). Risk of major adverse cardiovascular events (MACE) was assessed during 2.4 ± 1.4 years follow-up, with hazard ratios (HR) and 95% confidence intervals (CI). There was strong to excellent agreement between DL and expert ground truth for CAC in LM/LAD, LCX and RCA on gated CT [0.90 (95% CI 0.89 to 0.92); 0.70 (0.68 to 0.73); 0.79 (0.77 to 0.81)] and AC CT [0.78 (0.77 to 0.80); 0.60 (0.58 to 0.62); 0.70 (0.68 to 0.71)]. MACE occurred in 242 (12%) undergoing gated CT and 841(14%) of undergoing AC CT. LM/LAD CAC >400 AU was associated with the highest risk of MACE on gated (HR 12.0, 95% CI 7.96, 18.0, P < 0.001) and AC CT (HR 4.21, 95% CI 3.48, 5.08, P < 0.001)., Conclusion: Vessel-specific CAC assessment with DL can be performed accurately and rapidly on gated CT and AC CT and provides important prognostic information., Competing Interests: Conflict of interest: M.C.W. has given talks for Canon Medical Systems and Siemens Healthineers. Dr. Robert Miller has received consulting fees and research support from Pfizer. Drs. Berman and Slomka and Mr. Kavanagh participate in software royalties for QPS software at Cedars-Sinai Medical Center. Dr. Berman is a consultant for GE Healthcare and Dr. Edward Miller has served as Pfizer, Eidos, CSL Behring, Anylam, and GE Healthcare consultant with grant support from Eidos, Pfizer, and Anylam. Dr. Slomka has received research grant support from Siemens Medical Systems. The remaining authors have no relevant disclosures., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: The left internal mammary artery (LIMA) is protected from developing atherosclerosis. Perivascular inflammation, which is closely associated with atherosclerosis, can be measured by perivascular adipose tissue attenuation on computed tomography angiography. Whether the absence of atherosclerosis in LIMA is related to the lower level of perivascular inflammation is unknown. This study was performed to compare the level of perivascular inflammation between LIMA in situ and native coronary arteries in patients with coronary artery disease., Methods and Results: A total of 573 patients who underwent both computed tomography angiography and optical coherence tomography imaging were included. The level of perivascular adipose tissue attenuation between LIMA in situ and coronary arteries was compared. Perivascular adipose tissue attenuation around LIMA in situ was significantly lower around the 3 coronary arteries (-82.9 [-87.3 to -78.0] versus -70.8 [-75.9 to -65.9]; P <0.001), irrespective of the level of pericoronary inflammation or the number of vulnerable features on optical coherence tomography. When patients were divided into high and low pericoronary inflammation groups, those in the high inflammation group had more target vessel failure (hazard ratio, 2.97 [95% CI, 1.16-7.59]; P =0.017)., Conclusions: The current study demonstrated that perivascular adipose tissue attenuation was significantly lower around LIMA in situ than around native coronary arteries. The lower level of perivascular inflammation may be related to the low prevalence of atherosclerosis in LIMA., Registration: URL: https://www.clinicaltrials.gov; Unique Identifier: NCT04523194.

Background: Total coronary atherosclerotic plaque activity across the entire coronary arterial tree is associated with patient-level clinical outcomes., Objectives: We aimed to investigate whether vessel-level coronary atherosclerotic plaque activity is associated with vessel-level myocardial infarction., Methods: In this secondary analysis of an international multicenter study of patients with recent myocardial infarction and multivessel coronary artery disease, we assessed vessel-level coronary atherosclerotic plaque activity using coronary 18 F-sodium fluoride positron emission tomography to identify vessel-level myocardial infarction., Results: Increased 18 F-sodium fluoride uptake was found in 679 of 2,094 coronary arteries and 414 of 691 patients. Myocardial infarction occurred in 24 (4%) vessels with increased coronary atherosclerotic plaque activity and in 25 (2%) vessels without increased coronary atherosclerotic plaque activity (HR: 2.08; 95% CI: 1.16-3.72; P = 0.013). This association was not demonstrable in those treated with coronary revascularization (HR: 1.02; 95% CI: 0.47-2.25) but was notable in untreated vessels (HR: 3.86; 95% CI: 1.63-9.10; P interaction  = 0.024). Increased coronary atherosclerotic plaque activity in multiple coronary arteries was associated with heightened patient-level risk of cardiac death or myocardial infarction (HR: 2.43; 95% CI: 1.37-4.30; P = 0.002) as well as first (HR: 2.19; 95% CI: 1.18-4.06; P = 0.013) and total (HR: 2.50; 95% CI: 1.42-4.39; P = 0.002) myocardial infarctions., Conclusions: In patients with recent myocardial infarction and multivessel coronary artery disease, coronary atherosclerotic plaque activity prognosticates individual coronary arteries and patients at risk for myocardial infarction., Competing Interests: Funding Support and Author Disclosures The PRE(18)FFIR study was funded by the Wellcome Trust (WT103782AIA). The funder played no roles in the design and conduct of the study, collection, management, analysis, and interpretation of the data, preparation, review, or approval of the manuscript, and any decisions to submit the manuscript for publication. The University of Edinburgh and the National Health Service Lothian Health Board were cosponsors. Dr Rudd is part-supported by the National Institute for Health and Care Research Cambridge Biomedical Research Centre, the British Heart Foundation, the Higher Education Funding Council for England, the Engineering and Physical Sciences Research Council, and the Wellcome Trust. Dr Piotr is supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health (R35HL161195). Dr Mills is supported by the British Heart Foundation (CH/F/21/90010, RE/18/5/34216, and RG/20/10/34966). Dr van Beek is supported by the Scottish Imaging Network. Dr Williams is supported by the British Heart Foundation (FS/ICRF/20/26002). Dr Dweck is supported by the British Heart Foundation (FS/SCRF/21/32010). Dr Newby is supported by the British Heart Foundation (CH/09/002, RE/18/5/34216, and RG/F/22/110093). Dr Moss is a current employee of AstraZeneca. Dr Williams has given talks for Canon Medical Systems, Novartis, and Siemens Healthineers. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: High-intensity plaque (HIP) on magnetic resonance imaging (MRI) has been documented as a powerful predictor of periprocedural myocardial injury (PMI) following percutaneous coronary intervention (PCI). Despite the recent proposal of three-dimensional HIP quantification to enhance the predictive capability, the conventional pulse sequence, which necessitates the separate acquisition of anatomical reference images, hinders accurate three-dimensional segmentation along the coronary vasculature. Coronary atherosclerosis T 1 -weighted characterization (CATCH) enables the simultaneous acquisition of inherently coregistered dark-blood plaque and bright-blood coronary artery images. We aimed to develop a novel HIP quantification approach using CATCH and to ascertain its superior predictive performance compared to the conventional two-dimensional assessment based on plaque-to-myocardium signal intensity ratio (PMR)., Methods: In this prospective study, CATCH MRI was conducted before elective stent implantation in 137 lesions from 125 patients. On CATCH images, dedicated software automatically generated tubular three-dimensional volumes of interest on the dark-blood plaque images along the coronary vasculature, based on the precisely matched bright-blood coronary artery images, and subsequently computed PMR and HIP volume (HIP vol ). Specifically, HIP vol was calculated as the volume of voxels with signal intensity exceeding that of the myocardium, weighted by their respective signal intensities. PMI was defined as post-PCI cardiac troponin-T > 5 × the upper reference limit., Results: The entire analysis process was completed within 3 min per lesion. PMI occurred in 44 lesions. Based on the receiver operating characteristic curve analysis, HIP vol outperformed PMR for predicting PMI (C-statistics, 0.870 [95% CI, 0.805-0.936] vs. 0.787 [95% CI, 0.706-0.868]; p = 0.001). This result was primarily driven by the higher sensitivity HIP vol offered: 0.886 (95% CI, 0.754-0.962) vs. 0.750 for PMR (95% CI, 0.597-0.868; p = 0.034). Multivariable analysis identified HIP vol as an independent predictor of PMI (odds ratio, 1.15 per 10-μL increase; 95% CI, 1.01-1.30, p = 0.035)., Conclusions: Our semi-automated method of analyzing coronary plaque using CATCH MRI provided rapid HIP quantification. Three-dimensional assessment using this approach had a better ability to predict PMI than conventional two-dimensional assessment., Competing Interests: Declaration of Competing Interest Yoshiaki Komori is an employee of Siemens Japan KK. Other authors have no conflicts of interest to declare., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations., Competing Interests: The authors have no potential conflicts of interest to disclose., (Copyright © 2024 The Korean Society of Radiology.)

Background: It was recently reported that thin-cap fibroatheroma (TCFA) detected by optical coherence tomography was an independent predictor of future cardiac events in patients with diabetes. However, the clinical usefulness of this finding is limited by the invasive nature of optical coherence tomography. Computed tomography angiography (CTA) characteristics of TCFA have not been systematically studied. The aim of this study was to investigate CTA characteristics of TCFA in patients with diabetes., Methods and Results: Patients with diabetes who underwent preintervention CTA and optical coherence tomography were included. Qualitative and quantitative analyses were performed for plaques on CTA. TCFA was assessed by optical coherence tomography. Among 366 plaques in 145 patients with diabetes, 111 plaques had TCFA. The prevalence of positive remodeling (74.8% versus 50.6%, P <0.001), low attenuation plaque (63.1% versus 33.7%, P <0.001), napkin-ring sign (32.4% versus 11.0%, P <0.001), and spotty calcification (55.0% versus 34.9%, P <0.001) was significantly higher in TCFA than in non-TCFA. Low-density noncalcified plaque volume (25.4 versus 15.7 mm 3 , P <0.001) and remodeling index (1.30 versus 1.20, P =0.002) were higher in TCFA than in non-TCFA. The presence of napkin-ring sign, spotty calcification, high low-density noncalcified plaque volume, and high remodeling index were independent predictors of TCFA. When all 4 predictors were present, the probability of TCFA increased to 82.4%., Conclusions: The combined qualitative and quantitative plaque analysis of CTA may be helpful in identifying TCFA in patients with diabetes., Registration Information: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04523194.

Background: Despite its potential benefits, the utilization of stress-only protocol in clinical practice has been limited. We report utilizing stress-first single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI)., Methods: We assessed 12,472 patients who were referred for SPECT-MPI between 2013 and 2020. The temporal changes in frequency of stress-only imaging were assessed according to risk factors, mode of stress, prior coronary artery disease (CAD) history, left ventricular function, and symptom status. The clinical endpoint was all-cause mortality., Results: In our lab, stress/rest SPECT-MPI in place of rest/stress SPECT-MPI was first introduced in November 2011 and was performed more commonly than rest/stress imaging after 2013. Stress-only SPECT-MPI scanning has been performed in 30-34% of our SPECT-MPI studies since 2013 (i.e.. 31.7% in 2013 and 33.6% in 2020). During the study period, we routinely used two-position imaging (additional prone or upright imaging) to reduce attenuation and motion artifact and introduced SPECT/CT scanner in 2018. The rate of stress-only study remained consistent before and after implementing the SPECT/CT scanner. The frequency of stress-only imaging was 43% among patients without a history of prior CAD and 19% among those with a prior CAD history. Among patients undergoing treadmill exercise, the frequency of stress-only imaging was 48%, while 32% among patients undergoing pharmacologic stress test. In multivariate Cox analysis, there was no significant difference in mortality risk between stress-only and stress/rest protocols in patients with normal SPECT-MPI results (p = 0.271)., Conclusion: Implementation of a stress-first imaging protocol has consistently resulted in safe cancellation of 30% of rest SPECT-MPI studies., Competing Interests: Declaration of competing interest Dr. Berman participates in software royalties for QPS software at Cedars-Sinai Medical Center. All other authors have no conflicts of interest to disclose., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Immune-mediated inflammatory diseases (IMIDs) are recognised risk factors for accelerated atherosclerotic cardiovascular disease (CVD), particularly in younger individuals and women who lack traditional CVD risk factors. Reflective of the critical role that inflammation plays in the formation, progression and rupture of atherosclerotic plaques, research into immune mechanisms of CVD has led to the identification of a range of therapeutic targets that are the subject of ongoing clinical trials. Several key inflammatory pathways implicated in the pathogenesis of atherosclerosis are targeted in people with IMIDs. However, cardiovascular risk continues to be systematically underestimated by conventional risk assessment tools in the IMID population, resulting in considerable excess CVD burden and mortality. Hence, there is a pressing need to improve methods for CVD risk-stratification among patients with IMIDs, to better guide the use of statins and other prognostic interventions. CT coronary angiography (CTCA) is the current first-line investigation for diagnosing and assessing the severity of coronary atherosclerosis in many individuals with suspected angina. Whether CTCA is also useful in the general population for reclassifying asymptomatic individuals and improving long-term prognosis remains unknown. However, in the context of IMIDs, it is conceivable that the information provided by CTCA, including state-of-the-art assessments of coronary plaque, could be an important clinical adjunct in this high-risk patient population. This narrative review discusses the current literature about the use of coronary CT for CVD risk-stratification in three of the most common IMIDs including rheumatoid arthritis, psoriasis and systemic lupus erythematosus., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: It is not known whether there is a sex difference in the association between perivascular inflammation and plaque vulnerability. The aim of this study was to investigate the sex-specific association between perivascular inflammation and plaque vulnerability., Methods: Patients who underwent coronary computed tomography angiography and optical coherence tomography were enrolled. All images were analyzed at a core laboratory. The level of perivascular inflammation was assessed by pericoronary adipose tissue attenuation on computed tomography angiography and the level of plaque vulnerability by optical coherence tomography. Patients were classified into 3 groups according to tertile levels of culprit vessel pericoronary adipose tissue attenuation (low inflammation, ≤-73.1 Hounsfield units; moderate inflammation, -73.0 to -67.0 Hounsfield units; or high inflammation, ≥-66.9 Hounsfield units)., Results: A total of 968 lesions in 409 patients were included: 184 lesions in 82 women (2.2 plaques per patient) and 784 lesions in 327 men (2.4 plaques per patient). Women were older (median age, 71 versus 65 years; P <0.001) and had less severe coronary artery disease with a lower plaque burden than men. In women, it was found that perivascular inflammation was significantly associated with plaque vulnerability, with a higher prevalence of thin-cap fibroatheroma and greater macrophage grades in the high inflammation group compared with the low inflammation group (low versus moderate versus high inflammation in women: 18.5% versus 31.8% versus 46.9%, P =0.002 for low versus high inflammation; 3 versus 4 versus 12, P <0.001 for low versus high inflammation, respectively). However, no significant differences were observed among the 3 groups in men., Conclusions: Perivascular inflammation was associated with a higher prevalence of thin-cap fibroatheroma and more significant macrophage accumulation in women but not in men., Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04523194., Competing Interests: Disclosures Dr Jang reports receiving educational grants from Abbott Vascular and consulting fees from Svelte Medical Systems Inc. Dr Ferencik has received consulting fees from Siemens Healthineers, HeartFlow, and Elucid. The other authors report no conflicts.

Motion correction (MC) affects myocardial blood flow (MBF) measurements in 82 Rb PET myocardial perfusion imaging (MPI); however, frame-by-frame manual MC of dynamic frames is time-consuming. This study aims to develop an automated MC algorithm for time-activity curves used in compartmental modeling and compare the predictive value of MBF with and without automated MC for significant coronary artery disease (CAD). Methods: In total, 565 patients who underwent PET-MPI were considered. Patients without angiographic findings were split into training ( n = 112) and validation ( n = 112) groups. The automated MC algorithm used simplex iterative optimization of a count-based cost function and was developed using the training group. MBF measurements with automated MC were compared with those with manual MC in the validation group. In a separate cohort, 341 patients who underwent PET-MPI and invasive coronary angiography were enrolled in the angiographic group. The predictive performance in patients with significant CAD (≥70% stenosis) was compared between MBF measurements with and without automated MC. Results: In the validation group ( n = 112), MBF measurements with automated and manual MC showed strong correlations ( r = 0.98 for stress MBF and r = 0.99 for rest MBF). The automatic MC took less time than the manual MC (<12 s vs. 10 min per case). In the angiographic group ( n = 341), MBF measurements with automated MC decreased significantly compared with those without (stress MBF, 2.16 vs. 2.26 mL/g/min; rest MBF, 1.12 vs. 1.14 mL/g/min; MFR, 2.02 vs. 2.10; all P < 0.05). The area under the curve (AUC) for the detection of significant CAD by stress MBF with automated MC was higher than that without (AUC, 95% CI, 0.76 [0.71-0.80] vs. 0.73 [0.68-0.78]; P < 0.05). The addition of stress MBF with automated MC to the model with ischemic total perfusion deficit showed higher diagnostic performance for detection of significant CAD (AUC, 95% CI, 0.82 [0.77-0.86] vs. 0.78 [0.74-0.83]; P = 0.022), but the addition of stress MBF without MC to the model with ischemic total perfusion deficit did not reach significance (AUC, 95% CI, 0.81 [0.76-0.85] vs. 0.78 [0.74-0.83]; P = 0.067). Conclusion: Automated MC on 82 Rb PET-MPI can be performed rapidly with excellent agreement with experienced operators. Stress MBF with automated MC showed significantly higher diagnostic performance than without MC., (© 2024 by the Society of Nuclear Medicine and Molecular Imaging.)

Background: Recently, it was reported that noncalcified plaque (NCP) volume was an independent predictor for cardiac events. Pericoronary adipose tissue (PCAT) attenuation is a marker of vascular inflammation and has been associated with increased cardiac mortality. The aim of this study was to evaluate the relationships between NCP volume, plaque vulnerability, and PCAT attenuation., Methods: Patients who underwent preintervention coronary computed tomography angiography and optical coherence tomography were enrolled. Plaque volume was measured by computed tomography angiography, plaque vulnerability by optical coherence tomography, and the level of coronary inflammation by PCAT attenuation. The plaques were divided into 2 groups of high or low NCP volume based on the median NCP volume., Results: Among 704 plaques in 454 patients, the group with high NCP volume had a higher prevalence of lipid-rich plaque (87.2% versus 75.9%; P <0.001), thin-cap fibroatheroma (38.1% versus 20.7%; P <0.001), macrophage (77.8% versus 63.4%; P <0.001), microvessel (58.2% versus 42.9%; P <0.001), and cholesterol crystal (42.0% versus 26.7%; P <0.001) than the group with low NCP plaque volume. The group with high NCP volume also had higher PCAT attenuation than the group with low NCP volume (-69.6±10.0 versus -73.5±10.6 Hounsfield unit; P <0.001). In multivariable analysis, NCP volume was significantly associated with thin-cap fibroatheroma and high PCAT attenuation. In the analysis of the combination of PCAT attenuation and NCP volume, the prevalence of thin-cap fibroatheroma was the highest in the high PCAT attenuation and high NCP volume group and the lowest in the low PCAT attenuation and low NCP volume group., Conclusions: Higher NCP volume was associated with higher plaque vulnerability and vascular inflammation. The combination of PCAT attenuation and NCP volume may help identify plaque vulnerability noninvasively., Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04523194., Competing Interests: Disclosures Dr Jang received educational grants from Abbott Vascular and consulting fees from Svelte Medical Systems, Inc. Outside the current study, Dr Dey received software royalties from the Cedars-Sinai Medical Center and has a patent. The other authors report no conflicts.

Background: Myocardial perfusion imaging (MPI) is one of the most common cardiac scans and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk. However, the large majority of MPI patients have normal results. We evaluated whether unsupervised machine learning could identify unique phenotypes among patients with normal scans and whether those phenotypes were associated with risk of death or myocardial infarction., Methods: Patients from a large international multicenter MPI registry (10 sites) with normal perfusion by expert visual interpretation were included in this cohort analysis. The training population included 9849 patients, and external testing population 12,528 patients. Unsupervised cluster analysis was performed, with separate training and external testing cohorts, to identify clusters, with four distinct phenotypes. We evaluated the clinical and imaging features of clusters and their associations with death or myocardial infarction., Findings: Patients in Clusters 1 and 2 almost exclusively underwent exercise stress, while patients in Clusters 3 and 4 mostly required pharmacologic stress. In external testing, the risk for Cluster 4 patients (20.2% of population, unadjusted hazard ratio [HR] 6.17, 95% confidence interval [CI] 4.64-8.20) was higher than the risk associated with pharmacologic stress (HR 3.03, 95% CI 2.53-3.63), or previous myocardial infarction (HR 1.82, 95% CI 1.40-2.36)., Interpretation: Unsupervised learning identified four distinct phenotypes of patients with normal perfusion scans, with a significant proportion of patients at very high risk of myocardial infarction or death. Our results suggest a potential role for patient phenotyping to improve risk stratification of patients with normal imaging results., Funding: This work was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R35HL161195 to PS]. The REFINE SPECT database was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R01HL089765 to PS]. MCW was supported by the British Heart Foundation [FS/ICRF/20/26002]., Competing Interests: Declaration of interests Dr. Robert Miller has received consulting and research support from Pfizer. Drs Berman and Slomka participate in software royalties for QPS software at Cedars-Sinai Medical Center. Dr Williams serves as the President-Elect of the British Society of Cardiovascular Imaging and is on the Board of Directors for the Society of Cardiovascular Computed Tomography; she has received consulting support from FEOPS and has given lectures for Canon Medical Systems, Siemens Healthineers and Novartis. Dr. Pieszko has served as a consultant for Medicalgorithmics S.A. Dr. Slomka has received consulting fees from Synektik. Drs. Berman, Sharir, Kaufmann, and Edward Miller have served as consultants for GE Healthcare. Dr. Dorbala has received honoraria from Novo Nordisk and Pfizer; her institution has received grant support from Attralus, Pfizer, GE Healthcare, Siemans, and Phillips. Dr. DiCarli has received institutional research grant support from Gilead Sciences and Amgen and consulting honoraria from Sanofi, Valo Health and MedTrace. Dr. Ruddy has received research grant support from GE Healthcare and Pfizer. Dr. Edward Miller has served as a consultant for ROIVANT; has received grant support from Anylam, Pfizer and Siemens, and has participated on the study advisory board of BioBridge. Dr. Sinusas serves a leadership role on the Society of Nuclear Medicine and Molecular Imaging Cardiovascular Council. Dr. Einstein receives royalties from Wolters Kluwer UpToDate and the American Society of Nuclear Cardiology/Society of Nuclear Medicine and Molecular Imaging, consulting fees from W.L Gore & Associates, support through patents with Columbia Technology Ventures, and has given lectures for Ionetix. Dr. Einstein's institution has received research support from GE Healthcare, Roche Medical Systems, W. L. Gore & Associates, Eidos Therapeutics, Attralus, Pfizer, Neovasc, Intellia Therapeutics, Ionis Pharmaceuticals, Canon Medical Systems, the International Atomic Energy Agency, National Council on Radiation Protection and Measurements, and the United States Regulatory Commission. The remaining authors have nothing to disclose., (Copyright © 2023. Published by Elsevier B.V.)

Artificial intelligence (AI) is likely to revolutionize the way medical images are analysed and has the potential to improve the identification and analysis of vulnerable or high-risk atherosclerotic plaques in coronary arteries, leading to advances in the treatment of coronary artery disease. However, coronary plaque analysis is challenging owing to cardiac and respiratory motion, as well as the small size of cardiovascular structures. Moreover, the analysis of coronary imaging data is time-consuming, can be performed only by clinicians with dedicated cardiovascular imaging training, and is subject to considerable interreader and intrareader variability. AI has the potential to improve the assessment of images of vulnerable plaque in coronary arteries, but requires robust development, testing and validation. Combining human expertise with AI might facilitate the reliable and valid interpretation of images obtained using CT, MRI, PET, intravascular ultrasonography and optical coherence tomography. In this Roadmap, we review existing evidence on the application of AI to the imaging of vulnerable plaque in coronary arteries and provide consensus recommendations developed by an interdisciplinary group of experts on AI and non-invasive and invasive coronary imaging. We also outline future requirements of AI technology to address bias, uncertainty, explainability and generalizability, which are all essential for the acceptance of AI and its clinical utility in handling the anticipated growing volume of coronary imaging procedures., (© 2023. Springer Nature Limited.)

Background: The Diamond-Forrester model was used extensively to predict obstructive coronary artery disease (CAD) but overestimates probability in current populations. Coronary artery calcium (CAC) is a useful marker of CAD, which is not routinely integrated with other features. We derived simple likelihood tables, integrating CAC with age, sex, and cardiac chest pain to predict obstructive CAD., Methods and Results: The training population included patients from 3 multinational sites (n=2055), with 2 sites for external testing (n=3321). We determined associations between age, sex, cardiac chest pain, and CAC with the presence of obstructive CAD, defined as any stenosis ≥50% on coronary computed tomography angiography. Prediction performance was assessed using area under the receiver-operating characteristic curves (AUCs) and compared with the CAD Consortium models with and without CAC, which require detailed calculations, and the updated Diamond-Forrester model. In external testing, the proposed likelihood tables had higher AUC (0.875 [95% CI, 0.862-0.889]) than the CAD Consortium clinical+CAC score (AUC, 0.868 [95% CI, 0.855-0.881]; P =0.030) and the updated Diamond-Forrester model (AUC, 0.679 [95% CI, 0.658-0.699]; P <0.001). The calibration for the likelihood tables was better than the CAD Consortium model (Brier score, 0.116 versus 0.121; P =0.005)., Conclusions: We have developed and externally validated simple likelihood tables to integrate CAC with age, sex, and cardiac chest pain, demonstrating improved prediction performance compared with other risk models. Our tool affords physicians with the opportunity to rapidly and easily integrate a small number of important features to estimate a patient's likelihood of obstructive CAD as an aid to clinical management.

Objectives: Epicardial adipose tissue (EAT) is a proposed marker of cardiovascular risk; however, clinical application may be limited by variability in post-processing software platforms. We assessed inter-vendor agreement of EAT volume (EATv) and attenuation on both contrast-enhanced (CE) and non-contrast CT (NCT) using a standard coronary CT reporting software (Vitrea), an EAT research-specific software (QFAT) and a freeware imaging software (OsiriX)., Methods: Seventy-six consecutive patients undergoing simultaneous CE and NCT had complete volumetric EAT measurement. Between-software, within-software NCT vs. CE, and inter- and intra-observer agreement were evaluated with analysis by ANOVA (with post hoc adjustment), Bland-Altman with 95% levels of agreement (LoA) and intraclass correlation coefficient (ICC)., Results: Mean EATv (freeware 53 ± 31 mL vs. research 93 ± 43 mL vs. coronary 157 ± 64 mL) and attenuation (freeware  - 72 ± 25 HU vs. research  - 75 ± 3 HU vs. coronary  - 61 ± 10 HU) were significantly different between all vendors (ANOVA p < 0.001). EATv was consistently higher in NCT vs. CE for all software packages, with most reproducibility found in research software (bias 26 mL, 95% LoA: 2 to 56 mL), compared to freeware (bias 11 mL 95% LoA: - 46 mL to 69 mL) and coronary software (bias 10 mL 95% LoA: - 127 to 147 mL). Research software had more comparable NCT vs. CE attenuation (- 75 vs. - 72 HU) compared to freeware (- 72 vs. - 57 HU) and coronary (- 61 vs.  - 39 HU). Excellent inter-observer agreement was seen with research (ICC 0.98) compared to freeware (ICC 0.73) and coronary software (ICC 0.75) with narrow LoA on Bland-Altman analysis., Conclusion: There are significant inter-vendor differences in EAT assessment. Our study suggests that research-specific software has better agreement and reproducibility compared to freeware or coronary software platforms., Key Points: • There are significant differences between EAT volume and attenuation values between software platforms, regardless of scan type. • Non-contrast scans routinely have higher mean EAT volume and attenuation; however, this finding is only consistently seen with research-specific software. • Of the three analyzed packages, research-specific software demonstrates the highest reproducibility, agreement, and reliability for both inter-scan and inter-observer agreement., (© 2023. The Author(s).)

Coronary artery disease is the leading cause of morbidity and mortality worldwide. Despite remarkable advances in the management of coronary artery disease, the prediction of adverse coronary events remains challenging. Over the preceding decades, considerable effort has been made to improve risk stratification using noninvasive imaging. Recently, these efforts have increasingly focused on the direct imaging of coronary atherosclerotic plaque. Modern imaging now allows imaging of coronary plaque burden, plaque type, atherosclerotic plaque activity, and plaque thrombosis, which have major potential to refine patient risk stratification, aid decision making, and advance future clinical practice., Competing Interests: Funding Support and Author Disclosures Dr Newby (CH/09/002, RE/18/5/34216, RG/16/10/32375), Dr Dweck (FS/14/78/31020), and Dr Williams (FS/11/014, CH/09/002, FS/ICRF/20/26002) are supported by the British Heart Foundation. Dr Tzolos was supported by a grant from Dr Miriam and the Sheldon G. Adelson Medical Research Foundation. Dr Newby is the recipient of a Wellcome Trust Senior Investigator Award (WT103782AIA) and Dr Dweck of the Sir Jules Thorn Award for Biomedical Research Award (2015). Dr Dey (R01HL133616) and Dr Slomka (R35HL161195) are supported by the National Heart, Lung, and Blood Institute/National Institute of Health (NHLBI/NIH)., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Coronary artery disease reporting and data system (CAD-RADS) predicts future cardiovascular events in patients with coronary artery disease (CAD). However, information on vascular inflammation and vulnerability remains scarce., Methods: Patients who underwent coronary computed tomography angiography (CTA) and optical coherence tomography (OCT) prior to coronary intervention were enrolled. All three coronary arteries were evaluated for CAD-RADS score and pericoronary adipose tissue (PCAT) attenuation, while the culprit vessel was analyzed for plaque vulnerability by OCT., Results: A total of 385 patients with 915 lesions were divided into two groups based on CAD-RADS score: 103 (26.8%) were categorized as CAD-RADS 4b/5 and 282 (73.2%) as CAD-RADS ≤4a. Patients with CAD-RADS 4b/5 had a higher level of PCAT attenuation (mean of 3 coronary arteries) than those with CAD-RADS ≤4a (-68.4 ​± ​6.7 HU vs. -70.1 ​± ​6.5, P ​= ​0.022). The prevalence of macrophage was higher, and lipid index was greater in patients with CAD-RADS 4b/5 than CAD-RADS ≤4a (94.2% vs. 83.0%, P ​= ​0.004, 1845 vs. 1477; P ​= ​0.003). These associations were significant in the culprit vessels of patients with chronic coronary syndrome but not in those with acute coronary syndromes., Conclusions: Higher CAD-RADS score was associated with higher levels of vascular inflammation and plaque vulnerability., Competing Interests: Declaration of competing interest Dr. Jang reports receiving educational grants from Abbott Vascular and consulting fees from Svelte Medical Systems, Inc. Dr. Ferencik has received consulting fees from Siemens Healthineers, HeartFlow, and Elucid. All other authors have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

The detection and characterization of coronary artery stenosis and atherosclerosis using imaging tools are key for clinical decision-making in patients with known or suspected coronary artery disease. In this regard, imaging-based quantification can be improved by choosing the most appropriate imaging modality for diagnosis, treatment and procedural planning. In this Consensus Statement, we provide clinical consensus recommendations on the optimal use of different imaging techniques in various patient populations and describe the advances in imaging technology. Clinical consensus recommendations on the appropriateness of each imaging technique for direct coronary artery visualization were derived through a three-step, real-time Delphi process that took place before, during and after the Second International Quantitative Cardiovascular Imaging Meeting in September 2022. According to the Delphi survey answers, CT is the method of choice to rule out obstructive stenosis in patients with an intermediate pre-test probability of coronary artery disease and enables quantitative assessment of coronary plaque with respect to dimensions, composition, location and related risk of future cardiovascular events, whereas MRI facilitates the visualization of coronary plaque and can be used in experienced centres as a radiation-free, second-line option for non-invasive coronary angiography. PET has the greatest potential for quantifying inflammation in coronary plaque but SPECT currently has a limited role in clinical coronary artery stenosis and atherosclerosis imaging. Invasive coronary angiography is the reference standard for stenosis assessment but cannot characterize coronary plaques. Finally, intravascular ultrasonography and optical coherence tomography are the most important invasive imaging modalities for the identification of plaques at high risk of rupture. The recommendations made in this Consensus Statement will help clinicians to choose the most appropriate imaging modality on the basis of the specific clinical scenario, individual patient characteristics and the availability of each imaging modality., (© 2023. Springer Nature Limited.)

Purpose: Phase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore the prognostic value of phase variables for predicting mortality over standard PET-MPI variables., Methods: Consecutive patients who underwent pharmacological stress-rest 82 Rb PET study were enrolled. All PET-MPI variables including phase variables (phase entropy, phase bandwidth, and phase standard deviation) were automatically obtained by QPET software (Cedars-Sinai, Los Angeles, CA). Cox proportional hazard analyses were used to assess associations with all-cause mortality (ACM)., Results: In a total of 3963 patients (median age 71 years; 57% male), 923 patients (23%) died during a median follow-up of 5 years. Annualized mortality rates increased with stress phase entropy, with a 4.6-fold difference between the lowest and highest decile groups of entropy (2.6 vs. 12.0%/year). Abnormal stress phase entropy (optimal cutoff value, 43.8%) stratified ACM risk in patients with normal and impaired MFR (both p < 0.001). Among three phase variables, only stress phase entropy was significantly associated with ACM after the adjustment of standard clinical and PET-MPI variables including MFR and stress-rest change of phase variables, whether modeled as binary variables (adjusted hazard ratio, 1.44 for abnormal entropy [> 43.8%]; 95%CI, 1.18-1.75; p < 0.001) or continuous variables (adjusted hazard ratio, 1.05 per 5% increase; 95%CI, 1.01-1.10; p = 0.030). The addition of stress phase entropy to the standard PET-MPI variables significantly improved the discriminatory power for ACM prediction (p < 0.001), but the other phase variables did not (p > 0.1)., Conclusion: Stress phase entropy is independently and incrementally associated with ACM beyond standard PET-MPI variables including MFR. Phase entropy can be obtained automatically and included in clinical reporting of PET-MPI studies to improve patient risk prediction., (© 2023. The Author(s).)

Objective: Inflammatory activity is one of the potential mechanisms of spontaneous coronary artery dissection (SCAD). Recently, the pericoronary adipose tissue attenuation (PCAT) derived from CT angiography (CTA) has been established as a method for measuring vascular inflammation. We aimed to characterise the pancoronary and vessel-specific PCAT in patients with and without recent SCAD., Methods: The study comprised patients with SCAD referred to a tertiary centre between 2017 and 2022 who underwent CTA and were compared with individuals with no prior SCAD. PCAT was analysed on end-diastolic CTA reconstructions along proximal 40 mm of all major coronary vessels as well as the SCAD-related vessel. We analysed 48 patients with recent SCAD (median 6.1 (IQR 3.5-14.9) months since SCAD, 95.8% female) and 48 patients in the group without SCAD., Results: Pancoronary PCAT was higher in patients with SCAD compared with those without SCAD (-80.6±7.9 vs -85.3 HU±6.1, p=0.002). Vessel-specific PCAT in patients with SCAD compared with patients without SCAD was higher for both the RCA (-80.9±9.5 vs -87.1±6.9 HU, p=0.001) and the LCA (-80.3±7.8 vs -83.4±7.2 HU, p=0.04). In patients with SCAD, PCAT of the SCAD-related vessel was not significantly different from averaged PCAT of unaffected vessels (-81.2±9.2 vs -80.6±7.6, p=0.74). There was no association between PCAT and the interval from SCAD to CTA., Conclusions: Patients with recent SCAD have higher PCAT compared with patients without SCAD, suggesting an increased perivascular inflammatory activity. This association is not restricted to the dissected vessel., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Coronary 18 F-sodium fluoride ( 18 F-fluoride) uptake is a marker of both atherosclerotic disease activity and disease progression. It is currently unknown whether there are rapid temporal changes in coronary 18 F-fluoride uptake and whether these are more marked in those with clinically unstable coronary artery disease. This study aimed to determine the natural history of coronary 18 F-fluoride uptake over 12 mo in patients with either advanced chronic coronary artery disease or a recent myocardial infarction. Methods: Patients with established multivessel coronary artery disease and either chronic disease or a recent acute myocardial infarction underwent coronary 18 F-fluoride PET and CT angiography, which was repeated at 3, 6, or 12 mo. Coronary 18 F-fluoride uptake was assessed in each vessel by measuring the coronary microcalcification activity (CMA). Coronary calcification was quantified by measuring calcium score, mass, and volume. Results: Fifty-nine patients had chronic coronary artery disease (median age, 68 y; 93% male), and 52 patients had a recent myocardial infarction (median age, 65 y; 83% male). Reflecting the greater burden of coronary artery disease, baseline CMA values were higher in those with chronic coronary artery disease. Coronary 18 F-fluoride uptake (CMA > 0) was associated with higher baseline calcium scores (294 Agatston units [AU] [interquartile range, 116-483 AU] vs. 72 AU [interquartile range, 8-222 AU]; P < 0.001) and more rapid progression of coronary calcification scores (39 AU [interquartile range, 10-82 AU] vs. 12 AU [interquartile range, 1-36 AU]; P < 0.001) than was the absence of uptake (CMA = 0). Coronary 18 F-fluoride uptake did not markedly alter over the course of 3, 6, or 12 mo in patients with either chronic coronary artery disease or a recent myocardial infarction. Conclusion: Coronary 18 F-fluoride uptake is associated with the severity and progression of coronary artery disease but does not undergo a rapid dynamic change in patients with chronic or unstable coronary artery disease. This finding suggests that coronary 18 F-fluoride uptake is a temporally stable marker of established and progressive disease., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

Importance: Recurrent coronary events in patients with recent myocardial infarction remain a major clinical problem. Noninvasive measures of coronary atherosclerotic disease activity have the potential to identify individuals at greatest risk., Objective: To assess whether coronary atherosclerotic plaque activity as assessed by noninvasive imaging is associated with recurrent coronary events in patients with myocardial infarction., Design, Setting, and Participants: This prospective, longitudinal, international multicenter cohort study recruited participants aged 50 years or older with multivessel coronary artery disease and recent (within 21 days) myocardial infarction between September 2015 and February 2020, with a minimum 2 years' follow-up., Intervention: Coronary 18F-sodium fluoride positron emission tomography and coronary computed tomography angiography., Main Outcomes and Measures: Total coronary atherosclerotic plaque activity was assessed by 18F-sodium fluoride uptake. The primary end point was cardiac death or nonfatal myocardial infarction but was expanded during study conduct to include unscheduled coronary revascularization due to lower than anticipated primary event rates., Results: Among 2684 patients screened, 995 were eligible, 712 attended for imaging, and 704 completed an interpretable scan and comprised the study population. The mean (SD) age of participants was 63.8 (8.2) years, and most were male (601 [85%]). Total coronary atherosclerotic plaque activity was identified in 421 participants (60%). After a median follow-up of 4 years (IQR, 3-5 years), 141 participants (20%) experienced the primary end point: 9 had cardiac death, 49 had nonfatal myocardial infarction, and 83 had unscheduled coronary revascularizations. Increased coronary plaque activity was not associated with the primary end point (hazard ratio [HR], 1.25; 95% CI, 0.89-1.76; P = .20) or unscheduled revascularization (HR, 0.98; 95% CI, 0.64-1.49; P = .91) but was associated with the secondary end point of cardiac death or nonfatal myocardial infarction (47 of 421 patients with high plaque activity [11.2%] vs 19 of 283 with low plaque activity [6.7%]; HR, 1.82; 95% CI, 1.07-3.10; P = .03) and all-cause mortality (30 of 421 patients with high plaque activity [7.1%] vs 9 of 283 with low plaque activity [3.2%]; HR, 2.43; 95% CI, 1.15-5.12; P = .02). After adjustment for differences in baseline clinical characteristics, coronary angiography findings, and Global Registry of Acute Coronary Events score, high coronary plaque activity was associated with cardiac death or nonfatal myocardial infarction (HR, 1.76; 95% CI, 1.00-3.10; P = .05) but not with all-cause mortality (HR, 2.01; 95% CI, 0.90-4.49; P = .09)., Conclusions and Relevance: In this cohort study of patients with recent myocardial infarction, coronary atherosclerotic plaque activity was not associated with the primary composite end point. The findings suggest that risk of cardiovascular death or myocardial infarction in patients with elevated plaque activity warrants further research to explore its incremental prognostic implications.

Background: Positron emission tomography (PET) is the clinical gold standard for quantifying myocardial blood flow (MBF). Pericoronary adipose tissue (PCAT) attenuation may detect vascular inflammation indirectly. We examined the relationship between MBF by PET and plaque burden and PCAT on coronary CT angiography (CCTA)., Methods: This post hoc analysis of the PACIFIC trial included 208 patients with suspected coronary artery disease (CAD) who underwent [ 15 O]H 2 O PET and CCTA. Low-attenuation plaque (LAP, < 30HU), non-calcified plaque (NCP), and PCAT attenuation were measured by CCTA., Results: In 582 vessels, 211 (36.3%) had impaired per-vessel hyperemic MBF (≤ 2.30 mL/min/g). In multivariable analysis, LAP burden was independently and consistently associated with impaired hyperemic MBF (P = 0.016); over NCP burden (P = 0.997). Addition of LAP burden improved predictive performance for impaired hyperemic MBF from a model with CAD severity and calcified plaque burden (P < 0.001). There was no correlation between PCAT attenuation and hyperemic MBF (r = - 0.11), and PCAT attenuation was not associated with impaired hyperemic MBF in univariable or multivariable analysis of all vessels (P > 0.1)., Conclusion: In patients with stable CAD, LAP burden was independently associated with impaired hyperemic MBF and a stronger predictor of impaired hyperemic MBF than NCP burden. There was no association between PCAT attenuation and hyperemic MBF., (© 2023. The Author(s) under exclusive licence to American Society of Nuclear Cardiology.)

Purpose: Coronary inflammation is postulated as a driver of atherosclerosis and dysfunctional arterial healing which may trigger stent failure. Pericoronary adipose tissue (PCAT) attenuation, detected on computer tomography coronary angiography (CTCA), is an emerging non-invasive marker of coronary inflammation. This propensity matched study assessed the utility of both lesion specific (PCAT Lesion ) and standardized PCAT attenuation as assessed in the proximal RCA (PCAT RCA ) as a predictor of stent failure in patients undergoing elective percutaneous coronary intervention. This is the first study to our knowledge that assesses the association of PCAT with stent failure., Methods: Patients undergoing CTCA assessment for coronary artery disease with subsequent stent insertion within 60 days and repeat coronary angiography for any clinical reason within 5 years were included in the study. Stent failure was defined as binary restenosis of >50 % on quantitative coronary angiography analysis or stent thrombosis. Both PCAT Lesion and PCAT RCA was assessed utilizing semi-automated proprietary software on baseline CTCA. Patients with stent failure were propensity matched utilizing age, sex, cardiovascular risk factors and procedural characteristics., Results: One hundred and fifty-one patients met inclusion criteria. Of these, 26 (17.2 %) had study-defined failure. A significant difference in PCAT Lesion attenuation between patients with and without failure was observed (-79.0 ± 12.6 vs. -85.9 ± 10.3HU, p = 0.035). There was no significant difference in PCAT RCA attenuation between the two groups (-79.5 ± 10.1 vs -81.0 ± 12.3HU, p = 0.50). Univariate regression analysis showed PCAT Lesion attenuation was independently associated with stent failure (OR 1.06, 95 % CI 1.01-1.12, P = 0.035)., Conclusions: Patients with stent failure exhibit significantly increased PCAT Lesion attenuation at baseline. These data suggest that baseline plaque inflammation may be an important driver for coronary stent failure., Competing Interests: Conflict of interest All authors report no conflict of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Coronary artery calcium scoring (CAC) has garnered attention in the diagnostic approach to chest pain patients. However, little is known about the interplay between zero CAC, sex, race, ethnicity, and quantitative coronary plaque analysis., Methods: We conducted a retrospective analysis from our computed tomography registry of patients with stable angina without prior myocardial infarction or revascularization undergoing coronary computed tomography angiography at Montefiore Healthcare System. Follow-up end points collected included invasive angiography, type-1 myocardial infarction, coronary revascularization, cardiovascular and all-cause death., Results: A total of 2249 patients were included (66% female). The median follow-up was 5.5 years. The median age of those without CAC was 52 years (interquartile range, 44-59) and 60 years (interquartile range, 53-68) in those with CAC. Most patients were Hispanic (58%), and the rest were non-Hispanic Black (28%), non-Hispanic White (10%), and non-Hispanic Asian (5%). The majority had CAC=0 (55%). The negative predictive value of CAC=0 was 92.8%, 99.9%, and 99.9% for any plaque, obstructive coronary artery stenosis, and the composite outcome of all-cause death, myocardial infarction, or coronary revascularization, respectively. Among patients without CAC (n=1237), 89 patients (7%) had evidence of plaque on their coronary computed tomography angiography with a median low-attenuation noncalcified plaque burden of 4% (2-7). There were no significant differences in the negative predictive value for CAC=0 by sex, race, or ethnicity. Patients with ≥2 risk factors had higher odds of having plaque with zero CAC., Conclusions: In summary, no sex, race, or ethnicity differences were demonstrated in the negative predictive value of a zero CAC; however, patients with ≥2 risk factors had a higher prevalence of plaque. A small percentage (7%) of symptomatic patients undergoing coronary computed tomography angiography with zero CAC had noncalcified coronary plaque, with the implication that caution is needed for downscaling of preventive treatment in patients with zero CAC, chest pain, and multiple risk factors., Competing Interests: Disclosures Dr Virani has received research support from the Department of Veterans Affairs, National Institutes of Health (NIH), Tahir and Jooma Family and Honorarium from American College of Cardiology (Associate Editor for Innovations, acc.org). Dr Slipczuk has received consulting honorarium from Amgen, Regeneron, and Philips; and Grant support from Amgen. Drs Slomka, Berman, and Dey have received software royalties from Cedars-Sinai Medical Center. Dr Dey was supported by grants from National Heart, Lung and Blood Institute (1R01HL148787–01A1 and R01HL151266 and NIH diversity administrative supplement for grant R01 HL148787). Dr Blaha has received grants from NIH, Novo Nordisk, Novartis. Dr Zhang has received a grant from the New York Academy of Medicine. Dr Rodriguez is supported by grant from the NIH (R01 HL04199, 75N92019D00011, 1U01HL146204-01, 5R01HL144707) and the American Heart Association (5P50HL120163-04) and has participated in Advisory Boards for Amgen and has worked as a Consultant for Merck. Other authors declare no conflict.

Purpose: Patients with known coronary artery disease (CAD) comprise a heterogenous population with varied clinical and imaging characteristics. Unsupervised machine learning can identify new risk phenotypes in an unbiased fashion. We use cluster analysis to risk-stratify patients with known CAD undergoing single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI)., Methods: From 37,298 patients in the REFINE SPECT registry, we identified 9221 patients with known coronary artery disease. Unsupervised machine learning was performed using clinical (23), acquisition (17), and image analysis (24) parameters from 4774 patients (internal cohort) and validated with 4447 patients (external cohort). Risk stratification for all-cause mortality was compared to stress total perfusion deficit (< 5%, 5-10%, ≥10%)., Results: Three clusters were identified, with patients in Cluster 3 having a higher body mass index, more diabetes mellitus and hypertension, and less likely to be male, have dyslipidemia, or undergo exercise stress imaging (p < 0.001 for all). In the external cohort, during median follow-up of 2.6 [0.14, 3.3] years, all-cause mortality occurred in 312 patients (7%). Cluster analysis provided better risk stratification for all-cause mortality (Cluster 3: hazard ratio (HR) 5.9, 95% confidence interval (CI) 4.0, 8.6, p < 0.001; Cluster 2: HR 3.3, 95% CI 2.5, 4.5, p < 0.001; Cluster 1, reference) compared to stress total perfusion deficit (≥10%: HR 1.9, 95% CI 1.5, 2.5 p < 0.001; < 5%: reference)., Conclusions: Our unsupervised cluster analysis in patients with known CAD undergoing SPECT MPI identified three distinct phenotypic clusters and predicted all-cause mortality better than ischemia alone., (© 2023. The Author(s).)

Background: Assessments of coronary disease activity with 18 F-sodium fluoride positron emission tomography and radiomics-based precision coronary plaque phenotyping derived from coronary computed tomography angiography may enhance risk stratification in patients with coronary artery disease. We sought to investigate whether the prognostic information provided by these 2 approaches is complementary in the prediction of myocardial infarction., Methods: Patients with known coronary artery disease underwent coronary 18 F-sodium fluoride positron emission tomography and coronary computed tomography angiography on a hybrid positron emission tomography/computed tomography scanner. Coronary 18 F-NaF uptake was determined by the coronary microcalcification activity. We performed quantitative plaque analysis of coronary computed tomography angiography datasets and extracted 1103 radiomic features for each plaque. Using weighted correlation network analysis, we derived latent morphological features of coronary lesions which were aggregated to patient-level radiomics nomograms to predict myocardial infarction., Results: Among 260 patients with established coronary artery disease (age, 65±9 years; 83% men), 179 (69%) participants showed increased coronary 18 F-NaF activity (coronary microcalcification activity>0). Over 53 (40-59) months of follow-up, 18 patients had a myocardial infarction. Using weighted correlation network analysis, we derived 15 distinct eigen radiomic features representing latent morphological coronary plaque patterns in an unsupervised fashion. Following adjustments for calcified, noncalcified, and low-density noncalcified plaque volumes and 18 F-NaF coronary microcalcification activity, 4 radiomic features remained independent predictors of myocardial infarction (hazard ratio, 1.46 [95% CI, 1.03-2.08]; P =0.03; hazard ratio, 1.62 [95% CI, 1.04-2.54]; P =0.02; hazard ratio, 1.49 [95% CI, 1.07-2.06]; P =0.01; and hazard ratio, 1.50 (95% CI, 1.05-2.13); P =0.02)., Conclusions: In patients with established coronary artery disease, latent coronary plaque morphological features, quantitative plaque volumes, and disease activity on 18 F-sodium fluoride positron emission tomography are additive predictors of myocardial infarction., Competing Interests: Disclosures None.

Compared with plaque rupture, plaque erosion has distinct features, which can be diagnosed only by intravascular optical coherence tomography. Computed tomography angiography (CTA) features of plaque erosion have not been reported. The aim of the present study was to identify the CTA features specific for plaque erosion in patients with non-ST-segment elevation acute coronary syndromes to enable a diagnosis of erosion without invasive procedures. Patients with non-ST-segment elevation acute coronary syndromes who underwent preintervention CTA and optical coherence tomography imaging of culprit lesions were enrolled. Plaque volume and high-risk plaque (HRP) features were assessed by CTA. Among 191 patients, plaque erosion was the underlying mechanism in 89 patients (46.6%) and plaque rupture in 102 patients (53.4%). The total plaque volume (TPV) was lower in plaque erosion than in plaque rupture (133.6 vs 168.8 mm 3 , p = 0.001). Plaque erosion had a lower prevalence of positive remodeling than plaque rupture (75.3% vs 87.3%, p = 0.033). As the number of HRP features decreased, plaque erosion became more prevalent (p = 0.014). In the multivariable logistic regression analysis, lower TPV and less prevalent HRP features were associated with a higher prevalence of plaque erosion. The addition of TPV ≤116 mm 3 and HRP features ≤1 to the known predictors significantly increased the area under the curve of the plaque erosion prediction receiver operator characteristics. Plaque erosion, compared with plaque rupture, had a lower plaque volume and less prevalent HRP features. CTA may be helpful for identifying the underlying pathology of acute coronary syndromes., Competing Interests: Disclosures Dr. Jang has received educational grant support from Abbott Vascular and a consulting fee from Svelte Medical Systems. Outside the present study, Dr. Dey has received software royalties from Cedars-Sinai Medical Center and has a patent. Dr. Ferencik has received consulting fees from Siemens Healthineers, HeartFlow, and Elucid. The remaining authors have no conflicts of interest to declare., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Assessment of coronary artery calcium (CAC) by computed tomographic (CT) imaging provides an accurate measure of atherosclerotic burden. CAC is also visible in computed tomographic attenuation correction (CTAC) scans, always acquired with cardiac positron emission tomographic (PET) imaging., Objectives: The aim of this study was to develop a deep-learning (DL) model capable of fully automated CAC definition from PET CTAC scans., Methods: The novel DL model, originally developed for video applications, was adapted to rapidly quantify CAC. The model was trained using 9,543 expert-annotated CT scans and was tested in 4,331 patients from an external cohort undergoing PET/CT imaging with major adverse cardiac events (MACEs) (follow-up 4.3 years), including same-day paired electrocardiographically gated CAC scans available in 2,737 patients. MACE risk stratification in 4 CAC score categories (0, 1-100, 101-400, and >400) was analyzed and CAC scores derived from electrocardiographically gated CT scans (standard scores) by expert observers were compared with automatic DL scores from CTAC scans., Results: Automatic DL scoring required <6 seconds per scan. DL CTAC scores provided stepwise increase in the risk for MACE across the CAC score categories (HR up to 3.2; P < 0.001). Net reclassification improvement of standard CAC scores over DL CTAC scores was nonsignificant (-0.02; 95% CI: -0.11 to 0.07). The negative predictive values for MACE of zero CAC with standard (85%) and DL CTAC (83%) CAC scores were similar (P = 0.19)., Conclusions: DL CTAC scores predict cardiovascular risk similarly to standard CAC scores quantified manually by experienced operators from dedicated electrocardiographically gated CAC scans and can be obtained almost instantly, with no changes to PET/CT scanning protocol., Competing Interests: Funding Support and Author Disclosures This research was supported in part by grant R01HL089765 from the National Heart, Lung, and Blood Institute/National Institutes of Health (principal investigator, Piotr Slomka). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr Pieszko was supported by a research scholarship from the Polish National Agency for Academic Exchange. Cedars-Sinai has a pending patent application on the use of convolutional long short-term memory for multislice medical image segmentation. Drs Berman, Slomka, and Van Kriekinge and Mr Kavanagh participate in software royalties for nuclear cardiology software at Cedars-Sinai Medical Center. Dr Slomka has received research grant support from Siemens Medical Systems. Dr Berman has served as a consultant for GE Healthcare. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

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., (Published by Elsevier Inc.)

Objective: In patients with acute chest pain who have had myocardial infarction excluded, plasma cardiac troponin I concentrations ≥5 ng/L are associated with risk of future adverse cardiovascular events. We aim to evaluate the association between cardiac troponin and coronary plaque composition in such patients., Methods: In a prespecified secondary analysis of a prospective cohort study, blinded quantitative plaque analysis was performed on 242 CT coronary angiograms of patients with acute chest pain in whom myocardial infarction was excluded. Patients were stratified by peak plasma cardiac troponin I concentration ≥5 ng/L or <5 ng/L. Associations were assessed using univariable and multivariable logistic regression analyses., Results: The cohort was predominantly middle-aged (62±12 years) men (69%). Patients with plasma cardiac troponin I concentration ≥5 ng/L (n=161) had a higher total (median 33% (IQR 0-47) vs 0% (IQR 0-33)), non-calcified (27% (IQR 0-37) vs 0% (IQR 0-28)), calcified (2% (IQR 0-8) vs 0% (IQR 0-3)) and low-attenuation (1% (IQR 0-3) vs 0% (IQR 0-1)) coronary plaque burden compared with those with concentrations <5 ng/L (n=81; p≤0.001 for all). Low-attenuation plaque burden was independently associated with plasma cardiac troponin I concentration ≥5 ng/L after adjustment for clinical characteristics (adjusted OR per doubling 1.62 (95% CI 1.17 to 2.32), p=0.005) or presence of any visible coronary artery disease (adjusted OR per doubling 1.57 (95% CI 1.07 to 2.37), p=0.026)., Conclusion: In patients with acute chest pain but without myocardial infarction, plasma cardiac troponin I concentrations ≥5 ng/L are associated with greater burden of low-attenuation coronary plaque., Competing Interests: Competing interests: Outside the current study, DD received software royalties from Cedars-Sinai Medical Center and has a patent. MCW has spoken at meetings sponsored by Canon Medical Systems and Siemens Healthineers. DEN is on the Editorial Board of Heart. MRD, MCW and KKL are members of Heart’s Editorial Board., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Low-dose ungated CT attenuation correction (CTAC) scans are commonly obtained with SPECT/CT myocardial perfusion imaging. Despite the characteristically low image quality of CTAC, deep learning (DL) can potentially quantify coronary artery calcium (CAC) from these scans in an automatic manner. We evaluated CAC quantification derived with a DL model, including correlation with expert annotations and associations with major adverse cardiovascular events (MACE). Methods: We trained a convolutional long short-term memory DL model to automatically quantify CAC on CTAC scans using 6,608 studies (2 centers) and evaluated the model in an external cohort of patients without known coronary artery disease ( n = 2,271) obtained in a separate center. We assessed agreement between DL and expert annotated CAC scores. We also assessed associations between MACE (death, revascularization, myocardial infarction, or unstable angina) and CAC categories (0, 1-100, 101-400, or >400) for scores manually derived by experienced readers and scores obtained fully automatically by DL using multivariable Cox models (adjusted for age, sex, past medical history, perfusion, and ejection fraction) and net reclassification index. Results: In the external testing population, DL CAC was 0 in 908 patients (40.0%), 1-100 in 596 (26.2%), 100-400 in 354 (15.6%), and >400 in 413 (18.2%). Agreement in CAC category by DL CAC and expert annotation was excellent (linear weighted κ, 0.80), but DL CAC was obtained automatically in less than 2 s compared with about 2.5 min for expert CAC. DL CAC category was an independent risk factor for MACE with hazard ratios in comparison to a CAC of zero: CAC of 1-100 (2.20; 95% CI, 1.54-3.14; P < 0.001), CAC of 101-400 (4.58; 95% CI, 3.23-6.48; P < 0.001), and CAC of more than 400 (5.92; 95% CI, 4.27-8.22; P < 0.001). Overall, the net reclassification index was 0.494 for DL CAC, which was similar to expert annotated CAC (0.503). Conclusion: DL CAC from SPECT/CT attenuation maps agrees well with expert CAC annotations and provides a similar risk stratification but can be obtained automatically. DL CAC scores improved classification of a significant proportion of patients as compared with SPECT myocardial perfusion alone., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

Purpose of Review: Imaging of adverse coronary plaque features by coronary computed tomography angiography (CCTA) has advanced greatly and at a fast pace. We aim to describe the evolution, present and future in plaque analysis, and its value in comparison to plaque burden., Recent Findings: Recently, it has been demonstrated that in addition to plaque burden, quantitative and qualitative assessment of coronary plaque by CCTA can improve the prediction of future major adverse cardiovascular events in diverse coronary artery disease scenarios. The detection of high-risk non-obstructive coronary plaque can lead to higher use of preventive medical therapies such as statins and aspirin, help identify culprit plaque, and differentiate between myocardial infarction types. Even more, over traditional plaque burden, plaque analysis including pericoronary inflammation can potentially be useful tools for tracking disease progression and response to medical therapy. The identification of the higher risk phenotypes with plaque burden, plaque characteristics, or ideally both can allow the allocation of targeted therapies and potentially monitor response. Further observational data are now required to investigate these key issues in diverse populations, followed by rigorous randomized controlled trials., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Aims: We sought to assess and compare the association of epicardial adipose tissue (EAT) with cardiovascular disease (CVD) in HIV-positive and HIV-negative groups., Methods and Results: Using existing clinical databases, we analyzed 700 patients (195 HIV-positive, 505 HIV-negative). CVD was quantified by the presence of coronary calcification from both dedicated cardiac computed tomography (CT) and non-dedicated CT of the thorax. Epicardial adipose tissue (EAT) was quantified using dedicated software. The HIV-positive group had lower mean age (49.2 versus 57.8, p < 0.005), higher proportion of male sex (75.9 % versus 48.1 %, p < 0.005), and lower rates of coronary calcification (29.2 % versus 58.2 %, p < 0.005). Mean EAT volume was also lower in the HIV-positive group (68mm3 versus 118.3mm3, p < 0.005). Multiple linear regression demonstrated EAT volume was associated with hepatosteatosis (HS) in the HIV-positive group but not the HIV-negative group after adjustment for BMI (p < 0.005 versus p = 0.066). In the multivariate analysis, after adjustment for CVD risk factors, age, sex, statin use, and body mass index (BMI), EAT volume and hepatosteatosis were significantly associated with coronary calcification (odds ratio [OR] 1.14, p < 0.005 and OR 3.17, p < 0.005 respectively). In the HIV-negative group, the only significant association with EAT volume after adjustment was total cholesterol (OR 0.75, p = 0.012)., Conclusions: We demonstrated a strong and significant independent association of EAT volume and coronary calcium, after adjustment, in HIV-positive group but not in the HIV-negative group. This result hints at differences in the mechanistic drivers of atherosclerosis between HIV-positive and HIV-negative groups., Competing Interests: Conflict of interest statement T.H. received speaking fees from Merck Sharp & Dohme and Gilead and received investigator-sponsored research grant from Gilead Sciences. S.M. received speaking fees from Gilead Sciences. G.L. consultant and speaker for BMS/P!zer, Boehringer Ingelheim, and Daiichi-Sankyo. No fees received personally. DD: NIH/NHLBI grant 1R01HL133616. S.K. received grants from Gilead Sciences, Merck Sharp & Dohme, and Janssen and received grants and speaking fees from ViiV Healthcare. The remaining authors have no funding or conflicts of interest to disclose., (Copyright © 2023 The British Infection Association. Published by Elsevier Ltd. All rights reserved.)

Background: Vascular inflammation plays a key role in atherogenesis and in the development of acute coronary syndromes. Coronary inflammation can be measured by peri-coronary adipose tissue (PCAT) attenuation on computed tomography angiography. We examined the relationships between the level of coronary artery inflammation assessed by PCAT attenuation and coronary plaque characteristics by optical coherence tomography., Methods: A total of 474 patients (198 acute coronary syndromes and 276 stable angina pectoris) who underwent preintervention coronary computed tomography angiography and optical coherence tomography were included. To compare the relationships between the level of coronary artery inflammation and detailed plaque characteristics, we divided the subjects into high (n=244) and low (n=230) PCAT attenuation groups using a threshold value of -70.1 Hounsfield units., Results: The high PCAT attenuation group, compared with the low PCAT attenuation group, had more males (90.6% versus 69.6%; P <0.001), more non-ST-segment elevation myocardial infarction (38.5% versus 25.7%; P =0.003), and less stable angina pectoris (51.6% versus 65.2%; P =0.003). Aspirin, dual antiplatelet, and statins were less frequently used in the high PCAT attenuation group compared to the low PCAT attenuation group. Patients with high PCAT attenuation, compared with those with low PCAT attenuation, had lower ejection fraction (median 64% versus 65%; P =0.014) and lower levels of high-density lipoprotein cholesterol (median 45 versus 48 mg/dL; P =0.027). Optical coherence tomography features of plaque vulnerability were significantly more common in patients with high PCAT attenuation, compared to those with low PCAT attenuation, including lipid-rich plaque (87.3% versus 77.8%; P =0.006), macrophage (76.2% versus 67.8%; P =0.041), microchannels (61.9% versus 48.3%; P =0.003), plaque rupture (38.1% versus 23.9%; P <0.001), and layered plaque (60.2% versus 50.0%; P =0.025)., Conclusions: Optical coherence tomography features of plaque vulnerability were significantly more common in patients with high PCAT attenuation, compared with those with low PCAT attenuation. Vascular inflammation and plaque vulnerability are intimately related in patients with coronary artery disease., Registration: URL: https://www., Clinicaltrials: gov; Unique identifier: NCT04523194.

To improve diagnostic accuracy, myocardial perfusion imaging (MPI) SPECT studies can use CT-based attenuation correction (AC). However, CT-based AC is not available for most SPECT systems in clinical use, increases radiation exposure, and is impacted by misregistration. We developed and externally validated a deep-learning model to generate simulated AC images directly from non-AC (NC) SPECT, without the need for CT. Methods: SPECT myocardial perfusion imaging was performed using 99m Tc-sestamibi or 99m Tc-tetrofosmin on contemporary scanners with solid-state detectors. We developed a conditional generative adversarial neural network that applies a deep learning model (DeepAC) to generate simulated AC SPECT images. The model was trained with short-axis NC and AC images performed at 1 site ( n = 4,886) and was tested on patients from 2 separate external sites ( n = 604). We assessed the diagnostic accuracy of the stress total perfusion deficit (TPD) obtained from NC, AC, and DeepAC images for obstructive coronary artery disease (CAD) with area under the receiver-operating-characteristic curve. We also quantified the direct count change among AC, NC, and DeepAC images on a per-voxel basis. Results: DeepAC could be obtained in less than 1 s from NC images; area under the receiver-operating-characteristic curve for obstructive CAD was higher for DeepAC TPD (0.79; 95% CI, 0.72-0.85) than for NC TPD (0.70; 95% CI, 0.63-0.78; P < 0.001) and similar to AC TPD (0.81; 95% CI, 0.75-0.87; P = 0.196). The normalcy rate in the low-likelihood-of-coronary-disease population was higher for DeepAC TPD (70.4%) and AC TPD (75.0%) than for NC TPD (54.6%, P < 0.001 for both). The positive count change (increase in counts) was significantly higher for AC versus NC (median, 9.4; interquartile range, 6.0-14.2; P < 0.001) than for AC versus DeepAC (median, 2.4; interquartile range, 1.3-4.2). Conclusion: In an independent external dataset, DeepAC provided improved diagnostic accuracy for obstructive CAD, as compared with NC images, and this accuracy was similar to that of actual AC. DeepAC simplifies the task of artifact identification for physicians, avoids misregistration artifacts, and can be performed rapidly without the need for CT hardware and additional acquisitions., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

Background: Distinct sex-related differences exist in coronary artery plaque burden and distribution. We aimed to explore sex differences in quantitative plaque burden by coronary CT angiography (CCTA) in relation to ischemia by invasive fractional flow reserve (FFR)., Methods: This post-hoc analysis of the PACIFIC trial included 581 vessels in 203 patients (mean age 58.1 ​± ​8.7 years, 63.5% male) who underwent CCTA and per-vessel invasive FFR. Quantitative assessment of total, calcified, non-calcified, and low-density non-calcified plaque burden were performed using semiautomated software. Significant ischemia was defined as invasive FFR ≤0.8., Results: The per-vessel frequency of ischemia was higher in men than women (33.5% vs. 7.5%, p ​< ​0.001). Women had a smaller burden of all plaque subtypes (all p ​< ​0.01). There was no sex difference on total, calcified, or non-calcified plaque burdens in vessels with ischemia; only low-density non-calcified plaque burden was significantly lower in women (beta: -0.183, p ​= ​0.035). The burdens of all plaque subtypes were independently associated with ischemia in both men and women (For total plaque burden (5% increase): Men, OR: 1.15, 95%CI: 1.06-1.24, p ​= ​0.001; Women, OR: 1.96, 95%CI: 1.11-3.46, p ​= ​0.02). No significant interaction existed between sex and total plaque burden for predicting ischemia (interaction p ​= ​0.108). The addition of quantitative plaque burdens to stenosis severity and adverse plaque characteristics improved the discrimination of ischemia in both men and women., Conclusions: In symptomatic patients with suspected CAD, women have a lower CCTA-derived burden of all plaque subtypes compared to men. Quantitative plaque burden provides independent and incremental predictive value for ischemia, irrespective of sex., Competing Interests: Declaration of Competing Interest Outside of the current work, S.C., P.S., and D.D. received software royalties from Cedars-Sinai Medical Center. D.B, P.S., and D.D. hold a patent (US8885905B2 in USA and WO patent WO2011069120A1, Method and System for Plaque Characterization)., (Copyright © 2022 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

Competing Interests: Competing interests: None declared.

Background: Myocardial perfusion imaging (MPI) is frequently used to provide risk stratification, but methods to improve the accuracy of these predictions are needed., Objectives: The authors developed an explainable deep learning (DL) model (HARD MACE [major adverse cardiac events]-DL) for the prediction of death or nonfatal myocardial infarction (MI) and validated its performance in large internal and external testing groups., Methods: Patients undergoing single-photon emission computed tomography MPI were included, with 20,401 patients in the training and internal testing group (5 sites) and 9,019 in the external testing group (2 different sites). HARD MACE-DL uses myocardial perfusion, motion, thickening, and phase polar maps combined with age, sex, and cardiac volumes. The primary outcome was all-cause mortality or nonfatal MI. Prognostic accuracy was evaluated using area under the receiver-operating characteristic curve (AUC)., Results: During internal testing, patients with normal perfusion and elevated HARD MACE-DL risk were at higher risk than patients with abnormal perfusion and low HARD MACE-DL risk (annualized event rate, 2.9% vs 1.2%; P < 0.001). Patients in the highest quartile of HARD MACE-DL score had an annual rate of death or MI (4.8%) 10-fold higher than patients in the lowest quartile (0.48% per year). In external testing, the AUC for HARD MACE-DL (0.73; 95% CI: 0.71-0.75) was higher than a logistic regression model (AUC: 0.70), stress total perfusion deficit (TPD) (AUC: 0.65), and ischemic TPD (AUC: 0.63; all P < 0.01). Calibration, a measure of how well predicted risk matches actual risk, was excellent in both groups (Brier score, 0.079 for internal and 0.070 for external)., Conclusions: The DL model predicts death or MI directly from MPI, by estimating patient-level risk with good calibration and improved accuracy compared with traditional quantitative approaches. The model incorporates mechanisms to explain to the physician which image regions contribute to the adverse event prediction., Competing Interests: Funding Support and Author Disclosures This research (principal investigator: Dr Slomka) was supported in part by grant R01HL089765 from the National Heart, Lung and Blood Institute of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Mr Kavanagh has participated in software royalties for QPS software at Cedars-Sinai Medical Center. Dr Einstein has served as a consultant to GE Healthcare and W.L. Gore & Associates; and his institution has received research support from GE Healthcare, Philips Healthcare, Toshiba America Medical Systems, Roche Medical Systems, and W.L. Gore & Associates. Dr Ruddy has received research grant support from GE Healthcare and Advanced Accelerator Applications. Dr Edward Miller has served as a consultant to GE Healthcare. Dr Dorbala has served as a consultant to GE Healthcare and Bracco Diagnostics; and her institution has received grant support from Astellas. Dr Di Carli has received research grant support from Spectrum Dynamics; and has received consulting honoraria from Sanofi and GE Healthcare. Dr Berman has participated in software royalties for QPS software at Cedars-Sinai Medical Center; and has served as a consultant to GE Healthcare. Dr Slomka has participated in software royalties for QPS software at Cedars-Sinai Medical Center; and has received research grant support from Siemens Medical Systems. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Coronary CT angiography (CCTA) pericoronary adipose tissue (PCAT) markers are promising indicators of inflammation., Objective: To determine the effect of patient and imaging parameters on the associations between non-calcified plaque (NCP) and PCAT attenuation and gradient., Methods: This was a single-center, retrospective analysis of consecutive patients with stable chest pain who underwent CCTA and had zero calcium scores. CCTA images were evaluated for the presence of NCP, obstructive stenosis, segment stenosis and involvement score (SSS, SIS), and high-risk plaque (HRP). PCAT markers were assessed using semi-automated software. Uni- and multivariable regression models correcting for patient and imaging characteristics between plaque and PCAT markers were evaluated., Results: Overall, 1652 patients had zero calcium score (mean age: 51 years ​± ​11 [SD], 871 women); PCAT attenuation values ranged between -123 HU and -51 HU, and 649 patients had plaque. In univariable analysis, the presence of NCP, SSS, SIS, and HRP were associated with PCAT attenuation (2, 1, 1, 6 HU; respectively; p ​< ​.001 all); while obstructive stenosis was not (1 HU, p ​= ​.58). In multivariable analysis, none of the plaque markers were associated with PCAT attenuation (0 HU p ​= ​.93, 0 HU p ​= ​.39, 1 HU p ​= ​.18, 2 HU p ​= ​.10, 1 HU p ​= ​.71, respectively), while patient and imaging characteristics showed significant associations, such as: male sex (1 HU, p ​= ​.003), heart rate [1/min] (-0.2 HU, p ​< ​.001), 120 ​kVp (8 HU, p ​< ​.001) and pixel spacing [mm 3 ] (32 HU, p ​< ​.001). Similar results were observed for PCAT gradient., Conclusion: PCAT markers were significantly associated with NCP, however the associations did not persist following correction for patient and imaging characteristics., Competing Interests: Conflicts of interest None., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Increased pericoronary adipose tissue (PCAT) attenuation derived from coronary computed tomography (CT) angiography (CTA) relates to coronary inflammation and cardiac mortality. We aimed to investigate the association between CT-derived characterization of different cardiac fat compartments and myocardial ischemia as assessed by computed fractional flow reserve (FFRCT)., Methods: In all, 133 patients (median 64 y, 74% male) with coronary artery disease (CAD) underwent CTA including FFRCT measurement followed by invasive FFR assessment (FFRINVASIVE). CT attenuation and volume of PCAT were quantified around the proximal right coronary artery (RCA), left anterior descending artery (LAD), and left circumflex artery (LCX). Epicardial adipose tissue (EAT) and paracardial adipose tissue (PAT; all intrathoracic adipose tissue outside the pericardium) were quantified in noncontrast cardiac CT datasets., Results: Median FFRCT was 0.86 [0.79, 0.91] and median FFRINVASIVE was 0.87 [0.81, 0.93]. Subjects with the presence of myocardial ischemia (n=26) defined by an FFRCT-threshold of ≤0.75 showed significantly higher RCA PCAT attenuation than individuals without myocardial ischemia (n=107) (-75.1±10.8 vs. -81.1±10.6 HU, P=0.011). In multivariable analysis adjusted for age, body mass index, sex and risk factors, increased RCA PCAT attenuation remained a significant predictor of myocardial ischemia. Between individuals with myocardial ischemia compared with individuals without myocardial ischemia, there was no significant difference in the volume and CT attenuation of EAT and PAT or in the PCAT volume of RCA, LAD, and LCX., Conclusions: Increased RCA PCAT attenuation is associated with the presence of myocardial ischemia as assessed by FFR, while PCAT volume, EAT, and PAT are not., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)