The role of coronary CT angiography in athletes.

The sudden death of a young or high-level athlete or adolescent during recreational sports is one of the events with the greatest impact on public opinion in modern society. Sudden cardiac death (SCD) is the principal medical cause of death in athletes and can be the first and last clinical presentation of underlying disease. To prevent such episodes, pre-participation screening has been introduced in many countries to guarantee cardiovascular safety during sports and has become a common target among medical sports/governing organizations. Different cardiac conditions may cause SCD, with incidence depending on definition, evaluation methods, and studied populations, and a prevalence and etiology changing according to the age of athletes, with CAD most frequent in master athletes, while coronary anomalies and non-ischemic causes prevalent in young. To detect silent underlying causes early would be of considerable clinical value. This review summarizes the pre-participation screening in athletes, the specialist agonistic suitability visit performed in Italy, the anatomical characteristics of malignant coronary anomalies, and finally, the role of coronary CT angiography in such arena. In particular, the anatomical conditions suggesting potential disqualification from sport, the post-treatment follow-up to reintegrate young athletes, the diagnostic workflow to rule-out CAD in master athletes, and their clinical management are analyzed.

A coronary CT angiography-derived myocardial radiomics model for predicting adverse outcomes in chronic myocardial infarction.

BACKGROUND: The prognostic efficacy of a coronary computed tomography angiography (CCTA)-derived myocardial radiomics model in patients with chronic myocardial infarction (MI) is unclear. METHODS: In this retrospective study, a cohort of 236 patients with chronic MI who underwent both CCTA and cardiac magnetic resonance (CMR) examinations within 30 days were enrolled and randomly divided into training and testing datasets at a ratio of 7:3. The clinical endpoints were major adverse cardiovascular events (MACE), defined as all-cause death, myocardial reinfarction and heart failure hospitalization. The entire three-dimensional left ventricular myocardium on CCTA images was segmented as the volume of interest for the extraction of radiomics features. Five models, namely the clinical model, CMR model, clinical+CMR model, CCTA-radiomics model, and clinical+CCTA-radiomics model, were constructed using multivariate Cox regression. The prognostic performances of these models were evaluated through receiver operating characteristic curve analysis and the index of concordance (C-index). RESULTS: Fifty-one (20.16%) patients experienced MACE during a median follow-up of 1439.5 days. The predictive performance of the CCTA-radiomics model surpassed that of the clinical model, CMR model, and clinical+CMR model in both the training (area under the curve (AUC) of 0.904 vs. 0.691, 0.764, 0.785; C-index of 0.88 vs. 0.71, 0.75, 0.76, all p values <0.001) and testing (AUC of 0.893 vs. 0.704, 0.851, 0.888; C-index of 0.86 vs. 0.73, 0.85, 0.85, all p values <0.05) datasets. CONCLUSIONS: The CCTA-based myocardial radiomics model is a valuable tool for predicting adverse outcomes in chronic MI, providing incremental value to conventional clinical and CMR parameters.

Coronary Plaque in People With HIV vs Non-HIV Asymptomatic Community and Symptomatic Higher-Risk Populations.

Background: People with HIV (PWH) have a high burden of coronary plaques; however, the comparison to people without known HIV (PwoH) needs clarification. Objectives: The purpose of this study was to determine coronary plaque burden/phenotype in PWH vs PwoH. Methods: Nonstatin using participants from 3 contemporary populations without known coronary plaques with coronary CT were compared: the REPRIEVE (Randomized Trial to Prevent Vascular Events in HIV) studying PWH without cardiovascular symptoms at low-to-moderate risk (n = 755); the SCAPIS (Swedish Cardiopulmonary Bioimage Study) of asymptomatic community PwoH at low-to-intermediate cardiovascular risk (n = 23,558); and the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) of stable chest pain PwoH (n = 2,291). The coronary plaque prevalence on coronary CT was compared, and comparisons were stratified by 10-year atherosclerotic cardiovascular disease (ASCVD) risk, age, and coronary artery calcium (CAC) presence. Results: Compared to SCAPIS and PROMISE PwoH, REPRIEVE PWH were younger (50.8 ± 5.8 vs 57.3 ± 4.3 and 60.0 ± 8.0 years; P < 0.001) and had lower ASCVD risk (5.0% ± 3.2% vs 6.0% ± 5.3% and 13.5% ± 11.0%; P < 0.001). More PWH had plaque compared to the asymptomatic cohort (48.5% vs 40.3%; P < 0.001). When stratified by ASCVD risk, PWH had more plaque compared to SCAPIS and a similar prevalence of plaque compared to PROMISE. CAC = 0 was more prevalent in PWH (REPRIEVE 65.2%; SCAPIS 61.6%; PROMISE 49.6%); among CAC = 0, plaque was more prevalent in PWH compared to the PwoH cohorts (REPRIEVE 20.8%; SCAPIS 5.4%; PROMISE 12.3%, P < 0.001). Conclusions: Asymptomatic PWH in REPRIEVE had more plaque than asymptomatic PwoH in SCAPIS but had similar prevalence to a higher-risk stable chest pain cohort in PROMISE. In PWH, CAC = 0 does not reliably exclude plaque.

Improved stent sharpness evaluation with super-resolution deep learning reconstruction in coronary CT angiography.

OBJECTIVES: This study aimed to assess the impact of super-resolution deep learning reconstruction (SR-DLR) on coronary CT angiography (CCTA) image quality and blooming artifacts from coronary artery stents in comparison to conventional methods, including hybrid iterative reconstruction (HIR) and deep learning-based reconstruction (DLR). METHODS: A retrospective analysis included 66 CCTA patients from July to November 2022. Major coronary arteries were evaluated for image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Stent sharpness was quantified using 10%-90% edge rise slope (ERS) and 10%-90% edge rise distance (ERD). Qualitative analysis employed a 5-point scoring system to assess overall image quality, image noise, vessel wall, and stent structure. RESULTS: SR-DLR demonstrated significantly lower image noise compared to HIR and DLR. SNR and CNR were notably higher in SR-DLR. Stent ERS was significantly improved in SR-DLR, with mean ERD values of 0.70 ± 0.20 mm for SR-DLR, 1.13 ± 0.28 mm for HIR, and 0.85 ± 0.26 mm for DLR. Qualitatively, SR-DLR scored higher in all categories. CONCLUSIONS: SR-DLR produces images with lower image noise, leading to improved overall image quality, compared with HIR and DLR. SR-DLR is a valuable image reconstruction algorithm for enhancing the spatial resolution and sharpness of coronary artery stents without being constrained by hardware limitations. ADVANCES IN KNOWLEDGE: The overall image quality was significantly higher in SR-DLR, resulting in sharper coronary artery stents compared to HIR and DLR.

Artificial Intelligence-Enabled Quantitative Coronary Plaque and Hemodynamic Analysis for Predicting Acute Coronary Syndrome.

BACKGROUND: A lesion-level risk prediction for acute coronary syndrome (ACS) needs better characterization. OBJECTIVES: This study sought to investigate the additive value of artificial intelligence-enabled quantitative coronary plaque and hemodynamic analysis (AI-QCPHA). METHODS: Among ACS patients who underwent coronary computed tomography angiography (CTA) from 1 month to 3 years before the ACS event, culprit and nonculprit lesions on coronary CTA were adjudicated based on invasive coronary angiography. The primary endpoint was the predictability of the risk models for ACS culprit lesions. The reference model included the Coronary Artery Disease Reporting and Data System, a standardized classification for stenosis severity, and high-risk plaque, defined as lesions with ≥2 adverse plaque characteristics. The new prediction model was the reference model plus AI-QCPHA features, selected by hierarchical clustering and information gain in the derivation cohort. The model performance was assessed in the validation cohort. RESULTS: Among 351 patients (age: 65.9 ± 11.7 years) with 2,088 nonculprit and 363 culprit lesions, the median interval from coronary CTA to ACS event was 375 days (Q1-Q3: 95-645 days), and 223 patients (63.5%) presented with myocardial infarction. In the derivation cohort (n = 243), the best AI-QCPHA features were fractional flow reserve across the lesion, plaque burden, total plaque volume, low-attenuation plaque volume, and averaged percent total myocardial blood flow. The addition of AI-QCPHA features showed higher predictability than the reference model in the validation cohort (n = 108) (AUC: 0.84 vs 0.78; P < 0.001). The additive value of AI-QCPHA features was consistent across different timepoints from coronary CTA. CONCLUSIONS: AI-enabled plaque and hemodynamic quantification enhanced the predictability for ACS culprit lesions over the conventional coronary CTA analysis. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary Computed Tomography Angiography and Computational Fluid Dynamics II [EMERALD-II]; NCT03591328).

Use of coronary artery calcium score and coronary CT angiography to guide cardiovascular prevention and treatment.

Currently, cardiovascular risk stratification to guide preventive therapy relies on clinical scores based on cardiovascular risk factors. However, the discriminative power of these scores is relatively modest. The use of coronary artery calcium score (CACS) and coronary CT angiography (CCTA) has surfaced as methods for enhancing the estimation of risk and potentially providing insights for personalized treatment in individual patients. CACS improves overall cardiovascular risk prediction and may be used to improve the yield of statin therapy in primary prevention, and possibly identify patients with a favorable risk/benefit relationship for antiplatelet therapies. CCTA holds promise to guide anti-atherosclerotic therapies and to monitor individual response to these treatments by assessing individual plaque features, quantifying total plaque volume and composition, and assessing peri-coronary adipose tissue. In this review, we aim to summarize current evidence regarding the use of CACS and CCTA for guiding lipid-lowering and antiplatelet therapy and discuss the possibility of using plaque burden and plaque phenotyping to monitor response to anti-atherosclerotic therapies.

Coronary CTA-based Vascular Radiomics Predicts Atherosclerosis Development Proximal to LAD Myocardial Bridging.

BACKGROUND: Cardiac cycle morphological changes can accelerate plaque growth proximal to myocardial bridging (MB) in the left anterior descending artery (LAD). OBJECTIVE: To assess coronary CT angiography (CCTA)-based vascular radiomics for predicting proximal plaque development in LAD MB. METHODS: Patients with repeated CCTA scans showing LAD MB without proximal plaque in index CCTA were included from Jinling Hospital as development set. They were divided into training and internal testing in an 8:2 ratio. Patients from 4 other tertiary hospitals were set as external validation set. The endpoint was proximal plaque development of LAD MB in follow-up CCTA. Four vascular radiomics models were built: MB centerline (MB CL), proximal MB CL (pMB CL), MB cross section (MB CS), and proximal MB CS (pMB CS), whose performances were evaluated using area under the curve (AUC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI). RESULTS: 295 patients were included in the development (n=192; median age, 54±11 years; 137 men) and external validation sets (n=103; median age, 57±9 years; 57 men). The pMB CS vascular radiomics model exhibited higher AUCs in training, internal test, and external sets (AUC=0.78, 0.75, 0.75) than the clinical and anatomical model (all p<0.05). Integration of the pMB CS vascular radiomics model significantly raised the AUC of the clinical and anatomical model from 0.56 to 0.75 (p=0.002), along with enhanced NRI (0.76 [0.37-1.14], p<0.001) and IDI (0.17 [0.07-0.26], p<0.001) in the external validation set. CONCLUSION: The CCTA-based pMB CS vascular radiomics model can predict plaque development in LAD MB.

Ischemia-Guided Coronary Revascularization Following Lower-Extremity Revascularization Improves 5-Year Survival of Patients With Chronic Limb-Threatening Ischemia.

PURPOSE: To determine whether diagnosis of asymptomatic (silent) coronary ischemia using coronary computed tomography (CT)-derived fractional flow reserve (FFRCT) together with targeted coronary revascularization of ischemia-producing coronary lesions following lower-extremity revascularization can reduce adverse cardiac events and improve long-term survival of patients with chronic limb-threatening ischemia (CLTI). MATERIALS AND METHODS: Prospective cohort study of CLTI patients with no cardiac history or symptoms undergoing elective lower-extremity revascularization. Patients with pre-operative coronary computed tomography angiography (CTA) and FFRCT evaluation with selective post-operative coronary revascularization (FFRCT group) were compared with patients with standard pre-operative evaluation and no post-operative coronary revascularization (control group). Lesion-specific coronary ischemia was defined as FFRCT≤0.80 distal to a coronary stenosis with FFRCT≤0.75 indicating severe ischemia. Endpoints included all-cause death, cardiac death, myocardial infarction (MI) and major adverse cardiovascular (CV) events (MACE=CV death, MI, stroke, or unplanned coronary revascularization) during 5 year follow-up. RESULTS: In the FFRCT group (n=111), FFRCT analysis revealed asymptomatic (silent) coronary ischemia (FFRCT≤0.80) in 69% of patients, with severe ischemia (FFRCT≤0.75) in 58%, left main ischemia in 8%, and multivessel ischemia in 40% of patients. The status of coronary ischemia in the control group (n=120) was unknown. Following lower-extremity revascularization, 42% of patients in FFRCT had elective coronary revascularization with no elective revascularization in controls. Both groups received guideline-directed medical therapy. During 5 year follow-up, compared with control, the FFRCT group had fewer all-cause deaths (24% vs 47%, hazard ratio [HR]=0.43 [95% confidence interval [CI]=0.27-0.69], p<0.001), fewer cardiac deaths (5% vs 26%, HR=0.18 [95% CI=0.07-0.45], p<0.001), fewer MIs (7% vs 28%, HR=0.21 [95% CI=0.10-0.47], p<0.001), and fewer MACE events (14% vs 39%, HR=0.28 [95% CI=0.15-0.51], p<0.001). CONCLUSIONS: Ischemia-guided coronary revascularization of CLTI patients with asymptomatic (silent) coronary ischemia following lower-extremity revascularization resulted in more than 2-fold reduction in all-cause death, cardiac death, MI, and MACE with improved 5 year survival compared with patients with standard cardiac evaluation and care (76% vs 53%, p<0.001). CLINICAL IMPACT: Silent coronary ischemia in patients with chronic limb-threatening ischemia (CLTI) is common even in the absence of cardiac history or symptoms. FFRCT is a convenient tool to diagnose silent coronary ischemia perioperatively. Our data suggest that post-surgery elective FFRCT-guided coronary revascularization reduces adverse cardiac events and improves long-term survival in this very-high risk patient group. Randomized study is warranted to finally test this concept.

Radiology: Cardiothoracic Imaging Highlights 2023.

Radiology: Cardiothoracic Imaging publishes novel research and technical developments in cardiac, thoracic, and vascular imaging. The journal published many innovative studies during 2023 and achieved an impact factor for the first time since its inaugural issue in 2019, with an impact factor of 7.0. The current review article, led by the Radiology: Cardiothoracic Imaging trainee editorial board, highlights the most impactful articles published in the journal between November 2022 and October 2023. The review encompasses various aspects of coronary CT, photon-counting detector CT, PET/MRI, cardiac MRI, congenital heart disease, vascular imaging, thoracic imaging, artificial intelligence, and health services research. Key highlights include the potential for photon-counting detector CT to reduce contrast media volumes, utility of combined PET/MRI in the evaluation of cardiac sarcoidosis, the prognostic value of left atrial late gadolinium enhancement at MRI in predicting incident atrial fibrillation, the utility of an artificial intelligence tool to optimize detection of incidental pulmonary embolism, and standardization of medical terminology for cardiac CT. Ongoing research and future directions include evaluation of novel PET tracers for assessment of myocardial fibrosis, deployment of AI tools in clinical cardiovascular imaging workflows, and growing awareness of the need to improve environmental sustainability in imaging. Keywords: Coronary CT, Photon-counting Detector CT, PET/MRI, Cardiac MRI, Congenital Heart Disease, Vascular Imaging, Thoracic Imaging, Artificial Intelligence, Health Services Research © RSNA, 2024.

Diagnosis and treatment of ischemia-producing coronary stenoses improves 5-year survival of patients undergoing major vascular surgery.

OBJECTIVE: Patients undergoing vascular surgery procedures have poor long-term survival due to coexisting coronary artery disease (CAD), which is often asymptomatic, undiagnosed, and undertreated. We sought to determine whether preoperative diagnosis of asymptomatic (silent) coronary ischemia using coronary computed tomography (CT)-derived fractional flow reserve (FFRCT) together with postoperative ischemia-targeted coronary revascularization can reduce adverse cardiac events and improve long-term survival following major vascular surgery METHODS: In this observational cohort study of 522 patients with no known CAD undergoing elective carotid, peripheral, or aneurysm surgery we compared two groups of patients. Group I included 288 patients enrolled in a prospective Institutional Review Board-approved study of preoperative coronary CT angiography (CTA) and FFRCT testing to detect silent coronary ischemia with selective postoperative coronary revascularization in addition to best medical therapy (BMT) (FFRCT guided), and Group II included 234 matched controls with standard preoperative cardiac evaluation and postoperative BMT alone with no elective coronary revascularization (Usual Care). In the FFRCT group, lesion-specific coronary ischemia was defined as FFRCT ≤0.80 distal to a coronary stenosis, with severe ischemia defined as FFRCT ≤0.75. Results were available for patient management decisions. Endpoints included all-cause death, cardiovascular death, myocardial infarction (MI), and major adverse cardiovascular events (MACE [death, MI, or stroke]) during 5-year follow-up. RESULTS: The two groups were similar in age, gender, and comorbidities. In FFRCT, 65% of patients had asymptomatic lesion-specific coronary ischemia, with severe ischemia in 52%, multivessel ischemia in 36% and left main ischemia in 8%. The status of coronary ischemia was unknown in Usual Care. Vascular surgery was performed as planned in both cohorts with no difference in 30-day mortality. In FFRCT, elective ischemia-targeted coronary revascularization was performed in 103 patients 1 to 3 months following surgery. Usual Care had no elective postoperative coronary revascularizations. At 5 years, compared with Usual Care, FFRCT guided had fewer all-cause deaths (16% vs 36%; hazard ratio [HR], 0.37; 95% confidence interval [CI], 0.22-0.60; P < .001), fewer cardiovascular deaths (4% vs 21%; HR, 0.11; 95% CI, 0.04-0.33; P < .001), fewer MIs (4% vs 24%; HR, 0.13; 95% CI, 0.05-0.33; P < .001), and fewer MACE (20% vs 47%; HR, 0.36; 95% CI, 0.23-0.56; P < .001). Five-year survival was 84% in FFRCT compared with 64% in Usual Care (P < .001). CONCLUSIONS: Diagnosis of silent coronary ischemia with ischemia-targeted coronary revascularization in addition to BMT following major vascular surgery was associated with fewer adverse cardiovascular events and improved 5-year survival compared with patients treated with BMT alone as per current guidelines.

Polygenic Scores and Preclinical Cardiovascular Disease in Individuals With HIV: Insights From the REPRIEVE Trial.

BACKGROUND: Coronary artery disease (CAD) is a leading cause of death among the 38.4 million people with HIV globally. The extent to which cardiovascular polygenic risk scores (PRSs) derived in non-HIV populations generalize to people with HIV is not well understood. METHODS AND RESULTS: PRSs for CAD (GPSMult) and lipid traits were calculated in a global cohort of people with HIV treated with antiretroviral therapy with low-to-moderate atherosclerotic cardiovascular disease risk enrolled in REPRIEVE (Randomized Trial to Prevent Vascular Events in HIV). The PRSs were associated with baseline lipid traits in 4495 genotyped participants, and with subclinical CAD in a subset of 662 who underwent coronary computed tomography angiography. Among participants who underwent coronary computed tomography angiography (mean age, 50.9 [SD, 5.8] years; 16.1% women; 41.8% African, 57.3% European, 1.1% Asian), GPSMult was associated with plaque presence with odds ratio (OR) per SD in GPSMult of 1.42 (95% CI, 1.20-1.68; P=3.8×10-5), stenosis >50% (OR, 2.39 [95% CI, 1.48-3.85]; P=3.4×10-4), and noncalcified/vulnerable plaque (OR, 1.45 [95% CI, 1.23-1.72]; P=9.6×10-6). Effects were consistent in subgroups of age, sex, 10-year atherosclerotic cardiovascular disease risk, ancestry, and CD4 count. Adding GPSMult to established risk factors increased the C-statistic for predicting plaque presence from 0.718 to 0.734 (P=0.02). Furthermore, a PRS for low-density lipoprotein cholesterol was associated with plaque presence with OR of 1.21 (95% CI, 1.01-1.44; P=0.04), and partially calcified plaque with OR of 1.21 (95% CI, 1.01-1.45; P=0.04) per SD. CONCLUSIONS: Among people with HIV treated with antiretroviral therapy without documented atherosclerotic cardiovascular disease and at low-to-moderate calculated risk in REPRIEVE, an externally developed CAD PRS was predictive of subclinical atherosclerosis. PRS for low-density lipoprotein cholesterol was also associated with subclinical atherosclerosis, supporting a role for low-density lipoprotein cholesterol in HIV-associated CAD. REGISTRATION: URL: https://www.reprievetrial.org; Unique identifier: NCT02344290.

[Validation of Optimal Imaging Conditions for Coronary Computed Tomography Angiography Using High-definition Mode and Deep Learning Image Reconstruction Algorithm].

PURPOSE: To verify the optimal imaging conditions for coronary computed tomography angiography (CCTA) examinations when using high-definition (HD) mode and deep learning image reconstruction (DLIR) in combination. METHOD: A chest phantom and an in-house phantom using 3D printer were scanned with a 256-row detector CT scanner. The scan parameters were as follows - acquisition mode: ON (HD mode) and OFF (normal resolution [NR] mode), rotation time: 0.28 s/rotation, beam coverage width: 160 mm, and the radiation dose was adjusted based on CT-AEC. Image reconstruction was performed using ASiR-V (Hybrid-IR), TrueFidelity Image (DLIR), and HD-Standard (HD mode) and Standard (NR mode) reconstruction kernels. The task-based transfer function (TTF) and noise power spectrum (NPS) were measured for image evaluation, and the detectability index (d') was calculated. Visual evaluation was also performed on an in-house coronary phantom. RESULT: The in-plane TTF was better for the HD mode than for the NR mode, while the z-axis TTF was lower for DLIR than for Hybrid-IR. The NPS values in the high-frequency region were higher for the HD mode compared to those for the NR mode, and the NPS was lower for DLIR than for Hybrid-IR. The combination of HD mode and DLIR showed the best value for in-plane d', whereas the combination of NR mode and DLIR showed the best value for z-axis d'. In the visual evaluation, the combination of NR mode and DLIR showed the best values from a noise index of 45 HU. CONCLUSION: The optimal combination of HD mode and DLIR depends on the image noise level, and the combination of NR mode and DLIR was the best imaging condition under noisy conditions.

Another CCTA Incidental Finding: Case Report of an Idiopathic Pulmonary Vein Pseudo-thrombosis.

INTRODUCTION: While pulmonary vein filling defects on CT are typically considered diagnostic for thrombus, under certain circumstances, they can be artifactual as a result of flow phenomena. CASE PRESENTATION: We report a case of a 53-year-old female with chest pain who was found to have filling defects in pulmonary vein branches on CCTA that were initially treated as thromboses. However, follow-up cardiac MRI was negative for thrombi, and pseudo-thrombosis was therefore diagnosed. CONCLUSION: Pulmonary vein pseudo-thrombosis should be considered in the differential diagnosis of pulmonary vein filling defects.

Evaluation of the Atherogenic Effect of Covid-19 Pneumonia on Coronary and Carotid Arteries in Patients who Recovered from the Disease.

BACKGROUND: Acute inflammation induced by COVID-19 may lead to atherosclerotic plaque development or complicate existing plaque. In this study, we aimed to determine the atherogenic effect of COVID-19 pneumonia, confirmed by thoracic computed tomography, on coronary and carotid arteries in patients who recovered from the disease. METHODS: Our study included patients who were diagnosed with COVID-19 in our hospital at least 1 year ago, recovered, and then underwent coronary CT angiography with suspected coronary artery disease. The aim was to evaluate the burden of atherosclerotic plaque in the coronary arteries of these patients who underwent coronary CT angiography. RESULTS: Patients were assigned to 3 groups according to the results of the CT scan. Group 1 included patients in the control group with no history of COVID-19 (n=36), group 2 included those with mild to moderate pneumonia symptoms (n=43), and group 3 included those with severe pneumonia symptoms (n=29). The calcium scores were 23.25±36.8 in group 1, 27.65±33.4 in group 2, and 53.58±55.1 in group 3. The calcium score was found to be significantly higher in group 3 patients with severe pneumonia (group 1-2 p=0.885, group 1-3 p<0.05, group 2-3 p<0.05). CONCLUSION: Although there is no conclusive evidence of a relationship between COVID-19 and atherosclerosis, our study suggests a possible relationship between them. Since this relationship was found especially in cases with severe disease in our study, we believe that the treatment should focus on preventing excessive inflammatory response, and such patients should be under control in terms of coronary artery disease.

Virtual calcium removal in calcified coronary arteries with photon-counting detector CT-first in-vivo experience.

Purpose: To evaluate the feasibility and accuracy of quantification of calcified coronary stenoses using virtual non-calcium (VNCa) images in coronary CT angiography (CCTA) with photon-counting detector (PCD) CT compared with quantitative coronary angiography (QCA). Materials and methods: This retrospective, institutional-review board approved study included consecutive patients with calcified coronary artery plaques undergoing CCTA with PCD-CT and invasive coronary angiography between July and December 2022. Virtual monoenergetic images (VMI) and VNCa images were reconstructed. Diameter stenoses were quantified on VMI and VNCa images by two readers. 3D-QCA served as the standard of reference. Measurements were compared using Bland-Altman analyses, Wilcoxon tests, and intraclass correlation coefficients (ICC). Results: Thirty patients [mean age, 64 years ± 8 (standard deviation); 26 men] with 81 coronary stenoses from calcified plaques were included. Ten of the 81 stenoses (12%) had to be excluded because of erroneous plaque subtraction on VNCa images. Median diameter stenosis determined on 3D-QCA was 22% (interquartile range, 11%-35%; total range, 4%-88%). As compared with 3D-QCA, VMI overestimated diameter stenoses (mean differences -10%, p < .001, ICC: .87 and -7%, p < .001, ICC: .84 for reader 1 and 2, respectively), whereas VNCa images showed similar diameter stenoses (mean differences 0%, p = .68, ICC: .94 and 1%, p = .07, ICC: .93 for reader 1 and 2, respectively). Conclusion: First experience in mainly minimal to moderate stenoses suggests that virtual calcium removal in CCTA with PCD-CT, when feasible, has the potential to improve the quantification of calcified stenoses.

A novel hybrid machine learning model for auxiliary diagnosing myocardial ischemia.

Introduction: Accurate identification of the myocardial texture features of fat around the coronary artery on coronary computed tomography angiography (CCTA) images are crucial to improve clinical diagnostic efficiency of myocardial ischemia (MI). However, current coronary CT examination is difficult to recognize and segment the MI characteristics accurately during earlier period of inflammation. Materials and methods: We proposed a random forest model to automatically segment myocardium and extract peripheral fat features. This hybrid machine learning (HML) model is integrated by CCTA images and clinical data. A total of 1,316 radiomics features were extracted from CCTA images. To further obtain the features that contribute the most to the diagnostic model, dimensionality reduction was applied to filter features to three: LNS, GFE, and WLGM. Moreover, statistical hypothesis tests were applied to improve the ability of discriminating and screening clinical features between the ischemic and non-ischemic groups. Results: By comparing the accuracy, recall, specificity and AUC of the three models, it can be found that HML had the best performance, with the value of 0.848, 0.762, 0.704 and 0.729. Conclusion: In sum, this study demonstrates that ML-based radiomics model showed good predictive value in MI, and offer an enhanced tool for predicting prognosis with greater accuracy.

Computed tomographic angiography measures of coronary plaque in clinical trials: opportunities and considerations to accelerate drug translation.

Atherosclerotic coronary artery disease (CAD) is the causal pathological process driving most major adverse cardiovascular events (MACE) worldwide. The complex development of atherosclerosis manifests as intimal plaque which occurs in the presence or absence of traditional risk factors. There are numerous effective medications for modifying CAD but new pharmacologic therapies require increasingly large and expensive cardiovascular outcome trials to assess their potential impact on MACE and to obtain regulatory approval. For many disease areas, nearly a half of drugs are approved by the U.S. Food & Drug Administration based on beneficial effects on surrogate endpoints. For cardiovascular disease, only low-density lipoprotein cholesterol and blood pressure are approved as surrogates for cardiovascular disease. Valid surrogates of CAD are urgently needed to facilitate robust evaluation of novel, beneficial treatments and inspire investment. Fortunately, advances in non-invasive imaging offer new opportunity for accelerating CAD drug development. Coronary computed tomography angiography (CCTA) is the most advanced candidate, with the ability to measure accurately and reproducibly characterize the underlying causal disease itself. Indeed, favourable changes in plaque burden have been shown to be associated with improved outcomes, and CCTA may have a unique role as an effective surrogate endpoint for therapies that are designed to improve CAD outcomes. CCTA also has the potential to de-risk clinical endpoint-based trials both financially and by enrichment of participants at higher likelihood of MACE. Furthermore, total non-calcified, and high-risk plaque volume, and their change over time, provide a causally linked measure of coronary artery disease which is inextricably linked to MACE, and represents a robust surrogate imaging biomarker with potential to be endorsed by regulatory authorities. Global consensus on specific imaging endpoints and protocols for optimal clinical trial design is essential as we work towards a rigorous, sustainable and staged pathway for new CAD therapies.

2024 Consensus Statement on Coronary Stenosis and Plaque Evaluation in CT Angiography From the Asian Society of Cardiovascular Imaging-Practical Tutorial (ASCI-PT).

The Asian Society of Cardiovascular Imaging-Practical Tutorial (ASCI-PT) is an instructional initiative of the ASCI School designed to enhance educational standards. In 2021, the ASCI-PT was convened with the goal of formulating a consensus statement on the assessment of coronary stenosis and coronary plaque using coronary CT angiography (CCTA). Nineteen experts from four countries conducted thorough reviews of current guidelines and deliberated on eight key issues to refine the process and improve the clarity of reporting CCTA findings. The experts engaged in both online and on-site sessions to establish a unified agreement. This document presents a summary of the ASCI-PT 2021 deliberations and offers a comprehensive consensus statement on the evaluation of coronary stenosis and coronary plaque in CCTA.