The Effects of Fingolimod (FTY720) on Leukocyte Subset Circulation cannot be Behaviourally Conditioned in Rats.

Suppression of immune functions can be elicited by behavioural conditioning using drugs such as cyclosporin A or rapamycin. Nevertheless, little is known about the underlying mechanisms and generalisability of this phenomenon. Against this background, the present study investigated whether the pharmacological properties of fingolimod (FTY720), an immunosuppressive drug widely applied to treat multiple sclerosis, can be conditioned in rats by means of taste-immune associative learning. For this purpose, a conditioned taste avoidance paradigm was used, pairing the presentation of a novel sweet drinking solution (saccharin or sucrose) as conditioned stimulus (CS) with therapeutically effective doses of FTY720 as unconditioned stimulus (US). Subsequent re-exposure to the CS at a later time point revealed that conditioning with FTY720 induced a mild conditioned taste avoidance only when saccharin was employed as CS. However, on an immunological level, neither re-exposure with saccharin nor sucrose altered blood immune cell subsets or splenic cytokine production. Despite the fact that intraperitonally administered FTY720 could be detected in brain regions known to mediate neuro-immune interactions, the present findings show that the physiological action of FTY720 is not inducible by mere taste-immune associative learning. Whether conditioning generalises across all small-molecule drugs with immunosuppressive properties still needs to be investigated with modified paradigms probably using distinct sensory CS. Moreover, these findings emphasize the need to further investigate the underlying mechanisms of conditioned immunomodulation to assess the generalisability and usability of associative learning protocols as supportive therapies in clinical contexts.

Behaviorally Conditioned Immune Responses: "To Learn New Things, Read Old Books & Papers".

More than a century ago, experimental work and clinical observations revealed the functional communication between the brain and the peripheral immune system. This is documented on the one hand by studies firstly demonstrating the effects of catecholamines on the circulation of leukocytes in experimental animals and humans and on the other hand via the work of Russian physiologist Ivan Petrovic Pavlov and his co-workers, reporting observations that associative learning can modify peripheral immune functions. This work later fell into oblivion, since little was known about the endocrine and immune system's function and even less about the underlying mechanisms of how learning, a central nervous system activity, could affect peripheral immune responses. In this article, we embark on a fascinating exploration of the historical trajectory of behaviorally conditioned immune responses. We'll pay homage to the visionary scientists who laid the groundwork for this field of research, tracing its evolution from early theories of how associative learning can affect immunity to the modern-day insights that behavioral conditioning of pharmacological responses can be exploited to improve the efficacy of medical interventions for patients.

Prediction of the development of new coronary atherosclerotic plaques with radiomics.

BACKGROUND: Radiomics is expected to identify imaging features beyond the human eye. We investigated whether radiomics can identify coronary segments that will develop new atherosclerotic plaques on coronary computed tomography angiography (CCTA). METHODS: From a prospective multinational registry of patients with serial CCTA studies at ≥ 2-year intervals, segments without identifiable coronary plaque at baseline were selected and radiomic features were extracted. Cox models using clinical risk factors (Model 1), radiomic features (Model 2) and both clinical risk factors and radiomic features (Model 3) were constructed to predict the development of a coronary plaque, defined as total PV â€‹≥ â€‹1 â€‹mm3, at follow-up CCTA in each segment. RESULTS: In total, 9583 normal coronary segments were identified from 1162 patients (60.3 â€‹± â€‹9.2 years, 55.7% male) and divided 8:2 into training and test sets. At follow-up CCTA, 9.8% of the segments developed new coronary plaque. The predictive power of Models 1 and 2 was not different in both the training and test sets (C-index [95% confidence interval (CI)] of Model 1 vs. Model 2: 0.701 [0.690-0.712] vs. 0.699 [0.0.688-0.710] and 0.696 [0.671-0.725] vs. 0.0.691 [0.667-0.715], respectively, all p â€‹> â€‹0.05). The addition of radiomic features to clinical risk factors improved the predictive power of the Cox model in both the training and test sets (C-index [95% CI] of Model 3: 0.772 [0.762-0.781] and 0.767 [0.751-0.787], respectively, all p â€‹< â€‹00.0001 compared to Models 1 and 2). CONCLUSION: Radiomic features can improve the identification of segments that would develop new coronary atherosclerotic plaque. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT0280341.

Automated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning.

BACKGROUND: A deep learning (DL) model that automatically detects cardiac pathologies on cardiac MRI may help streamline the diagnostic workflow. To develop a DL model to detect cardiac pathologies on cardiac MRI T1-mapping and late gadolinium phase sensitive inversion recovery (PSIR) sequences were used. METHODS: Subjects in this study were either diagnosed with cardiac pathology (n = 137) including acute and chronic myocardial infarction, myocarditis, dilated cardiomyopathy, and hypertrophic cardiomyopathy or classified as normal (n = 63). Cardiac MR imaging included T1-mapping and PSIR sequences. Subjects were split 65/15/20% for training, validation, and hold-out testing. The DL models were based on an ImageNet pretrained DenseNet-161 and implemented using PyTorch and fastai. Data augmentation with random rotation and mixup was applied. Categorical cross entropy was used as the loss function with a cyclic learning rate (1e-3). DL models for both sequences were developed separately using similar training parameters. The final model was chosen based on its performance on the validation set. Gradient-weighted class activation maps (Grad-CAMs) visualized the decision-making process of the DL model. RESULTS: The DL model achieved a sensitivity, specificity, and accuracy of 100%, 38%, and 88% on PSIR images and 78%, 54%, and 70% on T1-mapping images. Grad-CAMs demonstrated that the DL model focused its attention on myocardium and cardiac pathology when evaluating MR images. CONCLUSIONS: The developed DL models were able to reliably detect cardiac pathologies on cardiac MR images. The diagnostic performance of T1 mapping alone is particularly of note since it does not require a contrast agent and can be acquired quickly.

Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry.

OBJECTIVES: No clear recommendations are endorsed by the different scientific societies on the clinical use of repeat coronary computed tomography angiography (CCTA) in patients with non-obstructive coronary artery disease (CAD). This study aimed to develop and validate a practical CCTA risk score to predict medium-term disease progression in patients at a low-to-intermediate probability of CAD. METHODS: Patients were part of the Progression of AtheRosclerotic PlAque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry. Specifically, 370 (derivation cohort) and 219 (validation cohort) patients with two repeat, clinically indicated CCTA scans, non-obstructive CAD, and absence of high-risk plaque (≥ 2 high-risk features) at baseline CCTA were included. Disease progression was defined as the new occurrence of ≥ 50% stenosis and/or high-risk plaque at follow-up CCTA. RESULTS: In the derivation cohort, 104 (28%) patients experienced disease progression. The median time interval between the two CCTAs was 3.3 years (2.7-4.8). Odds ratios for disease progression derived from multivariable logistic regression were as follows: 4.59 (95% confidence interval: 1.69-12.48) for the number of plaques with spotty calcification, 3.73 (1.46-9.52) for the number of plaques with low attenuation component, 2.71 (1.62-4.50) for 25-49% stenosis severity, 1.47 (1.17-1.84) for the number of bifurcation plaques, and 1.21 (1.02-1.42) for the time between the two CCTAs. The C-statistics of the model were 0.732 (0.676-0.788) and 0.668 (0.583-0.752) in the derivation and validation cohorts, respectively. CONCLUSIONS: The new CCTA-based risk score is a simple and practical tool that can predict mid-term CAD progression in patients with known non-obstructive CAD. CLINICAL RELEVANCE STATEMENT: The clinical implementation of this new CCTA-based risk score can help promote the management of patients with non-obstructive coronary disease in terms of timing of imaging follow-up and therapeutic strategies. KEY POINTS: • No recommendations are available on the use of repeat CCTA in patients with non-obstructive CAD. • This new CCTA score predicts mid-term CAD progression in patients with non-obstructive stenosis at baseline. • This new CCTA score can help guide the clinical management of patients with non-obstructive CAD.

Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study.

BACKGROUND: In the last 15 years, large registries and several randomized clinical trials have demonstrated the diagnostic and prognostic value of coronary computed tomography angiography (CCTA). Advances in CT scanner technology and developments of analytic tools now enable accurate quantification of coronary artery disease (CAD), including total coronary plaque volume and low attenuation plaque volume. The primary aim of CONFIRM2, (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is to perform comprehensive quantification of CCTA findings, including coronary, non-coronary cardiac, non-cardiac vascular, non-cardiac findings, and relate them to clinical variables and cardiovascular clinical outcomes. DESIGN: CONFIRM2 is a multicenter, international observational cohort study designed to evaluate multidimensional associations between quantitative phenotype of cardiovascular disease and future adverse clinical outcomes in subjects undergoing clinically indicated CCTA. The targeted population is heterogenous and includes patients undergoing CCTA for atherosclerotic evaluation, valvular heart disease, congenital heart disease or pre-procedural evaluation. Automated software will be utilized for quantification of coronary plaque, stenosis, vascular morphology and cardiac structures for rapid and reproducible tissue characterization. Up to 30,000 patients will be included from up to 50 international multi-continental clinical CCTA sites and followed for 3-4 years. SUMMARY: CONFIRM2 is one of the largest CCTA studies to establish the clinical value of a multiparametric approach to quantify the phenotype of cardiovascular disease by CCTA using automated imaging solutions.

Assessing the effects of oxytocin in changes of core body temperature during LPS-induced endotoxemia: A novel approach using Extended Poincaré Plot Analysis.

Oxytocin has shown cardioprotective effects during inflammation and may modify the core body temperature changes in LPS-induced endotoxemia. Notably, the time series analysis of core body temperature fluctuations may indicate thermoregulation alterations. This study aims to assess the effects of oxytocin on changes in the core body temperature by analyzing the fluctuations of the temperature time series of endotoxemic rats. Twelve hours of continuous core body temperature fluctuations time series were obtained from adult male Dark Agouti rats implanted with a telemetric transmitter under the following treatment: lipopolysaccharide (LPS); oxytocin (O); lipopolysaccharide + oxytocin (LPS + O), and vehicle or control (C). The temperature fluctuations time series were analyzed using the Extended Poincaré Plot Analysis (EPPA), a novel approach for measuring nonlinear features, to compute the autocorrelation by Pearson's correlation coefficient r, the standard deviation perpendicular to the line of identity (SD1), and the standard deviation parallel to the line of identity (SD2). The autocorrelation of the temperature fluctuations assessed by Pearson's coefficient was significantly higher in the LPS group compared to control rats (C). Likewise, the co-administration of oxytocin during endotoxemia (LPS + O) significantly reduced the autocorrelation and increased the short-term variability (SD1) of temperature fluctuations compared to those recorded with a single dose of LPS. Thus, we concluded that oxytocin may introduce thermoregulatory changes under LPS-induced endotoxemia. The EPPA is a simple and powerful approach to assess physiological variability that can provide valuable insights into changes in thermoregulation.

Hypothermia combined with extracellular vesicles from clonally expanded immortalized mesenchymal stromal cells improves neurodevelopmental impairment in neonatal hypoxic-ischemic brain injury.

BACKGROUND: Neonatal encephalopathy following hypoxia-ischemia (HI) is a leading cause of childhood death and morbidity. Hypothermia (HT), the only available but obligatory therapy is limited due to a short therapeutic window and limited efficacy. An adjuvant therapy overcoming limitations of HT is still missing. Mesenchymal stromal cell (MSC)-derived extracellular vesicles (EVs) have shown promising therapeutic effects in various brain injury models. Challenges associated with MSCs' heterogeneity and senescence can be mitigated by the use of EVs from clonally expanded immortalized MSCs (ciMSCs). In the present study, we hypothesized that intranasal ciMSC-EV delivery overcomes limitations of HT. METHODS: Nine-day-old C57BL/6 mice were exposed to HI by occlusion of the right common carotid artery followed by 1 h hypoxia (10% oxygen). HT was initiated immediately after insult for 4 h. Control animals were kept at physiological body core temperatures. ciMSC-EVs or vehicle were administered intranasally 1, 3 and 5 days post HI/HT. Neuronal cell loss, inflammatory and regenerative responses were assessed via immunohistochemistry, western blot and real-time PCR 7 days after insult. Long-term neurodevelopmental outcome was evaluated by analyses of cognitive function, activity and anxiety-related behavior 5 weeks after HI/HT. RESULTS: In contrast to HT monotherapy, the additional intranasal therapy with ciMSC-EVs prevented HI-induced cognitive deficits, hyperactivity and alterations of anxiety-related behavior at adolescence. This was preceded by reduction of striatal neuronal loss, decreased endothelial, microglia and astrocyte activation; reduced expression of pro-inflammatory and increased expression of anti-inflammatory cytokines. Furthermore, the combination of HT with intranasal ciMSC-EV delivery promoted regenerative and neurodevelopmental processes, including endothelial proliferation, neurotrophic growth factor expression and oligodendrocyte maturation, which were not altered by HT monotherapy. CONCLUSION: Intranasal delivery of ciMSC-EVs represents a novel adjunct therapy, overcoming limitations of acute HT thereby offering new possibilities for improving long-term outcomes in neonates with HI-induced brain injury.

How early can atherosclerosis be detected by coronary CT angiography? Insights from quantitative CT analysis of serial scans in the PARADIGM trial.

BACKGROUND: Non-obstructing small coronary plaques may not be well recognized by expert readers during coronary computed tomography angiography (CCTA) evaluation. Recent developments in atherosclerosis imaging quantitative computed tomography (AI-QCT) enabled by machine learning allow for whole-heart coronary phenotyping of atherosclerosis, but its diagnostic role for detection of small plaques on CCTA is unknown. METHODS: We performed AI-QCT in patients who underwent serial CCTA in the multinational PARADIGM study. AI-QCT results were verified by a level III experienced reader, who was blinded to baseline and follow-up status of CCTA. This retrospective analysis aimed to characterize small plaques on baseline CCTA and evaluate their serial changes on follow-up imaging. Small plaques were defined as a total plaque volume <50 â€‹mm3. RESULTS: A total of 99 patients with 502 small plaques were included. The median total plaque volume was 6.8 â€‹mm3 (IQR 3.5-13.9 â€‹mm3), most of which was non-calcified (median 6.2 â€‹mm3; 2.9-12.3 â€‹mm3). The median age at the time of baseline CCTA was 61 years old and 63% were male. The mean interscan period was 3.8 â€‹± â€‹1.6 years. On follow-up CCTA, 437 (87%) plaques were present at the same location as small plaques on baseline CCTA; 72% were larger and 15% decreased in volume. The median total plaque volume and non-calcified plaque volume increased to 18.9 â€‹mm3 (IQR 8.3-45.2 â€‹mm3) and 13.8 â€‹mm3 (IQR 5.7-33.4 â€‹mm3), respectively, among plaques that persisted on follow-up CCTA. Small plaques no longer visualized on follow-up CCTA were significantly more likely to be of lower volume, shorter in length, non-calcified, and more distal in the coronary artery, as compared with plaques that persisted at follow-up. CONCLUSION: In this retrospective analysis from the PARADIGM study, small plaques (<50 â€‹mm3) identified by AI-QCT persisted at the same location and were often larger on follow-up CCTA.

Effects of renin-angiotensin-aldosterone-system inhibitors on coronary atherosclerotic plaques: The PARADIGM registry.

BACKGROUND AND AIMS: Inhibition of Renin-Angiotensin-Aldosterone-System (RAAS) has been hypothesized to improve endothelial function and reduce plaque inflammation, however, their impact on the progression of coronary atherosclerosis is unclear. We aim to study the effects of RAAS inhibitor on plaque progression and composition assessed by serial coronary CT angiography (CCTA). METHODS: We performed a prospective, multinational study consisting of a registry of patients without history of CAD, who underwent serial CCTAs. Patients using RAAS inhibitors were propensity matched to RAAS inhibitor naïve patients based on clinical and CCTA characteristics at baseline. Atherosclerotic plaques in CCTAs were quantitatively analyzed for percent atheroma volume (PAV) according to plaque composition. Interactions between RAAS inhibitor use and baseline PAV on plaque progression were assessed in the unmatched cohort using a multivariate linear regression model. RESULTS: Of 1248 patients from the registry, 299 RAAS inhibitor taking patients were matched to 299 RAAS inhibitor naïve patients. Over a mean interval of 3.9 years, there was no significant difference in annual progression of total PAV between RAAS inhibitor naïve vs taking patients (0.75 vs 0.79%/year, p = 0.66). With interaction testing in the unmatched cohort, however, RAAS inhibitor use was significantly associated with lower non-calcified plaque progression (Beta coefficient -0.100, adjusted p = 0.038) with higher levels of baseline PAV. CONCLUSIONS: The use of RAAS inhibitors over a period of nearly 4 years did not significantly impact on total atherosclerotic plaque progression or various plaque components. However, interaction testing to assess the differential effect of RAAS inhibition based on baseline PAV suggested a significant decrease in progression of non-calcified plaque in patients with a higher burden of baseline atherosclerosis, which should be considered hypothesis generating.

Near-infrared spectroscopy-intravascular ultrasound to improve assessment of coronary artery disease severity in patients referred for transcatheter aortic valve implantation (The IMPACTavi registry): Design and rationale.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) was established as a standard treatment for high-operative risk patients with severe aortic stenosis (AS). Although coronary artery disease (CAD) often coexists with AS, clinical and angiographic evaluations of stenosis severity are unreliable in this specific setting. To provide precise risk stratification of coronary lesions, combined near-infrared spectroscopy and intravascular ultrasound (NIRS-IVUS) was developed to integrate morphological and molecular information on plaque composition. However, there is a lack of evidence on the association between NIRS-IVUS derived findings such as maximum 4mm lipid core burden index (maxLCBI4mm) and clinical outcomes in AS patients undergoing TAVI. This registry aims to assess feasibility and safety of NIRS-IVUS imaging in the setting of routine pre-TAVI coronary angiography to improve assessment of CAD severity. METHODS: The registry is designed as a non-randomized, prospective, observational, multicenter cohort registry. Patients referred for TAVI with angiographic evidence of CAD receive NIRS-IVUS imaging and are followed up to 24 months. Enrolled patients are classified as NIRS-IVUS positive and NIRS-IVUS negative, respectively, based on their maxLCBI4mm to compare their clinical outcomes. The primary endpoint of the registry is major adverse cardiovascular events over a 24-month follow-up period. CONCLUSIONS: Identification of patients likely or unlikely to benefit from revascularization prior to TAVI represents an important unmet clinical need. This registry is designed to investigate whether NIRS-IVUS-derived atherosclerotic plaque characteristics can identify patients and lesions at risk for future adverse cardiovascular events after TAVI, in order to refine interventional decision-making in this challenging patient population.

Sex and age-specific interactions of coronary atherosclerotic plaque onset and prognosis from coronary computed tomography.

AIMS: The totality of atherosclerotic plaque derived from coronary computed tomography angiography (CCTA) emerges as a comprehensive measure to assess the intensity of medical treatment that patients need. This study examines the differences in age onset and prognostic significance of atherosclerotic plaque burden between sexes. METHODS AND RESULTS: From a large multi-center CCTA registry the Leiden CCTA score was calculated in 24 950 individuals. A total of 11 678 women (58.5 ± 12.4 years) and 13 272 men (55.6 ± 12.5 years) were followed for 3.7 years for major adverse cardiovascular events (MACE) (death or myocardial infarction). The age where the median risk score was above zero was 12 years higher in women vs. men (64-68 years vs. 52-56 years, respectively, P < 0.001). The Leiden CCTA risk score was independently associated with MACE: score 6-20: HR 2.29 (1.69-3.10); score > 20: HR 6.71 (4.36-10.32) in women, and score 6-20: HR 1.64 (1.29-2.08); score > 20: HR 2.38 (1.73-3.29) in men. The risk was significantly higher for women within the highest score group (adjusted P-interaction = 0.003). In pre-menopausal women, the risk score was equally predictive and comparable with men. In post-menopausal women, the prognostic value was higher for women [score 6-20: HR 2.21 (1.57-3.11); score > 20: HR 6.11 (3.84-9.70) in women; score 6-20: HR 1.57 (1.19-2.09); score > 20: HR 2.25 (1.58-3.22) in men], with a significant interaction for the highest risk group (adjusted P-interaction = 0.004). CONCLUSION: Women developed coronary atherosclerosis approximately 12 years later than men. Post-menopausal women within the highest atherosclerotic burden group were at significantly higher risk for MACE than their male counterparts, which may have implications for the medical treatment intensity.

Impact of statins based on high-risk plaque features on coronary plaque progression in mild stenosis lesions: results from the PARADIGM study.

AIMS: To investigate the impact of statins on plaque progression according to high-risk coronary atherosclerotic plaque (HRP) features and to identify predictive factors for rapid plaque progression in mild coronary artery disease (CAD) using serial coronary computed tomography angiography (CCTA). METHODS AND RESULTS: We analyzed mild stenosis (25-49%) CAD, totaling 1432 lesions from 613 patients (mean age, 62.2 years, 63.9% male) and who underwent serial CCTA at a ≥2 year inter-scan interval using the Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging (NCT02803411) registry. The median inter-scan period was 3.5 ± 1.4 years; plaques were quantitatively assessed for annualized percent atheroma volume (PAV) and compositional plaque volume changes according to HRP features, and the rapid plaque progression was defined by the ≥90th percentile annual PAV. In mild stenotic lesions with ≥2 HRPs, statin therapy showed a 37% reduction in annual PAV (0.97 ± 2.02 vs. 1.55 ± 2.22, P = 0.038) with decreased necrotic core volume and increased dense calcium volume compared to non-statin recipient mild lesions. The key factors for rapid plaque progression were ≥2 HRPs [hazard ratio (HR), 1.89; 95% confidence interval (CI), 1.02-3.49; P = 0.042], current smoking (HR, 1.69; 95% CI 1.09-2.57; P = 0.017), and diabetes (HR, 1.55; 95% CI, 1.07-2.22; P = 0.020). CONCLUSION: In mild CAD, statin treatment reduced plaque progression, particularly in lesions with a higher number of HRP features, which was also a strong predictor of rapid plaque progression. Therefore, aggressive statin therapy might be needed even in mild CAD with higher HRPs. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT02803411.

When Does a Calcium Score Equate to Secondary Prevention?: Insights From the Multinational CONFIRM Registry.

BACKGROUND: Elevated coronary artery calcium (CAC) scores in subjects without prior atherosclerotic cardiovascular disease (ASCVD) have been shown to be associated with increased cardiovascular risk. OBJECTIVES: The authors sought to determine at what level individuals with elevated CAC scores who have not had an ASCVD event should be treated as aggressively for cardiovascular risk factors as patients who have already survived an ASCVD event. METHODS: The authors performed a cohort study comparing event rates of patients with established ASVCD to event rates in persons with no history of ASCVD and known calcium scores to ascertain at what level elevated CAC scores equate to risk associated with existing ASCVD. In the multinational CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter) registry, the authors compared ASCVD event rates in persons without a history of myocardial infarction (MI) or revascularization (as categorized on CAC scores) to event rates in those with established ASCVD. They identified 4,511 individuals without known coronary artery disease (CAC) who were compared to 438 individuals with established ASCVD. CAC was categorized as 0, 1 to 100, 101 to 300, and >300. Cumulative major adverse cardiovascular events (MACE), MACE plus late revascularization, MI, and all-cause mortality incidence was assessed using the Kaplan-Meier method for persons with no ASCVD history by CAC level and persons with established ASCVD. Cox proportional hazards regression analysis was used to calculate HRs with 95% CIs, which were adjusted for traditional cardiovascular risk factors. RESULTS: The mean age was 57.6 ± 12.4 years (56% male). In total, 442 of 4,949 (9%) patients experienced MACEs over a median follow-up of 4 years (IQR: 1.7-5.7 years). Incident MACEs increased with higher CAC scores, with the highest rates observed with CAC score >300 and in those with prior ASCVD. All-cause mortality, MACEs, MACE + late revascularization, and MI event rates were not statistically significantly different in those with CAC >300 compared with established ASCVD (all P > 0.05). Persons with a CAC score <300 had substantially lower event rates. CONCLUSIONS: Patients with CAC scores >300 are at an equivalent risk of MACE and its components as those treated for established ASCVD. This observation, that those with CAC >300 have event rates comparable to those with established ASCVD, supplies important background for further study related to secondary prevention treatment targets in subjects without prior ASCVD with elevated CAC. Understanding the CAC scores that are associated with ASCVD risk equivalent to stable secondary prevention populations may be important for guiding the intensity of preventive approaches more broadly.

Prognostic Value of Machine Learning-based Time-to-Event Analysis Using Coronary CT Angiography in Patients with Suspected Coronary Artery Disease.

Purpose: To assess the long-term prognostic value of a machine learning (ML) approach in time-to-event analyses incorporating coronary CT angiography (CCTA)-derived and clinical parameters in patients with suspected coronary artery disease. Materials and Methods: The retrospective analysis included patients with suspected coronary artery disease who underwent CCTA between October 2004 and December 2017. Major adverse cardiovascular events were defined as the composite of all-cause death, myocardial infarction, unstable angina, or late revascularization (>90 days after index scan). Clinical and CCTA-derived parameters were assessed as predictors of major adverse cardiovascular events and incorporated into two models: a Cox proportional hazards model with recursive feature elimination and an ML model based on random survival forests. Both models were trained and validated by employing repeated nested cross-validation. Harrell concordance index (C-index) was used to assess the predictive power. Results: A total of 5457 patients (mean age, 61 years ± 11 [SD]; 3648 male patients) were evaluated. The predictive power of the ML model (C-index, 0.74; 95% CI: 0.71, 0.76) was significantly higher than the Cox model (C-index, 0.71; 95% CI: 0.68, 0.74; P = .02). The ML model also outperformed the segment stenosis score (C-index, 0.69; 95% CI: 0.66, 0.72; P < .001), which was the best performing CCTA-derived parameter, and patient age (C-index, 0.66; 95% CI: 0.63, 0.69; P < .001), the best performing clinical parameter. Conclusion: An ML model for time-to-event analysis based on random survival forests had higher performance in predicting major adverse cardiovascular events compared with established clinical or CCTA-derived metrics and a conventional Cox model.Keywords: Machine Learning, CT Angiography, Cardiac, Arteries, Heart, Arteriosclerosis, Coronary Artery DiseaseSupplemental material is available for this article.© RSNA, 2023.

Convolutional neural networks on risk stratification of patients with suspected coronary artery disease undergoing coronary computed tomography angiography.

To assess the prognostic value of convolutional neural networks (CNN) on coronary computed tomography angiography (CCTA) in comparison to conventional computed tomography (CT) reporting and clinical risk scores. 5468 patients who underwent CCTA with suspected coronary artery disease (CAD) were included. Primary endpoint was defined as a composite of all-cause death, myocardial infarction, unstable angina or late revascularization (> 90 days after CCTA). Early revascularization was additionally included as a training endpoint for the CNN algorithm. Cardiovascular risk stratification was based on Morise score and the extent of CAD (eoCAD) as assessed on CCTA. Semiautomatic post-processing was performed for vessel delineation and annotation of calcified and non-calcified plaque areas. Using a two-step training of a DenseNet-121 CNN the entire network was trained with the training endpoint, followed by training the feature layer with the primary endpoint. During a median follow-up of 7.2 years, the primary endpoint occurred in 334 patients. CNN showed an AUC of 0.631 ± 0.015 for prediction of the combined primary endpoint, while combining it with conventional CT and clinical risk scores showed an improvement of AUC from 0.646 ± 0.014 (based on eoCAD only) to 0.680 ± 0.015 (p < 0.0001) and from 0.619 ± 0.0149 (based on Morise Score only) to 0.6812 ± 0.0145 (p < 0.0001), respectively. In a stepwise model including all prediction methods, it was found an AUC of 0.680 ± 0.0148. CNN analysis showed to improve conventional CCTA-derived and clinical risk stratification when evaluating CCTA of patients with suspected CAD.

Impact of body mass on P2Y12-inhibitor de-escalation in acute coronary syndromes-a substudy of the TROPICAL-ACS trial.

AIMS: Clinical guidelines recommend de-escalation antiplatelet strategies to reduce bleeding risk in acute coronary syndrome (ACS) patients, albeit with a weak recommendation. This substudy of the TROPICAL-ACS trial aimed to determine the impact of body mass on the efficacy of a platelet function testing-guided de-escalation regimen in ACS patients after percutaneous coronary intervention. METHODS AND RESULTS: Patients were randomized to prasugrel (control group) or a platelet function testing-guided regimen with clopidogrel or prasugrel defined after 1-week clopidogrel. The primary endpoint was the net clinical benefit [cardiovascular death, myocardial infarction, stroke, or Bleeding Academic Research Consortium (BARC) 2-5 bleeding] for 12 months. Overweight was defined as a body mass index >25 kg/m2.Patients without overweight showed a significant net clinical benefit from the de-escalation strategy, while in overweight cases de-escalation was comparable to prasugrel treatment [hazard ratio (HR): 0.52; 95% confidence interval (CI): 0.31-0.88; P = 0.013 and HR: 0.95; 95% CI: 0.69-1.31, P = 0.717, P-non-inferiority = 0.03, respectively, P-interaction = 0.053]. The benefit of de-escalation in terms of the risk of bleeding or of the ischaemic events did not reach statistical significance. Bleeding events with de-escalation were less frequent in non-overweight patients but comparable in overweight patients (HR: 0.55; 95% CI: 0.30-1.03; P = 0.057 and HR: 0.95; 95% CI: 0.64-1.41, respectively, P-interaction = 0.147). Non-overweight patients had lower ischaemic event rates with de-escalation, while overweight cases had slightly less (HR: 0.47; 95% CI: 0.18-1.25; P = 0.128 and HR: 0.89; 95% CI: 0.53-1.50, respectively, P-interaction = 0.261). CONCLUSION: The strategy of guided dual antiplatelet therapy de-escalation was associated with a significant net clinical benefit in non-overweight patients, while the two strategies were equivalent in overweight patients.

Clinical and Coronary Plaque Predictors of Atherosclerotic Nonresponse to Statin Therapy.

BACKGROUND: Statins reduce the incidence of major cardiovascular events, but residual risk remains. The study examined the determinants of atherosclerotic statin nonresponse. OBJECTIVES: This study aimed to investigate factors associated with statin nonresponse-defined atherosclerosis progression in patients treated with statins. METHODS: The multicenter PARADIGM (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging) registry included patients who underwent serial coronary computed tomography angiography ≥2 years apart, with whole-heart coronary tree quantification of vessel, lumen, and plaque, and matching of baseline and follow-up coronary segments and lesions. Patients with statin use at baseline and follow-up coronary computed tomography angiography were included. Atherosclerotic statin nonresponse was defined as an absolute increase in percent atheroma volume (PAV) of 1.0% or more per year. Furthermore, a secondary endpoint was defined by the additional requirement of progression of low-attenuation plaque or fibro-fatty plaque. RESULTS: The authors included 649 patients (age 62.0 ± 9.0 years, 63.5% male) on statin therapy and 205 (31.5%) experienced atherosclerotic statin nonresponse. Age, diabetes, hypertension, and all atherosclerotic plaque features measured at baseline scan (high-risk plaque [HRP] features, calcified and noncalcified PAV, and lumen volume) were significantly different between patients with and without atherosclerotic statin nonresponse, whereas only diabetes, number of HRP features, and noncalcified and calcified PAV were independently associated with atherosclerotic statin nonresponse (odds ratio [OR]: 1.41 [95% CI: 0.95-2.11], OR: 1.15 [95% CI: 1.09-1.21], OR: 1.06 [95% CI: 1.02-1.10], OR: 1.07 [95% CI: 1.03-1.12], respectively). For the secondary endpoint (N = 125, 19.2%), only noncalcified PAV and number of HRP features were the independent determinants (OR: 1.08 [95% CI: 1.03-1.13] and OR: 1.21 [95% CI: 1.06-1.21], respectively). CONCLUSIONS: In patients treated with statins, baseline plaque characterization by plaque burden and HRP is associated with atherosclerotic statin nonresponse. Patients with the highest plaque burden including HRP were at highest risk for plaque progression, despite statin therapy. These patients may need additional therapies for further risk reduction.

Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry.

BACKGROUND AND HYPOTHESIS: The recently introduced Bayesian quantile regression (BQR) machine-learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coronary artery disease (CAD) using the BQR model in a vessel-specific manner. METHODS: From the data of 1,463 patients obtained from the PARADIGM (NCT02803411) registry, we analyzed the lumen diameter stenosis (DS) of the three vessels: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). Two models for predicting DS and DS changes were developed. Baseline CV risk factors, symptoms, and laboratory test results were used as the inputs. The conditional 10%, 25%, 50%, 75%, and 90% quantile functions of the maximum DS and DS change of the three vessels were estimated using the BQR model. RESULTS: The 90th percentiles of the DS of the three vessels and their maximum DS change were 41%-50% and 5.6%-7.3%, respectively. Typical anginal symptoms were associated with the highest quantile (90%) of DS in the LAD; diabetes with higher quantiles (75% and 90%) of DS in the LCx; dyslipidemia with the highest quantile (90%) of DS in the RCA; and shortness of breath showed some association with the LCx and RCA. Interestingly, High-density lipoprotein cholesterol showed a dynamic association along DS change in the per-patient analysis. CONCLUSIONS: This study demonstrates the clinical utility of the BQR model for evaluating the comprehensive relationship between risk factors and baseline-grade CAD and its progression.

Echocardiographic evaluation of left ventricular function using an automated analysis algorithm is feasible for beginners and experts: comparison with invasive and non-invasive methods.

AIMS: Echocardiographic measurement of left ventricular function using a user-friendly automated three-dimensional algorithm is highly attractive as it promises quick and accurate diagnosis, circumventing limitations associated with visual estimation or manual biplane measurements. We sought to assess the feasibility and correlation of such automated analysis with clinically established methods. METHODS: A total of 198 patients undergoing transthoracic echocardiography (TTE) with assessment of left ventricular parameters by automated software algorithm (Philips 3D-Heartmodel; 3D-HM) which additionally had either left ventricular angiography (LVA) or cardiac magnetic resonance (CMR) within 24 h of the TTE examination were analyzed. Left ventricular parameters (left ventricular end-diastolic volume, LVEDV, left ventricular end-systolic volume, LVESV as well as left ventricular ejection fraction, LVEF) were compared between 3D-HM, CMR and LVA. RESULTS: Correlation of left ventricular measurements was overall good to excellent and stronger for CMR (EF r = 0.824) than for LVA (EF r = 0.746). Unexperienced and expert clinicians yielded comparable good results. For CMR, highest correlation was detected in patients with BMI < 25 and excellent image quality. High agreement was seen between 3D-HM and CMR or LVA when stratifying patients according to heart failure categories. CONCLUSIONS: Echocardiographic quantification of left ventricular parameters using a software-based algorithm correlated well with established invasive and non-invasive modalities in the clinical setting, even for unexperienced clinicians. Such automated approaches are promising as they allow a reliable, more observer-independent as well as reproducible assessment of left ventricular function.