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.

A comparison of intracardiac echocardiography and transesophageal echocardiography for guiding device closure of ostium secundum atrial septal defect: A 15-year experience.

BACKGROUND AND AIM: Our aim was to evaluate the fluoroscopy time (FT), procedure time (PT) safety and efficacy when using intracardiac echocardiography (ICE) in comparison to transesophageal echocardiography (TEE) guidance for transcatheter closure of Ostium Secundum Atrial Septal Defect (OS-ASD). METHOD: Ninety patients (n = 90) diagnosed with OS-ASD underwent transcatheter closure between March 2006 and October 2021. Fifty-seven patients were treated under ICE guidance, while 33 patients were treated under TEE guidance. RESULTS: Mean age was 43 ± 15 years and 42 ± 10 years in the ICE and TEE groups, respectively. The majority of patients had a centrally placed defect. Median FT was 8.40 min versus 11.70 min (p < .001) in the ICE group compared to the TEE group, respectively. Median PT was 43 min versus 94 min (p < .001) in the ICE group compared to the TEE group, respectively. Both ICE and TEE provided high quality images. All interventions were completed successfully, except for one patient in the ICE group who experienced a device migration, the development of atrial tachycardia in one patient and atrial fibrillation in two patients in the ICE group which spontaneously cardioverted. There were no other complications. CONCLUSION: This study on a consistent cohort of patients with OS-ASD undergoing percutaneous closure suggests that use of ICE is safe and efficacious. Compared to TEE, ICE demonstrated significantly shorter FT and PT, decreasing the entire duration of the procedure and x-ray exposure. No relevant differences were observed in terms of success rate and complications.

AI Cardiac MRI Scar Analysis Aids Prediction of Major Arrhythmic Events in the Multicenter DERIVATE Registry.

Background Scar burden with late gadolinium enhancement (LGE) cardiac MRI (CMR) predicts arrhythmic events in patients with postinfarction in single-center studies. However, LGE analysis requires experienced human observers, is time consuming, and introduces variability. Purpose To test whether postinfarct scar with LGE CMR can be quantified fully automatically by machines and to compare the ability of LGE CMR scar analyzed by humans and machines to predict arrhythmic events. Materials and Methods This study is a retrospective analysis of the multicenter, multivendor CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy (DERIVATE) registry. Patients with chronic heart failure, echocardiographic left ventricular ejection fraction (LVEF) of less than 50%, and LGE CMR were recruited (from January 2015 through December 2020). In the current study, only patients with ischemic cardiomyopathy were included. Quantification of total, dense, and nondense scars was carried out by two experienced readers or a Ternaus network, trained and tested with LGE images of 515 and 246 patients, respectively. Univariable and multivariable Cox analyses were used to assess patient and cardiac characteristics associated with a major adverse cardiac event (MACE). Area under the receiver operating characteristic curve (AUC) was used to compare model performances. Results In 761 patients (mean age, 65 years ± 11, 671 men), 83 MACEs occurred. With use of the testing group, univariable Cox-analysis found New York Heart Association class, left ventricle volume and/or function parameters (by echocardiography or CMR), guideline criterion (LVEF of ≤35% and New York Heart Association class II or III), and LGE scar analyzed by humans or the machine-learning algorithm as predictors of MACE. Machine-based dense or total scar conferred incremental value over the guideline criterion for the association with MACE (AUC: 0.68 vs 0.63, P = .02 and AUC: 0.67 vs 0.63, P = .01, respectively). Modeling with competing risks yielded for dense and total scar (AUC: 0.67 vs 0.61, P = .01 and AUC: 0.66 vs 0.61, P = .005, respectively). Conclusion In this analysis of the multicenter CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy (DERIVATE) registry, fully automatic machine learning-based late gadolinium enhancement analysis reliably quantifies myocardial scar mass and improves the current prediction model that uses guideline-based risk criteria for implantable cardioverter defibrillator implantation. ClinicalTrials.gov registration no.: NCT03352648 Published under a CC BY 4.0 license. Supplemental material is available for this article.

Prediction of myocardial blood flow under stress conditions by means of a computational model.

PURPOSE: Quantification of myocardial blood flow (MBF) and functional assessment of coronary artery disease (CAD) can be achieved through stress myocardial computed tomography perfusion (stress-CTP). This requires an additional scan after the resting coronary computed tomography angiography (cCTA) and administration of an intravenous stressor. This complex protocol has limited reproducibility and non-negligible side effects for the patient. We aim to mitigate these drawbacks by proposing a computational model able to reproduce MBF maps. METHODS: A computational perfusion model was used to reproduce MBF maps. The model parameters were estimated by using information from cCTA and MBF measured from stress-CTP (MBFCTP) maps. The relative error between the computational MBF under stress conditions (MBFCOMP) and MBFCTP was evaluated to assess the accuracy of the proposed computational model. RESULTS: Applying our method to 9 patients (4 control subjects without ischemia vs 5 patients with myocardial ischemia), we found an excellent agreement between the values of MBFCOMP and MBFCTP. In all patients, the relative error was below 8% over all the myocardium, with an average-in-space value below 4%. CONCLUSION: The results of this pilot work demonstrate the accuracy and reliability of the proposed computational model in reproducing MBF under stress conditions. This consistency test is a preliminary step in the framework of a more ambitious project which is currently under investigation, i.e., the construction of a computational tool able to predict MBF avoiding the stress protocol and potential side effects while reducing radiation exposure.

Diagnostic performance of deep learning algorithm for analysis of computed tomography myocardial perfusion.

PURPOSE: To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting hemodynamically significant coronary artery disease (CAD) by using a rest dataset of myocardial computed tomography perfusion (CTP) as compared to invasive evaluation. METHODS: One hundred and twelve consecutive symptomatic patients scheduled for clinically indicated invasive coronary angiography (ICA) underwent CCTA plus static stress CTP and ICA with invasive fractional flow reserve (FFR) for stenoses ranging between 30 and 80%. Subsequently, a DL algorithm for the prediction of significant CAD by using the rest dataset (CTP-DLrest) and stress dataset (CTP-DLstress) was developed. The diagnostic accuracy for identification of significant CAD using CCTA, CCTA + CTP stress, CCTA + CTP-DLrest, and CCTA + CTP-DLstress was measured and compared. The time of analysis for CTP stress, CTP-DLrest, and CTP-DLStress was recorded. RESULTS: Patient-specific sensitivity, specificity, NPV, PPV, accuracy, and area under the curve (AUC) of CCTA alone and CCTA + CTPStress were 100%, 33%, 100%, 54%, 63%, 67% and 86%, 89%, 89%, 86%, 88%, 87%, respectively. Patient-specific sensitivity, specificity, NPV, PPV, accuracy, and AUC of CCTA + DLrest and CCTA + DLstress were 100%, 72%, 100%, 74%, 84%, 96% and 93%, 83%, 94%, 81%, 88%, 98%, respectively. All CCTA + CTP stress, CCTA + CTP-DLRest, and CCTA + CTP-DLStress significantly improved detection of hemodynamically significant CAD compared to CCTA alone (p < 0.01). Time of CTP-DL was significantly lower as compared to human analysis (39.2 ± 3.2 vs. 379.6 ± 68.0 s, p < 0.001). CONCLUSION: Evaluation of myocardial ischemia using a DL approach on rest CTP datasets is feasible and accurate. This approach may be a useful gatekeeper prior to CTP stress..

Computed tomography predictors of structural valve degeneration in patients undergoing transcatheter aortic valve implantation with balloon-expandable prostheses.

OBJECTIVES: Computed tomography (CT) provides excellent anatomy assessment of the aortic annulus (AoA) and is utilized for pre-procedural planning of transcatheter aortic valve implantation (TAVI). We sought to investigate if geometrical characteristics of the AoA determined by CT may represent predictors of structural valve degeneration (SVD) in patients undergoing TAVI with balloon-expandable valves. METHODS: This is a retrospective study on 124 consecutive patients (mean age: 79 ± 7 years; female: 61%) undergoing balloon-expandable TAVI prospectively enrolled in a registry. AoA maximum diameter (Dmax), minimum diameter (Dmin), and area were assessed using pre-procedural CT. SVD was identified during follow-up with transthoracic echocardiography documenting structural prosthetic valve abnormalities with or without hemodynamic changes. RESULTS: The mean follow-up was 5.9 ± 1.7 years. SVD was found in 48 out of 124 patients (38%). AoA Dmax, Dmin, and area were significantly smaller in patients with SVD compared to patients without SVD (25.6 ± 2.2 mm vs. 27.1 ± 2.8 mm, p = 0.012; 20.5 ± 2.1 mm vs. 21.8 ± 2.1 mm, p = 0.001 and 419 ± 77 mm2 vs. 467 ± 88 mm2, p = 0.002, respectively). At univariable analysis, female sex, BSA, 23-mm prosthetic valve size, Dmax < 27.1 mm, and a Dmin < 19.9 mm were associated with SVD, whereas at multivariable analysis, only Dmin < 19.9 mm (OR = 2.873, 95% CI: 1.191-6.929, p = 0.019) and female sex (OR = 2.659, 95% CI: 1.095-6.458, p = 0.031) were independent predictors of SVD. CONCLUSIONS: Female sex and AoA Dmin < 19.9 mm are associated with SVD in patients undergoing TAVI with balloon-expandable valves. When implanting large prostheses in order to avoid paraprosthetic regurgitation, caution should be observed due to the risk of excessive stretching of the AoA Dmin, which may play a role in SVD. KEY POINTS: • Long-term durability is a concern for transcatheter aortic valve bioprosthesis. • CT provides an excellent assessment of the aortic annulus's geometrical characteristics for prosthesis sizing before transcatheter aortic valve implantation (TAVI). • Female sex and a small minimum aortic annulus diameter measured with CT are independent predictors of structural valve degeneration in patients undergoing TAVI with balloon-expandable valves.

Association of left atrial strain by cardiovascular magnetic resonance with recurrence of atrial fibrillation following catheter ablation.

BACKGROUND: Atrial fibrillation (AF) is a progressive condition, which is characterized by inflammation/fibrosis of left atrial (LA) wall, an increase in the LA size/volumes, and decrease in LA function. We sought to investigate the relationship of anatomical and functional parameters obtained by cardiovascular magnetic resonance (CMR), with AF recurrence in paroxysmal AF (pAF) patients after catheter ablation. METHODS: We studied 80 consecutive pAF patients referred for ablation, between January 2014 and December 2019, who underwent pre- and post-ablation CMR while in sinus rhythm. LA volumes were measured using the area-length method and included maximum, minimum, and pre-atrial-contraction volumes. CMR-derived LA reservoir strain (ℇR), conduit strain (ℇCD), and contractile strain (ℇCT) were measured by computer assisted manual planimetry. We used a multivariate logistical regression to estimate the independent predictors of AF recurrence after ablation. RESULTS: Mean age was 58.6 ± 9.4 years, 75% men, mean CHA2DS2-VASc score was 1.7, 36% had prior cardioversion and 51% were taking antiarrhythmic drugs. Patients were followed for a median of 4 years (Q1-Q3 = 2.5-6.2 years). Of the 80 patients, 21 (26.3%) patients had AF recurrence after ablation. There were no significant differences between AF recurrence vs. no recurrence groups in age, gender, CHA2DS2-VASc score, or baseline comorbidities. At baseline, patients with AF recurrence compared to without recurrence had lower LV end systolic volume index (32 ± 7 vs 37 ± 11 mL/m2; p = 0.045) and lower ℇCT (7.1 ± 4.6 vs 9.1 ± 3.7; p = 0.05). Post-ablation, patients with AF recurrence had higher LA minimum volume (68 ± 32 vs 55 ± 23; p = 0.05), right atrial volume index (62 ± 20 vs 52 ± 19 mL/m2; p = 0.04) and lower LA active ejection fraction (24 ± 8 vs 29 ± 11; p = 0.05), LA total ejection fraction (39 ± 14 vs 46 ± 12; p = 0.02), LA expansion index (73.6 ± 37.5 vs 94.7 ± 37.1; p = 0.03) and ℇCT (6.2 ± 2.9 vs 7.3 ± 1.7; p = 0.04). Adjusting for clinical variables in the multivariate logistic regression model, post-ablation minimum LA volume (OR 1.09; CI 1.02-1.16), LA expansion index (OR 0.98; CI 0.96-0.99), and baseline ℇR (OR 0.92; CI 0.85-0.99) were independently associated with AF recurrence. CONCLUSION: Significant changes in LA volumes and strain parameters occur after AF ablation. CMR derived baseline ℇR, post-ablation minimum LAV, and expansion index are independently associated with AF recurrence.

Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment.

BACKGROUND: Segmentation of cardiovascular magnetic resonance (CMR) images is an essential step for evaluating dimensional and functional ventricular parameters as ejection fraction (EF) but may be limited by artifacts, which represent the major challenge to automatically derive clinical information. The aim of this study is to investigate the accuracy of a deep learning (DL) approach for automatic segmentation of cardiac structures from CMR images characterized by magnetic susceptibility artifact in patient with cardiac implanted electronic devices (CIED). METHODS: In this retrospective study, 230 patients (100 with CIED) who underwent clinically indicated CMR were used to developed and test a DL model. A novel convolutional neural network was proposed to extract the left ventricle (LV) and right (RV) ventricle endocardium and LV epicardium. In order to perform a successful segmentation, it is important the network learns to identify salient image regions even during local magnetic field inhomogeneities. The proposed network takes advantage from a spatial attention module to selectively process the most relevant information and focus on the structures of interest. To improve segmentation, especially for images with artifacts, multiple loss functions were minimized in unison. Segmentation results were assessed against manual tracings and commercial CMR analysis software cvi42(Circle Cardiovascular Imaging, Calgary, Alberta, Canada). An external dataset of 56 patients with CIED was used to assess model generalizability. RESULTS: In the internal datasets, on image with artifacts, the median Dice coefficients for end-diastolic LV cavity, LV myocardium and RV cavity, were 0.93, 0.77 and 0.87 and 0.91, 0.82, and 0.83 in end-systole, respectively. The proposed method reached higher segmentation accuracy than commercial software, with performance comparable to expert inter-observer variability (bias ± 95%LoA): LVEF 1 ± 8% vs 3 ± 9%, RVEF - 2 ± 15% vs 3 ± 21%. In the external cohort, EF well correlated with manual tracing (intraclass correlation coefficient: LVEF 0.98, RVEF 0.93). The automatic approach was significant faster than manual segmentation in providing cardiac parameters (approximately 1.5 s vs 450 s). CONCLUSIONS: Experimental results show that the proposed method reached promising performance in cardiac segmentation from CMR images with susceptibility artifacts and alleviates time consuming expert physician contour segmentation.

Multimodality imaging in acute myocarditis.

The diagnosis of acute myocarditis often involves several noninvasive techniques that can provide information regarding volumes, ejection fraction, and tissue characterization. In particular, echocardiography is extremely helpful for the evaluation of biventricular volumes, strain and ejection fraction. Cardiac magnetic resonance, beyond biventricular volumes, strain, and ejection fraction allows to characterize myocardial tissue providing information regarding edema, hyperemia, and fibrosis. Contemporary cardiac computed tomography angiography (CCTA) can not only be extremely important for the assessment of coronary arteries, pulmonary arteries and aorta but also tissue characterization using CCTA can be an additional tool that can explain chest pain with a diagnosis of myocarditis.

T1 mapping and cardiac magnetic resonance feature tracking in mitral valve prolapse.

OBJECTIVES: T1 mapping (T1-map) and cardiac magnetic resonance feature tracking (CMR-FT) techniques have been introduced for the early detection of interstitial myocardial fibrosis and deformation abnormalities. We sought to demonstrate that T1-map and CMR-FT may identify the presence of subclinical myocardial structural changes in patients with mitral valve prolapse (MVP). METHODS: Consecutive MVP patients with moderate-to-severe mitral regurgitation and comparative matched healthy subjects were prospectively enrolled and underwent CMR-FT analysis to calculate 2D global and segmental circumferential (CS) and radial strain (RS) and T1-map to determine global and segmental native T1 (nT1) values. RESULTS: Seventy-three MVP patients (mean age, 57 ± 13 years old; male, 76%; regurgitant volume, 57 ± 21 mL) and 42 matched control subjects (mean age, 56 ± 18 years; male, 74%) were included. MVP patients showed a lower global CS (- 16.3 ± 3.4% vs. - 17.8 ± 1.9%, p = 0.020) and longer global nT1 (1124.9 ± 97.7 ms vs. 1007.4 ± 26.1 ms, p < 0.001) as compared to controls. Moreover, MVP patients showed lower RS and CS in basal (21.6 ± 12.3% vs. 27.6 ± 8.9%, p = 0.008, and - 13.0 ± 6.7% vs. - 14.9 ± 4.1%, p = 0.013) and mid-inferolateral (20.6 ± 10.7% vs. 28.4 ± 8.7%, p < 0.001, and - 12.8 ± 6.3% vs. - 16.5 ± 4.0%, p < 0.001) walls as compared to other myocardial segments. Similarly, MVP patients showed longer nT1 values in basal (1080 ± 68 ms vs. 1043 ± 43 ms, p < 0.001) and mid-inferolateral (1080 ± 77 ms vs. 1034 ± 37 ms, p < 0.001) walls as compared to other myocardial segments. Of note, nT1 values were significantly correlated with CS (r, 0.36; p < 0.001) and RS (r, 0.37; p < 0.001) but not with regurgitant volume. CONCLUSIONS: T1-map and CMR-FT identify subclinical left ventricle tissue changes in patients with MVP. Further studies are required to correlate these subclinical tissue changes with the outcome. KEY POINTS: • T1 mapping (T1-map) and cardiac magnetic resonance feature tracking (CMR-FT) techniques have been introduced for the early detection of interstitial myocardial fibrosis and deformation abnormalities. • In MVP patients, we demonstrated a longer global nT1 with associated reduced global circumferential (CS) and radial strain (RS) as compared to control subjects. • Among MVP patients, the mid-basal left ventricle inferolateral wall showed longer nT1 with reduced CS and RS as compared to other myocardial segments. Further studies are required to correlate these subclinical tissue changes with the outcome.

CarDiac magnEtic Resonance for prophylactic Implantable-cardioVerter defibrillAtor ThErapy in Non-Ischaemic dilated CardioMyopathy: an international Registry.

AIMS: The aim of this registry was to evaluate the additional prognostic value of a composite cardiac magnetic resonance (CMR)-based risk score over standard-of-care (SOC) evaluation in a large cohort of consecutive unselected non-ischaemic cardiomyopathy (NICM) patients. METHODS AND RESULTS: In the DERIVATE registry (www.clinicaltrials.gov/registration: RCT#NCT03352648), 1000 (derivation cohort) and 508 (validation cohort) NICM patients with chronic heart failure (HF) and left ventricular ejection fraction <50% were included. All-cause mortality and major adverse arrhythmic cardiac events (MAACE) were the primary and secondary endpoints, respectively. During a median follow-up of 959 days, all-cause mortality and MAACE occurred in 72 (7%) and 93 (9%) patients, respectively. Age and >3 segments with midwall fibrosis on late gadolinium enhancement (LGE) were the only independent predictors of all-cause mortality (HR: 1.036, 95% CI: 1.0117-1.056, P < 0.001 and HR: 2.077, 95% CI: 1.211-3.562, P = 0.008, respectively). For MAACE, the independent predictors were male gender, left ventricular end-diastolic volume index by CMR (CMR-LVEDVi), and >3 segments with midwall fibrosis on LGE (HR: 2.131, 95% CI: 1.231-3.690, P = 0.007; HR: 3.161, 95% CI: 1.750-5.709, P < 0.001; and HR: 1.693, 95% CI: 1.084-2.644, P = 0.021, respectively). A composite clinical and CMR-based risk score provided a net reclassification improvement of 63.7% (P < 0.001) for MAACE occurrence when added to the model based on SOC evaluation. These findings were confirmed in the validation cohort. CONCLUSION: In a large multicentre, multivendor cohort registry reflecting daily clinical practice in NICM work-up, a composite clinical and CMR-based risk score provides incremental prognostic value beyond SOC evaluation, which may have impact on the indication of implantable cardioverter-defibrillator implantation.

Appropriate use criteria for cardiovascular magnetic resonance imaging (CMR): SIC-SIRM position paper part 1 (ischemic and congenital heart diseases, cardio-oncology, cardiac masses and heart transplant).

Cardiac magnetic resonance (CMR) has emerged as new mainstream technique for the evaluation of patients with cardiac diseases, providing unique information to support clinical decision-making. This document has been developed by a joined group of experts of the Italian Society of Cardiology and Italian society of Radiology and aims to produce an updated consensus statement about the current state of technology and clinical applications of CMR. The writing committee consisted of members and experts of both societies who worked jointly to develop a more integrated approach in the field of cardiac radiology. Part 1 of the document will cover ischemic heart disease, congenital heart disease, cardio-oncology, cardiac masses and heart transplant.

Real-world clinical utility and impact on clinical decision-making of coronary computed tomography angiography-derived fractional flow reserve: lessons from the ADVANCE Registry.

Aims: Non-invasive assessment of stable chest pain patients is a critical determinant of resource utilization and clinical outcomes. Increasingly coronary computed tomography angiography (CCTA) with selective CCTA-derived fractional flow reserve (FFRCT) is being used. The ADVANCE Registry, is a large prospective examination of using a CCTA and FFRCT diagnostic pathway in real-world settings, with the aim of determining the impact of this pathway on decision-making, downstream invasive coronary angiography (ICA), revascularization, and major adverse cardiovascular events (MACE). Methods and results: A total of 5083 patients with symptoms concerning for coronary artery disease (CAD) and atherosclerosis on CCTA were enrolled at 38 international sites from 15 July 2015 to 20 October 2017. Demographics, symptom status, CCTA and FFRCT findings, treatment plans, and 90 days outcomes were recorded. The primary endpoint of reclassification between core lab CCTA alone and CCTA plus FFRCT-based management plans occurred in 66.9% [confidence interval (CI): 64.8-67.6] of patients. Non-obstructive coronary disease was significantly lower in ICA patients with FFRCT ≤0.80 (14.4%) compared to patients with FFRCT >0.80 (43.8%, odds ratio 0.19, CI: 0.15-0.25, P < 0.001). In total, 72.3% of subjects undergoing ICA with FFRCT ≤0.80 were revascularized. No death/myocardial infarction (MI) occurred within 90 days in patients with FFRCT >0.80 (n = 1529), whereas 19 (0.6%) MACE [hazard ratio (HR) 19.75, CI: 1.19-326, P = 0.0008] and 14 (0.3%) death/MI (HR 14.68, CI 0.88-246, P = 0.039) occurred in subjects with an FFRCT ≤0.80. Conclusions: In a large international multicentre population, FFRCT modified treatment recommendation in two-thirds of subjects as compared to CCTA alone, was associated with less negative ICA, predicted revascularization, and identified subjects at low risk of adverse events through 90 days.

Role of Cardiac Magnetic Resonance Imaging in Myocardial Infarction.

PURPOSE OF REVIEW: The purpose of the present paper is to analytically review the diagnostic and prognostic role of CMR in ST-segment elevation myocardial infarction (STEMI) survivors. Percutaneous coronary intervention (PCI) is the treatment of choice in patients STEMI. However, risk of future events remains substantial. Assessment of the extent of myocardial infarction (MI), cardiac function and ventricular remodelling has become the focus of recent studies. Electrocardiography, angiography and echocardiography parameters, as well as risk scores, lack sensitivity and reproducibility in predicting future cardiovascular events. A major advantage of cardiac magnetic resonance imaging (CMR) is that it provides myocardial tissue characterization. RECENT FINDINGS: CMR is able to quantify both reversible and irreversible myocardial injury and correlates with future events. This review will illustrate how microvascular function indices (myocardial salvage index, presence and amount of microvascular obstruction and intramyocardial haemorrhage) detectable by CMR add prognostic information and could impact on future strategies to improve outcomes in revascularized patients.

Coronary CT Angiography Derived Fractional Flow Reserve: The Game Changer in Noninvasive Testing.

PURPOSE OF REVIEW: To summarize the scientific basis of CT derived fractional flow reserve (FFRCT) and present an updated review on the evidence from clinical trials and real-world observational data RECENT FINDINGS: In prospective multicenter studies of patients with stable coronary artery disease (CAD), FFRCT showed high diagnostic performance. More recently, FFRCT has advanced to the realm of clinical utility and real-world clinical practice with emerging data showing that FFRCT when compared to standard care is efficient in safely reducing downstream utilization of invasive coronary angiography (ICA), and costs, as well as improving the diagnostic yield of ICA. Moreover, FFRCT may broaden applicability of frontline coronary CTA testing to patients with high pre-test risk of CAD. Introducing FFRCT into clinical practice has the potential to significantly improve the management of patients with stable CAD. The optimal FFRCT testing interpretation strategy, as well as the relative cost-efficiency of FFRCT against standard noninvasive functional testing, need further investigation.

Artificial Intelligence in Transcatheter Aortic Valve Replacement: Its Current Role and Ongoing Challenges.

Transcatheter aortic valve replacement (TAVR) has emerged as a viable alternative to surgical aortic valve replacement, as accumulating clinical evidence has demonstrated its safety and efficacy. TAVR indications have expanded beyond high-risk or inoperable patients to include intermediate and low-risk patients with severe aortic stenosis. Artificial intelligence (AI) is revolutionizing the field of cardiology, aiding in the interpretation of medical imaging and developing risk models for at-risk individuals and those with cardiac disease. This article explores the growing role of AI in TAVR procedures and assesses its potential impact, with particular focus on its ability to improve patient selection, procedural planning, post-implantation monitoring and contribute to optimized patient outcomes. In addition, current challenges and future directions in AI implementation are highlighted.

Clinical Validation of a Machine-Learned, Point-of-Care System to IDENTIFY Functionally Significant Coronary Artery Disease.

Many clinical studies have shown wide performance variation in tests to identify coronary artery disease (CAD). Coronary computed tomography angiography (CCTA) has been identified as an effective rule-out test but is not widely available in the USA, particularly so in rural areas. Patients in rural areas are underserved in the healthcare system as compared to urban areas, rendering it a priority population to target with highly accessible diagnostics. We previously developed a machine-learned algorithm to identify the presence of CAD (defined by functional significance) in patients with symptoms without the use of radiation or stress. The algorithm requires 215 s temporally synchronized photoplethysmographic and orthogonal voltage gradient signals acquired at rest. The purpose of the present work is to validate the performance of the algorithm in a frozen state (i.e., no retraining) in a large, blinded dataset from the IDENTIFY trial. IDENTIFY is a multicenter, selectively blinded, non-randomized, prospective, repository study to acquire signals with paired metadata from subjects with symptoms indicative of CAD within seven days prior to either left heart catheterization or CCTA. The algorithm's sensitivity and specificity were validated using a set of unseen patient signals (n = 1816). Pre-specified endpoints were chosen to demonstrate a rule-out performance comparable to CCTA. The ROC-AUC in the validation set was 0.80 (95% CI: 0.78-0.82). This performance was maintained in both male and female subgroups. At the pre-specified cut point, the sensitivity was 0.85 (95% CI: 0.82-0.88), and the specificity was 0.58 (95% CI: 0.54-0.62), passing the pre-specified endpoints. Assuming a 4% disease prevalence, the NPV was 0.99. Algorithm performance is comparable to tertiary center testing using CCTA. Selection of a suitable cut-point results in the same sensitivity and specificity performance in females as in males. Therefore, a medical device embedding this algorithm may address an unmet need for a non-invasive, front-line point-of-care test for CAD (without any radiation or stress), thus offering significant benefits to the patient, physician, and healthcare system.

PROGnostic RolE of strain measurements in stress cardiac MRI in predicting major adverse cardiac events.

OBJECTIVES: We aimed to investigate the role of feature-tracking (FT) strain in long-term risk stratification of patients with known or suspected coronary artery disease (CAD) who underwent stress cardiac MRI with dipyridamole; to determine if contrast-free stress cardiac MRI with strain measurements could provide comparable prognostic value to myocardial perfusion. MATERIALS AND METHODS: This retrospective study included consecutive patients with stable symptoms suggesting possible cardiac ischemia who underwent stress cardiac MRI with dipyridamole. The mean follow-up period was 5.8 years ±1.2 [SD]. FT cardiac MRI analysis was performed for each patient to obtain 2D global peak circumferential strain (GCS). The primary outcome measure was major adverse cardiac events (MACE), defined as nonfatal myocardial infarction and cardiac death. RESULTS: A total of 729 patients (mean age, 63 years ±10 [SD]; 616 males) were included. MACE occurred in 70 (9.6%) patients. The presence of late gadolinium enhancement (LGE) ([HR] 2.74, [95% CI: 1.53, 4.88]; P < .001) and stress GCS (HR, 1.06 [95% CI: 1.01, 1.12]; P = .016) were independently associated with MACE. A model based on contrast-free assessment of LVEF and stress GCS showed similar performance for predicting MACE than LVEF and perfusion (P = .056). CONCLUSIONS: In patients with known or suspected CAD undergoing stress cardiac MRI with dipyridamole, GCS and LGE presence were independent predictors of MACE. Contrast-free stress cardiac MRI with stress GCS measurement offered prognostic value akin to myocardial perfusion assessment. CLINICAL RELEVANCE STATEMENT: Stress global circumferential strain represented an additional method to predict major adverse cardiac events in patients undergoing stress cardiac MRI, even without the use of contrast agents. This would be of particular significance in patients with severe renal impairment.

Impact of Smoking on Coronary Volume-to-Myocardial Mass Ratio: An ADVANCE Registry Substudy.

Purpose To examine the relationship between smoking status and coronary volume-to-myocardial mass ratio (V/M) among individuals with coronary artery disease (CAD) undergoing CT fractional flow reserve (CT-FFR) analysis. Materials and Methods In this secondary analysis, participants from the ADVANCE registry evaluated for suspected CAD from July 15, 2015, to October 20, 2017, who were found to have coronary stenosis of 30% or greater at coronary CT angiography (CCTA) were included if they had known smoking status and underwent CT-FFR and V/M analysis. CCTA images were segmented to calculate coronary volume and myocardial mass. V/M was compared between smoking groups, and predictors of low V/M were determined. Results The sample for analysis included 503 current smokers, 1060 former smokers, and 1311 never-smokers (2874 participants; 1906 male participants). After adjustment for demographic and clinical factors, former smokers had greater coronary volume than never-smokers (former smokers, 3021.7 mm3 ± 934.0 [SD]; never-smokers, 2967.6 mm3 ± 978.0; P = .002), while current smokers had increased myocardial mass compared with never-smokers (current smokers, 127.8 g ± 32.9; never-smokers, 118.0 g ± 32.5; P = .02). However, both current and former smokers had lower V/M than never-smokers (current smokers, 24.1 mm3/g ± 7.9; former smokers, 24.9 mm3/g ± 7.1; never-smokers, 25.8 mm3/g ± 7.4; P < .001 [unadjusted] and P = .002 [unadjusted], respectively). Current smoking status (odds ratio [OR], 0.74 [95% CI: 0.59, 0.93]; P = .009), former smoking status (OR, 0.81 [95% CI: 0.68, 0.97]; P = .02), stenosis of 50% or greater (OR, 0.62 [95% CI: 0.52, 0.74]; P < .001), and diabetes (OR, 0.67 [95% CI: 0.56, 0.82]; P < .001) were independent predictors of low V/M. Conclusion Both current and former smoking status were independently associated with low V/M. Keywords: CT Angiography, Cardiac, Heart, Ischemia/Infarction Clinical trial registration no. NCT02499679 Supplemental material is available for this article. © RSNA, 2024.

Interaction of AI-Enabled Quantitative Coronary Plaque Volumes on Coronary CT Angiography, FFRCT, and Clinical Outcomes: A Retrospective Analysis of the ADVANCE Registry.

BACKGROUND: Luminal stenosis, computed tomography-derived fractional-flow reserve (FFRCT), and high-risk plaque features on coronary computed tomography angiography are all known to be associated with adverse clinical outcomes. The interactions between these variables, patient outcomes, and quantitative plaque volumes have not been previously described. METHODS: Patients with coronary computed tomography angiography (n=4430) and one-year outcome data from the international ADVANCE (Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care) registry underwent artificial intelligence-enabled quantitative coronary plaque analysis. Optimal cutoffs for coronary total plaque volume and each plaque subtype were derived using receiver-operator characteristic curve analysis. The resulting plaque volumes were adjusted for age, sex, hypertension, smoking status, type 2 diabetes, hyperlipidemia, luminal stenosis, distal FFRCT, and translesional delta-FFRCT. Median plaque volumes and optimal cutoffs for these adjusted variables were compared with major adverse cardiac events, late revascularization, a composite of the two, and cardiovascular death and myocardial infarction. RESULTS: At one year, 55 patients (1.2%) had experienced major adverse cardiac events, and 123 (2.8%) had undergone late revascularization (>90 days). Following adjustment for age, sex, risk factors, stenosis, and FFRCT, total plaque volume above the receiver-operator characteristic curve-derived optimal cutoff (total plaque volume >564 mm3) was associated with the major adverse cardiac event/late revascularization composite (adjusted hazard ratio, 1.515 [95% CI, 1.093-2.099]; P=0.0126), and both components. Total percent atheroma volume greater than the optimal cutoff was associated with both major adverse cardiac event/late revascularization (total percent atheroma volume >24.4%; hazard ratio, 2.046 [95% CI, 1.474-2.839]; P<0.0001) and cardiovascular death/myocardial infarction (total percent atheroma volume >37.17%, hazard ratio, 4.53 [95% CI, 1.943-10.576]; P=0.0005). Calcified, noncalcified, and low-attenuation percentage atheroma volumes above the optimal cutoff were associated with all adverse outcomes, although this relationship was not maintained for cardiovascular death/myocardial infarction in analyses stratified by median plaque volumes. CONCLUSIONS: Analysis of the ADVANCE registry using artificial intelligence-enabled quantitative plaque analysis shows that total plaque volume is associated with one-year adverse clinical events, with incremental predictive value over luminal stenosis or abnormal physiology by FFRCT. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02499679.