Computed tomography angiography-derived fractional flow reserve (CT-FFR) for the detection of myocardial ischemia with invasive fractional flow reserve as reference: systematic review and meta-analysis

High-resolution deep learning reconstruction to improve the accuracy of CT fractional flow reserve

OBJECTIVES

This study aimed to compare the diagnostic performance of CT-derived fractional flow reserve (CT-FFR) using model-based iterative reconstruction (MBIR) and high-resolution deep learning reconstruction (HR-DLR) images to detect functionally significant stenosis with invasive FFR as the reference standard.

MATERIALS AND METHODS

This single-center retrospective study included 79 consecutive patients (mean age, 70 ± 11 [SD] years; 57 male) who underwent coronary CT angiography followed by invasive FFR between February 2022 and March 2024. CT-FFR was calculated using a mesh-free simulation. The cutoff for functionally significant stenosis was defined as FFR ≤ 0.80. CT-FFR was compared with MBIR and HR-DLR using receiver operating characteristic curve analysis.

RESULTS

The mean invasive FFR value was 0.81 ± 0.09, and 46 of 98 vessels (47%) had FFR ≤ 0.80. The mean noise of HR-DLR was lower than that of MBIR (14.4 ± 1.7 vs 23.5 ± 3.1, p < 0.001). The area under the receiver operating characteristic curve for the diagnosis of functionally significant stenosis of HR-DLR (0.88; 95% CI: 0.80, 0.95) was higher than that of MBIR (0.76; 95% CI: 0.67, 0.86; p = 0.003). The diagnostic accuracy of HR-DLR (88%; 86 of 98 vessels; 95% CI: 80, 94) was higher than that of MBIR (70%; 69 of 98 vessels; 95% CI: 60, 79; p < 0.001).

CONCLUSIONS

HR-DLR improves image quality and the diagnostic performance of CT-FFR for the diagnosis of functionally significant stenosis.

KEY POINTS

Question The effect of HR-DLR on the diagnostic performance of CT-FFR has not been investigated. Findings HR-DLR improved the diagnostic performance of CT-FFR over MBIR for the diagnosis of functionally significant stenosis as assessed by invasive FFR. Clinical relevance HR-DLR would further enhance the clinical utility of CT-FFR in diagnosing the functional significance of coronary stenosis.

Diagnostic performance of target vs. vessel μFR in stable coronary artery disease

BACKGROUND

We aim to compare with the diagnostic performance of target-position quantitative flow ratio derived from Murray Law (target-μFR) and vessel quantitative flow ratio derived from Murray Law (vessel-μFR) using the fractional flow reserve (FFR) as reference standard. This study may provide more evidence for the novel clinical usage of target-μFR in the diagnosis of coronary artery disease.

METHODS

Six hundreds and fifty-six patients (685 lesions) with known or suspected coronary artery disease were screened for this retrospective analysis between January 2021 to March 2023. A total of 161 patients (190 lesions) underwent quantitative coronary angiography and FFR evaluations. In the final analysis, 137 patients (146 lesions) were included in this study. Both of target-μFR and vessel-μFR were compared the diagnostic performance using the FFR ≤ 0.80 as the reference standard.

RESULTS

Both target-μFR (R = 0.84) and vessel-μFR (R = 0.83) demonstrated a strong correlation with FFR, and both methods showed great agreement with FFR. The area under the receiver operating characteristic curve was 0.937 for target-μFR and 0.936 for vessel-μFR in predicting FFR ≤ 0.80. FFR ≤ 0.80 were predicted with high sensitivity (86.44%) and specificity (88.51%) using the pre-defined cutt-off of 0.80 for target-μFR. A good diagnostic performance (sensitivity 92.98% and specificity 91.01%) was also demonstrated by vessel-μFR which the pre-defined cutt-off was 0.80.

CONCLUSION

The target-μFR has the similar diagnostic performance with vessel-μFR. The accuracy of μFR does not seem to be affected by the selection of the measurement point. Both of the virtual models have been validated as computational tools for diagnosing ischemia and are instrumental in aiding clinical decision-making.

Incremental diagnostic value of coronary computed tomography angiography derived fractional flow reserve to detect ischemia

Over the past decade, coronary computed tomographic angiography (CCTA) has been the most robust non-invasive method for evaluating significant coronary stenosis. Thanks to new technologies, it is now possible to determine the fractional flow reserve (FFR) non-invasively using computed tomographic (CT) images. The aim of this work was to evaluate the incremental diagnostic value of CT-derived FFR for ischemia detection. In this retrospective monocentric study, we investigated 421 patients who underwent CCTA and subsequent ischemia testing between 04/2009 and 06/2020. Endpoint was ischemia on a coronary vessel level assessed by CMR (n = 20), SPECT (n = 225), invasive angiography (stenosis ≥ 90%; n = 80) or invasive FFR (positive if ≤ 0.8; n = 96). CT-FFR was derived from CCTA images by a machine learning (ML) based software prototype. Patients averaged 66.5 [58.2-73.6] years of age and 72.7% (n = 306) were male. Overall, 52.5% (n = 221) had hypertension and 67.9% (n = 286) had hypercholesteremia. Logistic regression analysis on a per vessel base showed that the diagnostic model with CT-FFR plus CCTA had significantly better-fit criteria than the diagnostic model with CCTA alone (log-likelihood χ2 230.21 vs. 192.17; p for difference < 0.001). In particular, the area under curve (AUC) by receiver operating characteristics curve (ROC) analysis for CT-FFR plus CCTA (0.87) demonstrated greater discrimination of hemodynamic ischemia compared to CCTA alone (0.83; p for difference < 0.0001). Combined CCTA and CT-FFR have improved diagnostic accuracy compared to CCTA alone in detecting ischemia on the coronary vessel level and thus could reduce the use of invasive coronary angiography in the future.

Prognostic Significance of Computed Tomography-Derived Fractional Flow Reserve for Long-Term Outcomes in Individuals With Coronary Artery Disease

BACKGROUND

Data on the predictive value of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) for long-term outcomes are limited.

METHODS AND RESULTS

A retrospective pooled analysis of individual patient data was performed. Deep-learning-based CT-FFR was calculated. All patients enrolled were followed-up for at least 5 years. The primary outcome was major adverse cardiovascular events. The secondary outcome was death or nonfatal myocardial infarction. Predictive abilities for outcomes were compared among 3 models (model 1, constructed using clinical variables; model 2, model 1+coronary computed tomography angiography-derived anatomical parameters; and model 3, model 2+CT-FFR). A total of 2566 patients (median age, 60 [53-65] years; 56.0% men) with coronary artery disease were included. During a median follow-up time of 2197 (2127-2386) days, 237 patients (9.2%) experienced major adverse cardiovascular events. In multivariable-adjusted Cox models, CT-FFR≤0.80 (hazard ratio [HR], 5.05 [95% CI, 3.64-7.01]; P<0.001) exhibited robust predictive value. The discriminant ability was higher in model 2 than in model 1 (Harrell's C-statistics, 0.79 versus 0.64; P<0.001) and was further promoted by adding CT-FFR to model 3 (Harrell's C-statistics, 0.83 versus 0.79; P<0.001). Net reclassification improvement was 0.264 (P<0.001) for model 2 beyond model 1. Of note, compared with model 2, model 3 also exhibited improvement (net reclassification improvement=0.085; P=0.001). As for predicting death or nonfatal myocardial infarction, only incorporating CT-FFR into model 3 showed improved reclassification (net reclassification improvement=0.131; P=0.021).

CONCLUSIONS

CT-FFR provides strong and incremental prognostic information for predicting long-term outcomes. The combined models incorporating CT-FFR exhibit modest improvement of prediction abilities, which may aid in risk stratification and decision-making.

Association study of NAFLD with pericoronary adipose tissue and pericardial adipose tissue: Diagnosis of stable CAD patients with NAFLD based on radiomic features

BACKGROUND AND AIM

Nonalcoholic fatty liver disease (NAFLD) is prone to complicated cardiovascular disease, and we aimed to identify patients with NAFLD who are prone to developing stable coronary artery disease (CAD).

METHODS AND RESULTS

We retrospectively recruited adults who underwent coronary computed tomography angiography (CTA). A total of 127 NAFLD patients and 127 non-NAFLD patients were included in this study. Clinical features and imaging parameters were analysed, mainly including pericardial adipose tissue (PAT), pericoronary adipose tissue (PCAT), and radiomic features of 6792 PCATs. The inflammatory associations of NAFLD patients with PAT and PCAT were analysed. Clinical features (model 1), CTA parameters (model 2), the radscore (model 3), and a composite model (model 4) were constructed to identify patients with NAFLD with stable CAD. The presence of NAFLD resulted in a greater inflammatory involvement in all three coronary arteries (all P < 0.01) and was associated with increased PAT volume (r = 0.178**, P < 0.05). In the presence of NAFLD, the mean CT value of the PAT was significantly correlated with the fat attenuation index (FAI) in all three vessels and had the strongest correlation with the RCA FAI (r = 0.55, p < 0.001). A total of 9 radiomic features were screened by LASSO regression to calculate radiomic scores. In the model comparison, model 4 had the best performance of all models (AUC 0.914 [0.863-0.965]) and the highest overall diagnostic value of the model (sensitivity: 0.814, specificity: 0.941).

CONCLUSIONS

NAFLD correlates with PAT volume and PCAT inflammation. Furthermore, combining clinical features, CTA parameters, and radiomic scores can improve the efficiency of early diagnosis of stable CAD in patients with NAFLD.

Current Status of Cardiac CT for Nuclear Medicine Professionals: Coronary Artery Disease Evaluation

With advances in computed tomography (CT) technology over the past two decades, cardiac CT has become a noninvasive diagnostic tool for morphological evaluation of coronary artery disease (CAD) caused by atherosclerotic plaques and stenosis and serves as a "gatekeeper" before invasive coronary angiography. Additionally, cardiac CT stress perfusion and CT-derived fractional flow reserve can be used to assess the hemodynamic significance of coronary artery stenosis. Delayed enhancement CT can detect and localize myocardial infarction and assess myocardial viability. Currently, cardiac CT serves as a potential "one-stop-shop" imaging modality for the comprehensive assessment of patients with suspected or known CAD by providing analysis of coronary anatomy, functional significance, and characterization of left ventricular myocardium in a single session. It is crucial for nuclear medicine professionals to be aware of the current capability of cardiac CT and its ability to perform comprehensive and accurate nuclear cardiac imaging studies, which are essential for functional assessment of CAD.

Coronary angiography: a review of the state of the art and the evolution of angiography in cardio therapeutics

Traditionally, coronary angiography was restricted to visual estimation of contrast-filled lumen in coronary obstructive diseases. Over the previous decades, considerable development has been made in quantitatively analyzing coronary angiography, significantly improving its accuracy and reproducibility.  Notably, the integration of artificial intelligence (AI) and machine learning into quantitative coronary angiography (QCA) holds promise for further enhancing diagnostic accuracy and predictive capabilities. In addition, non-invasive fractional flow reserve (FFR) indices, including computed tomography-FFR, have emerged as valuable tools, offering precise physiological assessment of coronary artery disease without the need for invasive procedures. These innovations allow for a more comprehensive evaluation of disease severity and aid in guiding revascularization decisions. This review traces the development of QCA technologies over the years, highlighting key milestones and current advancements. It also explores prospects that could revolutionize the field, such as AI integration and improved imaging techniques. By addressing both historical context and future directions, the article underscores the ongoing evolution of QCA and its critical role in the accurate assessment and management of coronary artery diseases. Through continuous innovation, QCA is poised to remain at the forefront of cardiovascular diagnostics, offering clinicians invaluable tools for improving patient care.

Noninvasive and fast method of calculation for instantaneous wave-free ratio based on haemodynamics and deep learning

BACKGROUND AND OBJECTIVES

Instantaneous wave-free ratio (iFR) is a new invasive indicator of myocardial ischaemia, and its diagnostic performance is as good as the "gold standard" of myocardial ischaemia diagnosis: fractional flow reserve (FFR). iFR can be approximated by iFRCT, which is calculated based on noninvasive coronary CT angiography (CTA) images and computational fluid dynamics (CFD). However, the existing methods for calculating iFRCT fail to accurately simulate the resting state of the coronary artery, resulting in low computational accuracy. Furthermore, the use of CFD technology limits its computational efficiency, making it difficult to meet clinical application needs. The role of coronary microcirculatory resistance compensation suggests that microcirculatory resistance can be adaptively reduced to compensate for increases in coronary stenotic resistance, thereby maintaining stable myocardial perfusion in the resting state. It is therefore necessary to consider this compensation mechanism to establish a high-fidelity microcirculation resistance model in the resting state in line with human physiology, and so to achieve accurate calculation of iFRCT.

METHODS

In this study we successfully collected clinical data, such as FFR, in 205 stenotic vessels from 186 patients with coronary heart disease. A neural network model was established to predict coronary artery stenosis resistance. Based on the compensation mechanism of coronary microcirculation resistance, an iterative solution algorithm for microcirculation resistance in the resting state was developed. Combining the two methods, a simplified single-branch model combining coronary stenosis and microcirculation resistance was established, and the noninvasive and rapid numerical calculation of iFRCT was performed.

RESULTS

The results showed that the mean squared error (MSE) between the pressure drop predicted by the neural network value for the coronary artery stenosis model and the ground truth in the test set was 0.053 %, and correlation analysis proved that there was a good correlation between them (r = 0.99, p < 0.001). With reference to clinical diagnosis of myocardial ischaemia (using FFR as the gold standard), the diagnostic accuracy of the iFRCT calculation model for the 205 cases was 88.29 % (r = 0.71, p < 0.001), and the total calculation time was < 8 s.

CONCLUSIONS

The results of this study demonstrate the utility of a simplified single-branch model in an iFRCT calculation method based on haemodynamics and deep learning, which is important for noninvasive and rapid diagnosis of myocardial ischaemia.

The clinical value of noninvasive left ventricular myocardial work in the diagnosis of myocardial ischemia in coronary heart disease: a comparative study with coronary flow reserve fraction

The prompt and precise identification of hemodynamically significant coronary artery lesions remains an ongoing challenge. This study investigated the diagnostic value of non-invasive global left ventricular myocardial work indices by echocardiography in functional status of coronary artery disease (CAD) patients with myocardial ischemia using fractional flow reserve (FFR) as the gold standard. A total of 77 consecutive patients with clinically suspected CAD were prospectively enrolled. All participants sequentially underwent echocardiography, invasive coronary angiography (ICA) and FFR measurement. According to the results of ICA, patients were divided into myocardial ischemia group (FFR ≤ 0.8, n = 27) and non-myocardial ischemia group (FFR > 0.8, n = 50). Myocardial work indices including global work index (GWI), global constructive work (GCW), global wasted work (GWW), global work efficiency (GWE), global positive work (GPW), global negative work (GNW), global systolic constructive work (GSCW) and global systolic wasted work (GSWW) were obtained by using the non-invasive left ventricular pressure strain loop (PSL) technique. Compared with the non-myocardial ischemia group, GWI, GCW, GPW and GSCW were significantly decreased in the myocardial ischemia group at either the 18-segment level or the 12-segment level (P < 0.001). At the 18-segment level, GWI < 1783.6 mmHg%, GCW < 1945.4 mmHg%, GPW < 1788.7 mmHg% and GSCW < 1916.5 mmHg% were optimal cut-off value to detect myocardial ischemia with an FFR ≤ 0.8. Global left ventricular myocardial work indices by echocardiography exhibited a good diagnostic value in patients with CAD and may have a good clinical significance for the screening of suspected myocardial ischemia.

Advances in the Computational Assessment of Disturbed Coronary Flow and Wall Shear Stress: A Contemporary Review

Coronary artery blood flow is influenced by various factors including vessel geometry, hemodynamic conditions, timing in the cardiac cycle, and rheological conditions. Multiple patterns of disturbed coronary flow may occur when blood flow separates from the laminar plane, associated with inefficient blood transit, and pathological processes modulated by the vascular endothelium in response to abnormal wall shear stress. Current simulation techniques, including computational fluid dynamics and fluid-structure interaction, can provide substantial detail on disturbed coronary flow and have advanced the contemporary understanding of the natural history of coronary disease. However, the clinical application of these techniques has been limited to hemodynamic assessment of coronary disease severity, with the potential to refine the assessment and management of coronary disease. Improved computational efficiency and large clinical trials are required to provide an incremental clinical benefit of these techniques beyond existing tools. This contemporary review is a clinically relevant overview of the disturbed coronary flow and its associated pathological consequences. The contemporary methods to assess disturbed flow are reviewed, including clinical applications of these techniques. Current limitations and future opportunities in the field are also discussed.

Predicting coronary artery occlusion risk from noninvasive images by combining CFD-FSI, cGAN and CNN

Wall Shear Stress (WSS) is one of the most important parameters used in cardiovascular fluid mechanics, and it provides a lot of information like the risk level caused by any vascular occlusion. Since WSS cannot be measured directly and other available relevant methods have issues like low resolution, uncertainty and high cost, this study proposes a novel method by combining computational fluid dynamics (CFD), fluid-structure interaction (FSI), conditional generative adversarial network (cGAN) and convolutional neural network (CNN) to predict coronary artery occlusion risk using only noninvasive images accurately and rapidly. First, a cGAN model called WSSGAN was developed to predict the WSS contours on the vessel wall by training and testing the model based on the calculated WSS contours using coupling CFD-FSI simulations. Then, an 11-layer CNN was used to classify the WSS contours into three grades of occlusions, i.e. low risk, medium risk and high risk. To verify the proposed method for predicting the coronary artery occlusion risk in a real case, the patient's Magnetic Resonance Imaging (MRI) images were converted into a 3D geometry for use in the WASSGAN model. Then, the predicted WSS contours by the WSSGAN were entered into the CNN model to classify the occlusion grade.

A meta-analysis comparing the diagnostic performance of computed tomography-derived fractional flow reserve and coronary computed tomography angiography at different levels of coronary artery calcium score

OBJECTIVES

The impact of coronary calcification on the diagnostic accuracy of computed tomography-derived fractional flow reserve (CT-FFR) and coronary computed tomography angiography (CCTA) remains a crucial consideration. This meta-analysis aims to compare the diagnostic performance of CT-FFR and CCTA at different levels of coronary artery calcium score (CACS).

METHODS AND RESULTS

We searched PubMed, Embase, and the Cochrane Library for relevant articles on CCTA, CT-FFR, and invasive fractional flow reserve (FFR). Ten studies were included to evaluate the diagnostic performance of CT-FFR and CCTA at the per-patient and per-vessel levels in four CACS groups. Invasive FFR was used as the reference standard. Except for the CACS ≥ 400 group, the AUC of CT-FFR was higher than those of CCTA in other subgroups of CACS (in CACS < 100 (per-patient, 0.9 (95% CI 0.87-0.92) vs. 0.32 (95% CI 0.28-0.36); per-vessel, 0.92 (95% CI 0.89-0.94) vs. 0.66 (95% CI 0.62-0.7); both p < 0.001), CACS ≥ 100 (per-patient, 0.86 (95% CI 0.82-0.88) vs. 0.44 (95% CI 0.4-0.48); per-vessel, 0.88 (95% CI 0.85-0.9) vs. 0.51 (95% CI 0.46-0.55); both p < 0.001), and CACS < 400 (per-patient, 0.9 (95% CI 0.87-0.93) vs. 0.74 (95% CI 0.7-0.78), p < 0.001; per-vessel, 0.8 (95% CI 0.76-0.83) vs. 0.74 (95% CI 0.7-0.78); p = 0.02)).

CONCLUSIONS

CT-FFR demonstrates superior diagnostic performance in low CACS groups (CACS < 400) than CCTA in detecting hemodynamic stenoses in patients with coronary artery disease (CAD).

CLINICAL RELEVANCE STATEMENT

Computed tomography-derived fractional flow reserve might be utilized to determine the necessity of invasive coronary angiography in coronary artery disease patients with coronary artery calcium score < 400.

KEY POINTS

• There is a lack of meta-analysis comparing the diagnostic performance of computed tomography-derived fractional flow reserve and coronary computed tomography angiography at different levels of calcification. • Computed tomography-derived fractional flow reserve only has a better diagnostic performance than coronary computed tomography angiography with low amounts of coronary calcium. • For the low coronary artery calcium score group, computed tomography-derived fractional flow reserve might be a good non-invasive method to detect hemodynamic stenoses in coronary artery disease patients.

Charting the Unseen: How Non-Invasive Imaging Could Redefine Cardiovascular Prevention

Cardiovascular diseases (CVDs) remain a major global health challenge, leading to significant morbidity and mortality while straining healthcare systems. Despite progress in medical treatments for CVDs, their increasing prevalence calls for a shift towards more effective prevention strategies. Traditional preventive approaches have centered around lifestyle changes, risk factors management, and medication. However, the integration of imaging methods offers a novel dimension in early disease detection, risk assessment, and ongoing monitoring of at-risk individuals. Imaging techniques such as supra-aortic trunks ultrasound, echocardiography, cardiac magnetic resonance, and coronary computed tomography angiography have broadened our understanding of the anatomical and functional aspects of cardiovascular health. These techniques enable personalized prevention strategies by providing detailed insights into the cardiac and vascular states, significantly enhancing our ability to combat the progression of CVDs. This review focuses on amalgamating current findings, technological innovations, and the impact of integrating advanced imaging modalities into cardiovascular risk prevention, aiming to offer a comprehensive perspective on their potential to transform preventive cardiology.

CT Myocardial Perfusion and CT-FFR versus Invasive FFR for Hemodynamic Relevance of Coronary Artery Disease

Background CT-derived fractional flow reserve (CT-FFR) and dynamic CT myocardial perfusion imaging enhance the specificity of coronary CT angiography (CCTA) for ruling out coronary artery disease (CAD). However, evidence on comparative diagnostic value remains scarce. Purpose To compare the diagnostic accuracy of CCTA plus CT-FFR, CCTA plus CT perfusion, and sequential CCTA plus CT-FFR and CT perfusion for detecting hemodynamically relevant CAD with that of invasive angiography. Materials and Methods This secondary analysis of a prospective study included patients with chest pain referred for invasive coronary angiography at nine centers from July 2016 to September 2019. CCTA and CT perfusion were performed with third-generation dual-source CT scanners. CT-FFR was assessed on-site. Independent core laboratories analyzed CCTA alone, CCTA plus CT perfusion, CCTA plus CT-FFR, and a sequential approach involving CCTA plus CT-FFR and CT perfusion for the presence of hemodynamically relevant stenosis. Invasive coronary angiography with invasive fractional flow reserve was the reference standard. Diagnostic accuracy metrics and the area under the receiver operating characteristic curve (AUC) were compared with the Sign test and DeLong test. Results Of the 105 participants (mean age, 64 years ± 8 [SD]; 68 male), 49 (47%) had hemodynamically relevant stenoses at invasive coronary angiography. CCTA plus CT-FFR and CCTA plus CT perfusion showed no evidence of a difference for participant-based sensitivities (90% vs 90%, P > .99), specificities (77% vs 79%, P > .99) and vessel-based AUCs (0.84 [95% CI: 0.77, 0.91] vs 0.83 [95% CI: 0.75, 0.91], P = .90). Both had higher participant-based specificity than CCTA alone (54%, both P < .001) without evidence of a difference in sensitivity between CCTA (94%) and CCTA plus CT perfusion (P = .50) or CCTA plus CT-FFR (P = .63). The sequential approach combining CCTA plus CT-FFR with CT perfusion achieved higher participant-based specificity than CCTA plus CT-FFR (88% vs 77%, P = .03) without evidence of a difference in participant-based sensitivity (88% vs 90%, P > .99) and vessel-based AUC (0.85 [95% CI: 0.77, 0.93], P = .78). Compared with CCTA plus CT perfusion, the sequential approach showed no evidence of a difference in participant-based sensitivity (P > .99), specificity (P = .06), or vessel-based AUC (P = .54). Conclusion There was no evidence of a difference in diagnostic accuracy between CCTA plus CT-FFR and CCTA plus CT perfusion for detecting hemodynamically relevant CAD. A sequential approach combining CCTA plus CT-FFR with CT perfusion led to improved participant-based specificity with no evidence of a difference in sensitivity compared with CCTA plus CT-FFR. ClinicalTrials.gov registration no.: NCT02810795 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Sinitsyn in this issue.

Coronary computed tomographic angiography-derived anatomic and hemodynamic plaque characteristics in prediction of cardiovascular events

This study investigated the association of anatomic and hemodynamic plaque characteristics based on deep learning coronary computed tomography angiography (CCTA) with high-risk plaques that caused subsequent major adverse cardiovascular events (MACE). A retrospective analysis was conducted on patients who underwent CCTA between 1 month and 3 years prior to the occurrence of a MACE. Deep learning and computational fluid dynamics algorithms based on CCTA were applied to extract adverse plaque characteristics (low-attenuation plaque, positive remodeling, napkin-ring sign, and spotty calcification), and hemodynamic parameters (fractional flow reserve derived by coronary computed tomographic angiography [FFRCT], change in FFRCT across the lesion [△FFRCT], wall shear stress [WSS], and axial plaque stress [APS]). Correlation analysis, logistic regression, and Cox proportional risk analysis were conducted to understand the relationship between these measures and the occurrence of MACE and assess the value of hemodynamic parameters in predicting the incidence of MACE events and their prognosis. Our study included 86 patients with a total of 134 vessels exhibiting plaque formation and 83 culprit vessels with a subsequent coronary event. Culprit vessels had percent diameter stenosis [%DS] (0.54 ± 0.16 vs. 0.62 ± 0.13, P = 0.003), larger non-calcified plaque volume (45.8 vs. 101.7, P < 0.001), larger low-attenuation plaque volume (3.6 vs. 14.5, P < 0.001), more lesions with ≥ 3 adverse plaque characteristics (APC) (4 vs.26, P = 0.002), and worse hemodynamic features of adverse plaque. FFRCT demonstrated better visualization of maximum achievable flow in the presence of coronary stenosis and better correlation with the stenosis severity, while maximum of wall shear stress (WSSmax) was highly correlated with low-attenuation plaques and APC. The inclusion of hemodynamic parameters improved the efficacy of the predictive model, and a high WSS suggested a higher probability of MACE. Hemodynamic parameters based on CCTA are significantly correlated with plaque morphology. Importantly, integrating CCTA-derived parameters can refine the predictive performance of MACE occurrence.

Diagnostic performance of the quantitative flow ratio and CT-FFR for coronary lesion-specific ischemia

Fractional flow reserve (FFR) has become the gold standard for evaluating coronary lesion-specific ischemia. However, FFR is an invasive method that may cause possible complications in the coronary artery and requires expensive equipment, which limits its use. Promising noninvasive diagnostic methods, such as computed tomography angiography-derived FFR (CT-FFR) and the quantitative flow ratio (QFR), have been proposed. In this study, we evaluated the diagnostic performance of the QFR and CT-FFR in predicting coronary lesion-specific ischemia, with the FFR serving as the reference standard. Patients with suspected or known coronary artery disease who underwent coronary CT angiography revealing 30-90% diameter stenosis in the main coronary artery (≥ 2.0 mm reference diameter) were enrolled. The FFR was measured during invasive coronary angiography (within 15 days after coronary CT angiography). An FFR ≤ 0.8 was the reference standard for coronary lesion-specific ischemia. A total of 103 vessels from 92 consecutive patients (aged 59.8 ± 9.2 years; 60.9% were men) were evaluated. The diagnostic performance of a QFR ≤ 0.80 for predicting coronary lesion-specific ischemia demonstrated good diagnostic accuracy, sensitivity, and specificity (92.2%, 87.2%, and 96.4%, respectively), with an area under the receiver operating characteristic curve (AUC) of 0.987 (P < 0.0001). The diagnostic performance of a CT-FFR ≤ 0.80 for predicting coronary lesion-specific ischemia also demonstrated good diagnostic accuracy, sensitivity, and specificity (96.1%, 95.7%, and 96.4%, respectively), with an AUC of 0.967 (P < 0.0001). However, there was no significant difference in the AUC between a QFR ≤ 0.80 and a CT-FFR ≤ 0.80 for predicting coronary lesion-specific ischemia (P = 0.319). There was an excellent correlation between the QFR and FFR (r = 0.856, P < 0.0001). The CT-FFR and FFR also showed a good direct correlation (r = 0.816, P < 0.0001). The QFR and CT-FFR are strongly correlated with the FFR and can provide excellent clinical diagnostic performance for coronary lesion-specific ischemia detection.

Chinese herbal compound preparation Qing-Xin-Jie-Yu granules for intermediate coronary lesions in patients with stable coronary artery disease: Study protocol for a multicenter, randomized, double-blind, placebo-controlled trial

INTRODUCTION

Despite the available secondary preventive treatments, the management of stable coronary artery disease (SCAD) remains challenging. Intermediate coronary lesion (ICL), defined as luminal stenosis between 50% and 70%, is a key stage of SCAD. However, existing therapeutic strategies are limitated in delaying plaque progression and associated with various adverse effects and economic burdens. Qing-Xin-Jie-Yu Granules (QXJYG) with proven anti-platelet, anti-inflammatory, and lipid-lowering effects may compensate for the drawbacks of current treatments and can be tested as a complementary therapy. Therefore, this study aims to investigate the efficacy and safety of QXJYG in treating ICL, with a particular focus on its impact on myocardial ischemia and plaque progression.

MATERIALS AND METHODS

This is a multicenter, randomized, double-blind, placebo-controlled trial. A total of 120 participants with ICL will be randomly assigned to two groups in a 1:1 ratio. In addition to basic medications, the intervention group will receive QXJYG, while the control group will receive a placebo for over 6 months, followed by a 12-month follow-up. The primary efficacy outcome is computed tomography-derived fractional flow reserve. The secondary outcomes include the degree of coronary stenosis, coronary artery calcification score, Gensini score, Seattle Angina Questionnaire score, high-sensitivity C-reactive protein, matrix metalloproteinase-9, blood lipids, and carotid artery ultrasound parameters. Major adverse cardiovascular events are recorded as endpoints. The safety outcomes include composite events of bleeding, laboratory test results, and adverse events. Clinical visits are scheduled at baseline, every 2 months during the treatment, and after a 12-month follow-up.

DISCUSSION

This trial is anticipated to yield reliable results to verify the efficacy and safety of QXJYG in the treatment of ICL, which will provide novel insights to help address the prevailing therapeutic dilemma of ICL, thereby facilitating for the management of SCAD.

TRIAL REGISTRATION

Chinese Clinical Trial Registry, ChiCTR2200059262. Registered on April 27, 2022.

CT-FFR by expanding coronary tree with Newton-Krylov-Schwarz method to solve the governing equations of CFD

Aims

A new model of computational fluid dynamics (CFD)-based algorithm for coronary CT angiography (CCTA)-derived fractional flow reserve (FFR) (CT-FFR) analysis by expanding the coronary tree to smaller-diameter lumen (0.8 mm) using Newton-Krylov-Schwarz (NKS) method to solve the three-dimensional time-dependent incompressible Navier-Stokes equations has been developed; however, the diagnostic performance of this new method has not been sufficiently investigated. The aim of this study was to determine the diagnostic performance of a novel CT-FFR technique by expanding the coronary tree in the CFD domain.

Methods and results

Six centres enrolled 338 symptomatic patients with suspected or known coronary artery disease (CAD) who prospectively underwent CCTA and FFR. Stenosis assessment in CCTA and CT-FFR analysis were performed in independent core laboratories. Haemodynamically significant stenosis was defined by a CT-FFR and FFR ≤ 0.80, and anatomically obstructive CAD was defined as a CCTA with stenosis ≥ 50%. Diagnostic performance of CT-FFR was evaluated against invasive FFR using receiver operating characteristic (ROC) curve analysis. The correlation between CT-FFR and invasive FFR was analysed using the Spearman correlation coefficient and Bland-Altman analysis. Intra-observer and inter-observer agreements were evaluated utilizing the intraclass correlation coefficient (ICC). In this study, 338 patients with 422 targeted vessels were investigated, revealing haemodynamically significant stenosis in 31.1% (105/338) of patients and anatomically obstructive stenosis in 54.1% of patients. On a per-vessel basis, the area under the ROC curve for CT-FFR was 0.94 vs. 0.76 for CCTA (P < 0.001). Per-vessel accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 89.8%, 89.3%, 90.0%, 79.0%, and 99.2%, respectively, for CT-FFR and were 68.4%, 82.8%, 62.3%, 48.1%, and 89.6%, respectively, for CCTA stenosis. CT-FFR and FFR were well correlated (r = 0.775, P < 0.001) with a Bland-Altman bias of 0.0011, and limits of agreement from -0.1509 to 0.1531 (P = 0.770). The ICCs with CT-FFR for intro- and inter-observer agreements were 0.919 (95% CI: 0.866-0.952) and 0.909 (95% CI: 0.851-0.945), respectively. The average computation time for CT-FFR analysis was maintained at 11.7 min.

Conclusion

This novel CT-FFR model with the inclusion of smaller lumen provides high diagnostic accuracy in detecting haemodynamically significant CAD. Furthermore, the integration of the NKS method ensures that the computation time remains within an acceptable range for potential clinical applications in the future.

Cardiac CT: Competition, complimentary or confounder

Coronary CT angiography (CCTA) has been gradually adopted into clinical practice over the last two decades. CCTA has high diagnostic accuracy, prognostic value, and unique features such as assessment of plaque composition. CCTA-derived functional assessment techniques such as fractional flow reserve and CT perfusion are also available and can increase the diagnostic specificity of the modality. These properties propound CCTA as a competitor of functional testing in diagnosis of obstructive CAD, however, utilizing CCTA in a concomitant fashion to potentiate the performance of the latter can lead to better patient care and may provide more accurate prognostic information. Although multiple diagnostic challenges such as evaluation of calcified segments, stents, and small distal vessels still exist, the technologic developments in hardware as well as growing incorporation of artificial intelligence to daily practice are all set to augment the diagnostic and prognostic role of CCTA in cardiovascular disorders.

Coronary computed tomography angiography for clinical practice

Coronary artery disease (CAD) is a common condition caused by the accumulation of atherosclerotic plaques. It can be classified into stable CAD or acute coronary syndrome. Coronary computed tomography angiography (CCTA) has a high negative predictive value and is used as the first examination for diagnosing stable CAD, particularly in patients at intermediate-to-high risk. CCTA is also adopted for diagnosing acute coronary syndrome, particularly in patients at low-to-intermediate risk. Myocardial ischemia does not always co-exist with coronary artery stenosis, and the positive predictive value of CCTA for myocardial ischemia is limited. However, CCTA has overcome this limitation with recent technological advancements such as CT perfusion and CT-fractional flow reserve. In addition, CCTA can be used to assess coronary artery plaques. Thus, the indications for CCTA have expanded, leading to an increased demand for radiologists. The CAD reporting and data system (CAD-RADS) 2.0 was recently proposed for standardizing CCTA reporting. This RADS evaluates and categorizes patients based on coronary artery stenosis and the overall amount of coronary artery plaque and links this to patient management. In this review, we aimed to review the major trials and guidelines for CCTA to understand its clinical role. Furthermore, we aimed to introduce the CAD-RADS 2.0 including the assessment of coronary artery stenosis, plaque, and other key findings, and highlight the steps for CCTA reporting. Finally, we aimed to present recent research trends including the perivascular fat attenuation index, artificial intelligence, and the advancements in CT technology.

Agreement of Fractional Flow Reserve Estimated by Computed Tomography With Invasively Measured Fractional Flow Reserve: A Systematic Review and Meta-Analysis

BACKGROUND

Fractional flow reserve (FFR) is the ratio of blood pressure measured distal to a stenosis and pressure proximal to a stenosis. FFR can be estimated noninvasively using computed tomography (CT) although the usefulness of this technique remains controversial. This meta-analysis evaluated the agreement of FFR estimated by CT (FFR-CT) with invasively measured FFR. The study also evaluated the diagnostic accuracy of FFR-CT, defined as the ability of FFR-CT to classify lesions as hemodynamically significant (invasive FFR ≤0.8) or insignificant (invasive FFR >0.8).

METHODS AND RESULTS

Forty-three studies reporting on 7291 blood vessels from 5236 patients were included. A moderate positive linear relationship between FFR-CT and invasively measured FFR was observed (Spearman correlation coefficient: 0.67). Agreement between the 2 measures increased as invasively measured FFR values approached 1. The overall diagnostic accuracy, sensitivity and specificity of FFR-CT were 82.2%, 80.9%, and 83.1%, respectively. Diagnostic accuracy of 90% could be demonstrated for FFR-CT values >0.90 and <0.49. The diagnostic accuracy of off-site tools was 79.4% and the diagnostic accuracy of on-site tools was 84.1%.

CONCLUSIONS

The agreement between FFR-CT and invasive FFR is moderate although agreement is highest in vessels with FFR-CT >0.9. Diagnostic accuracy varies widely with FFR-CT value but is above 90% for FFR-CT values >0.90 and <0.49. Furthermore, on-site and off-site tools have similar performance. Ultimately, FFR-CT may be a useful adjunct to CT coronary angiography as a gatekeeper for invasive coronary angiogram.

Virtual Hemodynamic Assessment of Coronary Lesions: The Advent of Functional Angiography and Coronary Imaging

The fractional flow reserve (FFR) is well recognized as a gold standard measure for the estimation of functional coronary stenosis. Technological progressions in image processing have empowered the reconstruction of three-dimensional models of the coronary arteries via both non-invasive and invasive imaging modalities. The application of computational fluid dynamics (CFD) techniques to coronary 3D anatomical models allows the virtual evaluation of the hemodynamic significance of a coronary lesion with high diagnostic accuracy.

METHODS

Search of the bibliographic database for articles published from 2011 to 2023 using the following search terms: invasive FFR and non-invasive FFR. Pooled analysis of the sensitivity and specificity, with the corresponding confidence intervals from 32% to 94%. In addition, the summary processing times were determined.

RESULTS

In total, 24 studies published between 2011 and 2023 were included, with a total of 13,591 patients and 3345 vessels. The diagnostic accuracy of the invasive and non-invasive techniques at the per-patient level was 89% (95% CI, 85-92%) and 76% (95% CI, 61-80%), respectively, while on the per-vessel basis, it was 92% (95% CI, 82-88%) and 81% (95% CI, 75-87%), respectively.

CONCLUSION

These opportunities providing hemodynamic information based on anatomy have given rise to a new era of functional angiography and coronary imaging. However, further validations are needed to overcome several scientific and computational challenges before these methods are applied in everyday clinical practice.

On-site CT-derived cFFR in patients with suspected coronary artery disease: Feasibility on a 128-row CT scanner in everyday clinical practice

PURPOSE

Technical feasibility of CT-based calculation of fractional flow reserve (cFFR) using a 128-row computed tomography scanner in an everyday routine setting. Post-processing and everyday practicability should be analyzed on the scanner on-site in connection with clinical parameters.

MATERIALS AND METHODS

This single-center retrospective analysis included 230 patients (74 female; mean age 63.8 years) with CCTA within 21 months between 01/2018 and 09/2019 without non-pathological examinations. cFFR values were obtained using a deep learning-based non-commercial research prototype (cFFR Version3.5.0; Siemens Healthineers GmbH, Erlangen). cFFR values were evaluated at two points: at the maximum point of the stenosis and 1.0 cm distal to the stenosis. Comparison with invasive coronary angiography in 57/230 patients (24.7 %) was performed. CT parameters and quality were evaluated. Further subgroup classification concerning criteria of technical postprocessing was performed: no changes necessary, minor corrections necessary, major corrections necessary, and no evaluation was possible. The required time from starting the software to the final result was evaluated.

RESULTS

A total of 116/448 (25.9 %) mild, 223/448 (49.8 %) moderate, and 109/448 (24.3 %) obstructive stenoses was found. The mean cFFR at the maximum point of the stenosis was 0.92 ± 0.09 and significantly higher than the cFRR value of 0.89 ± 0.13 distal to the stenosis (p < 0.001*). The mean degree of stenosis was 44.02 ± 26.99 % (range: 1-99 %) with an area of 5.39 ± 3.30 mm2. In a total of 45 patients (19.1 %), a relevant reduction in cFFR below 0.80 was determined. Overall, in 57/230 patients (24.8 %), catheter angiography was performed. No significant difference in the degree of maximal stenosis (CAD-RADS 0-2/3/4) was detected between the classification of CCTA and ICA (p = 0.171). The mean post-processing time varied significantly with 8.34 ± 4.66 min. in single-vessel CAD vs. 12.91 ± 3.92 min. in two-vessel CAD vs. 21.80 ± 5.94 min. in three-vessel CAD (each p < 0.001).

CONCLUSION

Noninvasive onsite quantification of cFFR is feasible with minimal observer interaction in a routine real-world setting on a 128-row scanner. Deep learning-based algorithms allow a robust and semi-automatic on-site determination of cFFR based on data from standard CT scanners.

KEY POINTS

· Non-invasive on-site quantification of cFFR is feasible with minimal observer interaction.. · Deep-learning based algorithms allow robust and semi-automatic on-site determination of cFFR.. · The mean follow-up time varied significantly with the extent of vascular CAD..

Hybrid model of CT-fractional flow reserve, pericoronary fat attenuation index and radiomics for predicting the progression of WMH: a dual-center pilot study

Objective

To develop and validate a hybrid model incorporating CT-fractional flow reserve (CT-FFR), pericoronary fat attenuation index (pFAI), and radiomics signatures for predicting progression of white matter hyperintensity (WMH).

Methods

A total of 226 patients who received coronary computer tomography angiography (CCTA) and brain magnetic resonance imaging from two hospitals were divided into a training set (n = 116), an internal validation set (n = 30), and an external validation set (n = 80). Patients who experienced progression of WMH were identified from subsequent MRI results. We calculated CT-FFR and pFAI from CCTA images using semi-automated software, and segmented the pericoronary adipose tissue (PCAT) and myocardial ROI. A total of 1,073 features were extracted from each ROI, and were then refined by Elastic Net Regression. Firstly, different machine learning algorithms (Logistic Regression [LR], Support Vector Machine [SVM], Random Forest [RF], k-nearest neighbor [KNN] and eXtreme Gradient Gradient Boosting Machine [XGBoost]) were used to evaluate the effectiveness of radiomics signatures for predicting WMH progression. Then, the optimal machine learning algorithm was used to compare the predictive performance of individual and hybrid models based on independent risk factors of WMH progression. Receiver operating characteristic (ROC) curve analysis, calibration and decision curve analysis were used to evaluate predictive performance and clinical value of the different models.

Results

CT-FFR, pFAI, and radiomics signatures were independent predictors of WMH progression. Based on the machine learning algorithms, the PCAT signatures led to slightly better predictions than the myocardial signatures and showed the highest AUC value in the XGBoost algorithm for predicting WMH progression (AUC: 0.731 [95% CI: 0.603-0.838] vs.0.711 [95% CI: 0.584-0.822]). In addition, pFAI provided better predictions than CT-FFR (AUC: 0.762 [95% CI: 0.651-0.863] vs. 0.682 [95% CI: 0.547-0.799]). A hybrid model that combined CT-FFR, pFAI, and two radiomics signatures provided the best predictions of WMH progression [AUC: 0.893 (95%CI: 0.815-0.956)].

Conclusion

pFAI was more effective than CT-FFR, and PCAT signatures were more effective than myocardial signatures in predicting WMH progression. A hybrid model that combines pFAI, CT-FFR, and two radiomics signatures has potential use for identifying WMH progression.

Value of CT‑derived fractional flow reserve in identifying patients with acute myocardial infarction based on coronary computed tomography angiography

The aim of the present study was to determine whether coronary stenosis and computed tomography-derived fractional flow reserve (CT-FFR), detected by coronary computed tomography angiography (CCTA), can potentially contribute to distinguish acute myocardial infarction (AMI) from unstable angina (UA). The study retrospectively collected data from consecutive patients who were admitted with obstructive coronary artery disease (CAD) and who received CCTA and invasive coronary angiography (ICA) as part of their clinical workup. According to the inclusion criteria, the patients were divided into the AMI group and UA group, and the basic clinical data, CCTA stenosis degree and CT-FFR values were compared between the two groups. Univariate and multivariate logistic regression methods were used to analyze the association between ≥70% CCTA stenosis, ≤0.80 CT-FFR and AMI. A diagnostic model of AMI was established (model 1, ≤0.80 CT-FFR; model 2, ≥70% CCTA stenosis; and model 3, ≤0.80 CT-FFR combined with ≥70% CCTA stenosis), and the diagnostic efficacy of the three models for AMI was compared. The significance level was set at P<0.05. A total of 116 participants were finally enrolled in this study. There were 37 patients in the AMI group, with an average age of 62.06±7.74 years, and 79 patients in the UA group, with an average age of 58.11±10.0 years; there was no significant difference in age (P>0.05). The multivariate regression analysis revealed that ≤0.80 CT-FFR (HR=28.074; 95% CI: 5.712-137.973; P<0.001), and ≥70% CCTA stenosis (HR=10.796; 95% CI: 2.566-45.425; P=0.001) were independent risk factors for AMI. The diagnostic model of ≤0.80 CT-FFR combined with ≥70% CCTA stenosis (AUC=0.914; 95% CI: 0.847-0.958) exhibited increased diagnosis performance than the ≤0.80 CT-FFR model (AUC=0.865; 95% CI: 0.790-0.922; P=0.0060) and the ≥70% CCTA stenosis model (AUC=0.827; 95% CI: 0.745-0.891; P=0.0008). Collectively, it was demonstrated that ≤0.80 CT-FFR and ≥70% CCTA stenosis were independent risk factors for the diagnosis of AMI, and the combination of CT-FFR and CCTA stenosis further improved AMI diagnosis performance.

Energy loss is related to CT fractional flow reserve progression in type 2 diabetes mellitus patients

Background

We aimed to investigate the diagnostic value of energy loss (EL) and baseline CT fractional flow reserve (CT-FFR) computed using computational fluid dynamics to predict functional progression of coronary stenosis in patients with type 2 diabetes mellitus.

Methods

This single-center prospective study included 61 patients with type 2 diabetes mellitus (mean age, 61 years ±9 [SD]; 43 men) showing 20-70 % stenosis who underwent serial coronary CT performed at 2-year interval between October 2015 and March 2020. A mesh-free simulation was performed to calculate the CT-FFR and EL. Functional progression was defined as ≥ 0.05 decrease in CT-FFR on the second coronary CT. Models using baseline CT-FFR and EL were compared by analyzing the receiver operating characteristic (ROC) curve.

Results

Of the 94 vessels evaluated, 25 vessels (27 %) showed functional progression. EL at distal stenosis (ELdis) of vessels with functional progression was higher than that of vessels without functional progression (27.6 W/m3 [interquartile range (IQR): 15.0, 53.0] vs. 5.7 W/m3 [IQR: 2.3, 10.1], p < 0.001). Multivariable analysis showed that ELdis (per unit Ln(EL); odds ratio, 11.8; 95 % CI: 4.0-34.9; p < 0.001) remained as a predictor of functional progression after adjustment for diameter stenosis and baseline CT-FFR. The area under the ROC curve using ELdis (0.89; 95 % CI: 0.82-0.96) was higher than that using baseline CT-FFR (0.71; 95 % CI: 0.59-0.83; p < 0.001).

Conclusion

When ELdis and baseline CT-FFR were considered, ELdis was a better predictor of functional progression of coronary stenosis.

Coronary computed tomography angiography imaging features combined with computed tomography-fractional flow reserve, pericoronary fat attenuation index, and radiomics for the prediction of myocardial ischemia

BACKGROUND

This study aimed to predict myocardial ischemia (MIS) by constructing models with imaging features, CT-fractional flow reserve (CT-FFR), pericoronary fat attenuation index (pFAI), and radiomics based on coronary computed tomography angiography (CCTA).

METHODS AND RESULTS

This study included 96 patients who underwent CCTA and single photon emission computed tomography-myocardial perfusion imaging (SPECT-MPI). According to SPECT-MPI results, there were 72 vessels with MIS in corresponding supply area and 105 vessels with no-MIS. The conventional model [lesion length (LL), MDS (maximum stenosis diameter × 100% / reference vessel diameter), MAS (maximum stenosis area × 100% / reference vessel area) and CT value], radiomics model (radiomics features), and multi-faceted model (all features) were constructed using support vector machine. Conventional and radiomics models showed similar predictive efficacy [AUC: 0.76, CI 0.62-0.90 vs. 0.74, CI 0.61-0.88; p > 0.05]. Adding pFAI to the conventional model showed better predictive efficacy than adding CT-FFR (AUC: 0.88, CI 0.79-0.97 vs. 0.80, CI 0.68-0.92; p < 0.05). Compared with conventional and radiomics model, the multi-faceted model showed the highest predictive efficacy (AUC: 0.92, CI 0.82-0.98, p < 0.05).

CONCLUSION

pFAI is more effective for predicting MIS than CT-FFR. A multi-faceted model combining imaging features, CT-FFR, pFAI, and radiomics is a potential diagnostic tool for MIS.

Physics-informed neural networks (PINNs) for 4D hemodynamics prediction: An investigation of optimal framework based on vascular morphology

Hemodynamic parameters are of great significance in the clinical diagnosis and treatment of cardiovascular diseases. However, noninvasive, real-time and accurate acquisition of hemodynamics remains a challenge for current invasive detection and simulation algorithms. Here, we integrate computational fluid dynamics with our customized analysis framework based on a multi-attribute point cloud dataset and physics-informed neural networks (PINNs)-aided deep learning modules. This combination is implemented by our workflow that generates flow field datasets within two types of patient personalized models - aorta with fine coronary branches and abdominal aorta. Deep learning modules with or without an antecedent hierarchical structure model the flow field development and complete the mapping from spatial and temporal dimensions to 4D hemodynamics. 88,000 cases on 4 randomized partitions in 16 controlled trials reveal the hemodynamic landscape of spatio-temporal anisotropy within two types of personalized models, which demonstrates the effectiveness of PINN in predicting the space-time behavior of flow fields and gives the optimal deep learning framework for different blood vessels in terms of balancing the training cost and accuracy dimensions. The proposed framework shows intentional performance in computational cost, accuracy and visualization compared to currently prevalent methods, and has the potential for generalization to model flow fields and corresponding clinical metrics within vessels at different locations. We expect our framework to push the 4D hemodynamic predictions to the real-time level, and in statistically significant fashion, applicable to morphologically variable vessels.

Accuracy of intravascular ultrasound-derived virtual fractional flow reserve (FFR) and FFR derived from computed tomography for functional assessment of coronary artery disease

BACKGROUND

Coronary computed tomography-derived fractional flow reserve (CT-FFR) and intravascular ultrasound-derived fractional flow reserve (IVUS-FFR) are two functional assessment methods for coronary stenoses. However, the calculation algorithms for these methods differ significantly. This study aimed to compare the diagnostic performance of CT-FFR and IVUS-FFR using invasive fractional flow reserve (FFR) as the reference standard.

METHODS

Six hundred and seventy patients (698 lesions) with known or suspected coronary artery disease were screened for this retrospective analysis between January 2020 and July 2021. A total of 40 patients (41 lesions) underwent intravascular ultrasound (IVUS) and FFR evaluations within six months after completing coronary CT angiography were included. Two novel CFD-based models (AccuFFRct and AccuFFRivus) were used to compute the CT-FFR and IVUS-FFR values, respectively. The invasive FFR ≤ 0.80 was used as the reference standard for evaluating the diagnostic performance of CT-FFR and IVUS-FFR.

RESULTS

Both AccuFFRivus and AccuFFRct demonstrated a strong correlation with invasive FFR (R = 0.7913, P < 0.0001; and R = 0.6296, P < 0.0001), and both methods showed good agreement with FFR. The area under the receiver operating characteristic curve was 0.960 (P < 0.001) for AccuFFRivus and 0.897 (P < 0.001) for AccuFFRct in predicting FFR ≤ 0.80. FFR ≤ 0.80 were predicted with high sensitivity (96.6%), specificity (85.7%), and the Youden index (0.823) using the same cutoff value of 0.80 for AccuFFRivus. A good diagnostic performance (sensitivity 89.7%, specificity 85.7%, and Youden index 0.754) was also demonstrated by AccuFFRct.

CONCLUSIONS

AccuFFRivus, computed from IVUS images, exhibited a high diagnostic performance for detecting myocardial ischemia. It demonstrated better diagnostic power than AccuFFRct, and could serve as an accurate computational tool for ischemia diagnosis and assist in clinical decision-making.

Non-Contrast and Contrast-Enhanced Cardiac Computed Tomography Imaging in the Diagnostic and Prognostic Evaluation of Coronary Artery Disease

In recent decades, cardiac computed tomography (CT) has emerged as a powerful non-invasive tool for risk stratification, as well as the detection and characterization of coronary artery disease (CAD), which remains the main cause of morbidity and mortality in the world. Advances in technology have favored the increasing use of cardiac CT by allowing better performance with lower radiation doses. Coronary artery calcium, as assessed by non-contrast CT, is considered to be the best marker of subclinical atherosclerosis, and its use is recommended for the refinement of risk assessment in low-to-intermediate risk individuals. In addition, coronary CT angiography (CCTA) has become a gate-keeper to invasive coronary angiography (ICA) and revascularization in patients with acute chest pain by allowing the assessment not only of the extent of lumen stenosis, but also of its hemodynamic significance if combined with the measurement of fractional flow reserve or perfusion imaging. Moreover, CCTA provides a unique incremental value over functional testing and ICA by imaging the vessel wall, thus allowing the assessment of plaque burden, composition, and instability features, in addition to perivascular adipose tissue attenuation, which is a marker of vascular inflammation. There exists the potential to identify the non-obstructive lesions at high risk of progression to plaque rupture by combining all of these measures.

Role of Quantitative Plaque Analysis and Fractional Flow Reserve Derived From Coronary Computed Tomography Angiography to Assess Plaque Progression

PURPOSE

To explore the role of quantitative plaque analysis and fractional flow reserve (CT-FFR) derived from coronary computed angiography (CCTA) in evaluating plaque progression (PP).

METHODS

A total of 248 consecutive patients who underwent serial CCTA examinations were enrolled. All patients' images were analyzed quantitatively by plaque analysis software. The quantitative analysis indexes included diameter stenosis (%DS), plaque length, plaque volume (PV), calcified PV, noncalcified PV, minimum lumen area (MLA), and remodeling index (RI). PP is defined as PAV (percentage atheroma volume) change rate >1%. CT-FFR analysis was performed using the cFFR software.

RESULTS

A total of 76 patients (30.6%) and 172 patients (69.4%) were included in the PP group and non-PP group, respectively. Compared with the non-PP group, the PP group showed greater %DS, smaller MLA, larger PV and non-calcified PV, larger RI, and lower CT-FFR on baseline CCTA (all P <0.05). Logistic regression analysis showed that RI≥1.10 (odds ratio [OR]: 2.709, 95% CI: 1.447-5.072), and CT-FFR≤0.85 (OR: 5.079, 95% CI: 2.626-9.283) were independent predictors of PP. The model based on %DS, quantitative plaque features, and CT-FFR (area under the receiver-operating characteristics curve [AUC]=0.80, P <0.001) was significantly better than that based rarely on %DS (AUC=0.61, P =0.007) and that based on %DS and quantitative plaque characteristics (AUC=0.72, P <0.001).

CONCLUSIONS

Quantitative plaque analysis and CT-FFR are helpful to identify PP. RI and CT-FFR are important predictors of PP. Compared with the prediction model only depending on %DS, plaque quantitative markers and CT-FFR can further improve the predictive performance of PP.

Optimal Measurement Sites of Coronary-Computed Tomography Angiography-derived Fractional Flow Reserve: The Insight From China CT-FFR Study

OBJECTIVES

To investigate the optimal measurement site of coronary-computed tomography angiography-derived fractional flow reserve (FFR CT ) for the assessment of coronary artery disease (CAD) in the whole clinical routine practice.

MATERIALS AND METHODS

This retrospective multicenter study included 396 CAD patients who underwent coronary-computed tomography angiography, FFR CT , and invasive FFR. FFR CT was measured at 1 cm (FFR CT -1 cm), 2 cm (FFR CT -2 cm), 3 cm (FFR CT -3 cm), and 4 cm (FFR CT -4 cm) distal to coronary stenosis, respectively. FFR CT and invasive FFR ≤0.80 were defined as lesion-specific ischemia. The diagnostic performance of FFR CT to detect ischemia was obtained using invasive FFR as the reference standard. Reduced invasive coronary angiography rate and revascularization efficiency were calculated. After a median follow-up of 35 months in 267 patients for major adverse cardiovascular events (MACE), Cox hazard proportional models were performed with FFR CT values at each measurement site.

RESULTS

For discriminating lesion-specific ischemia, the areas under the curve of FFR CT -1 cm (0.91) as well as FFR CT -2 cm (0.91) were higher than those of FFR CT -3 cm (0.89) and FFR CT -4 cm (0.88), respectively (all P <0.05). The higher reduced invasive coronary angiography rate (81.6%) was found at FFR CT -1 cm than FFR CT -2 cm (81.6% vs. 62.6%, P <0.05). Revascularization efficiency did not differ between FFR CT -1 cm and FFR CT -2 cm (80.8% vs. 65.5%, P =0.019). In 12.4% (33/267) MACE occurred and only values of FFR CT -2 cm were independently predictive of MACE (hazard ratio: 0.957 [95% CI: 0.925-0.989]; P =0.010).

CONCLUSIONS

This study indicates FFR CT -2 cm is the optimal measurement site with superior diagnostic performance and independent prognostic role.

Impact of coronary computed tomography angiography-derived fractional flow reserve based on deep learning on clinical management

Background

To examine the value of coronary computed tomography angiography (CCTA)-derived fractional flow reserve based on deep learning (DL-FFRCT) on clinical practice and analyze the limitations of the application of DL-FFRCT.

Methods

This is an observational, retrospective, single-center study. Patients with suspected coronary artery disease (CAD) were enrolled. The patients underwent invasive coronary angiography (ICA) examination within 1 months after CCTA examination. And quantitative coronary angiography (QCA) was performed to evaluate the area stenosis rate. The CCTA data of these patients were retrospectively analyzed to calculate the FFRCT value.

Results

A total of 485 lesions of coronary arteries in 229 patients were included in the analysis. Of the lesions, 275 (56.7%) were ICA-positive, and 210 (43.3%) were FFRCT-positive. The discordance rate of the risk stratification of FFRCT for ICA-positive lesions was 33.1% (91) and that for ICA-negative lesions was 12.4% (26). 14.6% (7/48) patients with mild to moderate coronary stenosis in ICA have functional ischemia according to FFRCT positive indications. In addition, hemodynamic analysis of severely calcified, occluded, or small (< 2 mm in diameter) coronary arteries by DL-FFRCT is not so reliable.

Conclusion

This study revealed that most patients with ICA negative did not require further invasive FFR. Besides, some patients with mild to moderate coronary stenosis in ICA may also have functional ischemia. However, for severely calcified, occluded, or small coronary arteries, treatment strategy should be selected based on ICA in combination with clinical practice.

The Cost Effectiveness of Coronary CT Angiography and the Effective Utilization of CT-Fractional Flow Reserve in the Diagnosis of Coronary Artery Disease

Given the high global disease burden of coronary artery disease (CAD), a major problem facing healthcare economic policy is identifying the most cost-effective diagnostic strategy for patients with suspected CAD. The aim of this review is to assess the long-term cost-effectiveness of coronary computed tomography angiography (CCTA) when compared with other diagnostic modalities and to define the cost and effective diagnostic utilization of computed tomography-fractional flow reserve (CT-FFR). A search was conducted through the MEDLINE database using PubMed with 16 of 119 manuscripts fitting the inclusion and exclusion criteria for review. An analysis of the data included in this review suggests that CCTA is a cost-effective strategy for both low risk acute chest pain patients presenting to the emergency department (ED) and low-to-intermediate risk stable chest pain outpatients. For patients with intermediate-to-high risk, CT-FFR is superior to CCTA in identifying clinically significant stenosis. In low-to-intermediate risk patients, CCTA provides a cost-effective diagnostic strategy with the potential to reduce economic burden and improve long-term health outcomes. CT-FFR should be utilized in intermediate-to-high risk patients with stenosis of uncertain clinical significance. Long-term analysis of cost-effectiveness and diagnostic utility is needed to determine the optimal balance between the cost-effectiveness and diagnostic utility of CT-FFR.

Assessment of the Efficiency of Non-Invasive Diagnostic Imaging Modalities for Detecting Myocardial Ischemia in Patients Suspected of Having Stable Angina

This study aimed to assess and compare the efficiency of non-invasive imaging modalities in detecting myocardial ischemia in patients with suspected stable angina as easy-to-understand indices. Our study included 1000 patients with chest pain and possible stable myocardial ischemia. The modalities to be assessed were cardiac magnetic resonance imaging (CMRI), single-photon emission computed tomography, positron emission computed tomography (PET), stress echocardiography, and fractional flow reserve derived from coronary computed tomography angiography (FFRCT). As a simulation study, we assumed that all five imaging modalities were performed on these patients, and a decision tree analysis was conducted. From the results, the following efficiencies were assessed and compared: (1) number of true positive (TP), false positive (FP), false negative (FN), and true negative (TN) test results; (2) positive predictive value (PPV); (3) negative predictive value (NPV); (4) post-test probability; (5) diagnostic accuracy (DA); and (6) number needed to diagnose (NND). In the basic settings (pre-test probability: 30%), PET generated the highest TP (267) and NPV (95%, 95% confidence interval (CI): 93-96%). In contrast, CMRI produced the highest TN (616), PPV (76%, 95% CI: 71-80%), and DA (88%, 95% CI: 86-90%) and the lowest NND (1.33, 95% CI: 1.24-1.47). Although FFRCT generated the highest TP (267) and lowest FN (33), it generated the highest FP (168). In terms of detecting myocardial ischemia, compared with the other modalities, PET and CMRI were more efficient. The results of our study might be helpful for both patients and medical professionals associated with their examination.

Imaging subclinical coronary atherosclerosis to guide lipid management, are we there yet?

Atherosclerotic cardiovascular disease risk (ASCVD) is an ongoing epidemic, and lipid abnormalities are its primordial cause. Most individuals suffering a first ASCVD event are previously asymptomatic and often do not receive preventative therapies. The cornerstone of primary prevention has been the identification of individuals at risk through risk calculators based on clinical and laboratory traditional risk factors plus risk enhancers. However, it is well accepted that a clinical risk calculator misclassifies a significant proportion of individuals leading to the prescription of a lipid-lowering medication with very little yield or a missed opportunity for lipid-lowering agents with a potentially preventable event. The development of coronary artery calcium scoring (CAC) and CT coronary angiography (CCTA) provide complementary tools to directly visualize coronary plaque and other risk-modifying imaging components that can potentially provide individualized lipid management. Understanding patient selection for CAC or potentially CCTA and the risk implications of the different parameters provided, such as CAC score, coronary stenosis, plaque characteristics and burden, epicardial adipose tissue, and pericoronary adipose tissue, have grown more complex as technologies evolve. These parameters directly affect the shared decision with patients to start or withhold lipid-lowering therapies, to adjust statin intensity or LDL cholesterol goals. Emerging lipid lowering studies with non-invasive imaging as a guide to patient selection and treatment efficacy, plus the evolution of lipid lowering therapies from statins to a diverse armament of newer high-cost agents have pushed these two fields forward with a complex interaction. This review will discuss existing risk estimators, and non-invasive imaging techniques for subclinical coronary atherosclerosis, traditionally studied using CAC and more recently CCTA with qualitative and quantitative measurements. We will also explore the current data, gaps of knowledge and future directions on the use of these techniques in the risk-stratification and guidance of lipid management.

Coronary Computed Tomography Angiography-derived Fractional Flow Reserve: An Expert Consensus Document of Chinese Society of Radiology

Invasive fractional flow reserve (FFR) measured by a pressure wire is a reference standard for evaluating functional stenosis in coronary artery disease. Coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) uses advanced computational analysis methods to noninvasively obtain FFR results from a single conventional coronary computed tomography angiography data to evaluate the hemodynamic significance of coronary artery disease. More and more evidence has found good correlation between the results of noninvasive CT-FFR and invasive FFR. CT-FFR has proven its potential in optimizing patient management, improving risk stratification and prognosis, and reducing total health care costs. However, there is still a lack of standardized interpretation of CT-FFR technology in real-world clinical settings. This expert consensus introduces the principle, workflow, and interpretation of CT-FFR; summarizes the state-of-the-art application of CT-FFR; and provides suggestions and recommendations for the application of CT-FFR with the aim of promoting the standardized application of CT-FFR in clinical practice.

Computed tomography-derived fractional flow reserve (FFRCT) has no additional clinical impact over the anatomical Coronary Artery Disease - Reporting and Data System (CAD-RADS) in real-world elective healthcare of coronary artery disease

AIM

To evaluate the impact of computed tomography-derived fractional flow reserve (FFR_CT) compared to the anatomical Coronary Artery Disease - Reporting and Data System (CAD-RADS) in the elective assessment of coronary artery disease in real-world cardiology practise.

MATERIALS AND METHODS

A retrospective review was undertaken of 1,239 coronary CT examinations from August 2018 to December 2019 with a minimum follow-up period of 1 year. Coronary disease was classified according to the CAD-RADS system. A non-occlusive ≥30% maximum diameter stenosis was considered eligible for FFR_CT. Lesion-specific FFR_CT and FFR were considered positive if ≤ 0.80. The patients were followed up using the hospital radiology information system and the electronic patient record. A positive outcome was defined by a subsequent invasive angiogram (ICA) showing disease requiring revascularisation or FFR ≤0.80 or a positive stress test or medical therapy for angina in CAD-RADS 4.

RESULTS

Of the 1,145 analysable studies (mean follow up 618 ± 153 days) the incidence of a positive result was 7% with a 5.4% elective revascularisation rate. Two hundred and forty-five patients (CAD-RADS 2-4) had FFR_CT. FFR_CT reduced the accuracy of the CAD-RADS grade from 91% to 78.4% (p<0.001). In CAD-RADS 2, the accuracy is reduced from 99% to 90.7% (p=0.005), and in CAD-RADS 3 from 93.9% to 67.7% (p<0.001). In CAD-RADS 4, FFR_CT increases accuracy from 69.4% to 75.5% (p=0.025), but 89.8% of FFR_CT are positive and specificity is low (26.7%).

CONCLUSION

In the present "real-world" practise, FFR_CT does not improve standard radiological assessment of coronary disease graded by the CAD-RADS alone.

The Role of Cardiac Computed Tomography in Heart Failure

PURPOSE OF REVIEW

Cardiac computed tomography (CT) is becoming a more widely applied tool in the diagnosis and management of a variety of cardiovascular conditions, including heart failure. The aim of this narrative review is to examine the role of cardiac CT in patients with heart failure.

RECENT FINDINGS

Coronary computed tomographic angiography has robust diagnostic accuracy for ruling out coronary artery disease. These data are reflected in updated guidelines from major cardiology organizations. New roles for cardiac CT in myocardial imaging, perfusion scanning, and periprocedural planning, execution, and monitoring are being implemented. Cardiac CT is useful in ruling out coronary artery disease its diagnostic accuracy, accessibility, and safety. It is also intricately linked to invasive cardiac procedures that patients with heart failure routinely undergo.

ACR Appropriateness Criteria® Chronic Chest Pain-High Probability of Coronary Artery Disease: 2021 Update

Management of patients with chronic chest pain in the setting of high probability of coronary artery disease (CAD) relies heavily on imaging for determining or excluding presence and severity of myocardial ischemia, hibernation, scarring, and/or the presence, site, and severity of obstructive coronary lesions, as well as course of management and long-term prognosis. In patients with no known ischemic heart disease, imaging is valuable in determining and documenting the presence, extent, and severity of obstructive coronary narrowing and presence of myocardial ischemia. In patients with known ischemic heart disease, imaging findings are important in determining the management of patients with chronic myocardial ischemia and can serve as a decision-making tool for medical therapy, angioplasty, stenting, or surgery. This document summarizes the recent growing body of evidence on various imaging tests and makes recommendations for imaging based on the available data and expert opinion. This document is focused on epicardial CAD and does not discuss the microvascular disease as the cause for CAD. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Diagnostic accuracy of CT-derived and angiogram-derived fractional flow reserve

AIMS

Although accumulating evidence demonstrated that virtual fractional flow reserve (FFR) based on coronary computed tomography angiography (CCTA) (CT-FFR) or invasive coronary angiogram (ICA) (CA-FFR) are promising alternatives to wire based FFR, which method has better diagnostic accuracy was still unclear. In our study, we aim to directly compare the diagnostic performance of CT-FFR and CA-FFR.

METHODS

During the period of September 2019 to December 2020, patients with at least one 30%-90% coronary artery stenosis were enrolled and received invasive FFR. Then, virtual FFR values were calculated based on both CCTA and ICA, and then compared with the invasive FFR value.

RESULTS

Invasive FFR measurements were successfully performed in 114 vessels of 96 patients. Both CT-FFR and CA-FFR showed good correlation with wire-based FFR, with r values of 0.84 and 0.71 respectively. In paired t-test, the deviation of CT-FFR and CA-FFR was not significantly different (t = -1.9083, p = 0.05889). In Bland-Altman analysis, the coefficients of variation were 8.4% and 13.2% for CT-FFR and CA-FFR respectively. In ROC curve analysis, the per-vessel diagnostic accuracy of CT-FFR and CA-FFR was 94.7% and 92.1% respectively. The area under the curve of CT-FFR was slightly higher than that of CA-FFR (0.986 and 0.916 respectively, the difference between areas = 0.070, 95% CI 0.003-0.137, p = 0.0227).

CONCLUSION

Both CT-FFR and CA-FFR had good diagnostic concordance with wire-based FFR. In ROC Curve analysis, CT-FFR demonstrated slightly higher diagnostic accuracy than CA-FFR.

CLINICAL TRIAL REGISTRATION

URL: https://www.chictr.org.cn/showproj.aspx?proj=44719. Unique Identifier: ChiCTR1900026971.

Influence of diabetes mellitus on the diagnostic performance of machine learning-based coronary CT angiography-derived fractional flow reserve: a multicenter study

OBJECTIVES

To examine the diagnostic accuracy of machine learning-based coronary CT angiography-derived fractional flow reserve (FFR_CT) in diabetes mellitus (DM) patients.

METHODS

In total, 484 patients with suspected or known coronary artery disease from 11 Chinese medical centers were retrospectively analyzed. All patients underwent CCTA, FFR_CT, and invasive FFR. The patients were further grouped into mild (25~49 %), moderate (50~69 %), and severe (≥ 70 %) according to CCTA stenosis degree and Agatston score < 400 and Agatston score ≥ 400 groups according to coronary artery calcium severity. Propensity score matching (PSM) was used to match DM (n  = 112) and non-DM (n  = 214) groups. Sensitivity, specificity, accuracy, and area under the curve (AUC) with 95 % confidence interval (CI) were calculated and compared.

RESULTS

Sensitivity, specificity, accuracy, and AUC of FFR_CT were 0.79, 0.96, 0.87, and 0.91 in DM patients and 0.82, 0.93, 0.89, and 0.89 in non-DM patients without significant difference (all p > 0.05) on a per-patient level. The accuracies of FFR_CT had no significant difference among different coronary stenosis subgroups and between two coronary calcium subgroups (all p > 0.05) in the DM and non-DM groups. After PSM grouping, the accuracies of FFR_CT were 0.88 in the DM group and 0.87 in the non-DM group without a statistical difference (p > 0.05).

CONCLUSIONS

DM has no negative impact on the diagnostic accuracy of machine learning-based FFR_CT.

KEY POINTS

• ML-based FFR_CT has a high discriminative accuracy of hemodynamic ischemia, which is not affected by DM. • FFR_CT was superior to the CCTA alone for the detection of ischemia relevance of coronary artery stenosis in both DM and non-DM patients. • Coronary calcification had no significant effect on the diagnostic accuracy of FFR_CT to detect ischemia in DM patients.

Beyond Coronary CT Angiography: CT Fractional Flow Reserve and Perfusion

심장 전산화단층촬영은 비약적인 기술발전과 다양한 연구 결과를 바탕으로 심혈관위험 계층화와 치료 결정을 위한 관상동맥 질환의 진단과 예후 평가성능이 입증되었다. 전산화단층촬영 관상동맥조영술은 폐쇄성 관상동맥 질환에 대한 음성 예측도가 높아서 침습적 혈관조영술의 빈도를 줄일 수 있는 관상동맥 질환 관련 검사의 관문으로 부상했지만, 진단특이도가 상대적으로 낮다. 하지만 심장 전산화단층촬영을 이용한 분획혈류예비력과 심근관류를 분석하여 관상동맥 질환의 혈역학적 유의성을 확인하는 기능적 평가를 통해 그 한계를 극복할 수 있다. 최근에는 이를 보다 객관적이고 재현 가능하도록 인공지능을 접목하는 연구들이 활발히 진행되고 있다. 본 종설에서는 심장 전산화단층촬영의 기능적 영상화 기법들에 대해 알아보고자 한다.

Prognostic Value of Computed Tomography-Derived Fractional Flow Reserve Comparison With Myocardial Perfusion Imaging

OBJECTIVES

The aim of this study was to compare the incremental prognostic value of coronary computed tomography (CT) angiography (CCTA)-derived machine learning fractional flow reserve CT (ML-FFRct) versus that of ischemia detected on single-photon emission-computed tomography (SPECT) myocardial perfusion imaging (MPI) on incident cardiovascular outcomes.

BACKGROUND

SPECT MPI and ML-FFRct are noninvasive tools that can assess the hemodynamic significance of coronary atherosclerotic disease.

METHODS

We studied a retrospective cohort of consecutive patients who underwent clinically indicated CCTA and SPECT MPI. ML-FFRct was computed using a ML prototype. The primary outcome was all-cause mortality and nonfatal myocardial infarction (D/MI), and the secondary outcome was D/MI and unplanned revascularization, percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) occurring more than 90 days postimaging. Multiple nested multivariate cox regression was used to model a scenario wherein an initial anatomical assessment was followed by a functional assessment.

RESULTS

A total of 471 patients (mean age: 64 ± 13 year; 53% males) were included. Comorbidities were prevalent (78% hypertension, 66% diabetes, 81% dyslipidemia). ML-FFRct was <0.8 in at least 1 proximal/midsegment was present in 41.6% of patients, and ischemia on MPI was present in 13.8%. After a median follow-up of 18 months, 7% of patients (n = 33) experienced D/MI. On multivariate Cox proportional analysis, the presence of ischemia on MPI but not ML-FFRct significantly predicted D/MI (HR: 2.3; 95% CI: 1.0-5.0; P = 0.047; or HR: 0.7; 95% CI: 0.3-1.4; P = 0.306 respectively) when added to CCTA obstructive stenosis. Furthermore, the model with SPECT ischemia had higher global chi-square result and significantly improved reclassification. Results were similar using the secondary outcome and on several sensitivity analyses.

CONCLUSIONS

In a high-risk patient cohort, SPECT MPI but not ML-FFRct adds independent and incremental prognostic information to CCTA-based anatomical assessment and clinical risk factors in predicting incident outcomes.