Combination of coronary CT angiography, FFRCT , and risk factors in the prediction of major adverse cardiovascular events in patients suspected CAD

BACKGROUND

To examine the utility of fractional flow reserve by coronary computed tomography (CT) angiography (FFR_CT ) for predicting major adverse cardiovascular events (MACE) in patients with suspected coronary artery disease (CAD).

METHODS

This was a nationwide multicenter prospective cohort study including consecutive 1187 patients aged 50-74 years with suspected CAD and had available coronary CT angiography (CCTA). In patients with ≥50% coronary artery stenosis (CAS), FFR_CT was further analyzed. The Cox proportional hazards model was used to examine the association of FFR_CT and cardiovascular risk factors with incident MACE within 2 years.

RESULTS

Among 933 patients with available information on MACE within 2 years after enrollment, the incidence rate of MACE was higher in 281 patients with CAS than in those without CAS (6.11 vs. 1.16 per 100 patient-year). In 241 patients with CAS, the Cox proportional hazards analysis showed that FFR_CT as well as diabetes mellitus and low high-density lipoprotein cholesterol level were independently associated with incident MACE. Moreover, the hazard ratio was significantly higher in patients harboring all three factors compared to those harboring 0-2 of the three factors (6.01; 95% confidence interval: 2.77-13.03).

CONCLUSIONS

Combinatorial assessment using CCTA for stenosis, FFR_CT , and risk factors was useful for more accurate prediction of MACE in patients with suspected CAD. Among patients with CAS, those with lower FFR_CT , diabetes mellitus, and low high-density lipoprotein cholesterol level were at highest risk for MACE during the 2-year period following enrollment.

Development and evaluation of a radiomics model of resting 13N-ammonia positron emission tomography myocardial perfusion imaging to predict coronary artery stenosis in patients with suspected coronary heart disease

BACKGROUND

Coronary angiography (CAG) is usually performed in patients with coronary heart disease (CHD) to evaluate the coronary artery stenosis. However, patients with iodine allergy and renal dysfunction are not suitable for CAG. We try to develop a radiomics machine learning model based on rest 13N-ammonia (13N-NH3) positron emission tomography (PET) myocardial perfusion imaging (MPI) to predict coronary stenosis.

METHODS

Eighty-four patients were included with the inclusion criteria: adult patients; suspected CHD; resting MPI and CAG were performed; and complete data. Coronary artery stenosis >75% were considered to be significant stenosis. Patients were randomly divided into a training group and a testing group with a ratio of 1:1. Myocardial blood flow (MBF), perfusion defect extent (EXT), total perfusion deficit (TPD), and summed rest score (SRS) were obtained. Myocardial static images of the left ventricular (LV) coronary segments were segmented, and radiomics features were extracted. In the training set, the conventional parameter (MPI model) and radiomics (Rad model) models were constructed using the machine learning method and were combined to construct a nomogram. The models' performance was evaluated by area under the curve (AUC), accuracy, sensitivity, specificity, decision analysis curve (DCA), and calibration curves. Testing and subgroup analysis were performed.

RESULTS

MPI model was composed of MBF and EXT, and Rad model was composed of 12 radiomics features. In the training set, the AUC/accuracy/sensitivity/specificity of the MPI model, Rad model, and the nomogram were 0.795/0.778/0.937/0.511, 0.912/0.825/0.760/0.936 and 0.911/0.865/0.924/0.766 respectively. In the testing set, the AUC/accuracy/sensitivity/specificity of the MPI model, Rad model, and the nomogram were 0.798/0.722/0.659/0.841, 0.887/0.810/0.744/0.932 and 0.900/0.849/0.854/0.841 respectively. The AUC of Rad model and nomogram were significantly higher than that of MPI model. The DCA curve also showed that the clinical net benefit of the Rad model and nomogram was similar but greater than that of MPI model. The calibration curve showed good agreement between the observed and predicted values of the Rad model. In the subgroup analysis of Rad model, there was no significant difference in AUC between subgroups.

CONCLUSIONS

The Rad model is more accurate than the MPI model in predicting coronary stenosis. This noninvasive technique could help improve risk stratification and had good generalization ability.

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.

CT-derived fractional flow reserve (FFRct) for functional coronary artery evaluation in the follow-up of patients after heart transplantation

OBJECTIVES

Invasively measured fractional flow reserve (FFR) is associated with outcome in heart transplant (HTx) patients. Coronary computed tomography angiography (CCTA)-derived FFR (FFRct) provides additional functional information from anatomical CT images. We describe the first use of FFRct in HTx patients.

METHODS

HTx patients underwent CCTA with FFRct to screen for cardiac allograft vasculopathy. FFRct was measured distal to each coronary stenosis > 30% and FFRct ≤ 0.8 indicated hemodynamically significant stenosis. FFRct was also measured at the most distal location of each vessel. Overall distal FFRct was calculated as the mean of the distal values in the left, right, and circumflex coronary artery in each patient.

RESULTS

Seventy-three patients (age 56 (42-65) years, 63% males) at 11 (8-16) years after HTx were included. Eighteen (25%) patients had a focal hemodynamically significant stenosis (stenosis > 30% with FFRct ≤ 0.8). In the 55 patients without a hemodynamically significant focal FFRct stenosis (FFRct > 0.80), the distal left anterior descending artery FFRct was < 0.90 in 74% of the patients and 10 (18%) patients had ≥ 1 coronary artery with a distal FFRct ≤ 0.8, including 1 with a distal FFRct ≤ 0.8 in all coronaries. Overall distal FFRct in patients without focal stenosis was 0.88 (0.86-0.91), 0.87 (0.86-0.90), and 0.88 (0.86-0.91) (median with 25th-75th percentile) at 5-9, 10-14, or ≥ 15 years post-transplantation, respectively (p = 0.93).

CONCLUSIONS

FFRct performed on CCTA scans of HTx patients demonstrated that 25% of patients had a focal coronary stenosis with FFRct ≤ 0.8. Even without a focal stenosis, FFRct values are often abnormal in HTx patients.

KEY POINTS

• This is the first report describing the use of FFRct in in heart transplant patients. • FFRct identifies patients after heart transplantation with hemodynamically significant coronary stenosis. • Even without a focal stenosis, FFRct values are often abnormal in heart transplant patients.

Fractional Flow Reserve Derived from Computer Tomography in Asymptomatic Patients with Type 2 Diabetes and Albuminuria without Significant Coronary Artery Stenosis—A Surrogate for Coronary Microvascular Dysfunction?

Background: Type 2 diabetes mellitus (T2D) patients with albuminuria have coronary microvascular dysfunction (CMD). Fractional flow reserve assessed by coronary computed tomography angiography (FFRct) is dependent on the structure and function of the microcirculation and is likely influenced by CMD. We aimed to evaluate if asymptomatic patients with T2D who had no significant coronary artery stenosis but had been diagnosed with albuminuria had lower value of nadir FFRct compared to asymptomatic patients with T2D and no albuminuria. Methods and results: This was a cross-sectional study which compared the mean nadir FFRct values in coronary arteries in patients with T2D who had no symptoms of angina. The T2D patients were divided into two groups (albuminuria and no albuminuria) with albuminuria being defined as albumin–creatinine-ratio (ACR) ≥30 milligram per gram. The nadir FFRct values were compared between the two groups for left anterior descendent artery (FFRct-LAD), circumflex artery (FFRct-CX), and right coronary artery (FFRct-RCA) by using a two-sample Wilcoxon rank-sum (Mann–Whitney) test. Ninety-eight patients without albuminuria and 26 patients with albuminuria were included. No significant differences in mean values were detected for FFRct-CX 0.86 ± 0.07 and 0.88 ± 0.0, FFRct-RCA 0.88 ± 0.05 and 0.88 ± 0.07, or for FFRct-LAD 0.82 ± 0.07 and 0.82 ± 0.07 in patients with albuminuria and without albuminuria, respectively. Conclusion: In this observational study, we did not find that FFRct was affected by CMD. Therefore, it is not a surrogate for microvascular dysfunction in asymptomatic T2D patients with albuminuria.

Diagnostic Performance of Machine Learning Based CT-FFR in Detecting Ischemia in Myocardial Bridging and Concomitant Proximal Atherosclerotic Disease

BACKGROUND

The diagnostic performance of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) in detecting ischemia in myocardial bridging (MB) has not been investigated to date.

METHODS

This retrospective multicentre study included 104 patients with left anterior descending MBs. MB was classified as either superficial or deep, short, or long, whereas all MB vessels were further divided into <50%, 50% to 69%, and ≥70% groups, according to proximal lumen stenosis on invasive coronary angiography. Diagnostic performance and receiver operating characteristics (ROC) of CT-FFR to detect lesion-specific ischemia was assessed on a per-vessel level, using invasive FFR as reference standard. Intraclass correlation coefficient (ICC) and Bland-Altman plots were used for agreement measurement.

RESULTS

Forty-eight MB vessels (46.2%) showed ischemia by invasive FFR (≤0.80). Sensitivity, specificity, and accuracy of CT-FFR to detect functional ischemia were 0.96 (0.85 to 0.99), 0.84 (0.71 to 0.92), and 0.89 (0.81 to 0.94), respectively, in all MB vessels. There were no differences in diagnostic performance between superficial and deep MB or between short and long MB (all P > 0.05). The accuracy of CT-FFR was 0.96 (0.85 to 0.99) in ≥70% stenosis, 0.82 (0.67 to 0.91) in 50% to 69% stenosis, and 0.89 (0.51 to 0.99) in <50% stenosis (P = 0.081). Bland-Altman analysis showed a slight mean difference between CT-FFR and invasive FFR of 0.014 (95% limit of agreement, -0.117 to 0.145). The ICC was 0.775 (95% confidence interval, 0.685-0.842, P < 0.001).

CONCLUSIONS

CT-FFR demonstrated high diagnostic performance for identifying functional ischemia in vessels with MB and concomitant proximal atherosclerotic disease when compared with invasive FFR. However, the clinical use of CT-FFR in patients with MB needs further study for stronger and more robust results.

The year 2017 in the European Heart Journal-Cardiovascular Imaging: Part I

The European Heart Journal - Cardiovascular Imaging was launched in 2012. It has gained an impressive impact factor of 8.336 during its first 6 years and is now established as one of the top 10 cardiovascular journals in the world and the most important cardiovascular imaging journal in Europe. The most important studies published in the journal in 2017 will be highlighted in two reports. Part I will focus on studies about myocardial function, coronary artery disease and myocardial ischaemia, and emerging techniques and applications in cardiovascular imaging, whereas Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.

Computed tomography derived fractional flow reserve testing in stable patients with typical angina pectoris: influence on downstream rate of invasive coronary angiography

Aims

To assess the use of downstream coronary angiography (ICA) and short-term safety of frontline coronary CT angiography (CTA) with selective CT-derived fractional flow reserve (FFR_CT) testing in stable patients with typical angina pectoris.

Methods and results

Between 1 January 2016 and 30 June 2016 all patients (N = 774) referred to non-emergent ICA or coronary CTA at Aarhus University Hospital on a suspicion of CAD had frontline CTA performed. Downstream testing and treatment within 3 months and adverse events ≥90 days were registered. Patients were divided into two groups according to the presence of typical angina pectoris, which according to local practice would have resulted in referral to ICA, (low-intermediate-risk, n = 593 [76%]; high-risk, n = 181 [24%]) with mean pre-test probability of CAD of 31 ± 16% and 67 ± 16%, respectively. Coronary CTA was performed in 745 (96%) patients in whom FFR_CT was prescribed in 212 (28%) patients. In the high- vs. low-intermediate-risk group, ICA was cancelled in 75% vs. 91%. Coronary revascularization was performed more frequently in high-risk than in low-intermediate-risk patients, 76% vs. 52% (P = 0.03). Mean follow-up time was 157 ± 50 days. Serious clinical events occurred in four patients, but not in any patients with cancelled ICA by coronary CTA with selective FFR_CT testing.

Conclusion

Frontline coronary CTA with selective FFR_CT testing in stable patients with typical angina pectoris in real-world practice is associated with a high rate of safe cancellation of planned ICAs.

Fusion of Three-Dimensional Echocardiographic Regional Myocardial Strain with Cardiac Computed Tomography for Noninvasive Evaluation of the Hemodynamic Impact of Coronary Stenosis in Patients with Chest Pain

BACKGROUND

Combined evaluation of coronary stenosis and the extent of ischemia is essential in patients with chest pain. Intermediate-grade stenosis on computed tomographic coronary angiography (CTCA) frequently triggers downstream nuclear stress testing. Alternative approaches without stress and/or radiation may have important implications. Myocardial strain measured from echocardiographic images can be used to detect subclinical dysfunction. The authors recently tested the feasibility of fusion of three-dimensional (3D) echocardiography-derived regional resting longitudinal strain with coronary arteries from CTCA to determine the hemodynamic significance of stenosis. The aim of the present study was to validate this approach against accepted reference techniques.

METHODS

Seventy-eight patients with chest pain referred for CTCA who also underwent 3D echocardiography and regadenoson stress computed tomography were prospectively studied. Left ventricular longitudinal strain data (TomTec) were used to generate fused 3D displays and detect resting strain abnormalities (RSAs) in each coronary territory. Computed tomographic coronary angiographic images were interpreted for the presence and severity of stenosis. Fused 3D displays of subendocardial x-ray attenuation were created to detect stress perfusion defects (SPDs). In patients with stenosis >25% in at least one artery, fractional flow reserve was quantified (HeartFlow). RSA as a marker of significant stenosis was validated against two different combined references: stenosis >50% on CTCA and SPDs seen in the same territory (reference standard A) and fractional flow reserve < 0.80 and SPDs in the same territory (reference standard B).

RESULTS

Of the 99 arteries with no stenosis >50% and no SPDs, considered as normal, 19 (19%) had RSAs. Conversely, with stenosis >50% and SPDs, RSAs were considerably more frequent (17 of 24 [71%]). The sensitivity, specificity, and accuracy of RSA were 0.71, 0.81, and 0.79, respectively, against reference standard A and 0.83, 0.81, and 0.82 against reference standard B.

CONCLUSIONS

Fusion of CTCA and 3D echocardiography-derived resting myocardial strain provides combined displays, which may be useful in determination of the hemodynamic or functional impact of coronary abnormalities, without additional ionizing radiation or stress testing.

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 (FFR_CT) 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), FFR_CT showed high diagnostic performance. More recently, FFR_CT has advanced to the realm of clinical utility and real-world clinical practice with emerging data showing that FFR_CT 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, FFR_CT may broaden applicability of frontline coronary CTA testing to patients with high pre-test risk of CAD. Introducing FFR_CT into clinical practice has the potential to significantly improve the management of patients with stable CAD. The optimal FFR_CT testing interpretation strategy, as well as the relative cost-efficiency of FFR_CT against standard noninvasive functional testing, need further investigation.