Comprehensive assessment of coronary artery stenoses: computed tomography coronary angiography versus conventional coronary angiography and correlation with fractional flow reserve in patients with stable angina. J Am Coll Cardiol. 2008;52:636-643. [PMID: 18702967 DOI: 10.1016/j.jacc.2008.05.024]

Comparison of machine learning-based CT fractional flow reserve with cardiac MR perfusion mapping for ischemia diagnosis in stable coronary artery disease

OBJECTIVES

To compare the diagnostic performance of machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.

METHODS

Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.

RESULTS

The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).

CONCLUSION

ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.

CLINICAL RELEVANCE STATEMENT

ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.

KEY POINTS

• Both machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis. • Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis. • ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.

Diagnostic Performance of On-Site Automatic Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve

BACKGROUND AND OBJECTIVES

Fractional flow reserve (FFR) is an invasive standard method to identify ischemia-causing coronary artery disease (CAD). With the advancement of technology, FFR can be noninvasively computed from coronary computed tomography angiography (CCTA). Recently, a novel simpler method has been developed to calculate on-site CCTA-derived FFR (CT-FFR) with a commercially available workstation.

METHODS

A total of 319 CAD patients who underwent CCTA, invasive coronary angiography, and FFR measurement were included. The primary outcome was the accuracy of CT-FFR for defining myocardial ischemia evaluated with an invasive FFR as a reference. The presence of ischemia was defined as FFR ≤0.80. Anatomical obstructive stenosis was defined as diameter stenosis on CCTA ≥50%, and the diagnostic performance of CT-FFR and CCTA stenosis for ischemia was compared.

RESULTS

Among participants (mean age 64.7±9.4 years, male 77.7%), mean FFR was 0.82±0.10, and 126 (39.5%) patients had an invasive FFR value of ≤0.80. The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CT-FFR were 80.6% (95% confidence interval [CI], 80.5-80.7%), 88.1% (95% CI, 82.4-93.7%), 75.6% (95% CI, 69.6-81.7%), 70.3% (95% CI, 63.1-77.4%), and 90.7% (95% CI, 86.2-95.2%), respectively. CT-FFR had higher diagnostic accuracy (80.6% vs. 59.1%, p<0.001) and discriminant ability (area under the curve from receiver operating characteristic curve 0.86 vs. 0.64, p<0.001), compared with anatomical obstructive stenosis on CCTA.

CONCLUSIONS

This novel CT-FFR obtained from an on-site workstation demonstrated clinically acceptable diagnostic performance and provided better diagnostic accuracy and discriminant ability for identifying hemodynamically significant lesions than CCTA alone.

Longitudinal Evaluation of Coronary Arteries and Myocardium in Breast Cancer Using Coronary Computed Tomographic Angiography

BACKGROUND

The association of coronary computed tomography angiography (CTA) and left ventricular (LV) myocardium measurements with cancer therapy-related cardiac dysfunction (CTRCD) is limited.

OBJECTIVES

In this study, the authors sought to evaluate the changes in coronary arteries and LV myocardium in patients with left breast cancer (BC) receiving anthracycline with or without radiotherapy, with the use of coronary CTA.

METHODS

Participants with left BC receiving anthracycline with or without radiotherapy were prospectively included. All participants underwent coronary CTA before and after treatment, including nonenhanced calcium-scoring scan, computed tomography angiography, and dual-energy late enhancement scan. Computed tomographic fractional flow reserve (CT-FFR), pericoronary adipose tissue (PCAT) CT attenuation, and LV segments' extracellular volume (ECV) before and after treatment were compared. Logistic regression analysis was used to assess the association between baseline coronary CTA parameters and CTRCD.

RESULTS

Eighty participants receiving anthracycline and 59 participants receiving anthracycline with radiotherapy were included. CT-FFR decreased and PCAT CT attenuation and LV global and segments' ECV increased after treatment (all P < 0.05). After chemoradiotherapy, CT-FFR was lower and PCAT CT attenuation and LV myocardial ECV were higher than after chemotherapy. Twenty-four participants developed CTRCD. After adjustment by Heart Failure Association-International Cardio-Oncology Society risk in multivariable logistic regression analysis, baseline stenosis of the left anterior descending artery (LAD) (OR: 1.987 [95% CI: 1.322-2.768]; P = 0.021), left circumflex artery (LCX) (OR: 1.895 [95% CI: 1.281-2.802]; P = 0.031), and right coronary artery (RCA) (OR: 1.920 [95% CI: 1.405-2.811]; P = 0.028), and baseline CT-FFR of the LAD (OR: 3.425 [95% CI: 1.621-9.434]; P < 0.001), LCX (OR: 2.058 [95% CI: 1.030-5.076]; P = 0.006), and RCA (OR: 2.469 [95% CI: 1.232-6.944]; P = 0.004) were associated with CTRCD.

CONCLUSIONS

Multiparameter coronary CTA contributes to comprehensive assessment of the coronary arteries and myocardium in patients with left BC receiving anthracycline with or without radiotherapy. Baseline coronary artery stenosis and CT-FFR might be imaging markers for predicting CTRCD in these patients.

Diagnostic and prognostic performance of artificial intelligence-based fully-automated on-site CT-FFR in patients with CAD

Currently, clinically available coronary CT angiography (CCTA) derived fractional flow reserve (CT-FFR) is time-consuming and complex. We propose a novel artificial intelligence-based fully-automated, on-site CT-FFR technology, which combines the automated coronary plaque segmentation and luminal extraction model with reduced order 3 dimentional (3D) computational fluid dynamics. A total of 463 consecutive patients with 600 vessels from the updated China CT-FFR study in Cohort 1 undergoing both CCTA and invasive fractional flow reserve (FFR) within 90 d were collected for diagnostic performance evaluation. For Cohort 2, a total of 901 chronic coronary syndromes patients with index CT-FFR and clinical outcomes at 3-year follow-up were retrospectively analyzed. In Cohort 3, the association between index CT-FFR from triple-rule-out CTA and major adverse cardiac events in patients with acute chest pain from the emergency department was further evaluated. The diagnostic accuracy of this CT-FFR in Cohort 1 was 0.82 with an area under the curve of 0.82 on a per-patient level. Compared with the manually dependent CT-FFR techniques, the operation time of this technique was substantially shortened by 3 times and the number of clicks from about 60 to 1. This CT-FFR technique has a highly successful (> 99%) calculation rate and also provides superior prediction value for major adverse cardiac events than CCTA alone both in patients with chronic coronary syndromes and acute chest pain. Thus, the novel artificial intelligence-based fully automated, on-site CT-FFR technique can function as an objective and convenient tool for coronary stenosis functional evaluation in the real-world clinical setting.

Peri-coronary fat attenuation index combined with high-risk plaque characteristics quantified from coronary computed tomography angiography for risk stratification in new-onset chest pain individuals without acute myocardial infarction

This study aims to evaluate the role of the peri-coronary Fat Attenuation Index (FAI) and High-Risk Plaque Characteristics (HRPC) in the assessment of coronary heart disease risk. By conducting coronary CT angiography and coronary angiography on 217 patients with newly developed chest pain (excluding acute myocardial infarction), their degree of vascular stenosis, FAI, and the presence and quantity of HRPC were assessed. The study results demonstrate a correlation between FAI and HRPC, and the combined use of FAI and HRPC can more accurately predict the risk of major adverse cardiovascular events (MACE). Additionally, the study found that patients with high FAI were more prone to exhibit high-risk plaque characteristics, severe stenosis, and multiple vessel disease. After adjustment, the combination of FAI and HRPC improved the ability to identify and reclassify MACE. Furthermore, the study identified high FAI as an independent predictor of MACE in patients undergoing revascularization, while HRPC served as an independent predictor of MACE in patients not undergoing revascularization. These findings suggest the potential clinical value of FAI and HRPC in the assessment of coronary heart disease risk, particularly in patients with newly developed chest pain excluding acute myocardial infarction.

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.

Personalized coronary and myocardial blood flow models incorporating CT perfusion imaging and synthetic vascular trees

Computational simulations of coronary artery blood flow, using anatomical models based on clinical imaging, are an emerging non-invasive tool for personalized treatment planning. However, current simulations contend with two related challenges - incomplete anatomies in image-based models due to the exclusion of arteries smaller than the imaging resolution, and the lack of personalized flow distributions informed by patient-specific imaging. We introduce a data-enabled, personalized and multi-scale flow simulation framework spanning large coronary arteries to myocardial microvasculature. It includes image-based coronary anatomies combined with synthetic vasculature for arteries below the imaging resolution, myocardial blood flow simulated using Darcy models, and systemic circulation represented as lumped-parameter networks. We propose an optimization-based method to personalize multiscale coronary flow simulations by assimilating clinical CT myocardial perfusion imaging and cardiac function measurements to yield patient-specific flow distributions and model parameters. Using this proof-of-concept study on a cohort of six patients, we reveal substantial differences in flow distributions and clinical diagnosis metrics between the proposed personalized framework and empirical methods based purely on anatomy; these errors cannot be predicted a priori. This suggests virtual treatment planning tools would benefit from increased personalization informed by emerging imaging methods.

Prognostic value of a novel artificial intelligence-based coronary computed tomography angiography-derived ischaemia algorithm for patients with suspected coronary artery disease

AIMS

Coronary computed tomography angiography (CTA) imaging is used to diagnose patients with suspected coronary artery disease (CAD). A novel artificial intelligence-guided quantitative computed tomography ischaemia algorithm (AI-QCTischaemia) aims to identify myocardial ischaemia directly from CTA images and may be helpful to improve risk stratification. The aims were to investigate (i) the prognostic value of AI-QCTischaemia amongst symptomatic patients with suspected CAD entering diagnostic imaging with coronary CTA and (ii) the prognostic value of AI-QCTischaemia separately amongst patients with no/non-obstructive CAD (≤50% visual diameter stenosis) and obstructive CAD (>50% visual diameter stenosis).

METHODS AND RESULTS

For this cohort study, AI-QCTischaemia was calculated by blinded analysts amongst patients with suspected CAD undergoing coronary CTA. The primary endpoint was the composite of death, myocardial infarction (MI), or unstable angina pectoris (uAP) (median follow-up 6.9 years). A total of 1880/2271 (83%) patients had conclusive AI-QCTischaemia result. Patients with an abnormal AI-QCTischaemia result (n = 509/1880) vs. patients with a normal AI-QCTischaemia result (n = 1371/1880) had significantly higher crude and adjusted rates of the primary endpoint [adjusted hazard ratio (HRadj) 1.96, 95% confidence interval (CI) 1.46-2.63, P < 0.001; covariates: age/sex/hypertension/diabetes/smoking/typical angina]. An abnormal AI-QCTischaemia result was associated with significantly higher crude and adjusted rates of the primary endpoint amongst patients with no/non-obstructive CAD (n = 1373/1847) (HRadj 1.81, 95% CI 1.09-3.00, P = 0.022), but not amongst those with obstructive CAD (n = 474/1847) (HRadj 1.26, 95% CI 0.75-2.12, P = 0.386) (P-interaction = 0.032).

CONCLUSION

Amongst patients with suspected CAD, an abnormal AI-QCTischaemia result was associated with a two-fold increased adjusted rate of long-term death, MI, or uAP. AI-QCTischaemia may be useful to improve risk stratification, especially amongst patients with no/non-obstructive CAD on coronary CTA.

Selective Use of CT Fractional Flow at a Large Academic Medical Center: Insights from Clinical Implementation after 1 Year of Practice

Purpose This special report outlines a retrospective observational study of CT fractional flow reserve (CT-FFR) analysis using dual-source coronary CT angiography (CTA) scans performed without heart rate control and its impact on clinical outcomes. Materials and Methods All patients who underwent clinically indicated coronary CTA between August 2020 and August 2021 were included in this retrospective observational study. Scans were performed in the late systolic to early diastolic period without heart rate control and analyzed at the interpreting physician's discretion. Demographics, coronary CTA features, and rates of invasive coronary angiography (ICA), percutaneous coronary intervention (PCI), myocardial infarction, and all-cause death at 3 months were assessed by chart review. Results During the study period, 3098 patients underwent coronary CTA, of whom 113 with coronary bypass grafting were excluded. Of the remaining 2985 patients, 292 (9.7%) were referred for CT-FFR analysis. Two studies (0.7%) were rejected from CT-FFR analysis, and six (2.1%) analyses did not evaluate the lesion of concern. A total of 160 patients (56.3%) had CT-FFR greater than 0.80. Among patients with significant stenosis at coronary CTA, patients who underwent CT-FFR analysis presented with lower rates of ICA (74.5% vs 25.5%, P = .04) and PCI (78.9% vs 21.1%, P = .05). Conclusion CT-FFR was implemented in patients not requiring heart rate control by using dual-source coronary CTA acquisition and showed the potential to decrease rates of ICA and PCI without compromising safety in patients with significant stenosis and an average heart rate of 65 beats per minute. Keywords: Angiography, CT, CT-Angiography, Fractional Flow Reserve, Cardiac, Heart, Arteriosclerosis Supplemental material is available for this article. © RSNA, 2024.

Association between vessel-specific coronary Aggregated plaque burden, Agatston score and hemodynamic significance of coronary disease (The CAPTivAte study)

Background

CT coronary angiography (CTCA) is a guideline-endorsed assessment for patients with stable angina and suspected coronary disease. Although associated with excellent negative predictive value in ruling out obstructive coronary disease, there are limitations in the ability of CTCA to predict hemodynamically significant coronary disease. The CAPTivAte study aims to assess the utility of Aggregated Plaque Burden (APB) in predicting ischemia based on Fractional Flow Reserve (FFR).

Methods

In this retrospective study, patients who had a CTCA and invasive FFR of the LAD were included. The entire length of the LAD was analyzed using semi-automated software which characterized total plaque burden and plaque morphological subtype (including Low Attenuation Plaque (LAP), Non-calcific plaque (NCP) and Calcific Plaque (CP). Aggregated Plaque Burden (APB) was calculated. Univariate and multivariate analysis were performed to assess the association between these CT-derived parameters and invasive FFR.

Results

There were 145 patients included in this study. 84.8 % of patients were referred with stable angina. There was a significant linear association between APB and FFR in both univariate and multivariate analysis (Adjusted R-squared = 0.0469; p = 0.035). Mean Agatston scores are higher in FFR positive vessels compared to FFR negative vessels (371.6 (±443.8) vs 251.9 (±283.5, p = 0.0493).

Conclusion

CTCA-derived APB is a reliable predictor of ischemia assessed using invasive FFR and may aid clinicians in rationalizing invasive vs non-invasive management strategies. Vessel-specific Agatston scores are significantly higher in FFR-positive vessels than in FFR-negative vessels. Associations between HU-derived plaque subtype and invasive FFR were inconclusive in this study.

Intra-individual comparison of coronary CT angiography-based FFR between energy-integrating and photon-counting detector CT systems

BACKGROUND

Coronary computed tomography angiography (CCTA)-based fractional flow reserve (CT-FFR) allows for noninvasive determination of the functional severity of anatomic lesions in patients with coronary artery disease. The aim of this study was to intra-individually compare CT-FFR between photon-counting detector (PCD) and conventional energy-integrating detector (EID) CT systems.

METHODS

In this single-center prospective study, subjects who underwent clinically indicated CCTA on an EID-CT system were recruited for a research CCTA on PCD-CT within 30 days. Image reconstruction settings were matched as closely as possible between EID-CT (Bv36 kernel, iterative reconstruction strength level 3, slice thickness 0.5 mm) and PCD-CT (Bv36 kernel, quantum iterative reconstruction level 3, virtual monoenergetic level 55 keV, slice thickness 0.6 mm). CT-FFR was measured semi-automatically using a prototype on-site machine learning algorithm by two readers. CT-FFR analysis was performed per-patient and per-vessel, and a CT-FFR ≤ 0.75 was considered hemodynamically significant.

RESULTS

A total of 22 patients (63.3 ± 9.2 years; 7 women) were included. Median time between EID-CT and PCD-CT was 5.5 days. Comparison of CT-FFR values showed no significant difference and strong agreement between EID-CT and PCD-CT in the per-vessel analysis (0.88 [0.74-0.94] vs. 0.87 [0.76-0.93], P = 0.096, mean bias 0.02, limits of agreement [LoA] -0.14/0.19, r = 0.83, ICC = 0.92), and in the per-patient analysis (0.81 [0.60-0.86] vs. 0.76 [0.64-0.86], P = 0.768, mean bias 0.02, LoA -0.15/0.19, r = 0.90, ICC = 0.93). All included patients were classified into the same category (CT-FFR > 0.75 vs ≤0.75) with both CT systems.

CONCLUSIONS

CT-FFR evaluation is feasible with PCD-CT and it shows a strong agreement with EID-CT-based evaluation when images are similarly reconstructed.

Optimal diagnostic approach for using CT-derived quantitative flow ratio in patients with stenosis on coronary computed tomography angiography

BACKGROUND

Coronary computed tomography angiography (CCTA)-derived quantitative flow ratio (CT-QFR) is an on-site non-invasive technique estimating invasive fractional flow reserve (FFR). This study assesses the diagnostic performance of using most distal CT-QFR versus lesion-specific CT-QFR approach for identifying hemodynamically obstructive coronary artery disease (CAD).

METHODS

Prospectively enrolled de novo chest pain patients (n ​= ​445) with ≥50 ​% visual diameter stenosis on CCTA were referred for invasive evaluation. On-site CT-QFR was analyzed post-hoc blinded to angiographic data and obtained as both most distal (MD-QFR) and lesion-specific CT-QFR (LS-QFR). Abnormal CT-QFR was defined as ≤0.80. Hemodynamically obstructive CAD was defined as invasive FFR ≤0.80 or ≥70 ​% diameter stenosis by 3D-quantitative coronary angiography.

RESULTS

In total 404/445 patients had paired CT-QFR and invasive analyses of whom 149/404 (37 ​%) had hemodynamically obstructive CAD. MD-QFR and LS-QFR classified 188 (47 ​%) and 165 (41 ​%) patients as abnormal, respectively. Areas under the receiver-operating characteristic curve for MD-QFR was 0.83 vs. 0.85 for LS-QFR, p ​= ​0.01. Sensitivities for MD-QFR and LS-QFR were 80 ​% (95%CI: 73-86) vs. 77 ​% (95%CI: 69-83), p ​= ​0.03, respectively, and specificities were 73 ​% (95%CI: 67-78) vs. 80 ​% (95%CI: 75-85), p ​< ​0.01, respectively. Positive predictive values for MD-QFR and LS-QFR were 63 ​% vs. 69 ​%, p ​< ​0.01, respectively, and negative predictive values for MD-QFR and LS-QFR were 86 ​% vs. 85 ​%, p ​= ​0.39, respectively).

CONCLUSION

Using a lesion-specific CT-QFR approach has superior discrimination of hemodynamically obstructive CAD compared to a most distal CT-QFR approach. CT-QFR identified most cases of hemodynamically obstructive CAD while a normal CT-QFR excluded hemodynamically obstructive CAD in the majority of patients.

Diagnostic accuracy of CT-FFR with a new coarse-to-fine subpixel algorithm in detecting lesion-specific ischemia: a prospective multicenter study

INTRODUCTION AND OBJECTIVES

A new computed tomography-derived fractional flow reserve (CT-FFR) technique with a "coarse-to-fine subpixel" algorithm has been developed to generate precise lumen contours. The aim of this study was to assess the diagnostic performance of this new CT-FFR algorithm for discriminating lesion-specific ischemia using wire-based FFR ≤ 0.80 as the reference standard in patients with coronary artery disease.

METHODS

This prospective, multicenter study screened 330 patients undergoing coronary CT angiography (CCTA) and invasive FFR (median interval 2 days) from 6 tertiary hospitals. CT-FFR was evaluated in a blinded fashion with a "coarse-to-fine subpixel" algorithm for lumen contour.

RESULTS

Between March 2019 and May 2020, we included 316 patients with 324 vessels. There was a good correlation between CT-FFR and invasive FFR (r=0.76, P<.001). The diagnostic sensitivity, specificity, and accuracy on a per-vessel level were 95.3%, 89.8%, and 92.0% for CT-FFR, and 96.4%, 26.4%, and 53.1% for CCTA>50% stenosis, respectively. CT-FFR showed improved discrimination of ischemia compared with CCTA alone overall (AUC, 0.95 vs 0.74, P<.001) and in intermediate (AUC, 0.96 vs 0.62, P<.001) and "gray zone" lesions (AUC, 0.88 vs 0.61, P<.001). The diagnostic specificity, accuracy, and AUC for CT-FFR (71.9%, 82.8%, and 0.84) outperformed CCTA (9.4%, 48.3%, and 0.66) in patients or in vessels with severe calcification (all P<.05).

CONCLUSIONS

CT-FFR with a new "coarse-to-fine subpixel" algorithm showed high performance in identifying hemodynamically significant stenosis. The diagnostic performance of CT-FFR was superior to that of CCTA in intermediate lesions, "gray zone" lesions, and severely calcified lesions. Clinical Trial Register: NCT04731285.

Positive Predictive Value of Computerized Tomography Coronary Angiography versus Computerized Tomography Fractional Flow Reserve in a Real-world Population

Background

Computed Tomography coronary angiography and fractional flow reserve (CTCA and CT-FFR) are noninvasive diagnostic tools for the detection of flow-limiting coronary artery stenoses. Although their negative predictive values are well established, there is a concern that the high sensitivity of these tests may lead to overestimation of coronary artery disease (CAD) and unnecessary invasive coronary angiography (ICA). We compared the positive predictive value (PPV) of CT-FFR with computerized tomography coronary angiography (CTCA) against the gold standard of ICA in different real-world patient groups.

Methods

A retrospective analysis of 477 patients referred for CTCA or CT-FFR for investigation of possible coronary ischemia. Patients were excluded if the image quality was poor or inconclusive. Patient-based PPV was calculated to detect or rule out significant CAD, defined as more than 70% stenosis on ICA. A sub-analysis of PPV by indication for the scan was also performed. Patients who underwent invasive nonhyperemic pressure wire measurements had their instant wave-free ratio or resting full-cycle ratio compared with their CT-FFR values.

Results

In a patient-based analysis, the overall PPV was 59.3% for CTCA and 76.2% for CT-FFR. This increased to 81.0% and 86.7%, respectively, for patients with stable angina symptoms. In patients with atypical angina symptoms, CT-FFR considerably outperformed CTCA with a PPV of 61.3% vs. 37.5%. There was not a linear relationship between invasive pressure wire measurement and CT-FFR value (r = 0.23, P = 0.265).

Conclusion

The PPV of CTCA and CT-FFR is lower in the real world than in previously published trials, partly due to the heterogeneity of indication for the scan. However, in patients with typical angina symptoms, both are reliable diagnostic tools to determine the presence of clinically significant coronary stenoses. CT-FFR significantly outperforms CTCA in patients with more atypical symptoms and the targeted use of CT-FFR in this group may help to avoid unnecessary invasive procedures.

Coronary artery disease in atrial fibrillation ablation: impact on arrhythmic outcomes

AIMS

Catheter ablation (CA) is an established treatment for atrial fibrillation (AF). A computed tomography (CT) may be performed before ablation to evaluate the anatomy of pulmonary veins. The aim of this study is to investigate the prevalence of patients with coronary artery disease (CAD) detected by cardiac CT scan pre-ablation and to evaluate the impact of CAD and revascularization on outcomes after AF ablation.

METHODS AND RESULTS

All consecutive patients with AF diagnosis, hospitalized at Universitair Ziekenhuis Brussel, Belgium, between 2015 and 2019, were prospectively screened for enrolment in the study. Inclusion criteria were (i) AF diagnosis, (ii) first procedure of AF ablation with cryoballoon CA, and (iii) contrast CT scan performed pre-ablation. A total of 576 consecutive patients were prospectively included and analysed in this study. At CT scan, 122 patients (21.2%) were diagnosed with CAD, of whom 41 patients (7.1%) with critical CAD. At survival analysis, critical CAD at CT scan was a predictor of atrial tachyarrhythmia (AT) recurrence during the follow-up, only in Cox univariate analysis [hazard ratio (HR) = 1.79] but was not an independent predictor in Cox multivariate analysis. At Cox multivariate analysis, independent predictors of AT recurrence were as follows: persistent AF (HR = 2.93) and left atrium volume index (HR = 1.04).

CONCLUSION

In patients undergoing CT scan before AF ablation, critical CAD was diagnosed in 7.1% of patients. Coronary artery disease and revascularization were not independent predictors of recurrence; thus, in this patient population, AF ablation should not be denied and can be performed together with CAD treatment.

Feasibility of four-dimensional similarity filter for radiation dose reduction in dynamic myocardial computed tomography perfusion imaging

Rationale and objectives

We aimed to evaluate the impact of four-dimensional noise reduction filtering using a four-dimensional similarity filter (4D-SF) on radiation dose reduction in dynamic myocardial computed tomography perfusion (CTP).

Materials and methods

Forty-three patients who underwent dynamic myocardial CTP using 320-row computed tomography (CT) were included in the study. The original images were reconstructed using iterative reconstruction (IR). Three different CTP datasets with simulated noise, corresponding to 25%, 50%, and 75% reduction of the original dose (300 mA), were reconstructed using a combination of IR and 4D-SF. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed, and CT-derived myocardial blood flow (CT-MBF) was quantified. The results were compared between the original and simulated images with radiation dose reduction.

Results

The median SNR (first quartile-third quartile) at the original, 25%-, 50%-, and 75%-dose reduced-simulated images with 4D-SF was 8.3 (6.5-10.2), 16.5 (11.9-21.7), 15.6 (11.0-20.1), and 12.8 (8.8-18.1) and that of CNR was 4.4 (3.2-5.8), 6.7 (4.6-10.3), 6.6 (4.3-10.1), and 5.5 (3.5-9.1), respectively. All the dose-reduced-simulated CTPs with 4D-SF had significantly higher image quality scores in SNR and CNR than the original ones (25%-, 50%-, and 75%-dose reduced vs. original images, p < 0.05, in each). The CT-MBF in 75%-dose reduced-simulated CTP was significantly lower than 25%-, 50%- dose-reduced-simulated, and original CTPs (vs. 75%-dose reduced-simulated images, p < 0.05, in each).

Conclusion

4D-SF has the potential to reduce the radiation dose associated with dynamic myocardial CTP imaging by half, without impairing the robustness of MBF quantification.

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.

Prognostic Value of Coronary CT Angiography-derived Fractional Flow Reserve on 3-year Outcomes in Patients with Stable Angina

Background The prognostic value of coronary CT angiography (CTA)-derived fractional flow reserve (FFR) beyond 1-year outcomes and in patients with high levels of coronary artery calcium (CAC) is uncertain. Purpose To assess the prognostic value of coronary CTA-derived FFR test results on 3-year clinical outcomes in patients with coronary stenosis and among a subgroup of patients with high levels of CAC. Materials and Methods This study represents a 3-year follow-up of patients with new-onset stable angina pectoris who were consecutively enrolled in the Assessing Diagnostic Value of Noninvasive CT-FFR in Coronary Care, known as ADVANCE (ClinicalTrials.gov: NCT02499679) registry, between December 2015 and October 2017 at three Danish sites. A high CAC was defined as an Agatston score of at least 400. A lesion-specific coronary CTA-derived FFR value of 2 cm with distal-to-stenosis value at or below 0.80 represented an abnormal test result. The primary end point was a composite of all-cause death and nonfatal spontaneous myocardial infarction. Event rates were estimated using the one-sample binomial model, and relative risk was compared between participants stratified by results of coronary CTA-derived FFR. Results This study included 900 participants: 523 participants with normal results (mean age, 64 years ± 9.6 [SD]; 318 male participants) and 377 with abnormal results from coronary CTA-derived FFR (mean age, 65 years ± 9.6; 264 male participants). The primary end point occurred in 11 of 523 (2.1%) and 25 of 377 (6.6%) participants with normal and abnormal coronary CTA-derived FFR results, respectively (relative risk, 3.1; 95% CI: 1.6, 6.3; P < .001). In participants with high CAC, the primary end point occurred in four of 182 (2.2%) and 19 of 212 (9.0%) participants with normal and abnormal coronary CTA-derived FFR results, respectively (relative risk, 4.1; 95% CI: 1.4, 11.8; P = .001). Conclusion In individuals with stable angina, a normal coronary CTA-derived FFR test result identified participants with a low 3-year risk of all-cause death or nonfatal spontaneous myocardial infarction, both in the overall cohort and in participants with high CAC scores. Clinical trial registration no. NCT02499679 Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Sinitsyn in this issue.

Personalized coronary and myocardial blood flow models incorporating CT perfusion imaging and synthetic vascular trees

Computational simulations of coronary artery blood flow, using anatomical models based on clinical imaging, are an emerging non-invasive tool for personalized treatment planning. However, current simulations contend with two related challenges - incomplete anatomies in image-based models due to the exclusion of arteries smaller than the imaging resolution, and the lack of personalized flow distributions informed by patient-specific imaging. We introduce a data-enabled, personalized and multi-scale flow simulation framework spanning large coronary arteries to myocardial microvasculature. It includes image-based coronary models combined with synthetic vasculature for arteries below the imaging resolution, myocardial blood flow simulated using Darcy models, and systemic circulation represented as lumped-parameter networks. Personalized flow distributions and model parameters are informed by clinical CT myocardial perfusion imaging and cardiac function using surrogate-based optimization. We reveal substantial differences in flow distributions and clinical diagnosis metrics between the proposed personalized framework and empirical methods based on anatomy; these errors cannot be predicted a priori. This suggests virtual treatment planning tools would benefit from increased personalization informed by emerging imaging methods.

Multimodal Imaging of a Culotte Bifurcation Procedure in the Left Main Coronary Artery of a Perfusion-Fixed Human Heart: Step-by-Step with Serial Micro-CT Analyses

Percutaneous coronary intervention can be a high-risk procedure that would benefit from optimizing device-tissue interactions between stents and coronary vessels. Using a perfusion-fixed human heart with coronary artery disease, we performed a percutaneous coronary intervention of the left main coronary artery bifurcation. This heart was perfused and multimodal imaging was utilized to view the procedure with direct visualization, fluoroscopy, and optical coherence tomography (OCT). We followed the European Bifurcation Club's guidelines to perform a single-stent bifurcation before transitioning to a two-stent Culotte technique. After each procedural step, the heart was removed from the perfusion apparatus and transferred to a micro-CT scanner to obtain unique scans. We conducted apposition analyses of the computational 3D models from micro-CT DICOM datasets, and compared them to the results from direct visualization and commercial OCT's Apposition Indicator software. Additional measurements of resulting coronary anatomic expansions were taken to determine the potential roles of each step in improving procedural outcomes. Micro-CT images show stent deformation during a percutaneous coronary intervention (provisional to Culotte bifurcation procedure) in an isolated diseased human heart.

Comprehensive Computed Tomography Imaging of Vessel-specific and Lesion-specific Myocardial Ischemia

Coronary computed tomographic angiography (CCTA) has emerged as a fast and robust tool with high sensitivity and excellent negative predictive value for the evaluation of coronary artery disease, but is unable to estimate the hemodynamic significance of a lesion. Advances in computed tomography (CT)-based diagnostic techniques, for example, CT-derived fractional flow reserve and CT perfusion, have helped transform CCTA primarily from an anatomic assessment tool to a technique that is able to provide both anatomic and functional information for a stenosis. With the results of the ISCHEMIA trial published in 2019, these advanced techniques can elevate CCTA into the role of a better gatekeeper for decision-making and can help guide referral for invasive management. In this article, we review the principles, limitations, diagnostic performance, and clinical utility of these 2 functional CT-based techniques in the evaluation of vessel-specific and lesion-specific ischemia.

Detecting lesion-specific ischemia in patients with coronary artery disease with computed tomography fractional flow reserve measured at different sites

OBJECTIVES

Whether a stenosis can cause hemodynamic lesion-specific ischemia is critical for the treatment decision in patients with coronary artery disease (CAD). Based on coronary computed tomography angiography (CCTA), CT fractional flow reserve (FFR_CT) can be used to assess lesion-specific ischemia. The selection of an appropriate site along the coronary artery tree is vital for measuring FFR_CT. However the optimal site to measure FFR_CT for a target stenosis remains to be adequately determined. The purpose of this study was to determine the optimal site to measure FFR_CT for a target lesion in detecting lesion-specific ischemia in CAD patients by evaluating the performance of FFR_CT measured at different sites distal to the target lesion in detecting lesion-specific ischemia with FFR measured with invasive coronary angiography (ICA) as reference standard.

METHODS

In this single-center retrospective cohort study, a total of 401 patients suspected of having CAD underwent invasive ICA and FFR between March 2017 and December 2021 were identified. 52 patients having both CCTA and invasive FFR within 90 days were enrolled. Patients with vessels 30%-90% diameter stenosis as determined by ICA were referred to invasive FFR evaluation, which was performed 2-3 cm distal to the stenosis under the condition of hyperemia. For each vessel with 30%-90% diameter stenosis, if only one stenosis was present, this stenosis was selected as the target lesion; if serial stenoses were present, the stenosis most distal to the vessel end was chosen as the target lesion. FFR_CT was measured at four sites: 1 cm, 2 cm, and 3 cm distal to the lower border of the target lesion (FFR_CT-1 cm, FFR_CT-2 cm, FFR_CT-3 cm), and the lowest FFR_CT at the distal vessel tip (FFR_CT-lowest). The normality of quantitative data was assessed using the Shapiro-Wilk test. Pearson's correlation analysis and Bland-Altman plots were used for assessing the correlation and difference between invasive FFR and FFR_CT. Correlation coefficients derived from Chi-suqare test were used to assess the correlation between invasive FFR and the cominbaiton of FFR_CT measred at four sites. The performances of significant obstruction stenosis (diameter stenosis ≥ 50%) at CCTA and FFR_CT measured at the four sites and their combinations in diagnosing lesion-specific ischemia were evaluated by receiver-operating characteristic (ROC) curves using invasive FFR as the reference standard. The areas under ROC curves (AUCs) of CCTA and FFR_CT were compared by the DeLong test.

RESULTS

A total of 72 coronary arteries in 52 patients were included for analysis. Twenty-five vessels (34.7%) had lesion-specific ischemia detected by invasive FFR and 47 vesseles (65.3%) had no lesion-spefifice ischemia. Good correlation was found between invasive FFR and FFR_CT-2 cm and FFR_CT-3 cm (r = 0.80, 95% CI, 0.70 to 0.87, p < 0.001; r = 0.82, 95% CI, 0.72 to 0.88, p < 0.001). Moderate correlation was found between invasive FFR and FFR_CT-1 cm and FFR_CT-lowest (r = 0.77, 95% CI, 0.65 to 0.85, p < 0.001; r = 0.78, 95% CI, 0.67 to 0.86, p < 0.001). FFR_CT-1 cm + FFR_CT-2 cm, FFR_CT-2 cm + FFR_CT-3 cm, FFR_CT-3 cm + FFR_CT-lowest, FFR_CT-1 cm + FFR_CT-2 cm + FFR_CT-3 cm, and FFR_CT-2 cm + FFR_CT-3 cm + FFR_CT-lowest were correatled with invasive FFR (r = 0.722; 0.722; 0.701; 0.722; and 0.722, respectively; p < 0.001 for all). Bland-Altman plots revealed a mild difference between invasive FFR and the four FFR_CT (invasive FFR vs. FFR_CT-1 cm, mean difference -0.0158, 95% limits of agreement: -0.1475 to 0.1159; invasive FFR vs. FFR_CT-2 cm, mean difference 0.0001, 95% limits of agreement: -0.1222 to 0.1220; invasive FFR vs. FFR_CT-3 cm, mean difference 0.0117, 95% limits of agreement: -0.1085 to 0.1318; and invasive FFR vs. FFR_CT-lowest, mean difference 0.0343, 95% limits of agreement: -0.1033 to 0.1720). AUCs of CCTA, FFR_CT-1 cm, FFR_CT-2 cm, FFR_CT-3 cm, and FFR_CT-lowest in detecting lesion-specific ischemia were 0.578, 0.768, 0.857, 0.856 and 0.770, respectively. All FFR_CT had a higher AUC than CCTA (all p < 0.05), FFR_CT-2 cm achieved the highest AUC at 0.857. The AUCs of FFR_CT-2 cm and FFR_CT-3 cm were comparable (p > 0.05). The AUCs were similar between FFR_CT-1 cm + FFR_CT-2 cm, FFR_CT-3 cm + FFR_CT-lowest and FFR_CT-2 cm alone (AUC = 0.857, 0.857, 0.857, respectively; p > 0.05 for all). The AUCs of FFR_CT-2 cm + FFR_CT-3 cm, FFR_CT-1 cm + FFR_CT-2 cm + FFR_CT-3 cm, FFR_CT-and 2 cm + FFR_CT-3 cm + FFR_CT-lowest (0.871, 0.871, 0.872, respectively) were slightly higher than that of FFR_CT-2 cm alone (0.857), but without significnacne differences (p > 0.05 for all).

CONCLUSIONS

FFR_CT measured at 2 cm distal to the lower border of the target lesion is the optimal measurement site for identifying lesion-specific ischemia in patients with CAD.

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.

Deep learning-based detection of functionally significant stenosis in coronary CT angiography

Patients with intermediate anatomical degree of coronary artery stenosis require determination of its functional significance. Currently, the reference standard for determining the functional significance of a stenosis is invasive measurement of the fractional flow reserve (FFR), which is associated with high cost and patient burden. To address these drawbacks, FFR can be predicted non-invasively from a coronary CT angiography (CCTA) scan. Hence, we propose a deep learning method for predicting the invasively measured FFR of an artery using a CCTA scan. The study includes CCTA scans of 569 patients from three hospitals. As reference for the functional significance of stenosis, FFR was measured in 514 arteries in 369 patients, and in the remaining 200 patients, obstructive coronary artery disease was ruled out by Coronary Artery Disease-Reporting and Data System (CAD-RADS) category 0 or 1. For prediction, the coronary tree is first extracted and used to reconstruct an MPR for the artery at hand. Thereafter, the coronary artery is characterized by its lumen, its attenuation and the area of the coronary artery calcium in each artery cross-section extracted from the MPR using a CNN. Additionally, characteristics indicating the presence of bifurcations and information indicating whether the artery is a main branch or a side-branch of a main artery are derived from the coronary artery tree. All characteristics are fed to a second network that predicts the FFR value and classifies the presence of functionally significant stenosis. The final result is obtained by merging the two predictions. Performance of our method is evaluated on held out test sets from multiple centers and vendors. The method achieves an area under the receiver operating characteristics curve (AUC) of 0.78, outperforming other works that do not require manual correction of the segmentation of the artery. This demonstrates that our method may reduce the number of patients that unnecessarily undergo invasive measurements.

Predictive role of novel echocardiographic parameter aortic velocity propagation, QRISK3 and Framingham risk score for presence and severity of CAD in Asian patients

Introduction: Despite having clinical relevance, arterial stiffness is neglected and not routinely used parameter for evaluation of atherosclerosis. This study aimed to investigate the predictive role of simple non-invasive echocardiographic index of aortic stiffness aortic velocity propagation (AVP), Framingham risk score (FHS) and QRISK3 score for presence and severity of CAD. Methods: This cross-sectional comparative study included 250 patients who required conventional coronary angiogram for stable CAD. The relationship of AVP, FHS and QRISK3 score with CAD were evaluated using spearman’s correlation, logistic regression analysis and ROC curve. Results: On logistic regression analysis, AVP, FHS and QRISK3 were found significant predictors for the presence and severity of CAD. Inverse correlation between AVP and presence of CAD, number of coronary vessels involved and severity of CAD was observed with P=0.001. AVP value≤78 cm/s predicted presence of CAD with 86.4% sensitivity and 84.6% specificity (P≤0.0001, AUC=0.948) and≤39 cm/s predicted severe CAD (Syntax score>22) with 66.7% sensitivity and 97.9% specificity (P≤0.0001, AUC=0.868). FHS value>10 predicted the presence of CAD with a sensitivity of 33.9% and specificity of 91 % (P=0.01, AUC=0.644). QRISK3value>13.4 predicted presence of CAD with 57.1% sensitivity and 87% specificity (P≤0.0001, AUC=0.788). Conclusion: Arterial stiffness parameter AVP is inversely associated with the presence and severity of CAD. AVP and QRISK3 score may be used as a simple bedside tool for risk stratification of patients suspected of having atherosclerotic CAD.

Comparison of diagnostic performance between dynamic versus static adenosine-stress myocardial CT perfusion to detect hemodynamically significant coronary artery stenosis: A prospective multicenter study

Myocardial computed tomography perfusion (CTP) imaging is a noninvasive method for detecting myocardial ischemia. This study aimed to compare the diagnostic performance of dynamic and static adenosine-stress CTPs for detecting hemodynamically significant coronary stenosis. We prospectively enrolled 42 patients (mean age, 59.7 ± 8.8 years; 31 males) with ≥40% coronary artery stenosis. All patients underwent dynamic CTP for adenosine stress. The static CTP was simulated by choosing the seventh dynamic dataset after the initiation of the contrast injection. Diagnostic performance was compared with invasive fractional flow reserve (FFR) <0.8 as the reference. Of the 125 coronary vessels in 42 patients, 20 (16.0%) in 16 (38.1%) patients were categorized as hemodynamically significant. Dynamic and static CTP yielded similar diagnostic accuracy (90.4% vs 88.8% using visual analysis, P = .558; 77.6% vs 80.8% using quantitative analysis, P = .534; 78.4% vs 82.4% using combined visual and quantitative analyses, P = .426). The diagnostic accuracy of combined coronary computed tomography angiography (CCTA) and dynamic CTP (89.6% using visual analysis, P = .011; 88.8% using quantitative analysis, P = .018; 89.6% using combined visual and quantitative analyses, P = .011) and that of combined CCTA and static CTP (88.8% using visual analysis, P = .018; 90.4% using quantitative analysis, P = .006; 91.2% using combined visual and quantitative analyses, P = .003) were significantly higher than that of CCTA alone (77.6%). Dynamic CTP and static CTP showed similar diagnostic performance in the detection of hemodynamically significant stenosis.

Even chained acylcarnitines predict long-term cardiovascular prognosis in patients with chest pain and non-obstructive coronary artery disease

Background

Acylcarnitines are essential for mitochondrial fatty acid oxidation. Earlier studies suggest that impaired energy metabolism may be implicated in the pathogenesis of microvascular angina. We explored metabolites from the carnitine pathway as predictors of cardiovascular disease (CVD) - and all-cause mortality among patients with non-obstructive coronary artery disease (NOCAD).

Methods

A total of 1046 patients with suspected stable coronary syndrome underwent coronary angiography during 2000–2004, with findings of NOCAD. Serum levels of 8 selected carnitine metabolites were analyzed through liquid chromatography tandem mass spectrometry. Associations with CVD- and all-cause mortality were assessed by multivariable Cox regression models.

Results

Median age at inclusion was 57 years. 51.5% were men. During median (25th- 75th percentiles), 14.1 (13.2–15.4) years of follow-up, 5.7% of the participants died from CVD and the incidence of all-cause mortality was 17.3%. Serum acetyl, octanoyl- and palmitoylcarnitine predicted CVD mortality with multivariable HR and 95% CI (per SD increment log transformed) of 1.36 (1.01–1.83), 1.49 (1.15–1.93) and 2.07 (1.49–2.85), p ≤ 0.04, respectively. Higher serum acetyl- and palmitoylcarnitines were also associated with increased risk of all-cause mortality (HR (95% CI): 1.27 (1.01–1.50), and 1.51 (1.26–1.81), p ≤ 0.007. Baseline levels of the precursors trimethyllysine and ƴ-butyrobetaine, carnitine or the odd chained propionylcarnitine and (iso)valerylcarnitine were not associated with adverse outcomes.

Conclusion

Elevated serum even-chained acylcarnitines predicted adverse long-term prognosis in NOCAD. The strongest risk estimates were observed for palmitoylcarnitine, which predicted both CVD- and all-cause mortality after extensive multivariable adjustments. Underlying pathomechanisms should be further elucidated.

Performance of Hybrid Imaging in the Diagnosis of Coronary Artery Disease

Single-photon emission computed tomography (SPECT) and computed tomography coronary angiography (CTCA) are usually performed independently in patients with suspected coronary artery disease. We assessed the hypothesis that hybrid SPECT/CTCA imaging results in higher diagnostic accuracy than either method alone, particularly in cases presenting with high levels of coronary calcification. A total of 243 major coronary vessels in 81 patients with known or suspected coronary artery disease were screened using SPECT with semiconductor detectors and CTCA with 256-detector row computed tomography. Patients who were diagnosed with myocardial ischemia underwent coronary angiography. Coronary angiography results were defined as positive for stenosis when the stenosis diameter was >70% or fractional flow reserve was <0.8. These data were then compared with a fused image of the SPECT and CTCA datasets generated using a dedicated workstation. To detect significant coronary artery stenosis, the respective sensitivity, specificity, and accuracy were 73%, 61%, and 67% with SPECT alone, 96%, 44%, and 67% with CTCA alone, and 95%, 75%, and 84% with hybrid imaging. Moreover, hybrid imaging allowed the accurate diagnosis of 47 vessels with severe calcification that CTCA alone could not evaluate correctly. Hybrid imaging shows greater diagnostic accuracy than single-modality evaluation through more comprehensive information on potential coronary stenosis and its hemodynamic significance.

Improved Functional Assessment of Ischemic Severity Using 3D Printed Models

Objective

To develop a novel in vitro method for evaluating coronary artery ischemia using a combination of non-invasive coronary CT angiograms (CCTA) and 3D printing (FFR_3D).

Methods

Twenty eight patients with varying degrees of coronary artery disease who underwent non-invasive CCTA scans and invasive fractional flow reserve (FFR) of their epicardial coronary arteries were included in this study. Coronary arteries were segmented and reconstructed from CCTA scans using Mimics (Materialize). The segmented models were then 3D printed using a Carbon M1 3D printer with urethane methacrylate (UMA) family of rigid resins. Physiological coronary circulation was modeled in vitro as flow-dependent stenosis resistance in series with variable downstream resistance. A range of physiological flow rates (Q) were applied using a peristaltic steady flow pump and titrated with a flow sensor. The pressure drop (ΔP) and the pressure ratio (P_d/P_a) were assessed for patient-specific aortic pressure (P_a) and differing flow rates (Q) to evaluate FFR_3D using the 3D printed model.

Results

There was a good positive correlation (r = 0.87, p < 0.0001) between FFR_3D and invasive FFR. Bland-Altman analysis revealed a good concordance between the FFR_3D and invasive FFR values with a mean bias of 0.02 (limits of agreement: −0.14 to 0.18; p = 0.2).

Conclusions

3D printed patient-specific models can be used in a non-invasive in vitro environment to quantify coronary artery ischemia with good correlation and concordance to that of invasive FFR.

Diagnostic accuracy of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) in patients before liver transplantation using CT-FFR machine learning algorithm

OBJECTIVES

Liver transplantation (LT) is associated with high stress on the cardiovascular system. Ruling out coronary artery disease (CAD) is an important part of evaluation for LT. The aim of our study was to assess whether CT-derived fractional flow reserve (CT-FFR) allows for differentiation of hemodynamically significant and non-significant coronary stenosis in patients evaluated for LT.

METHODS

In total, 201 patients undergoing LT evaluation were included in the study. The patients received coronary computed tomography angiography (CCTA) to rule out CAD and invasive coronary angiography (ICA) to further evaluate coronary lesions found in CCTA if a significant (≥ 50 % on CCTA) stenosis was suspected. CT-FFR was computed from CCTA datasets using a machine learning-based algorithm and compared to ICA as a standard of reference. Coronary lesions with CT-FFR ≤ 0.80 were defined as hemodynamically significant.

RESULTS

In 127 of 201 patients (63%), an obstructive CAD was ruled out by CCTA. In the remaining 74 patients (37%), at least one significant stenosis was suspected in CCTA. Compared to ICA, sensitivity, specificity, PPV, and NPV of the CT-FFR measurements were 71% (49-92%), 90% (82-98%), 67% (45-88%), and 91% (84-99%), respectively. The diagnostic accuracy was 85% (85-86%). In 69% of cases (52 of 75 lesions), additional analysis by CT-FFR correctly excluded the hemodynamic significance of the stenosis.

CONCLUSIONS

Machine learning-based CT-FFR seems to be a very promising noninvasive approach for exclusion of hemodynamic significant coronary stenoses in patients undergoing evaluation for LT and could help to reduce the rate of invasive coronary angiography in this high-risk population.

KEY POINTS

• Machine learning-based computed tomography-derived fractional flow reserve (CT-FFR) seems to be a very promising noninvasive approach for exclusion of hemodynamic significance of coronary stenoses in patients undergoing evaluation for liver transplantation and could help to reduce the rate of invasive coronary angiography in this high-risk population.

Prediction of multivessel coronary artery disease and candidates for stress-only imaging using multivariable models with myocardial perfusion imaging

Purpose

Selecting patients with coronary multivessel disease (MVD) or no stenosis using myocardial perfusion imaging (MPI) is challenging. We aimed to create a model to predict MVD using a combination of quantitative MPI values and background factors of patients. We also assessed whether patients in the same database could be selected who do not require rest studies (stress-only imaging).

Methods

We analyzed data from 1001 patients who had been assessed by stress MPI at 12 centers and 463 patients who had not undergone revascularization in Japan. Quantitative values based on MPI were obtained using cardioREPO software, which included myocardial perfusion defect scores, left ventricular ejection fractions and volumes. Factors in MPI and clinical backgrounds that could predict MVD were investigated using univariate and multivariate analyses. We also investigated whether stress data alone could predict patients without coronary stenosis to identify candidates for stress-only imaging.

Results

We selected summed stress score (SSS), rest end-diastolic volume, and hypertension to create a predictive model for MVD. A logistic regression model was created with an area under the receiver operating characteristics curve (AUC) of 0.825. To more specifically predict coronary three-vessel disease, the AUC was 0.847 when SSS, diabetes, and hypertension were selected. The mean probabilities of abnormality based on the MVD prediction model were 12%, 24%, 40%, and 51% for no-, one-, two-, and three-vessel disease, respectively (p < 0.0001). For the model to select patients with stress-only imaging, the AUC was 0.78 when the model was created using SSS, stress end-systolic volume and the number of risk factors (diabetes, hypertension, chronic kidney disease, and a history of smoking).

Conclusion

A model analysis combining myocardial SPECT and clinical data can predict MVD, and can select patients for stress-only tests. Our models should prove useful for clinical applications.

Health economics-based verification of functional myocardial ischemia evaluation of stable coronary artery disease in Japan: A long-term longitudinal study using propensity score matching

BACKGROUND

The procedural numbers and medical costs of percutaneous coronary intervention (PCI), mainly elective PCI, have been increasing in Japan. Owing to increased interest in the appropriateness of coronary revascularization, we conducted this medical economics-based evaluation of testing and diagnosis of stable coronary artery disease (CAD).

METHODS AND RESULTS

We reviewed patients' medical insurance data to identify stable CAD patients who underwent coronary computed tomography angiography, cardiac single-photon emission computed tomography, coronary angiography, or fractional flow reserve. Subjects were divided into anatomical and functional evaluation groups according to the modality of testing, and background factors were matched by propensity score. The endpoints were major adverse cardiovascular events (MACE), life years (LYs), medical costs, and cost-effectiveness analysis (CEA). The observations were performed for 36 months. MACE, medical costs, and CEA of the functional group in the overall category were trending to be better than the anatomical group (MACE, P = .051; medical costs: 3,105 US$ vs 4,430 US$, P = .007; CEA: 2,431 US$/LY vs 2,902 US$/LY, P = .043).

CONCLUSIONS

The functional evaluation approach improved long-term clinical outcomes and reduced cumulative medical costs. As a result, the modality composition of functional myocardial ischemia evaluation was demonstrated to offer superior cost-effectiveness in stable CAD.

Synergistic prognostic value of coronary distensibility index and fractional flow reserve based cCTA for major adverse cardiac events in patients with Coronary artery disease

BACKGROUND

Coronary distensibility index (CDI), as an early predictor of cardiovascular diseases, has the potential to complement coronary computed tomography angiography (cCTA)-derived fractional flow reserve (CT-FFR) for predicting major adverse cardiac events (MACEs). Thus, the prognostic value of CT-FFR combined with CDI for MACEs is worth exploring.

METHODS

Patients with a moderate or severe single left anterior descending coronary artery stenosis were included and underwent FFR and CDI analysis based on cCTA, followed up at least 1 year, and recorded MACEs. Multivariate logistic regression analysis was performed to determine independent predictors of MACEs. The area under of receiver operating characteristic (ROC) curve was used to evaluated evaluate the diagnostic performance of CT-FFR, CDI, and a combination of the two.

RESULTS

All the vessel-specific data were from LAD. 150 patients were analysed. 55 (37%) patients experienced MACEs during follow-up. Patients with CT-FFR ≤ 0.8 had higher percentage of MACEs compared with CT-FFR > 0.8 (56.3% vs.7.3%, p < 0.05). Patients' CDI was significantly decreased in MACEs group compared with non-MACEs group (p < 0.05). Multivariate analysis revealed that diabetes (p = 0.025), triglyceride (p = 0.015), CT-FFR ≤ 0.80 (p = 0.038), and CDI (p < 0.001) are independent predictors of MACEs. According to ROC curve analysis, CT-FFR combined CDI showed incremental diagnostic performance over CT-FFR alone for prediction of MACEs (AUC = 0.831 vs. 0.656, p = 0.0002).

CONCLUSION

Our study provides initial evidence that combining CDI with CT-FFR shows incremental discriminatory power for MACEs over CT-FFR alone, independent of clinical risk factors. Diabetes and triglyceride are also associated with MACEs.

The Perivascular Fat Attenuation Index Improves the Diagnostic Performance for Functional Coronary Stenosis

Background: Coronary computed tomography angiography (CCTA) is an established first-line test in the investigation of patients with suspected coronary artery disease (CAD), while the perivascular fat attenuation index (FAI) derived from CT seems to be a feasible and efficient tool for the identification of ischemia. The association between the FAI and lesion-specific ischemia as assessed by fractional flow reserve (FFR) remains unclear. Methods: In a total of 261 patients, 294 vessels were assessed for CCTA stenosis, vessel-specific FAI, lesion-specific FAI, and plaque characteristics. The diagnostic accuracies of each parameter and the combined approach were analyzed via the receiver operating characteristic curve (ROC) with FFR as the reference standard. The determinants of FAI were statistically analyzed. Results: The cutoff values of vessel-specific FAI and lesion-specific FAI scores calculated according to the Youden index were −70.97 and −73.95 HU, respectively. No significant differences were noted between them; however, they exhibited a strong correlation. No significant differences were noted between the area under the curve (AUC) scores of vessel-specific FAI (0.677), lesion-specific FAI (0.665), and CCTA (0.607) (p > 0.05 for all) results. The addition of two FAI measures to the CCTA showed improvements in the discrimination (AUC) and reclassification ability (relative integrated discrimination improvement (IDI) and category-free net reclassification index (NRI)), vessel-specific FAI (AUC, 0.696; NRI, 49.6%; IDI, 5.9%), and lesion-specific FAI scores (AUC, 0.676; NRI, 43.3%; IDI, 5.4%); (p < 0.01 for all). Multivariate analysis revealed that low-attenuation plaque (LAP) volume was an independent predictor of two FAI measures. Conclusion: The combined approach of adding vessel-specific FAI or lesion-specific FAI scores could improve the identification of ischemia compared with CCTA alone. The LAP volume was the independent risk factor for both tools.

Myocardial Strain Imaging With Electrocardiogram-Gated and Coherent Compounding for Early Diagnosis of Coronary Artery Disease

Myocardial elastography (ME) is an ultrasound-based technique that uses radiofrequency signals for 2-D cardiac motion tracking and strain imaging at a high frame rate. Early diagnosis of coronary artery disease (CAD) is critical for timely treatment and improvement of patient outcome. The objective of this study was to assess the performance of ME radial and circumferential strains in the detection and characterization of CAD in patients. In this study, 86 patients suspected of CAD were imaged with ME prior to invasive coronary angiography (ICA). End-systolic radial and circumferential left ventricular strains were estimated in all patients in each of their perfusion territories: left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA). ME radial strains were capable of differentiating the obstructive CAD group (55.3 ± 29.8%) from the non-obstructive CAD (72.5 ± 46.8%, p < 0.05) and no CAD groups (73.4 ± 30.4%, p < 0.05) in the RCA territory. ME circumferential strains were capable of differentiating the obstructive CAD group (-3.1 ± 7.5%) from the non-obstructive CAD (-7.2 ± 6.8%, p < 0.05) and normal (-6.9 ± 8.0%, p < 0.05) groups in the LAD territory and to differentiate the normal group (-17.1 ± 8.2%) from the obstructive (-12.8 ± 7.2%, p < 0.05) and non-obstructive CAD (-13.6 ± 8.5%, p < 0.05) groups in the RCA territory. ME circumferential strain performed better than ME radial strain in differentiating normal, non-obstructive and obstructive perfusion territories. In the LCX territory, both ME radial and circumferential strains decreased when the level of stenosis was higher. However, it was not statistically significant. The findings presented herein indicate that ME radial and circumferential estimation obtained from ECG-gated and compounded acquisitions is a promising tool for early, non-invasive and radiation-free detection of CAD in patients.

Pericoronary fat attenuation index and coronary plaque quantified from coronary computed tomography angiography identify ischemia-causing lesions

BACKGROUND

The association between pericoronary fat attenuation index (FAI), plaque characteristics, and lesion-specific ischemia identified by fractional flow reserve (FFR) remains unclear.

METHODS

Coronary computed tomography angiography (CCTA) stenosis, FAI, plaque characteristics, FFR derived from computed tomography (FFR_CT) and FFR were assessed in 280 vessels of 247 patients. Stenosis ≥50% was considered obstructive. Optimal thresholds of FAI and plaque variables were defined by the area under the receiver-operating characteristics curve (AUC) analysis. Ischemia was defined by FFR ≤ 0.80.

RESULTS

FAI ≥ -71.9 HU, low-attenuation plaque (LAP) ≥ 49.62 mm³ and aggregate plaque volume (APV) ≥ 28.91% predicted ischemia independent of other plaque characteristics. The addition of FAI ≥ -71.9 HU improved discrimination (AUC, 0.720 vs. 0.674, P = 0.035) and reclassification abilities (category-free net reclassification index [NRI], 0.470, P < 0.001; relative integrated discrimination improvement [IDI], 0.047, P < 0.001) of ischemia compared with stenosis evaluation alone, with further discrimination (AUC, 0.772 vs. 0.720, P = 0.028) and reclassification abilities (NRI, 0.385, P = 0.001; relative IDI, 0.077, P < 0.001) of ischemia by adding information regarding LAP ≥49.62 mm³ + APV ≥ 28.91%. And the diagnostic performance of combination approach was comparable to that of FFR_CT alone (AUC, 0.772 vs. 0.762, P = 0.771).

CONCLUSIONS

Stenosis severity, FAI, plaque characteristics predicted lesion-specific ischemia. The combination of FAI and plaque assessment improved the discrimination of ischemia compared with stenosis assessment alone.

Dose Reduction of Dynamic Computed Tomography Myocardial Perfusion Imaging by Tube Voltage Change: Investigation in a Swine Model

Background

It is unclear whether tube voltage influences the measurement of perfusion parameters. The present study sought to evaluate the influence of tube voltage change on myocardial blood flow (MBF) measurements in dynamic computed tomography myocardial perfusion imaging (CTP).

Methods and Results

Seven swine [mean weight 55.8 kg ± 1.6 (standard deviation)] underwent rest and stress dynamic CTP with tube voltages of 100 and 70 kV. The image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), radiation dose and MBF value were compared. The 70 kV images had higher CT attenuation and higher image noise (27.9 ± 2.4 vs. 21.5 ± 1.9, P < 0.001) than the 100 kV images, resulting in a higher SNR (20.5 ± 1.6 vs. 15.6 ± 1.8, P < 0.001) and CNR (17.6 ± 1.5 vs. 12.4 ± 1.7, P < 0.001). Compared to the use of conventional 100 kV, 70 kV yielded an approximately 64.6% radiation dose reduction while generating comparable MBF values, both at rest (88.3 ± 14.9 ml/100 g/min vs. 85.6 ± 17.4 ml/100 g/min, P = 0.21) and stress (101.4 ± 21.5 ml/100 g/min vs. 99.6 ± 21.4 ml/100 g/min, P = 0.58) states.

Conclusion

Dynamic CTP using 70 kV instead of 100 kV does not substantially influence the MBF value but significantly reduces the radiation dose. Additional research is required to investigate the clinical significance of this change.

CT Fractional Flow Reserve: A Practical Guide to Application, Interpretation, and Problem Solving

CT fractional flow reserve (FFR_CT) is a physiologic simulation technique that models coronary flow from routine coronary CT angiography (CTA). To evaluate lesion-specific ischemia, FFR_CT is measured 2 cm distal to a stenotic lesion. FFR_CT greater than 0.8 is normal, 0.76-0.8 is borderline, and 0.75 or less is abnormal. FFR_CT should always be interpreted in correlation with clinical and anatomic coronary CTA findings. FFR_CT increases the specificity of coronary CTA in the evaluation of coronary artery disease, decreases the prevalence of nonobstructive disease in invasive coronary angiography (ICA), and helps with revascularization decisions and planning. Patients with intermediate-risk coronary anatomy at CTA and abnormal FFR_CT can undergo ICA and revascularization, whereas those with normal FFR_CT can be safely deferred from ICA. In borderline FFR_CT values, management is decided in the context of the clinical scenario, but many cases could be safely managed with medical treatment. There are some limitations and pitfalls of FFR_CT. Abnormal FFR_CT values can be seen in mild stenosis, and normal FFR_CTvalues can be seen in severe stenosis. Gradually decreasing or abnormal low FFR_CT values at the distal vessel without a proximal focal lesion could be due to diffuse atherosclerosis. Coronary stents, bypass grafts, coronary anomalies, coronary dissection, transcatheter aortic valve replacement, unstable angina, and acute or recent myocardial infarction are situations in which FFR_CT has not been validated and should not be used at this time. The authors provide a practical guide to the applications and interpretation of FFR_CT, focusing on common pitfalls and challenges. Online supplemental material is available for this article. ^©RSNA, 2022.

Stable patients with suspected myocardial ischemia: comparison of machine-learning computed tomography-based fractional flow reserve and stress perfusion cardiovascular magnetic resonance imaging to detect myocardial ischemia

BACKGROUND

Machine-Learning Computed Tomography-Based Fractional Flow Reserve (CT-FFRML) is a novel tool for the assessment of hemodynamic relevance of coronary artery stenoses. We examined the diagnostic performance of CT-FFRML compared to stress perfusion cardiovascular magnetic resonance (CMR) and tested if there is an additional value of CT-FFRML over coronary computed tomography angiography (cCTA).

METHODS

Our retrospective analysis included 269 vessels in 141 patients (mean age 67 ± 9 years, 78% males) who underwent clinically indicated cCTA and subsequent stress perfusion CMR within a period of 2 months. CT-FFRML values were calculated from standard cCTA.

RESULTS

CT-FFRML revealed no hemodynamic significance in 79% of the patients having ≥ 50% stenosis in cCTA. Chi2 values for the statistical relationship between CT-FFRML and stress perfusion CMR was significant (p < 0.0001). CT-FFRML and cCTA (≥ 70% stenosis) provided a per patient sensitivity of 88% (95%CI 64-99%) and 59% (95%CI 33-82%); specificity of 90% (95%CI 84-95%) and 85% (95%CI 78-91%); positive predictive value of 56% (95%CI 42-69%) and 36% (95%CI 24-50%); negative predictive value of 98% (95%CI 94-100%) and 94% (95%CI 90-96%); accuracy of 90% (95%CI 84-94%) and 82% (95%CI 75-88%) when compared to stress perfusion CMR. The accuracy of cCTA (≥ 50% stenosis) was 19% (95%CI 13-27%). The AUCs were 0.89 for CT-FFRML and 0.74 for cCTA (≥ 70% stenosis) and therefore significantly different (p < 0.05).

CONCLUSION

CT-FFRML compared to stress perfusion CMR as the reference standard shows high diagnostic power in the identification of patients with hemodynamically significant coronary artery stenosis. This could support the role of cCTA as gatekeeper for further downstream testing and may reduce the number of patients undergoing unnecessary invasive workup.

Diagnostic performance of AccuFFRangio in the functional assessment of coronary stenosis compared with pressure wire-derived fractional flow reserve

BACKGROUND

Non-invasive fractional flow reserve (FFR) has been increasingly used in the clinical workflow to assist clinical decision-making for percutaneous coronary intervention (PCI). This clinical study evaluates the diagnostic accuracy of coronary stenosis assessed by a non-invasive FFR analysis method (termed AccuFFRangio) based on invasive coronary angiography (ICA). It is a blinded, self-controlled, retrospective, and dual-center clinical investigation study.

METHODS

Coronary angiography data and the related information of 320 patients with 320 vessels were collected, and AccuFFRangio was used to assess the FFR for these patients. Compared with the wire-measured FFR values, we evaluated AccuFFRangio performance by its accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

The diagnostic accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRangio in identifying hemodynamically significant coronary stenosis were 93.3%, 92.6%, 93.5%, 84.3%, and 97.1%, respectively. The direct correlation between computed AccuFFRangio and measured FFR was 0.812 (P<0.001), and the area under the receiver operating characteristic curve (AUC) value of AccuFFRangio was 0.96.

CONCLUSIONS

This clinical study demonstrates the efficiency and accuracy of AccuFFRangio for clinical implementation when using invasive wire-measured FFR as a reference. Further validation is required in a large prospective multicenter study.

Predicting Chronic Myocardial Ischemia Using CCTA-Based Radiomics Machine Learning Nomogram

BACKGROUND

Coronary computed tomography angiography (CCTA) is a well-established non-invasive diagnostic test for the assessment of coronary artery diseases (CAD). CCTA not only provides information on luminal stenosis but also permits non-invasive assessment and quantitative measurement of stenosis based on radiomics.

PURPOSE

This study is aimed to develop and validate a CT-based radiomics machine learning for predicting chronic myocardial ischemia (MIS).

METHODS

CCTA and SPECT-myocardial perfusion imaging (MPI) of 154 patients with CAD were retrospectively analyzed and 94 patients were diagnosed with MIS. The patients were randomly divided into two sets: training (n = 107) and test (n = 47). Features were extracted for each CCTA cross-sectional image to identify myocardial segments. Multivariate logistic regression was used to establish a radiomics signature after feature dimension reduction. Finally, the radiomics nomogram was built based on a predictive model of MIS which in turn was constructed by machine learning combined with the clinically related factors. We then validated the model using data from 49 CAD patients and included 18 MIS patients from another medical center. The receiver operating characteristic curve evaluated the diagnostic accuracy of the nomogram based on the training set and was validated by the test and validation set. Decision curve analysis (DCA) was used to validate the clinical practicability of the nomogram.

RESULTS

The accuracy of the nomogram for the prediction of MIS in the training, test and validation sets was 0.839, 0.832, and 0.816, respectively. The diagnosis accuracy of the nomogram, signature, and vascular stenosis were 0.824, 0.736 and 0.708, respectively. A significant difference in the number of patients with MIS between the high and low-risk groups was identified based on the nomogram (P < .05). The DCA curve demonstrated that the nomogram was clinically feasible.

CONCLUSION

The radiomics nomogram constructed based on the image of CCTA act as a non-invasive tool for predicting MIS that helps to identify high-risk patients with coronary artery disease.

Change in Computed Tomography-Derived Fractional Flow Reserve Across the Lesion Improve the Diagnostic Performance of Functional Coronary Stenosis

Aims: This study sought to evaluate the diagnostic performance of change in computed tomography-derived fractional flow reserve (CT-FFR) across the lesion (ΔCT-FFR) for identifying ischemia lesions with FFR as the reference standard.

Methods: Patients who underwent coronary CT angiography (CCTA) and FFR measurement within 1 week from December 2018 to December 2019 were retrospectively enrolled. CT-FFR within 2 cm distal to the lesion, ΔCT-FFR and plaque characteristics were analyzed. The diagnostic accuracy of CCTA (coronary stenosis ≥ 50%), CT-FFR ≤ 0.80, and ΔCT-FFR ≥ 0.15 (based on the largest Youden index) were assessed with FFR as the reference standard. The relationship between plaque characteristics and ΔCT-FFR was analyzed.

Results: The specificity of ΔCT-FFR and CT-FFR were 70.8 and 67.4%, respectively, which were both higher than CCTA (39.3%) (both P &lt; 0.001), while there were no statistical significance in sensitivity among the three (84.5, 77.4, 88.1%, respectively; P = 0.08). The area under the curves (AUCs) of ΔCT-FFR and CT-FFR were 0.803 and 0.743, respectively, which were both higher than that of CCTA (0.637) (both P &lt; 0.05), and the AUC of ΔCT-FFR was higher than that of CT-FFR (P &lt; 0.001). Multivariable analysis showed that low-attenuation plaque (LAP) volume (odds ratio [OR], 1.006) and plaque length (OR, 1.021) were independently correlated with ΔCT-FFR (both P &lt; 0.05).

Conclusions: CT-FFR and ΔCT-FFR and here especially the ΔCT-FFR could improve the diagnostic performance of ischemia compared with CCTA alone. LAP volume and plaque length were the independent risk factors of ΔCT-FFR.

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.

Static CT myocardial perfusion imaging: image quality, artifacts including distribution and diagnostic performance compared to 82Rb PET

Background

Rubidium-82 positron emission tomography (⁸²Rb PET) MPI is considered a noninvasive reference standard for the assessment of myocardial perfusion in coronary artery disease (CAD) patients. Our main goal was to compare the diagnostic performance of static rest/ vasodilator stress CT myocardial perfusion imaging (CT-MPI) to stress/ rest ⁸²Rb PET-MPI for the identification of myocardial ischemia.

Methods

Forty-four patients with suspected or diagnosed CAD underwent both static CT-MPI and ⁸²Rb PET-MPI at rest and during pharmacological stress. The extent and severity of perfusion defects on PET-MPI were assessed to obtain summed stress score, summed rest score, and summed difference score. The extent and severity of perfusion defects on CT-MPI was visually assessed using the same grading scale. CT-MPI was compared with PET-MPI as the gold standard on a per-territory and a per-patient basis.

Results

On a per-patient basis, there was moderate agreement between CT-MPI and PET-MPI with a weighted 0.49 for detection of stress induced perfusion abnormalities. Using PET-MPI as a reference, static CT-MPI had 89% sensitivity (SS), 58% specificity (SP), 71% accuracy (AC), 88% negative predictive value (NPV), and 59% positive predictive value (PPV) to diagnose stress-rest perfusion deficits on a per-patient basis. On a per-territory analysis, CT-MPI had 73% SS, 65% SP, 67% AC, 90.8% NPV, and 34% PPV to diagnose perfusion deficits.

Conclusions

CT-MPI has high sensitivity and good overall accuracy for the diagnosis of functionally significant CAD using ⁸²Rb PET-MPI as the reference standard. CT-MPI may play an important role in assessing the functional significance of CAD especially in combination with CCTA.

Effect of Coronary Calcification Severity on Measurements and Diagnostic Performance of CT-FFR With Computational Fluid Dynamics: Results From CT-FFR CHINA Trial

Aims: To explore the effect of coronary calcification severity on the measurements and diagnostic performance of computed tomography-derived fractional flow reserve (FFR; CT-FFR).

Methods: This study included 305 patients (348 target vessels) with evaluable coronary calcification (CAC) scores from CT-FFR CHINA clinical trial. The enrolled patients all received coronary CT angiography (CCTA), CT-FFR, and invasive FFR examinations within 7 days. On both per-patient and per-vessel levels, the measured values, accuracy, and diagnostic performance of CT-FFR in identifying hemodynamically significant lesions were analyzed in all CAC score groups (CAC = 0, > 0 to <100, ≥ 100 to <400, and ≥ 400), with FFR as reference standard.

Results: In total, the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under receiver operating characteristics curve (AUC) of CT-FFR were 85.8, 88.7, 86.9, 87.8, 87.1%, 0.90 on a per-patient level and 88.3, 89.3, 89.5, 88.2, 88.9%, 0.88 on a per-vessel level, respectively. Absolute difference of CT-FFR and FFR values tended to elevate with increased CAC scores (CAC = 0: 0.09 ± 0.10; CAC > 0 to <100: 0.06 ± 0.06; CAC ≥ 100 to <400: 0.09 ± 0.10; CAC ≥ 400: 0.11 ± 0.13; p = 0.246). However, no statistically significant difference was found in patient-based and vessel-based diagnostic performance of CT-FFR among all CAC score groups.

Conclusion: This prospective multicenter trial supported CT-FFR as a viable tool in assessing coronary calcified lesions. Although large deviation of CT-FFR has a tendency to correlate with severe calcification, coronary calcification has no significant influence on CT-FFR diagnostic performance using the widely-recognized cut-off value of 0.8.

Additional value of deep learning computed tomographic angiography-based fractional flow reserve in detecting coronary stenosis and predicting outcomes

BACKGROUND

Deep learning (DL) has achieved great success in medical imaging and could be utilized for the non-invasive calculation of fractional flow reserve (FFR) from coronary computed tomographic angiography (CCTA) (CT-FFR).

PURPOSE

To examine the ability of a DL-based CT-FFR in detecting hemodynamic changes of stenosis.

MATERIAL AND METHODS

This study included 73 patients (85 vessels) who were suspected of coronary artery disease (CAD) and received CCTA followed by invasive FFR measurements within 90 days. The diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristics curve (AUC) were compared between CT-FFR and CCTA. Thirty-nine patients who received drug therapy instead of revascularization were followed for up to 31 months. Major adverse cardiac events (MACE), unstable angina, and rehospitalization were evaluated and compared between the study groups.

RESULTS

At the patient level, CT-FFR achieved 90.4%, 93.6%, 88.1%, 85.3%, and 94.9% in accuracy, sensitivity, specificity, PPV, and NPV, respectively. At the vessel level, CT-FFR achieved 91.8%, 93.9%, 90.4%, 86.1%, and 95.9%, respectively. CT-FFR exceeded CCTA in these measurements at both levels. The vessel-level AUC for CT-FFR also outperformed that for CCTA (0.957 vs. 0.599, P < 0.0001). Patients with CT-FFR ≤0.8 had higher rates of rehospitalization (hazard ratio [HR] 4.51, 95% confidence interval [CI] 1.08-18.9) and MACE (HR 7.26, 95% CI 0.88-59.8), as well as a lower rate of unstable angina (HR 0.46, 95% CI 0.07-2.91).

CONCLUSION

CT-FFR is superior to conventional CCTA in differentiating functional myocardial ischemia. In addition, it has the potential to differentiate prognoses of patients with CAD.