The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning-based FFRCT, or high-risk plaque features?

Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography: The ACCURATE-CT Study

BACKGROUND

ArteryFlow Technology (AccuFFRct) is a novel noninvasive method for calculating fractional flow reserve (FFR) from coronary computed tomography angiography (CCTA). The accuracy of AccuFFRct has not been adequately assessed.

OBJECTIVES

This study sought to evaluate the diagnostic performance of AccuFFRct in detecting lesion-specific ischemia.

METHODS

This prospective study enrolled 339 patients with 404 vessels. CCTA-derived FFR was calculated using an on-site computational fluid dynamics-based method and compared with invasive FFR. The performance of AccuFFRct was comprehensively analyzed in all lesions and subgroups, including "gray zone" lesions, various lesion classifications, clinical presentations, stenosis severities, and lesion locations.

RESULTS

Using FFR ≤0.80 as a reference standard, the overall diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for AccuFFRct were 90.6% (95% CI: 87.3%-93.3%), 90.9% (95% CI: 85.1%-94.9%), 90.4% (95% CI: 86.1%-93.8%), 85.3% (95% CI: 79.8%-89.5%), and 94.2% (95% CI: 90.8%-96.4%), respectively. Good correlation and agreement were found between the computed AccuFFRct and measured FFR. AccuFFRct showed superior discrimination ability to CCTA (AUC: 0.93 [95% CI: 0.89-0.95] vs 0.77 [95% CI: 0.72-0.81]; P < 0.001) and quantitative coronary angiography (AUC: 0.93 [95% CI: 0.89-0.95] vs 0.89 [95% CI: 0.85-0.92]; P = 0.048) for identifying functionally significant stenosis. Notably, AccuFFRct maintained high diagnostic accuracy across the spectrum of lesion classifications, clinical presentations, stenosis severities, lesion locations, and in the gray zone. Furthermore, in the cohort with ≥70% stenosis, AccuFFRct could significantly reduce the rate of un-necessary invasive tests (33.1% vs 6.6%; P < 0.001).

CONCLUSIONS

The study confirms the potential of AccuFFRct as a noninvasive alternative to invasive FFR for detecting ischemia in coronary artery disease and to risk stratify patients. The results highlight AccuFFRct's robust diagnostic ability across a wide range of lesion classifications, clinical presentations, stenosis severities, lesion locations, and in the gray zone. (Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography [ACCURATE-CT]; NCT04426396).

A predictive model of 30-day mortality in patients with acute type A aortic dissection

OBJECTIVE

Acute type A aortic dissection (ATAAD) is a life-threatening cardiovascular disease that requires an effective predictive model to predict and assess a patient's risk of death. Our study aimed to construct a model for predicting the risk of 30-day death in patients with ATAAD and the prediction accuracy of the German Registry of Acute Aortic Dissection Type A (GERAADA) Score and the European System for Cardiac Operative Risk Evaluation (EuroSCORE II) was verified.

MATERIALS AND METHODS

Between June 2019 and June 2023, 109 patients with ATAAD underwent surgical treatment at our hospital (35 in the death group and 74 in the survival group). The differences in image parameters between the two groups were compared. Search for independent predictors and develop models that predict 30-day mortality in patients with ATAAD. GERAADA Score and EuroSCORE II were retrospectively calculated and indicated mortality was assessed using the receiver operating characteristic (ROC) curve.

RESULTS

Logistic regression analysis showed that ascending aortic length and pericardial effusion were independent predictors of death within 30 days in patients with ATAAD. We constructed four models, GERAADA Score (Model 1), EuroSCORE II (Model 2), Model 1, ascending aorta length, and pericardial effusion (Model 3), and Model 2, ascending aorta length, and pericardial effusion (Model 4). The area under the curve (AUC = 0.832) of Model 3 was significantly different from those of Models 1 (AUC = 0.683) and 2 (AUC = 0.599), respectively (p < 0.05, DeLong test).

CONCLUSIONS

Adding ascending aorta length and pericardial effusion to the GERAADA Score can improve the predictive power of 30-day mortality in patients with ATAAD.

Differential sensitivities to blood pressure variations in internal carotid and intracranial arteries: a numerical approach to stroke prediction

Stroke remains a global health concern, necessitating early prediction for effective management. Atherosclerosis-induced internal carotid and intra cranial stenosis contributes significantly to stroke risk. This study explores the relationship between blood pressure and stroke prediction, focusing on internal carotid artery (ICA) branches: middle cerebral artery (MCA), anterior cerebral artery (ACA), and their role in hemodynamics. Computational fluid dynamics (CFD) informed by the Windkessel model were employed to simulate patient-specific ICA models with introduced stenosis. Central to our investigation is the impact of stenosis on blood pressure, flow velocity, and flow rate across these branches, incorporating Fractional Flow Reserve (FFR) analysis. Results highlight differential sensitivities to blood pressure variations, with M1 branch showing high sensitivity, ACA moderate, and M2 minimal. Comparing blood pressure fluctuations between ICA and MCA revealed heightened sensitivity to potential reverse flow compared to ICA and ACA comparisons, emphasizing MCA's role. Blood flow adjustments due to stenosis demonstrated intricate compensatory mechanisms. FFR emerged as a robust predictor of stenosis severity, particularly in the M2 branch. In conclusion, this study provides comprehensive insights into hemodynamic complexities within major intracranial arteries, elucidating the significance of blood pressure variations, flow attributes, and FFR in stenosis contexts. Subject-specific data integration enhances model reliability, aiding stroke risk assessment and advancing cerebrovascular disease understanding.

Global trans-lesional computed tomography-derived fractional flow reserve gradient is associated with clinical outcomes in diabetic patients with non-obstructive coronary artery disease

BACKGROUND

Coronary computed tomography angiography (CCTA)-derived fractional flow reserve (CT-FFR) enables physiological assessment and risk stratification, which is of significance in diabetic patients with nonobstructive coronary artery disease (CAD). We aim to evaluate prognostic value of the global trans-lesional CT-FFR gradient (GΔCT-FFR), a novel metric, in patients with diabetes without flow-limiting stenosis.

METHODS

Patients with diabetes suspected of having CAD were prospectively enrolled. GΔCT-FFR was calculated as the sum of trans-lesional CT-FFR gradient in all epicardial vessels greater than 2 mm. Patients were stratified into low-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR < 0.20), high-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR ≥ 0.20), and flow-limiting group (CT-FFR ≤ 0.75). Discriminant ability for major adverse cardiovascular events (MACE) prediction was compared among 4 models [model 1: Framingham risk score; model 2: model 1 + Leiden score; model 3: model 2 + high-risk plaques (HRP); model 4: model 3 + GΔCT-FFR] to determine incremental prognostic value of GΔCT-FFR.

RESULTS

Of 1215 patients (60.1 ± 10.3 years, 53.7% male), 11.3% suffered from MACE after a median follow-up of 57.3 months. GΔCT-FFR (HR: 2.88, 95% CI 1.76-4.70, P < 0.001) remained independent risk factors of MACE in multivariable analysis. Compared with the low-gradient without flow-limiting group, the high-gradient without flow-limiting group (HR: 2.86, 95% CI 1.75-4.68, P < 0.001) was associated with higher risk of MACE. Among the 4 risk models, model 4, which included GΔCT-FFR, showed the highest C-statistics (C-statistics: 0.75, P = 0.002) as well as a significant net reclassification improvement (NRI) beyond model 3 (NRI: 0.605, P < 0.001).

CONCLUSIONS

In diabetic patients with non-obstructive CAD, GΔCT-FFR was associated with clinical outcomes at 5 year follow-up, which illuminates a novel and feasible approach to improved risk stratification for a global hemodynamic assessment of coronary artery in diabetic patients.

Diagnosis of coronary artery disease in patients with type 2 diabetes mellitus based on computed tomography and pericoronary adipose tissue radiomics: a retrospective cross-sectional study

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) are highly susceptible to cardiovascular disease, and coronary artery disease (CAD) is their leading cause of death. We aimed to assess whether computed tomography (CT) based imaging parameters and radiomic features of pericoronary adipose tissue (PCAT) can improve the diagnostic efficacy of whether patients with T2DM have developed CAD.

METHODS

We retrospectively recruited 229 patients with T2DM but no CAD history (146 were diagnosed with CAD at this visit and 83 were not). We collected clinical information and extracted imaging manifestations from CT images and 93 radiomic features of PCAT from all patients. All patients were randomly divided into training and test groups at a ratio of 7:3. Four models were constructed, encapsulating clinical factors (Model 1), clinical factors and imaging indices (Model 2), clinical factors and Radscore (Model 3), and all together (Model 4), to identify patients with CAD. Receiver operating characteristic curves and decision curve analysis were plotted to evaluate the model performance and pairwise model comparisons were performed via the DeLong test to demonstrate the additive value of different factors.

RESULTS

In the test set, the areas under the curve (AUCs) of Model 2 and Model 4 were 0.930 and 0.929, respectively, with higher recognition effectiveness compared to the other two models (each p < 0.001). Of these models, Model 2 had higher diagnostic efficacy for CAD than Model 1 (p < 0.001, 95% CI [0.129-0.350]). However, Model 4 did not improve the effectiveness of the identification of CAD compared to Model 2 (p = 0.776); similarly, the AUC did not significantly differ between Model 3 (AUC = 0.693) and Model 1 (AUC = 0.691, p = 0.382). Overall, Model 2 was rated better for the diagnosis of CAD in patients with T2DM.

CONCLUSIONS

A comprehensive diagnostic model combining patient clinical risk factors with CT-based imaging parameters has superior efficacy in diagnosing the occurrence of CAD in patients with T2DM.

Distribution of FFRCT in single obstructive coronary stenosis and predictors for major adverse cardiac events: a propensity score matching study

Background

Fractional flow reserve derived from computed tomography (FFRCT) has been demonstrated to improve identification of lesion-specific ischemia significantly compared with coronary computed tomography angiography (CCTA). It remains unclear whether the distribution of FFRCT values in obstructive stenosis between patients who received percutaneous coronary intervention (PCI) or not in routine clinical practice, as well as its association with clinical outcome. This study aims to reveal the distribution of FFRCT value in patients with single obstructive coronary artery stenosis and explored the independent factors for predicting major adverse cardiac events (MACE).

Methods

This was a retrospective study of adults with non-ST-segment elevation acute coronary syndrome undergoing FFRCT assessment by using CCTA data from January 1, 2016 to December 31, 2020. Propensity score matching (PSM) method was used to account for patient selection bias. The risk factors for predicting MACE were evaluated by a Cox proportional hazards regression analysis.

Results

Overall, 655 patients with single obstructive (≥ 50%) stenosis shown on CCTA were enrolled and divided into PCI group (279 cases) and conservative group (376 cases) according to treatment strategy. The PSM cohort analysis demonstrated that the difference in history of unstable angina, Canadian Cardiovascular Society Class (CCSC) and FFRCT between PCI group (188 cases) and conservative group (315 cases) was statistically significant, with all P values < 0.05, while the median follow-up time between them was not statistically significant (24 months vs. 22.5 months, P = 0.912). The incidence of MACE in PCI group and conservative group were 14.9% (28/188) and 23.5% (74/315) respectively, P = 0.020. Multivariate analysis of Cox proportional hazards regression revealed that history of unstable angina (adjusted odds ratio (adjOR), 3.165; 95% confidence interval (CI), 2.087–4.800; P < 0.001), FFRCT ≤ 0.8 (OR, 1.632;95% CI 1.095–2.431; P = 0.016), and PCI therapy (OR 0.481; 95% CI 0.305–0.758) were the independent factors for MACE.

Conclusions

History of unstable angina and FFRCT value of ≤ 0.8 were the independent risk factors for MACE, while PCI therapy was the independent protective factor for MACE.

Long-term prognostic value of the serial changes of CT-derived fractional flow reserve and perivascular fat attenuation index

BACKGROUND

To investigate the serial changes of computed tomography (CT) fractional flow reserve (CT-FFR) and fat attenuation index (FAI), and explore their relationships with long-term clinical outcomes.

METHODS

Consecutive symptomatic patients with an intermediate pretest probability of coronary artery disease 1-4 were prospectively enrolled if coronary CT angiography (CCTA) revealed at least 1 lesion with 30-70% stenosis on major epicardial arteries. Follow-up CCTA was performed at 1 to 1.5-year intervals. All patients were further followed up after the second CCTA until September 2019. The Coronary Artery Disease - Reporting and Data System (CAD-RADS) grade, high-risk plaque features, lesion-specific CT-FFR, and FAI were measured for prognosis analysis.

RESULTS

A total of 263 patients were included in the analysis, and 38 major adverse cardiac events (MACEs) occurred. In the MACE group, the lesion-specific CT-FFR decreased significantly at the follow-up CCTA [0.80 (0.74-0.90) versus 0.85 (0.76-0.93); P=0.01], whereas the FAI did not notably increase (-70.4±8.9 versus -71.3±7.1 HU; P=0.436). In the non-MACE group, lesion-specific CT-FFR increased markedly [0.91 (0.84-0.95) versus 0.90 (0.82-0.94); P<0.001], while the FAI decreased substantially (-74.0±10.8 versus -72.4±11.5 HU; P=0.004). Decreased CT-FFR (adjusted overall hazard ratio =2.455; P=0.023) and increased FAI (adjusted hazard ratio =2.956; P=0.002) were the strongest independent predictors of MACEs. Serial changes of CT-FFR and FAI provided incremental prognostic value (Concordance statistic =0.716; P=0.003; over conventional clinical and imaging parameters (Concordance statistic =0.762; P=0.004).

CONCLUSIONS

Decreased CT-FFR and increased FAI at follow-up CCTA were the 2 strongest predictors of MACEs. Serial changes of CT-FFR and FAI provided incremental prognostic value over conventional clinical and imaging parameters for risk stratification. In addition, decreased CT-FFR provided incremental predictive value for MACEs from 15 months after second CCTA, while increased FAI added prognostic value from the second CCTA onwards.

Effect of plaque compositions on fractional flow reserve in a fluid-structure interaction analysis

Coronary artery disease involves the reduction of blood flow to the myocardium due to atherosclerotic plaques. The findings of myocardial ischemia may indicate severe coronary stenosis, but many studies have demonstrated a mismatch between lumen stenosis and fractional flow reserve (FFR). Recently, some clinical studies have found that the composition of atherosclerotic plaques may be a potential missing link between stenosis and ischemia. To investigate the relationship between myocardial ischemia and plaque composition, we have developed and adopted a new fluid-structure interaction (FSI) patient-specific coronary plaque model, based on computed tomography angiography data, to assess the impact on FFR as a biomechanical indicator of ischemia. A total of 180 analyses have been performed in 3D-FSI coronary artery disease models based on plaque compositions, plaque location, and stenosis degree. Hemodynamic analysis of simulation results and comparisons with other methods has been conducted to validate our models. Our results have successfully verified that the different compositions of plaques have resulted in differences in the calculated FFR. The mean FFR values with lipid plaques are [Formula: see text] as compared to the mean FFR values in lesions with fibrous plaques [Formula: see text] and calcified plaques [Formula: see text]. Besides, FFR differences between the three different plaque compositions have been shown to increase as the diameter stenosis increased. Plaque composition affects vascular stiffness and vascular dilation ability, and thereby affects the stenosis degree, resulting in abnormal FFR leading to myocardial ischemia. This interrelationship can help to diagnose the cause of high-risk coronary artery disease, leading to myocardial ischemia.

CT Fractional Flow Reserve for the Diagnosis of Myocardial Bridging-Related Ischemia: A Study Using Dynamic CT Myocardial Perfusion Imaging as a Reference Standard

Objective

To investigate the diagnostic performance of CT fractional flow reserve (CT-FFR) for myocardial bridging-related ischemia using dynamic CT myocardial perfusion imaging (CT-MPI) as a reference standard.

Materials and Methods

Dynamic CT-MPI and coronary CT angiography (CCTA) data obtained from 498 symptomatic patients were retrospectively reviewed. Seventy-five patients (mean age ± standard deviation, 62.7 ± 13.2 years; 48 males) who showed myocardial bridging in the left anterior descending artery without concomitant obstructive stenosis on the imaging were included. The change in CT-FFR across myocardial bridging (ΔCT-FFR, defined as the difference in CT-FFR values between the proximal and distal ends of the myocardial bridging) in different cardiac phases, as well as other anatomical parameters, were measured to evaluate their performance for diagnosing myocardial bridging-related myocardial ischemia using dynamic CT-MPI as the reference standard (myocardial blood flow < 100 mL/100 mL/min or myocardial blood flow ratio ≤ 0.8).

Results

ΔCT-FFR_systolic (ΔCT-FFR calculated in the best systolic phase) was higher in patients with vs. without myocardial bridging-related myocardial ischemia (median [interquartile range], 0.12 [0.08–0.17] vs. 0.04 [0.01–0.07], p < 0.001), while CT-FFR_systolic (CT-FFR distal to the myocardial bridging calculated in the best systolic phase) was lower (0.85 [0.81–0.89] vs. 0.91 [0.88–0.96], p = 0.043). In contrast, ΔCT-FFR_diastolic (ΔCT-FFR calculated in the best diastolic phase) and CT-FFR_diastolic (CT-FFR distal to the myocardial bridging calculated in the best diastolic phase) did not differ significantly. Receiver operating characteristic curve analysis showed that ΔCT-FFR_systolic had largest area under the curve (0.822; 95% confidence interval, 0.717–0.901) for identifying myocardial bridging-related ischemia. ΔCT-FFR_systolic had the highest sensitivity (91.7%) and negative predictive value (NPV) (97.8%). ΔCT-FFR_diastolic had the highest specificity (85.7%) for diagnosing myocardial bridging-related ischemia. The positive predictive values of all CT-related parameters were low.

Conclusion

ΔCT-FFR_systolic reliably excluded myocardial bridging-related ischemia with high sensitivity and NPV. Myocardial bridging showing positive CT-FFR results requires further evaluation.

Prognostic value of CT-derived myocardial blood flow, CT fractional flow reserve and high-risk plaque features for predicting major adverse cardiac events

Background

Myocardial blood flow (MBF), CT fractional flow reserve (CT-FFR) and high-risk plaque (HRP) features have been revealed to be associated with patients' prognosis. However, direct intra-individual comparison of these CT-derived parameters has not been explored yet. The aim of this study was to investigate the prognostic value of CT-derived MBF, CT-FFR and HRP features for predicting major adverse cardiac events (MACEs).

Methods

Consecutive patients with chest pain and intermediate-to-high pre-test probability of coronary artery disease (CAD) were prospectively enrolled. All patients were referred for dynamic CT myocardial perfusion imaging (CT-MPI) + coronary CT angiography (CCTA) and followed up for at least 1 year. MBF_ischemic (mean MBF of all ischemic segments), MBF_ratio (MBF of ischemic segments/MBF of reference segments), CT-FFR and HRP features were measured and multivariate analysis was used to evaluate the predictive value of all above parameters for MACEs.

Results

One hundred and forty-two patients were included into final analysis. MBF_ischemic and MBF_ratio was significantly lower in patients with MACE compared to patients without MACE (87 vs. 153 mL/100 mL/min and 0.64 vs. 0.95, both P<0.001). Similarly, CT-FFR was also markedly lower in patients with MACE (0.58 vs. 0.88, P<0.001) whereas coronary artery calcium score (CACS) was significantly higher (1,038.9 vs. 34.2, P<0.001). According to ROC curve analysis, MBF_ischemic, MBF_ratio and CACS had largest area under curve (AUC =0.872, 0.855 and 0.813 respectively, all P<0.001) for identifying patients with MACE. After adjusted by multivariate analysis, MBF_ischemic (hazard ratio =23.382, P=0.003) and CACS (hazard ratio =3.759, P=0.029) were revealed to be the independent predictors for MACE where CT-FFR and HRP features failed to have prognostic value.

Conclusions

MBF_ischemic derived from dynamic CT-MPI was the strongest predictor for MACE, followed by CACS. MBF_ischemic outperformed HRP features and CT-FFR for prediction of unfavorable clinical outcome.

Value of semiquantitative assessment of high-risk plaque features on coronary CT angiography over stenosis in selection of studies for FFRct

INTRODUCTION

The degree of stenosis on coronary CT angiography (CCTA) guides referral for CT-derived flow reserve (FFRct). We sought to assess whether semiquantitative assessment of high-risk plaque (HRP) features on CCTA improves selection of studies for FFRct over stenosis assessment alone.

METHODS

Per-vessel FFRct was computed in 1,395 vessels of 836 patients undergoing CCTA with 25-99% maximal stenosis. By consensus analysis, stenosis severity was graded as 25-49%, 50-69%, 70-89%, and 90-99%. HRPs including low attenuation plaque (LAP), positive remodeling (PR), and spotty calcification (SC) were assessed in lesions with maximal stenosis. Lesion FFRct was measured distal to the lesion with maximal stenosis, and FFRct<0.80 was defined as abnormal. Association of HRP and abnormal lesion FFRct was evaluated by univariable and multivariable logistic regression models.

RESULTS

The frequency of abnormal lesion FFRct increased with increase of stenosis severity across each stenosis category (25-49%:6%; 50-69%:30%; 70-89%:54%; 90-99%:91%, p ​< ​0.001). Univariable analysis demonstrated that stenosis severity, LAP, and PR were predictive of abnormal lesion FFRct, while SC was not. In multivariable analyses considering stenosis severity, presence of PR, LAP, and PR and/or LAP were independently associated with abnormal FFRct: Odds ratio 1.58, 1.68, and 1.53, respectively (p ​< ​0.02 for all). The presence of PR and/or LAP increased the frequency of abnormal FFRct with mild stenosis (p ​< ​0.05) with a similar trend with 70-89% stenosis. The combination of 2 HRP (LAP and PR) identified more lesions with FFR < 0.80 than only 1 HRP.

CONCLUSIONS

Semiquantitative visual assessment of high-risk plaque features may improve the selection of studies for FFRct.

Clinical application of computed tomography angiography and fractional flow reserve computed tomography in patients with coronary artery disease: A meta-analysis based on pre- and post-test probability

PURPOSE

To assess the diagnostic role of coronary computed tomography angiography (CCTA) and fractional flow reserve computed tomography (FFRCT) in confirming or excluding ischemic coronary artery disease (CAD) and to provide a rational use of CCTA and FFRCT in different pre-test probability (PTP) of CAD.

METHODS

We searched the electronic databases from the earliest relevant literature to July 2020 comparing FFRCT or CCTA with FFR. The bivariate random-effects models and Bayes' theorem were used to investigate the diagnostic performance of CCTA and FFRCT with the sensitivity, specificity, pre- and post-test probability.

RESULTS

Fifty-three articles with 4817 patients and 7026 vessels finally met our inclusion criteria. At the patient level, the sensitivity and specificity of CCTA were (0.94, 0.89-0.97), and (0.50, 0.43-0.58), respectively. For FFRCT, the sensitivity and specificity were (0.90, 0.87-0.93) and (0.81, 0.73-0.87). CCTA or FFRCT could increase the post-test probability to >85 % in patients with a PTP > 74.9 % or 54.5 %; CCTA or FFRCT could decrease the post-test probability to <15 % in patients with a pre-test probability <61.3 % or 59.3 %.

CONCLUSIONS

In patients with low to intermediate PTP, CCTA is suggested to exclude CAD, while the time-consuming calculation of FFRCT may be unnecessary. If CCTA detects significant or uncertain stenosis with intermediate to high PTP of CAD, further FFRCT is suggested. The advantages of FFRCT for guiding CAD treatment have sufficiently been demonstrated.

Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications

Research into machine learning (ML) for clinical vascular analysis, such as those useful for stroke and coronary artery disease, varies greatly between imaging modalities and vascular regions. Limited accessibility to large diverse patient imaging datasets, as well as a lack of transparency in specific methods, are obstacles to further development. This paper reviews the current status of quantitative vascular ML, identifying advantages and disadvantages common to all imaging modalities. Literature from the past 8 years was systematically collected from MEDLINE^® and Scopus database searches in January 2021. Papers satisfying all search criteria, including a minimum of 50 patients, were further analysed and extracted of relevant data, for a total of 47 publications. Current ML image segmentation, disease risk prediction, and pathology quantitation methods have shown sensitivities and specificities over 70%, compared to expert manual analysis or invasive quantitation. Despite this, inconsistencies in methodology and the reporting of results have prevented inter-model comparison, impeding the identification of approaches with the greatest potential. The clinical potential of this technology has been well demonstrated in Computed Tomography of coronary artery disease, but remains practically limited in other modalities and body regions, particularly due to a lack of routine invasive reference measurements and patient datasets.

Practical utilization of cardiac computed tomography for the success in complex coronary intervention

Percutaneous coronary intervention (PCI) for complex lesions is still technically demanding and is associated with less favorable procedural parameters such as lower success rate, longer procedural time, higher contrast volume and unexpected complications. Because the conventional angiographic analysis is limited by the inability to visualize the plaque information and the occluded segment, cardiac computed tomography has evolved as an adjunct to invasive angiography to better characterize coronary lesions to improve success rates of PCI. Adding to routine image reconstructions by coronary computed tomography angiography, the thin-slab maximum intensity projection method, which is a handy reconstruction technique on an ordinary workstation, could provide easy-to-understand images to reveal the anatomical characteristics and the lumen and plaque information simultaneously, and then assist to build an in-depth strategy for PCI. Especially in the treatment of chronic total occlusion lesion, these informations have big advantages in the visualization of the morphologies of entry and exit, the occluded segment and the distribution of calcium compared to invasive coronary angiography. Despite of the additional radiation exposure, contrast use and cost for cardiac computed tomography, the precise analysis of lesion characteristics would consequently improve the procedural success and prevent the complication in complex PCI.

Diagnostic performance of quantitative, semi-quantitative, and visual analysis of dynamic CT myocardial perfusion imaging: a validation study with invasive fractional flow reserve

OBJECTIVES

To investigate the diagnostic performance of absolute myocardial blood flow (MBF), MBF_ratio, and visual analysis of dynamic CT myocardial perfusion imaging (CT-MPI) for the detection of hemodynamically significant coronary stenosis.

METHODS

Consecutive patients with chest pain and intermediate-to-high pre-test probability of obstructive coronary artery disease were prospectively enrolled. All patients were referred for dynamic CT-MPI and fractional flow reserve (FFR) measurements within 4 weeks. Absolute MBF, MBF_ratio (mean MBF of stenosis-subtended territories versus that of reference territories), and visually identified perfusion defect were tested for the diagnostic performance with reference to FFR.

RESULTS

Sixty-two patients with 95 target vessels were included for final analysis. The mean radiation dose for dynamic CT-MPI was 3.0 (2.2-4.0) mSv. The mean lesion-based absolute MBF value was significantly lower in ischemic segments than that in non-ischemic segments (78.0 (65.0-86.0) mL/min/100 mL vs. 133.0 (117.5-163.8) mL/min/100 mL, p < 0.001). Similarly, the lesion-based MBF_ratio was also markedly lower in territories with positive FFR results (0.52 (0.44-0.64) vs. 0.93 (0.91-0.97), p < 0.001). According to per-lesion ROC curve analysis, MBF and MBF_ratio had a similar area under the curve (AUC) for detecting hemodynamically significant lesions (AUC = 0.942 vs. 0.956, p = 0.413), which were larger than that of visual analysis (AUC = 0.802, both p < 0.01). The vessel-based sensitivity, specificity, and diagnostic accuracy were 84.3%, 97.7%, and 90.5% for MBF and 96.1%, 93.2%, and 94.7% for MBF_ratio.

CONCLUSIONS

Absolute MBF and MBF_ratio had similarly excellent diagnostic performance with reference to FFR. In addition, these two parameters outperformed visual analysis for the detection of myocardial ischemia.

KEY POINTS

• The mean MBF and MBF_ratio were significantly lower in ischemic segments than those in non-ischemic segments. • Absolute MBF and MBF_ratio had similar AUCs for the detection of hemodynamically significant lesions (AUC = 0.942 vs. 0.956, p = 0.413), which were larger than that of visual analysis (AUC = 0.802, both p < 0.01). • The vessel-based sensitivity, specificity, and diagnostic accuracy were 84.3%, 97.7%, and 90.5% for absolute MBF and 96.1%, 93.2%, and 94.7% for MBF_ratio.

Hemodynamic Change of Coronary Atherosclerotic Plaque After Statin Treatment: A Serial Follow-Up Study by Computed Tomography-Derived Fractional Flow Reserve

Background

Whether statin treatment can improve hemodynamic status of coronary atherosclerotic plaque remains unknown. It is of clinical interest to explore the hemodynamic change of coronary lesions after statin treatment.

Methods and Results

Consecutive patients with intermediate pre‐test probability of coronary artery disease were prospectively enrolled and underwent baseline coronary computed tomography angiography (CCTA) as well as follow‐up CCTA. The primary end point was to determine the lesion‐specific change of △computed tomography‐derived fractional flow reserve (△CT‐FFR, defined as the change of CT‐FFR value across each lesion) after rosuvastatin treatment. The secondary end point was to compare the change of other plaque characteristics according to serial CCTA findings. 152 patients (mean age: 67.1±9.7 years, 100 men, mean follow‐up duration of 13.9±2.5 months) were finally included. In non‐calcified plaque subgroup, △CT‐FFR was significantly lower at follow‐up compared with baseline (0.051±0.010 versus 0.035±0.012, P=0.013). All other parameters were not found to be significantly different between baseline and follow‐up CCTA measurements. In calcified plaque and mixed plaque subgroups, all parameters showed no significant differences between baseline and follow‐up CCTA groups (P>0.05 for all). According to multivariate regression analysis, non‐calcified plaque was >2 times more likely than calcified plaque to observe the decrease of △CT‐FFR (adjusted hazard ratio: 2.05 [1.03–4.09], P=0.042).

Conclusions

In patients with mild to intermediate coronary stenosis, rosuvastatin treatment resulted in a reduction in lesion‐specific △CT‐FFR at mid‐term follow‐up. This hemodynamic improvement was mainly observed for non‐calcified lesions.

Combined assessment of subtended myocardial volume and myocardial blood flow for diagnosis of obstructive coronary artery disease using cardiac computed tomography: A feasibility study

BACKGROUND

This study aimed to evaluate the combined diagnostic performance of coronary artery stenosis-subtended myocardial volume (V_sub) and myocardial blood flow (MBFsub) on computed tomography (CT) for detecting obstructive coronary artery disease (CAD) assessed by invasive coronary angiography (ICA) and fractional flow reserve (FFR).

METHODS

Thirty-nine patients who underwent coronary CT angiography (CTA) and stress dynamic myocardial CT perfusion (CTP) prior to ICA were enrolled. Obstructive CAD was defined as severe (≥70%) or moderate (30-69%) stenosis with FFR ≤0.8 on ICA. The V_sub was semi-automatically calculated from coronary CTA data using Voronoi diagram-based myocardial segmentation. The standard CT-MBF based on the 17-segment model was calculated using dynamic stress CTP data and deconvolution analysis. The CT-MBFsub was automatically analyzed by integrating the CT-MBF and Voronoi diagram-based myocardial segmentation analyses. The diagnostic performance of combined CT-MBFsub and V_sub assessment was determined using receiver operating characteristic analysis and compared with standard CT-MBF and CT-MBFsub.

RESULTS

Of 117 vessels in 39 patients, 72 vessels were suspected of significant stenosis on CTA and 33 vessels had obstructive CAD on ICA and FFR. The sensitivity and specificity for identifying obstructive CAD were 67% and 82% for standard CT-MBF, 70% and 77% for CT-MBFsub, and 85% and 82% for combined CT-MBFsub and V_sub assessment. The area under the receiver operating characteristic curve of the combined CT-MBFsub and V_sub assessment was significantly higher than those of standard CT-MBF and CT-MBFsub (0.89 vs. 0.75, 0.77; p<0.05).

CONCLUSIONS

The V_sub may aid in increasing the diagnostic performance of CT-MBFsub for detecting obstructive CAD.

The value of quantified plaque analysis by dual-source coronary CT angiography to detect vulnerable plaques: a comparison study with intravascular ultrasound

Background

To investigate the diagnostic performance of quantified plaque analysis and high-risk plaque characterization by coronary computed tomography angiography (CCTA) for identifying thin-cap fibroatheroma (TCFA).

Methods

Patients who underwent both CCTA and intravascular ultrasound (IVUS) within 4 weeks were retrospectively included. CT-derived quantitative and qualitative parameters, including diameter stenosis, minimal lumen area (MLA), low attenuation plaque (LAP) volume napkin-ring sign (NRS), positive remodeling (PR) and spotty calcification, were recorded. TCFA lesions and non-TCFA lesions were determined by IVUS. Multivariate regression analysis was used to determine the independent predictors of TCFA lesions.

Results

Sixty-five patients (mean age: 69.8±9.2 years, 29 females) with 89 lesions were finally included. LAP and NRS were more frequently presented in the group of TCFA lesions. The mean LAP volume of TCFA lesions was significantly larger than that of non-TCFA lesions [16.5 (11.0-23.0) vs. 0 (0-1.5) mm³, P<0.001]. According to multivariate logistic regression analysis, LAP volume was the only significant predictor for IVUS-confirmed vulnerable plaques (odds ratio =3.294, 95% confidence interval: 1.177-9.223, P=0.023). LAP volume showed largest area under curve (AUC) for diagnosing TCFA lesions (AUC =0.901, 95% confidence interval: 0.819-0.954, P<0.0001). When using >8 mm³ as the best cutoff value, the diagnostic accuracy, sensitivity and specificity of LAP volume for predicting TCFA lesions were 91.0% (81/89), 84.6% (22/26) and 96.8% (61/63) respectively.

Conclusions

CT-derived LAP volume of TCFA lesions was significantly higher than those of non-TCFA lesions. LAP volume was the strongest predictor for TCFA lesions as validated by IVUS.

Machine Learning for Assessment of Coronary Artery Disease in Cardiac CT: A Survey

Cardiac computed tomography (CT) allows rapid visualization of the heart and coronary arteries with high spatial resolution. However, analysis of cardiac CT scans for manifestation of coronary artery disease is time-consuming and challenging. Machine learning (ML) approaches have the potential to address these challenges with high accuracy and consistent performance. In this mini review, we present a survey of the literature on ML-based analysis of coronary artery disease in cardiac CT. We summarize ML methods for detection and characterization of atherosclerotic plaque as well as anatomically and functionally significant coronary artery stenosis.

Diagnostic performance of perivascular fat attenuation index to predict hemodynamic significance of coronary stenosis: a preliminary coronary computed tomography angiography study

OBJECTIVE

This study aimed to investigate the association between perivascular fat attenuation index (FAI) and hemodynamic significance of coronary lesions.

METHODS

Patients with stable angina who underwent coronary computed tomography (CT) angiography and invasive fractional flow reserve (FFR) measurement within 2 weeks were retrospectively included. Lesion-based perivascular FAI, high-risk plaque features, total plaque volume (TPV), machine learning-based FFR_CT, and other parameters were recorded. Lesions with invasive FFR ≤ 0.8 were considered functionally significant.

RESULTS

This study included 167 patients with 219 lesions. Diameter stenosis (DS), lesion length, TPV, and perivascular FAI were significantly larger or longer in the group of hemodynamically significant lesions (FFR ≤ 0.8). In addition, smaller FFR_CT value was associated with functionally significant lesions (0.720 ± 0.11 vs 0.846 ± 0.10, p < 0.001). No significant difference was found between the hemodynamically significant and insignificant subgroups with respect to CT-derived high-risk plaque features. According to multivariate analysis, DS, TPV, and perivascular FAI were significant predictors of lesion-specific ischemia. When integrating DS, TPV, and perivascular FAI, the area under the curve (AUC) of this combined method was 0.821, which was similar to that of FFR_CT (AUC, 0.821 vs 0.850; p = 0.426). The diagnostic accuracy of FFR_CT was higher than that of the combined approach, but the difference was statistically insignificant (79.0% vs 74.0%, p = 0.093).

CONCLUSIONS

Perivascular FAI was significantly higher for flow-limiting lesions than for non-flow-limiting lesions. The combined use of FAI, TPV, and DS could predict ischemic coronary stenosis with high diagnostic accuracy.

KEY POINTS

• Perivascular FAI was significantly higher for flow-limiting lesions than for non-flow-limiting lesions. • Combined use of FAI, plaque volume, and DS provided diagnostic performance comparable to that of machine learning-based FFR _CTfor predicting ischemic coronary stenosis. • No significant difference was found between the hemodynamically significant and insignificant subgroups with respect to CT-derived high-risk plaque features.