Fractional Flow Reserve Estimated at Coronary CT Angiography in Intermediate Lesions: Comparison of Diagnostic Accuracy of Different Methods to Determine Coronary Flow Distribution

Valuable Predictors for Non-measurability of Fractional Flow Reserve Derived From Coronary Computed Tomography Angiography

Background The fractional flow reserve (FFR) derived from coronary computed tomography (CT) angiography (FFRCT) is a variable tool for coronary disease diagnosis that non-invasively provides the value of FFR. It can add physiological information to coronary CT angiography (CCTA) and reduce unnecessary invasive coronary angiography (CAG). However, it cannot be analyzed in some cases, which is also called "non-measurability." While FFRCT has become globally widespread, the current data on non-measurability are lacking. This study aimed to determine the rate of non-measurability and identify predictors thereof in routine clinical settings to explore potential approaches to reduce the non-measurability rate. Methods and results This retrospective observational single-center study included consecutive patients who underwent FFRCTanalysis in Japan. The mean age of the overall population was 71.3 ± 10.6, and an FFRCTof ≤0.8 was seen in 47.6% of patients with a measurable FFRCT. Of the 307 enrolled patients, FFRCT analysis was not feasible in 21 cases (6.8%). Heart rate (HR) at a CT scan and coronary calcium scores (CCS) were significantly higher in patients with non-measurability than those in patients whose FFRCT was appropriately analyzed (HR: 69.6±8.9 bpm vs. 61.0±11.1 bpm; p < 0.01; CCS; 931.2 (290.8, 1451.3) vs. 322.9 (100.7, 850.0); p < 0.01). Multiple logistic regression showed that HR was an independent predictor for non-measurability (odds ratio: 1.05; 95% confidential interval: 1.02, 1.09; p < 0.01)). Based on the receiver operating characteristic curve analysis, the optimal cut-off value of HR and CCS was 63 bpm (specificity: 67.1%; sensitivity: 76.2%) and 729.2 (specificity: 71.3%; sensitivity: 66.7%). In addition, the combination of two features (HR > 63 bpm and CCS > 729.2) showed a high negative predictive value (99.3%) for FFRCT non-measurability. Conclusions In this study, the rate of FFRCTnon-measurability was 6.8%. Higher HR at a CT scan and CCS were significantly associated with non-measurability, and in cases with both HR and CCS below a specified threshold, the likelihood of ruling out non-measurability could be significantly high. Our findings suggest that reducing the HR to ideally under 63 bpm at the time of the CT scan significantly ensures feasibility. Further study on large-scale cohorts is warranted.

The influence of flow distribution strategy for the quantification of pressure- and wall shear stress-derived parameters in the coronary artery: A CTA-based computational fluid dynamics analysis

For image-based computational fluid dynamics (CFD) analysis to characterize the local coronary hemodynamic environment, the accuracy depends on the flow rate which is in turn associated with outlet branches' morphology. A good flow distribution strategy is important to mitigate the effect when certain branches cannot be considered. In this study, stenotic coronary arteries from 13 patients were used to analyze the effect of missing branches and different flow distribution strategies. Pressure- and wall shear stress (WSS)-derived parameters around the stenotic region (ROI) were compared, including fractional flow reserve (CT-FFR), instantaneous wave-free ratio (CT-iFR), resting distal to aortic coronary pressure (CT-Pd/Pa), time-averaged WSS, oscillatory shear index (OSI) and relative residence time (RRT). Three flow distribution strategies were the Huo-Kassab model at distal outlets (Type I), flow distribution based on outlet resistances (Type II), and a developed algorithm distributing flow at each bifurcation until the final outlets (Type III). Results showed that Type III strategy for models with truncated branch(es) had a good agreement in both pressure- and WSS-related results (interquatile range less than 0.12% and 4.02%, respectively) with the baseline model around the ROI. The relative difference of pressure- and WSS-related results were correlated with the flow differences in the ROI to the baseline mode. Type III strategy had the best performance in maintaining the flow in intermediate branches. It is recommended for CFD analysis. Removal of branches distal to a stenosis can be undertaken with an improved performance and maintained accuracy, while those proximal to the ROI should be kept.

High-Speed On-Site Deep Learning-Based FFR-CT Algorithm: Evaluation Using Invasive Angiography as the Reference Standard

BACKGROUND. Estimation of fractional flow reserve from coronary CTA (FFR-CT) is an established method of assessing the hemodynamic significance of coronary lesions. However, clinical implementation has progressed slowly, partly because of off-site data transfer with long turnaround times for results. OBJECTIVE. The purpose of this study was to evaluate the diagnostic performance of FFR-CT computed on-site with a high-speed deep learning-based algorithm with invasive hemodynamic indexes as the reference standard. METHODS. This retrospective study included 59 patients (46 men, 13 women; mean age, 66.5 ± 10.2 years) who underwent coronary CTA (including calcium scoring) followed within 90 days by invasive angiography with invasive fractional flow reserve (FFR) and/or instantaneous wave-free ratio measurements from December 2014 to October 2021. Coronary artery lesions were considered to have hemodynamically significant stenosis in the presence of invasive FFR of 0.80 or less and/or instantaneous wave-free ratio of 0.89 or less. A single cardiologist evaluated the CTA images using an on-site deep learning-based semiautomated algorithm entailing a 3D computational flow dynamics model to determine FFR-CT for coronary artery lesions detected with invasive angiography. Time for FFR-CT analysis was recorded. FFR-CT analysis was repeated by the same cardiologist in 26 randomly selected examinations and by a different cardiologist in 45 randomly selected examinations. Diagnostic performance and agreement were assessed. RESULTS. A total of 74 lesions were identified with invasive angiography. FFR-CT and invasive FFR had strong correlation (r = 0.81) and, in Bland-Altman analysis, bias of 0.01 and 95% limits of agreement of -0.13 to 0.15. FFR-CT had AUC for hemodynamically significant stenosis of 0.975. At a cutoff of 0.80 or less, FFR-CT had 95.9% accuracy, 93.5% sensitivity, and 97.7% specificity. In 39 lesions with severe calcifications (≥ 400 Agatston units), FFR-CT had AUC of 0.991 and at a cutoff of 0.80, 94.7% sensitivity, 95.0% specificity, and 94.9% accuracy. Mean analysis time per patient was 7 minutes 54 seconds. Intraobserver agreement (intraclass correlation coefficient, 0.85; bias, -0.01; 95% limits of agreement, -0.12 and 0.10) and interobserver agreement (intraclass correlation coefficient, 0.94; bias, -0.01; 95% limits of agreement, -0.08 and 0.07) were good to excellent. CONCLUSION. A high-speed on-site deep learning-based FFR-CT algorithm had excellent diagnostic performance for hemodynamically significant stenosis with high reproducibility. CLINICAL IMPACT. The algorithm should facilitate implementation of FFR-CT technology into routine clinical practice.

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

OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Diagnostic performance of computational fluid dynamics (CFD)-based fractional flow reserve (FFR) derived from coronary computed tomographic angiography (CCTA) for assessing functional severity of coronary lesions

Background

Fractional flow reserve (FFR) is the gatekeeper for lesion-specific revascularization decision-making in patients with stable coronary artery disease (CAD). The potential of noninvasive calculation of FFR from coronary computed tomographic angiography (CCTA) to identify ischemia-causing lesions has not been sufficiently assessed. The objective of this study was to evaluate the feasibility and diagnostic accuracy of a novel computational fluid dynamics (CFD)-based technology, termed as AccuFFRct, for the diagnosis of functionally significant lesions from CCTA, using wire-based FFR as a reference standard.

Methods

A total of 191 consecutive patients who underwent CCTA and FFR measurement for suspected or known CAD were retrospectively enrolled at 2 medical centers. Three-dimensional anatomic model of coronary tree was extracted from CCTA data, CFD was applied subsequently with a novel strategy for the computation of FFR in a blinded fashion by professionals. Results were compared to invasive FFR, a threshold of ≤0.80 was used to indicate the hemodynamically relevant stenosis.

Results

On a per-patient basis, the overall accuracy, sensitivity, specificity of AccuFFRct for detecting ischemia were 91.78% (95% CI: 86.08% to 95.68%), 92.31% (95% CI: 81.46% to 97.86%) and 91.49% (95% CI: 83.92% to 96.25%), respectively; those for per-vessel basis were 91.05% (95% CI: 86.06% to 94.70%), 92.73% (95% CI: 82.41% to 97.98%) and 90.37% (95% CI: 84.10% to 94.77%), respectively. The AccuFFRct and FFR was well correlated on per-patient (r=0.709, P<0.001) and per-vessel basis (r=0.655, P<0.001). The AUC of AccuFFRct determination was 0.935 (95% CI: 0.881 to 0.969) and 0.927 (95% CI: 0.880 to 0.960) on per-patient and per-vessel basis.

Conclusions

This novel CFD-based CCTA-derived FFR shows good diagnostic performance for detecting hemodynamic significance of coronary stenoses and may potentially become a new gatekeeper for invasive coronary angiography (ICA).

Novel fast FFR derived from coronary CT angiography based on static first-pass algorithm: a comparison study

BACKGROUND

Fractional flow reserve (FFR) is the invasive gold standard for evaluating coronary arterial stenosis. However, there have been a few non-invasive methods such as computational fluid dynamics FFR (CFD-FFR) with coronary CT angiography (CCTA) images that can perform FFR assessment. This study aims to develop a new method based on the principle of static first-pass of CT perfusion imaging technique (SF-FFR) and evaluate the efficacy in direct comparisons between CFD-FFR and the invasive FFR.

METHODS

A total of 91 patients (105 coronary artery vessels) who were admitted from January 2015 to March 2019 were enrolled in this study, retrospectively. All patients underwent CCTA and invasive FFR. 64 patients (75 coronary artery vessels) were successfully analyzed. The correlation and diagnostic performance of SF-FFR method on per-vessel basis were analyzed, using invasive FFR as the gold standard. As a comparison, we also evaluated the correlation and diagnostic performance of CFD-FFR.

RESULTS

The SF-FFR showed a good Pearson correlation (r = 0.70, P < 0.001) and intra-class correlation (r = 0.67, P < 0.001) with the gold standard. The Bland-Altman analysis showed that the average difference between the SF-FFR and invasive FFR was 0.03 (0.11-0.16); between CFD-FFR and invasive FFR was 0.04 (-0.10-0.19). Diagnostic accuracy and area under the ROC curve on a per-vessel level were 0.89, 0.94 for SF-FFR, and 0.87, 0.89 for CFD-FFR, respectively. The SF-FFR calculation time was about 2.5 s per case while CFD calculation was about 2 min on an Nvidia Tesla V100 graphic card.

CONCLUSIONS

The SF-FFR method is feasible and shows high correlation compared to the gold standard. This method could simplify the calculation procedure and save time compared to the CFD method.

The mechanisms of arterial signal intensity profile in non-contrast coronary MRA (NC-MRCA): a 3D printed phantom investigation and clinical translations

Signal intensity (SI) drop has been proposed as an indirect stenosis assessment in non-contrast coronary MRA (NC-MRCA) but it uses unproven assumptions. We aimed to clarify the mechanisms that govern the SI in vitro and develop a stenosis detection method in vivo. Flow phantom tubes with/without stenosis were scanned under two spatial resolutions (0.5/1.0 mm³) on a 3.0 T MRI. Thirty-two coronary arteries from 11 volunteers were prospectively scanned with an EKG- and respiratory-gated 3D NC-MRCA with a resolution of 1.0 mm³, with coronary computed tomography angiography (CTA) as reference. The normalized SI along the centerline of the tubes or the coronary arteries was assessed against the distance from the orifice using a linear regression model. Its coefficient (SI decay slope) and goodness-of-fit (R2) were extracted to assess the effect of flow velocity and stenosis on the SI profile curve. The R2 was utilized for the stenosis detection. Phantom study: A slow flow velocity caused a steep SI decay slope. The SI drop revealed only at the inlet and outlet of stenosis due to the flow turbulence/vortex and yielded low R2, in which shape changed by the resolution. Clinical study: The R2 cutoff to detect ≥ 50% stenosis for the left and right coronary arteries were 0.64 and 0.20 with a sensitivity/specificity of 71.5/71.5 and 66.7/100 (%), respectively. The SI drop did not reflect the actual stenosis position and not suitable for the stenosis localization. The R2 cutoff represents an alternative method to detect stenoses on NC-MRCA at vessel level.Trial registration: ClinicalTrials.gov; NCT03768999, registered on December 7, 2018.

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

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

Fractional Flow Reserve (FFR) Estimation from OCT-Based CFD Simulations: Role of Side Branches

The computational fluid dynamic method has been widely used to quantify the hemodynamic alterations in a diseased artery and investigate surgery outcomes. The artery model reconstructed based on optical coherence tomography (OCT) images generally does not include the side branches. However, the side branches may significantly affect the hemodynamic assessment in a clinical setting, i.e., the fractional flow reserve (FFR), defined as the ratio of mean distal coronary pressure to mean aortic pressure. In this work, the effect of the side branches on FFR estimation was inspected with both idealized and optical coherence tomography (OCT)-reconstructed coronary artery models. The electrical analogy of blood flow was further used to understand the impact of the side branches (diameter and location) on FFR estimation. Results have shown that the side branches decrease the total resistance of the vessel tree, resulting in a higher inlet flowrate. The side branches located at the downstream of the stenosis led to a lower FFR value, while the ones at the upstream had a minimal impact on the FFR estimation. Side branches with a diameter larger than one third of the main vessel diameter are suggested to be considered for a proper FFR estimation. The findings in this study could be extended to other coronary artery imaging modalities and facilitate treatment planning.

Research Progress of Machine Learning and Deep Learning in Intelligent Diagnosis of the Coronary Atherosclerotic Heart Disease

The coronary atherosclerotic heart disease is a common cardiovascular disease with high morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of the coronary atherosclerotic heart disease is of great significance. The rise of artificial intelligence technologies, represented by machine learning and deep learning, provides new methods to address the above issues. In recent years, artificial intelligence has achieved an extraordinary progress in multiple aspects of coronary atherosclerotic heart disease diagnosis, including the construction of intelligent diagnostic models based on artificial intelligence algorithms, applications of artificial intelligence algorithms in coronary angiography, coronary CT angiography, intravascular imaging, cardiac magnetic resonance, and functional parameters. This paper presents a comprehensive review of the technical background and current state of research on the application of artificial intelligence in the diagnosis of the coronary atherosclerotic heart disease and analyzes recent challenges and perspectives in this field.

Use of the volume-averaged Murray's deviation method for the characterization of branching geometry in liver fibrosis: a preliminary study on vascular circulation

Background

Vascular changes in liver fibrosis can result in increased intrahepatic vascular resistance and impaired blood circulation. This can hinder the recovery from fibrosis and may eventually lead to portal hypertension, a major cirrhosis complication. This report proposed a volume-averaged Murray's deviation method to characterize intrahepatic circulation in the liver during fibrosis and its subsequent regression via X-ray phase-contrast computed tomography (PCCT).

Methods

Liver fibrosis was induced in 24 Sprague-Dawley rats by exposure to carbon tetrachloride (CCl₄) for up to 10 weeks, after which, spontaneous regression commenced and continued until week 30. High-resolution three-dimensional (3D) imaging of the livers was performed with PCCT. The values of Murray's deviation based on the volume-averaged and the conventional diameter-based methods were compared. After that, the intrahepatic circulation at different stages of fibrosis was evaluated using the volume-averaged method. The increase in collagen during liver fibrosis was assessed by pathological analyses.

Results

A comparison of the 2 methods showed that with an increase in the number of diameter measurements, the value of Murrary's deviation obtained using the diameter-based method gradually approaches those of the volume-averaged method, with minimal variations. The value of Murray's deviation increased with the development of fibrosis. After reversal, the value rapidly decreased and approached that of the normal state in both the main branches (1.05±0.17, 1.17±0.21, 1.34±0.18, and 1.17±0.19 in the normal, moderate, severe, and regressive groups, respectively; P<0.05 between the severe group and other groups) and the small branches (1.05±0.09, 1.42±0.48, 1.79±0.57, and 1.18±0.28 in the normal, moderate, severe, and regressive group, respectively; P<0.05 between adjacent groups). An analysis of Murray's deviation and the pathological results showed that the vascular circulation in this disease model was consistent with the progression and recovery from fibrosis.

Conclusions

This study showed the validity of the volume-averaged method for calculating Murray's deviation and demonstrated that it could accurately evaluate the blood circulation state of the liver during fibrosis and its subsequent regression. Thus, the volume-averaged method of calculating Murray's deviation may be an objective and valuable staging criterion to evaluate intrahepatic circulation during liver fibrosis.

Estimation of coronary stenosis severity based on flow distribution ratios

We suggest improving minimally-invasive stenosis severity estimation, using a combination of existing geometry-based methods with Transluminal Attenuation Gradient measurements. Instead of local flow values, the method uses flow distribution ratios along the entire tree. The tree geometry is used to derive a lumped model and predict the 'theoretical' ratios in each bifurcation, while attenuation measurements are used for extracting 'actual' ratios. The discrepancies between the measured and the theoretical values are utilized to assess a functional degree of stenosis. Our experimental and numerical analyses show that the quantitative value of discrepancy is proportional to stenosis severity, regardless of boundary conditions.

Diagnostic accuracy of 3D deep-learning-based fully automated estimation of patient-level minimum fractional flow reserve from coronary computed tomography angiography

AIMS

Although deep-learning algorithms have been used to compute fractional flow reserve (FFR) from coronary computed tomography angiography (CCTA), no study has achieved 'fully automated' (i.e. free from human input) FFR calculation using deep-learning algorithms. The purpose of the study was to evaluate the accuracy of a fully automated 3D deep-learning model for estimating minimum FFR from CCTA data, with invasive FFR as the reference standard.

METHODS AND RESULTS

This retrospective study of 1052 patients included 131 patients whose CCTA studies showed 30-90% stenosis and underwent invasive FFR (abnormal FFR observed in 72/131, 55%), and 921 patients who underwent clinically indicated CCTA without invasive FFR. We designed a fully automated 3D deep-learning model that inputs CCTA data and outputs minimum FFR without requiring human input. The model comprised a series of deep-learning algorithms: a conditional generative adversarial network, a 3D convolutional ladder network, and two independent neural networks with integrated virtual adversarial training. We used Monte Carlo cross-validation to evaluate the accuracy of the model for estimating FFR, with invasive FFR as the reference standard. The deep-learning FFR achieved area under the receiver-operating characteristic curve of 0.78 for detection of abnormal FFR; and was significantly higher than for visually determined CCTA >50% stenosis (area under the curve = 0.56). The deep-learning FFR model achieved 76% accuracy for detecting abnormal FFR, with sensitivity of 85% (79-89%) and specificity of 63% (54-70%).

CONCLUSION

The 3D deep-learning model, which performs fully automatic estimation of minimum FFR from cardiac CT data, achieved 76% accuracy in detecting abnormal FFR.

Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve

BACKGROUND

To evaluate the feasibility of non-invasive fractional flow reserve (FFR) estimation using histologically-validated assessment of plaque morphology on coronary CTA (CCTA) as inputs to a predictive model further validated against invasive FFR.

METHODS

Patients (n = 113, 59 ± 8.9 years, 77% male) with suspected coronary artery disease (CAD) who had undergone CCTA and invasive FFR between August 2013 and May 2018 were included. Commercially available software was used to extract quantitative plaque morphology inclusive of both vessel structure and composition. The extracted plaque morphology was then fed as inputs to an optimized artificial neural network to predict lesion-specific ischemia/hemodynamically significant CAD with performance validated by invasive FFR.

RESULTS

A total of 122 lesions were considered, 59 (48%) had low FFR values. Plaque morphology-based FFR assessment achieved an area under the curve, sensitivity and specificity of 0.94, 0.90 and 0.81, respectively, versus 0.71, 0.71, and 0.50, respectively, for an optimized threshold applied to degree of stenosis. The optimized ridge regression model for continuous value estimation of FFR achieved a cross-correlation coefficient of 0.56 and regression slope of 0.59 using cross validation, versus 0.18 and 0.10 for an optimized threshold applied to degree of stenosis.

CONCLUSIONS

Our results show that non-invasive plaque morphology-based FFR assessment may be used to predict lesion-specific ischemia resulting in hemodynamically significant CAD. This substantially outperforms degree of stenosis interpretation and has a comparable level of sensitivity and specificity relative to publicly reported results from computational fluid dynamics-based approaches.

Progress of Clinical Evaluation for Vascular Aging in Humans

Human society is experiencing a serious aging process. Age-related arteriosclerotic cardiovascular diseases (ASCVD) are the most common cause of deaths around the world and bring a huge burden on the whole society. Vascular aging-related pathological alterations of the vasculature play an important role in the pathogenesis of ASCVD and morbidity and mortality of older adults. In this review, we describe the progress of clinical evaluation of vascular aging in humans, including functional evaluation, structural assessment, and cellular molecular markers. The significance of detection for vascular aging is highlighted, and we call for close attention to the evaluation for a better quality of life in the elderly population.

Advances in Cardiac Computed Tomography Functional Imaging Technology

Cardiovascular disease (CVD) is the leading cause of death among patients in China, and cardiac computed tomography (CT) is one of the most commonly used examination methods for CVD. Coronary artery CT angiography can be used for the morphologic evaluation of the coronary artery. At present, cardiac CT functional imaging has become an important direction of development of CT. At present, common CT functional imaging technologies include transluminal attenuation gradient, stress dynamic CT myocardial perfusion imaging, and CT-fractional flow reserve. These three imaging modes are introduced and analyzed in this review.

Clinical Predictors of Coronary Artery Plaque Progression by Quantitative Serial Assessment Using 320-Row Computed Tomography Coronary Angiography in Asymptomatic Patients with Type 2 Diabetes Mellitus

BACKGROUND

Natural history of coronary plaque progression (PP) in patients with diabetes mellitus (DM) remains unclear. This study aimed to investigate the clinical predictors of coronary PP in patients with DM.

METHODS

In this prospective observational study, we analyzed 70 asymptomatic patients (age, 64.4 years; male, 67%) with type 2 DM without prior history of coronary artery disease who underwent serial 320-row computed tomography coronary angiography with an interscan interval of more than 24 months (median 37.7 months). Study endpoint was PP, which was defined if coronary plaque volumes (PVs) at follow-up minus PVs at baseline was >0. We evaluated plaque composition using the Hounsfield Unit thresholds and insulin resistance estimated by the homeostasis model assessment of insulin resistance (HOMA-IR).

RESULTS

Thirty-nine patients who showed PP had a higher increase in hemoglobin A1c (⊿HbA1c) from baseline to follow-up than those without PP (0.3% ± 0.8% vs -0.4% ± 1.1%; p = 0.01), although there was no statistical difference in HbA1c at baseline (7.1 ± 0.5% vs. 7.3 ± 1.4%; p = 0.24). In multivariable analysis, ⊿HbA1c [odds ratio (OR): 3.05; 95% confidence interval (CI): 1.39-6.67; p = 0.001] was an independent predictor for PP. Increase in low-density lipoprotein cholesterol (⊿LDL-C), not ⊿HbA1c, was significantly correlated to percent change in necrotic core (NC) volume (β-coefficients: 0.04; 95% CI: 0.004 - 0.08; p = 0.03). Among 48 patients without insulin therapy, patients with PP (n = 28) had a higher increase in HOMA-IR than those without PP (n = 20) (0.95 ± 2.00 vs. -0.63 ± 1.31; p = 0.003).

CONCLUSIONS

Increase in HbA1c and HOMA-IR was associated with PP in asymptomatic patients with type 2 DM, whereas increase in LDL-C was correlated to increase in NC.

[Prognosis of patients with vulnerable plaques indicated by coronary CT angiography]

OBJECTIVE

To investigate the prognosis of patients with vulnerable plaque indicated by coronary CT angiography (CCTA).

METHODS

Totally 1963 patients underwent CCTA from February 2nd 2015 to September 13th 2015, and 2728 coronary borderline lesions (stenosis of 50%-70%) were detected. Among them 804 patients had vulnerable plaques and 1159 patients had stable plaques. The primary endpoint was major cardiac adverse events (MACE), including cardiac death, acute myocardial infarction and target lesion revascularization.

RESULTS

Patients were followed up for a mean follow-up of 27.4±2.3 months. The incidence of MACE in the vulnerable plaque group was significantly higher than that in the stable plaque group (10.8%vs 2.3%, P &lt; 0.01). After adjusting for age, gender, smoking, hypertension, diabetes, hyperlipidemia, the MACE hazard ratio (HR) in the vulnerable plaque group was 5.022 (95% CI:3.254-7.751, P &lt; 0.01).Subgroup analysis showed that in the vulnerable plaque group, the incidence of MACE in patients taking antiplatelet and statin ≤3 months and those taking antiplatelet and statin &gt; 3 months was 17.0%and 5.8%, respectively (HR=3.149, 95% CI:1.987-4.992, P &lt; 0.01); but the difference did not seen in stable plaque group (HR=1.721, 95% CI:0.798-3.712, P&gt;0.05).

CONCLUSIONS

This study confirmed the risk of MACE in patients with vulnerable plaque detected by CCTA and the drug treatment may reduce the risk for patients with vulnerable plaque.

Patient-specific 3D-printed coronary models based on coronary computed tomography angiography volumes to investigate flow conditions in coronary artery disease

BACKGROUND

3D printed patient-specific coronary models have the ability to enable repeatable benchtop experiments under controlled blood flow conditions. This approach can be applied to CT-derived patient geometries to emulate coronary flow and related parameters such as Fractional Flow Reserve (FFR).

METHODS

This study uses 3D printing to compare such benchtop FFR results with a non-invasive CT-FFR research software algorithm and catheter based invasive FFR (I-FFR) measurements. Fifty-two patients with a clinical indication for I-FFR underwent a research Coronary CT Angiography (CCTA) prior to catheterization. CT images were used to measure CT-FFR and to generate patient-specific 3D printed models of the aortic root and three main coronary arteries. Each patient-specific model was connected to a programmable pulsatile pump and benchtop FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for two coronary outflow rates ('normal', 250 ml min^-1; and 'hyperemic', 500 ml min^-1) by adjusting the model's distal coronary resistance.

RESULTS

Pearson correlations and ROC AUC were calculated using invasive I-FFR as reference. The Pearson correlation factor of CT-FFR and B-FFR-500 was 0.75 and 0.71, respectively. Areas under the ROCs for CT-FFR and B-FFR-500 were 0.80 (95%CI: 0.70-0.87) and 0.81 (95%CI: 0.64-0.91) respectively.

CONCLUSION

Benchtop flow simulations with 3D printed models provide the capability to measure pressure changes at any location in the model, for ultimately emulating the FFR at several simulated physiological blood flow conditions.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/show/NCT03149042.

Multimodal Multiparametric Three-dimensional Image Fusion in Coronary Artery Disease: Combining the Best of Two Worlds

PURPOSE

To allow for comprehensive noninvasive diagnostics of coronary artery disease (CAD) by using three-dimensional (3D) image fusion of CT coronary angiography, CT-derived fractional flow reserve (CT FFR), whole-heart dynamic 3D cardiac MRI perfusion, and 3D cardiac MRI late gadolinium enhancement (LGE).

MATERIALS AND METHODS

Seventeen patients (54 years ± 10 [standard deviation], one female) who underwent cardiac CT and cardiac MRI were included (combined subcohort of three prospective trials). Software facilitating multimodal 3D image fusion was developed. Postprocessing of CT data included segmentation of the coronary tree and heart contours, calculation of CT FFR values, and color coding of the coronary tree according to CT FFR. Postprocessing of cardiac MRI data included segmentation of the left ventricle (LV) in cardiac MRI perfusion and cardiac MRI LGE, co-registration of cardiac MRI to CT data, and projection of cardiac MRI perfusion and LGE values onto the high spatial resolution LV from CT.

RESULTS

Image quality was rated as good to excellent (scores: 2.5-2.6; 3 = excellent). CT coronary angiography revealed significant stenoses in seven of 17 cases (41%). CT FFR was possible in 16 of 17 cases (94%) and showed pathologic flow in seven of 17 cases (41%), six of which coincided with cases revealing significant stenoses at CT coronary angiography. Cardiac MRI perfusion identified eight of 17 patients (47%) with hypoperfusion (ischemic burden of 17% ± 5). Cardiac MRI LGE showed myocardial scar in three of 17 cases (18%, scar burden of 7% ± 4). Conventional two-dimensional readout of CT coronary angiography and cardiac MRI resulted in eight of 17 cases (47%) with uncertain findings. Most of these divergent findings could be solved when adding information from CT FFR and 3D image fusion (six of eight, 75%).

CONCLUSION

Multimodal 3D cardiac image fusion is feasible and may help with comprehensive noninvasive CAD diagnostics.Supplemental material is available for this article.© RSNA, 2020.

Inter- and Intraoperator Variability in Measurement of On-Site CT-derived Fractional Flow Reserve Based on Structural and Fluid Analysis: A Comprehensive Analysis

Purpose

To measure the inter- and intraobserver variability among operators of varying expertise in conducting CT-derived fractional flow reserve (CT FFR) measurements on-site by using structural and fluid analysis and to evaluate differences in reproducibility between two different training methods for end users.

Materials and Methods

This retrospective analysis of the prospectively enrolled cohort included 22 symptomatic patients who underwent both 320-detector row coronary CT angiography and catheter-derived fractional flow reserve (FFR) within 90 days. Thirteen operators of varying expertise were assigned to one of two training arms: arm 1, on-site training by a specialist in CT FFR technology; arm 2, self-training through use of written materials. After the training, all 13 operators reviewed the CT data and measured CT FFR in 24 vessels in 22 patients. Inter- and intraoperator variability and agreements between CT FFR and catheter-derived FFR measurements were evaluated.

Results

The overall intraclass correlation coefficient (ICC) among operators was 0.71 (95% confidence interval: 0.58, 0.83) with a mean absolute difference (± standard deviation) of 0.027 ± 0.022. The operators in arm 2 showed greater interoperator differences than those in arm 1 (0.031 ± 0.024 vs 0.023 ± 0.018; P = .024). Among operators who recalculated CT FFR, the mean CT FFR value did not significantly differ between the first and second calculations (ICC, 0.66; 95% confidence interval: 0.46, 0.87), with the medical specialists producing the lowest intraoperator variability (0.053 ± 0.060). The overall correlation coefficient between CT FFR and catheter FFR was r = 0.61, with a mean absolute difference of 0.096 ± 0.089.

Conclusion

Good reproducibility of CT FFR values calculated on-site on the basis of structural and fluid analysis was observed among operators of varying expertise. Face-to-face training sessions may cause less variability.© RSNA, 2019Supplemental material is available for this article.

CT FFR for Ischemia-Specific CAD With a New Computational Fluid Dynamics Algorithm: A Chinese Multicenter Study

OBJECTIVES

The aim of this study was to validate the feasibility of a novel structural and computational fluid dynamics-based fractional flow reserve (FFR) algorithm for coronary computed tomography angiography (CTA), using alternative boundary conditions to detect lesion-specific ischemia.

BACKGROUND

A new model of computed tomographic (CT) FFR relying on boundary conditions derived from structural deformation of the coronary lumen and aorta with transluminal attenuation gradient and assumptions regarding microvascular resistance has been developed, but its accuracy has not yet been validated.

METHODS

A total of 338 consecutive patients with 422 vessels from 9 Chinese medical centers undergoing CTA and invasive FFR were retrospectively analyzed. CT FFR values were obtained on a novel on-site computational fluid dynamics-based CT FFR (uCT-FFR [version 1.5, United-Imaging Healthcare, Shanghai, China]). Performance characteristics of uCT-FFR and CTA in detecting lesion-specific ischemia in all lesions, intermediate lesions (luminal stenosis 30% to 70%), and "gray zone" lesions (FFR 0.75 to 0.80) were calculated with invasive FFR as the reference standard. The effect of coronary calcification on uCT-FFR measurements was also assessed.

RESULTS

Per vessel sensitivities, specificities, and accuracies of 0.89, 0.91, and 0.91 with uCT-FFR, 0.92, 0.34, and 0.55 with CTA, and 0.94, 0.37, and 0.58 with invasive coronary angiography, respectively, were found. There was higher specificity, accuracy, and AUC for uCT-FFR compared with CTA and qualitative invasive coronary angiography in all lesions, including intermediate lesions (p < 0.001 for all). No significant difference in diagnostic accuracy was observed in the "gray zone" range versus the other 2 lesion groups (FFR ≤0.75 and >0.80; p = 0.397) and in patients with "gray zone" versus FFR ≤0.75 (p = 0.633) and versus FFR >0.80 (p = 0.364), respectively. No significant difference in the diagnostic performance of uCT-FFR was found between patients with calcium scores ≥400 and <400 (p = 0.393).

CONCLUSIONS

This novel computational fluid dynamics-based CT FFR approach demonstrates good performance in detecting lesion-specific ischemia. Additionally, it outperforms CTA and qualitative invasive coronary angiography, most notably in intermediate lesions, and may potentially have diagnostic power in gray zone and highly calcified lesions.

Coronary CT Angiography: Reversal of Earlier Utilization Trends

PURPOSE

To assess recent trends in utilization of coronary CT angiography (CCTA), based upon place of service and provider specialty.

MATERIALS AND METHODS

The nationwide Medicare Part B master files for 2006 through 2016 were the data source. Current Procedural Terminology, version 4 codes for CCTA were selected. The files provided procedure volume for each code. Utilization rates per 100,000 Medicare fee-for-service enrollees were then calculated. Medicare's place-of-service codes were used to identify CCTAs performed in private offices, hospital outpatient departments (HOPDs), emergency departments (EDs), and inpatient settings. Physician specialty codes were used to identify CCTAs interpreted by radiologists, cardiologists, and all other physicians as a group. Medicare practice share was defined as the percent of total Medicare utilization that was billed by each specialty.

RESULTS

The total utilization rate of CCTA in the Medicare population rose sharply from 2006 to 2007, peaking at 210.3 per 100,000 enrollees in 2007. Radiologists' CCTA practice share in 2007 was 32%, compared with 60% for cardiologists. The overall utilization rate then declined to a nadir of 107.1 per 100,000 enrollees in 2013, but subsequently increased to 131.0 by 2016. By that year, radiologists' share of CCTA practice had risen to 58%, compared with 38% for cardiologists. HOPD utilization increased sharply since 2010, primarily among radiologists. In EDs and inpatient settings, greater utilization has also occurred recently, primarily among radiologists. By contrast, private office utilization has dropped sharply since 2007.

CONCLUSION

After years of declining utilization, the utilization rate of CCTA is now increasing, predominantly among radiologists.

The transluminal attenuation gradient in coronary CT angiography for the detection of hemodynamically significant disease: can all arteries be treated equally?

OBJECTIVE

Results of the use of the transluminal attenuation gradient (TAG) at coronary CT angiography (CCTA) to predict hemodynamically significant disease vary widely. This study tested whether diagnostic performance of TAG to predict fractional flow reserve (FFR) ≤ 0.8 is improved when applied separately to subsets of coronary arteries that carry similar physiological flow.

METHODS

28 patients with 64 × 0.5 mm CCTA and invasive FFR in ≥1 major coronary artery were retrospectively evaluated. Two readers assessed TAG in each artery. The receiver operating characteristic (ROC) area under the curve (AUC) was used to assess the diagnostic performance of TAG to detect hemodynamically significant disease following a clinical use rule [negative: FFR > 0.8 or ≤ 25% diameter stenosis (DS) at invasive catheter angiography; positive: FFR ≤ 0.8 or ≥ 90% DS at invasive catheter angiography]. ROC AUC was compared for all arteries pooled together, vs separately for arteries carrying similar physiological flow (Group 1: all left anterior descending plus right-dominant left circumflex; Group 2: right-dominant RCA plus left/co-dominant left circumflex).

RESULTS

Of the 84 arteries, 30 had FFR measurements, 30 had ≤25% DS and 13 had ≥90% DS. 11 arteries with 26-89% DS and no FFR measurement were excluded. TAG interobserver reproducibility was excellent (Pearson r = 0.954, Bland-Altman bias: 0.224 Hounsfield unit cm^-1). ROC AUC to detect hemodynamically significant disease was higher when considering arteries separately (Group 1 AUC = 0.841, p = 0.039; Group 2 AUC = 0.840, p = 0.188), than when pooling all arteries together (AUC = 0.661).

CONCLUSION

Incorporating information on the physiology of coronary flow via the particular vessel interrogated and coronary dominance may improve the accuracy of TAG, a simple measurement that can be quickly performed at the time of CCTA interpretation to detect hemodynamically significant stenosis in individual coronary arteries. Advances in knowledge: The interpretation of TAG may benefit by incorporating information regarding which coronary artery is being interrogated.

Hybrid Imaging in Ischemic Heart Disease

Hybrid imaging for ischemic heart disease refers to the fusion of information from a single or usually from multiple cardiovascular imaging modalities enabling synergistic assessment of the presence, the extent, and the severity of coronary atherosclerotic disease along with the hemodynamic significance of lesions and/or with evaluation of the myocardial function. A combination of coronary computed tomography angiography with myocardial perfusion imaging, such as single-photon emission computed tomography and positron emission tomography, has been adopted in several centers and implemented in international coronary artery disease management guidelines. Interest has increased in novel hybrid methods including coronary computed tomography angiography-derived fractional flow reserve and computed tomography perfusion and these techniques hold promise for the imminent diagnostic and management approaches of patients with coronary artery disease. In this review, we discuss the currently available hybrid noninvasive imaging modalities used in clinical practice, research approaches, and exciting potential future technological developments.