Noninvasive FFR derived from coronary CT angiography in the management of coronary artery disease: technology and clinical update

The Effect of Severe Coronary Calcification on Diagnostic Performance of Computed Tomography-Derived Fractional Flow Reserve Analyses in People with Coronary Artery Disease

BACKGROUND

Negative CCTA can effectively exclude significant CAD, eliminating the need for further noninvasive or invasive testing. However, in the presence of severe CAD, the accuracy declines, thus necessitating additional testing. The aim of our study was to evaluate the diagnostic performance of noninvasive cFFR derived from CCTA, compared to ICA in detecting hemodynamically significant stenoses in participants with high CAC scores (>400).

METHODS

This study included 37 participants suspected of having CAD who underwent CCTA and ICA. CAC was calculated and cFFR analyses were performed using an on-site machine learning-based algorithm. Diagnostic accuracy parameters of CCTA and cFFR were calculated on a per-vessel level.

RESULTS

The median total CAC score was 870, with an IQR of 642-1370. Regarding CCTA, sensitivity and specificity for RCA were 60% and 67% with an AUC of 0.639; a LAD of 87% and 50% with an AUC of 0.688; an LCX of 33% and 90% with an AUC of 0.617, respectively. Regarding cFFR, sensitivity and specificity for RCA were 60% and 61% with an AUC of 0.606; a LAD of 75% and 54% with an AUC of 0.647; an LCX of 50% and 77% with an AUC of 0.647. No significant differences between AUCs of coronary CTA and cFFR for each vessel were found.

CONCLUSIONS

Our results showed poor diagnostic accuracy of CCTA and cFFR in determining significant ischemia-related lesions in participants with high CAC scores when compared to ICA. Based on our results and study limitations we cannot exclude cFFR as a method for determining significant stenoses in people with high CAC. A key issue is accurate and detailed lumen segmentation based on good-quality CCTA images.

The Role of Artificial Intelligence in Healthcare: Enhancing Coronary Computed Tomography Angiography for Coronary Artery Disease Management

This review aims to explore the potential of artificial intelligence (AI) in coronary CT angiography (CCTA), a key tool for diagnosing coronary artery disease (CAD). Because CAD is still a major cause of death worldwide, effective and accurate diagnostic methods are required to identify and manage the condition. CCTA certainly is a noninvasive alternative for diagnosing CAD, but it requires a large amount of data as input. We intend to discuss the idea of incorporating AI into CCTA, which enhances its diagnostic accuracy and operational efficiency. Using such AI technologies as machine learning (ML) and deep learning (DL) tools, CCTA images are automated to perfection and the analysis is significantly refined. It enables the characterization of a plaque, assesses the severity of the stenosis, and makes more accurate risk stratifications than traditional methods, with pinpoint accuracy. Automating routine tasks through AI-driven CCTA will reduce the radiologists' workload considerably, which is a standard benefit of such technologies. More importantly, it would enable radiologists to allocate more time and expertise to complex cases, thereby improving overall patient care. However, the field of AI in CCTA is not without its challenges, which include data protection, algorithm transparency, as well as criteria for standardization encoding. Despite such obstacles, it appears that the integration of AI technology into CCTA in the future holds great promise for keeping CAD itself in check, thereby aiding the fight against this disease and begetting better clinical outcomes and more optimized modes of healthcare. Future research on AI algorithms for CCTA, making ethical use of AI, and thereby overcoming the technical and clinical barriers to widespread adoption of this new tool, will hopefully pave the way for profound AI-driven transformations in healthcare.

Noninvasive computed tomography derived fractional flow reserve simulation based on microvascular tree model reconstruction

To establish a novel method for noninvasive computed tomography derived fractional flow reserve (CT-FFR) simulation based on microvascular tree model reconstruction and to evaluate the feasibility and diagnostic performance of the novel method in coronary artery disease compared with invasive fractional flow reserve (FFR). Twenty patients (20 vessels) who underwent coronary computed tomography angiography (CCTA) and invasive FFR were retrospectively studied. The anatomic epicardial coronary artery model was reconstructed based on CCTA image, and the microvascular tree model was simulated based on patient-specific anatomical structures and physiological principles. Numerical simulation was subsequently performed using the CFD method with full consideration of the variation of viscosity in microvascular. Two patients with the FFR value of .80 were selected for adjusting the parameters of the model, while the remaining 18 patients were selected as a validation cohort. After simulation, CT-FFR was compared with invasive FFR with a threshold of .80. Eleven (55%) patients had an abnormal FFR that was less than or equal to .80. Compared with invasive FFR, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CT-FFR with an optimal threshold of .80 were 100%, 77.8%, 81.8%, 100%, 88.89%, respectively. There were a good correlation and consistency between CT-FFR and invasive FFR. Time per patient of CT-FFR analysis was less than 15 min. CT-FFR based on microvascular tree model reconstruction is feasible with good diagnostic performance. It requires a short processing time with excellent accuracy. Large multicenter prospective studies are required for further demonstrating the diagnostic performance of this novel model in myocardium ischemia evaluation.

Real world impact of added FFR-CT to coronary CT angiography on clinical decision-making and patient prognosis - IMPACT FFR study

OBJECTIVES

The addition of CT-derived fractional flow reserve (FFR-CT) increases the diagnostic accuracy of coronary CT angiography (CCTA). We assessed the impact of FFR-CT in routine clinical practice on clinical decision-making and patient prognosis in patients suspected of stable coronary artery disease (CAD).

METHODS

This retrospective, single-center study compared a cohort that received CCTA with FFR-CT to a historical cohort that received CCTA before FFR-CT was available. We assessed the clinical management decisions after FFR-CT and CCTA and the rate of major adverse cardiac events (MACEs) during the 1-year follow-up using chi-square tests for independence. Kaplan-Meier curves were used to visualize the occurrence of safety outcomes over time.

RESULTS

A total of 360 patients at low to intermediate risk of CAD were included, 224 in the CCTA only group, and 136 in the FFR-CT group. During follow-up, 13 MACE occurred in 12 patients, 9 (4.0%) in the CCTA group, and three (2.2%) in the FFR-CT group. Clinical management decisions differed significantly between both groups. After CCTA, 60 patients (26.5%) received optimal medical therapy (OMT) only, 115 (51.3%) invasive coronary angiography (ICA), and 49 (21.9%) single positron emission CT (SPECT). After FFR-CT, 106 patients (77.9%) received OMT only, 27 (19.9%) ICA, and three (2.2%) SPECT (p < 0.001 for all three options). The revascularization rate after ICA was similar between groups (p = 0.15). However, patients in the CCTA group more often underwent revascularization (p = 0.007).

CONCLUSION

Addition of FFR-CT to CCTA led to a reduction in (invasive) diagnostic testing and less revascularizations without observed difference in outcomes after 1 year.

KEY POINTS

• Previous studies have shown that computed tomography-derived fractional flow reserve improves the accuracy of coronary computed tomography angiography without changes in acquisition protocols. • This study shows that use of computed tomography-derived fractional flow reserve as gatekeeper to invasive coronary angiography in patients suspected of stable coronary artery disease leads to less invasive testing and revascularization without observed difference in outcomes after 1 year. • This could lead to a significant reduction in costs, complications and (retrospectively unnecessary) usage of diagnostic testing capacity, and a significant increase in patient satisfaction.

CFD Computation of Flow Fractional Reserve (FFR) in Coronary Artery Trees Using a Novel Physiologically Based Algorithm (PBA) Under 3D Steady and Pulsatile Flow Conditions

A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA was based on an extension of Murray’s law and additional inlet conditions prescribed iteratively and was implemented in OpenFOAM v1912 for testing and validation. 3D models of CATs were created using CT scans and computational meshes, and the results were compared to invasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between the calculated and experimental FFR was within 2.33–5.26% in the steady-state and transient simulations, respectively, when convergence was reached. The PBA was a reliable and physiologically sound technique compared to a current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for convergence. The accuracy of the PBA method was further confirmed using an FDA nozzle, which demonstrated good alignment with the CFD-validated values.

Artificial intelligence in coronary computed tomography angiography: Demands and solutions from a clinical perspective

Coronary computed tomography angiography (CCTA) is increasingly the cornerstone in the management of patients with chronic coronary syndromes. This fact is reflected by current guidelines, which show a fundamental shift towards non-invasive imaging - especially CCTA. The guidelines for acute and stable coronary artery disease (CAD) of the European Society of Cardiology from 2019 and 2020 emphasize this shift. However, to fulfill this new role, a broader availability in adjunct with increased robustness of data acquisition and speed of data reporting of CCTA is needed. Artificial intelligence (AI) has made enormous progress for all imaging methodologies concerning (semi)-automatic tools for data acquisition and data post-processing, with outreach toward decision support systems. Besides onco- and neuroimaging, cardiac imaging is one of the main areas of application. Most current AI developments in the scenario of cardiac imaging are related to data postprocessing. However, AI applications (including radiomics) for CCTA also should enclose data acquisition (especially the fact of dose reduction) and data interpretation (presence and extent of CAD). The main effort will be to integrate these AI-driven processes into the clinical workflow, and to combine imaging data/results with further clinical data, thus - beyond the diagnosis of CAD- enabling prediction and forecast of morbidity and mortality. Furthermore, data fusing for therapy planning (e.g., invasive angiography/TAVI planning) will be warranted. The aim of this review is to present a holistic overview of AI applications in CCTA (including radiomics) under the umbrella of clinical workflows and clinical decision-making. The review first summarizes and analyzes applications for the main role of CCTA, i.e., to non-invasively rule out stable coronary artery disease. In the second step, AI applications for additional diagnostic purposes, i.e., to improve diagnostic power (CAC = coronary artery classifications), improve differential diagnosis (CT-FFR and CT perfusion), and finally improve prognosis (again CAC plus epi- and pericardial fat analysis) are reviewed.

Value of Delta Fractional Flow Reserve (ΔFFR) For Predicting Coronary Ischemic Lesions

Background:

The decrease in fractional flow reserve (FFR) after adenosine administration from baseline FFR value (termed as ΔFFR) may reflect the compensatory capacity of the microvascular circulation and thus may predict significant coronary stenotic lesions. We aimed to investigate whether baseline FFR and ΔFFR can help identify the coronary ischemic lesion and its severity.

Materials and Methods:

This cross-sectional study was performed on 154 consecutive patients (Mean age 62.42 ± 9.36 years) that underwent coronary angiography and with definitive intermediate coronary lesions at any of the coronary vessels. FFR was calculated by dividing the mean distal intracoronary pressure by the mean arterial pressure. ΔFFR was also defined as the difference between baseline FFR and hyperemic FFR (considering FFR<0.75 as the criteria for ischemia).

Results:

The area under receiver-operating characteristic curve for baseline FFR was found as 0.933, and for ΔFFR was 0.946 indicated high values of both indices for predicting ischemic lesions. The best cut-off point for baseline FFR and ΔFFR for discriminating ischemic lesions from the normal condition was 89.5 (yielding a sensitivity of 92.2% and a specificity of 68.0%) and 9.5 (yielding a sensitivity of 96.0% and a specificity of 85.3%), respectively.

Conclusion:

Our study could successfully demonstrate the high value of both baseline FFR and ΔFFR for predicting coronary ischemic lesions with the cut-off values of <89.5 and >9.5, respectively.

Coronary computed tomography angiography using model-based iterative reconstruction algorithms in the detection of significant coronary stenosis: how the plaque type influences the diagnostic performance

Purpose

To evaluate the ability of coronary computed tomography angiography (CCTA) with model-based iterative reconstruction (MBIR) algorithm in detecting significant coronary artery stenosis compared with invasive coronary angiography (ICA).

Material and methods

We retrospectively identified 55 patients who underwent CCTA using the MBIR algorithm with evidence of at least one significant stenosis (≥ 50%) and an ICA within three months. Patients were stratified based on calcium score; stenoses were classified by type and by coronary segment involved. Dose-length-product was compared with the literature data obtained with previous reconstruction algorithms. Coronary artery stenosis was estimated on ICAs based on a qualitative method.

Results

CCTA data were confirmed by ICA in 89% of subjects, and in 73% and 94% of patients with CS < 400 and ≥ 400, respectively. ICA confirmed 81% of calcific stenoses, 91% of mixed, and 67% of soft plaques. Both the dose exposure of patients with prospective acquisition (34) and the exposure of the whole population were significantly lower than the standard of reference (p < 0.001 and p = 0.007).

Conclusions

CCTA with MBIR is valuable in detecting significant coronary artery stenosis with a solid reduction of radiation dose. Diagnostic performance was influenced by plaque composition, being lower compared with ICA for patients with lower CAC score and soft plaques; the visualisation of an intraluminal hypodensity could cause false positives, particularly in D1 and MO segments.

Computational instantaneous wave-free ratio (IFR) for patient-specific coronary artery stenoses using 1D network models

In this work, we estimate the diagnostic threshold of the instantaneous wave-free ratio (iFR) through the use of a one-dimensional haemodynamic framework. To this end, we first compared the computed fractional flow reserve (cFFR) predicted from a 1D computational framework with invasive clinical measurements. The framework shows excellent promise and utilises minimal patient data from a cohort of 52 patients with a total of 66 stenoses. The diagnostic accuracy of the cFFR model was 75.76%, with a sensitivity of 71.43%, a specificity of 77.78%, a positive predictive value of 60%, and a negative predictive value of 85.37%. The validated model was then used to estimate the diagnostic threshold of iFR. The model determined a quadratic relationship between cFFR and the ciFR. The iFR diagnostic threshold was determined to be 0.8910 from a receiver operating characteristic curve that is in the range of 0.89 to 0.9 that is normally reported in clinical studies.

Cardiac Computed Tomography - More Than Coronary Arteries? A Clinical Update

BACKGROUND

 Rapid improvement of scanner and postprocessing technology as well as the introduction of minimally invasive procedures requiring preoperative imaging have led to the broad utilization of cardiac computed tomography (CT) beyond coronary CT angiography (CTA).

METHOD

 This review article presents an overview of recent literature on cardiac CT. The goal is to summarize the current guidelines on performing cardiac CT and to list established as well as emerging techniques with a special focus on extracoronary applications.

RESULTS AND CONCLUSION

 Most recent guidelines for the appropriate use of cardiac CT include the evaluation of coronary artery disease, cardiac morphology, intra- and extracardiac structures, and functional and structural assessment of the myocardium under certain conditions. Besides coronary CTA, novel applications such as the calculation of a CT-derived fractional flow reserve (CT-FFR), assessment of myocardial function and perfusion imaging, as well as pre-interventional planning in valvular heart disease or prior pulmonary vein ablation in atrial fibrillation are becoming increasingly important. Especially these extracoronary applications are of growing interest in the field of cardiac CT and are expected to be gradually implemented in the daily clinical routine.

KEY POINTS

  · Coronary artery imaging remains the main indication for cardiac CT. · Novel computational fluid dynamics allow the calculation of a CT-derived fractional flow reserve in patients with known or suspected coronary artery disease. · Cardiac CT delivers information on left ventricular volume as well as myocardial function and perfusion. · CT is the cardinal element for pre-interventional planning in transcatheter valve implantation and pulmonary vein isolation.

CITATION FORMAT

· Taron J, Foldyna B, Eslami P et al. Cardiac Computed Tomography - More Than Coronary Arteries? A Clinical Update. Fortschr Röntgenstr 2019; 191: 817 - 826.

Advances in Imaging and Heart Failure: Where are we Heading?

Advanced cardiac imaging, following technological advances, has progressed significantly; it now serves as a diagnostic as well as a prognostic tool. Heart failure patients demand constant follow-up with baseline imaging such as echocardiography or more advanced imaging such as stress imaging. Imaging guides treatment as well as interventional procedures for the improvement of heart failure patients. This review aims to summarise the latest imaging techniques in heart failure diagnosis and treatment.

Anomalous Origin of Left Anterior Descending Artery and Left Circumflex Artery from Right Coronary Sinus with Malignant Left Anterior Descending Artery Course: Role of Coronary CT Angiography Derived Fractional Flow Reserve in Decision Making

Congenital coronary anomalies are uncommon and are mostly asymptomatic; however, patients may have symptoms depending on the origin and course of anomalous artery. Very rarely, coronary anomalies can also lead to life-threatening complications especially in young athletes. A malignant course of the left main (LM) or left anterior descending (LAD) artery between aorta and pulmonary artery is considered the most significant risk factor for such complications. Various noninvasive tests are available to evaluate myocardial ischemia due to anomalous coronary artery. Coronary computed tomography (CT) angiogram derived fractional flow reserve (CT-FFR) is a noninvasive diagnostic test which has shown promising results in the hemodynamic assessment of obstructive coronary artery disease. However, its role in coronary anomalies has not been studied. We present a case of a 22-year-old male who presented with atypical chest pain and was found to have anomalous origin of left anterior descending (LAD) artery and left circumflex (LCX) artery from right coronary sinus. LAD had a malignant course for which CT-FFR was done which was hemodynamically nonsignificant. The decision was made to manage the patient conservatively.

Comparison of Computed Tomography derived Fractional Flow Reserve to invasive Fractional Flow Reserve in Diagnosis of Functional Coronary Stenosis: A Meta-Analysis

Computed Tomography derived Fractional Flow Reserve (CTFFR) is an emerging non-invasive imaging modality to assess functional significance of coronary stenosis. We performed a meta-analysis to compare the diagnostic performance of CTFFR to invasive Fractional Flow reserve (FFR). Electronic search was performed to identify relevant articles. Pooled Estimates of sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-) and diagnostic odds ratio (DOR) with corresponding 95% confidence intervals (CI) were calculated at the patient level as well as the individual vessel level using hierarchical logistic regression, summary receiver operating characteristic (SROC) curve and area under the curve were estimated. Our search yielded 559 articles and of these 17 studies was included in the analysis. A total of 2,191 vessels in 1294 patients were analyzed. Pooled estimates of sensitivity, specificity, LR+, LR- and DOR with corresponding 95% CI at per-patient level were 83% (79-87), 72% (68-76), 3.0 (2.6-3.5), 0.23 (0.18-0.29) and 13 (9-18) respectively. Pooled estimates of sensitivity, specificity, LR+, LR- and DOR with corresponding 95% CI at per-vessel level were 85% (83-88), 76% (74-79), 3.6 (3.3-4.0), 0.19 (0.16-0.22) and 19 (15-24). The area under the SROC curve was 0.89 for both per patient level and at the per vessel level. In our meta-analysis, CTFFR demonstrated good diagnostic performance in identifying functionally significant coronary artery stenosis compared to the FFR.

Diagnostic performance of machine-learning-based computed fractional flow reserve (FFR) derived from coronary computed tomography angiography for the assessment of myocardial ischemia verified by invasive FFR

To explore the diagnostic performance of a machine-learning-based (ML-based) computed fractional flow reserve (cFFR) derived from coronary computed tomography angiography (CCTA) in identifying ischemia-causing lesions verified by invasive FFR in catheter coronary angiography (ICA). We retrospectively studied 117 intermediate coronary artery lesions [40-80% diameter stenosis (DS)] from 105 patients (mean age 62 years, 32 female) who had undergone invasive FFR. CCTA images were used to compute cFFR values on the workstation. DS and the myocardium jeopardy index (MJI) of coronary stenosis were also assessed with CCTA. The diagnostic performance of cFFR was evaluated, including its correlation with invasive FFR and its diagnostic accuracy. Then, its performance was compared to that of combined DS and MJI. Of the 117 lesions, 36 (30.8%) had invasive FFR ≤ 0.80; 22 cFFR were measured as true positives and 74 cFFR as true negatives. The average time of cFFR assessment was 18 ± 7 min. The cFFR correlated strongly to invasive FFR (Spearman's coefficient 0.665, p < 0.01). When diagnosing invasive FFR ≤ 0.80, the accuracy of cFFR was 82% with an AUC of 0.864, which was significantly higher than that of DS (accuracy 75%, AUC 0.777, p = 0.013). The AUC of cFFR was not significantly different from that of combined DS and MJI (0.846, p = 0.743). cFFR ≤ 0.80 based on CCTA showed good diagnostic performance for detecting ischemia-producing lesions verified by invasive FFR. The short calculation time required renders cFFR promising for clinical use.

A new look at the heart-novel imaging techniques

The development and successful implementation of cutting-edge imaging technologies to visualise cardiac anatomy and function is a key component of effective diagnostic efforts in cardiology. Here, we describe a number of recent exciting advances in the field of cardiology spanning from macro- to micro- to nano-scales of observation, including magnetic resonance imaging, computed tomography, optical mapping, photoacoustic imaging, and electron tomography. The methodologies discussed are currently making the transition from scientific research to routine clinical use, albeit at different paces. We discuss the most likely trajectory of this transition into clinical research and standard diagnostics, and highlight the key challenges and opportunities associated with each of the methodologies.

Coronary CT angiography in acute chest pain

Coronary computed tomographic angiography has become a reliable diagnostic tool in the evaluation of patients with chest pain. Studies have shown this modality to be accurate and safe when compared with conventional methods of assessing patients with chest pain. We review the recent developments with coronary computed tomographic angiography and devote particular attention toward its application to triage patients in the emergency department.