Current Evidence in Cardiothoracic Imaging: Growing Evidence for Coronary Computed Tomography Angiography as a First-line Test in Stable Chest Pain

Ultrasound Carotid Plaque Score and Severity of Coronary Artery Disease Assessed by Computed Tomography Angiography in Patients with Arterial Hypertension

The aim of the study was to assess the relationship between the presence of atherosclerotic lesions in the carotid arteries detected by ultrasound and the occurrence of atherosclerosis in the coronary arteries determined by computed tomography (CT) in patients with arterial hypertension (HTA). A total of 83 patients with HTA were qualified for the study (age: 71.3 ± 8.5 years). All subjects underwent carotid arteries ultrasound and coronary arteries CT. The carotid plaque score was assessed using ultrasound. The studied group was divided into two subgroups: a subgroup with the carotid plaque score ≤ 1 (A) and a subgroup with carotid plaque score ≥2 (B). Coronary arteries CT assessed coronary artery calcium score (CACS) and degree of coronary stenosis based on CAD-RADS. In subgroup B, a significantly higher CACS (411.3 ± 70.1 vs. 93.5 ± 31.8) and significantly higher grade in the CAD-RADS classification were demonstrated than in subgroup A (CAD-RADS ≥ 3: 21.8 vs. 6.0%). The regression analysis showed that carotid plaque score and age are independent risk factors for the severity of atherosclerotic lesions in the coronary arteries. In summary, ultrasound assessment of the carotid plaque score in patients with HTA could be considered as surrogate indicator of the risk and severity of atherosclerotic changes in the coronary arteries, but further studies are necessary to corroborate these results.

Deep Learning-Based Automated Labeling of Coronary Segments for Structured Reporting of Coronary Computed Tomography Angiography in Accordance With Society of Cardiovascular Computed Tomography Guidelines

PURPOSE

To evaluate a novel deep learning (DL)-based automated coronary labeling approach for structured reporting of coronary artery disease according to the guidelines of the Society of Cardiovascular Computed Tomography (CT) on coronary CT angiography (CCTA).

PATIENTS AND METHODS

A retrospective cohort of 104 patients (60.3 ± 10.7 y, 61% males) who had undergone prospectively electrocardiogram-synchronized CCTA were included. Coronary centerlines were automatically extracted, labeled, and validated by 2 expert readers according to Society of Cardiovascular CT guidelines. The DL algorithm was trained on 706 radiologist-annotated cases for the task of automatically labeling coronary artery centerlines. The architecture leverages tree-structured long short-term memory recurrent neural networks to capture the full topological information of the coronary trees by using a two-step approach: a bottom-up encoding step, followed by a top-down decoding step. The first module encodes each sub-tree into fixed-sized vector representations. The decoding module then selectively attends to the aggregated global context to perform the local assignation of labels. To assess the performance of the software, percentage overlap was calculated between the labels of the algorithm and the expert readers.

RESULTS

A total number of 1491 segments were identified. The artificial intelligence-based software approach yielded an average overlap of 94.4% compared with the expert readers' labels ranging from 87.1% for the posterior descending artery of the right coronary artery to 100% for the proximal segment of the right coronary artery. The average computational time was 0.5 seconds per case. The interreader overlap was 96.6%.

CONCLUSIONS

The presented fully automated DL-based coronary artery labeling algorithm provides fast and precise labeling of the coronary artery segments bearing the potential to improve automated structured reporting for CCTA.

Approach to Imaging of Patients Presenting With Acute Coronary Syndrome With No Culprit Lesion Identified at Angiography

Chest pain is a common chief complaint among patients presenting to the emergency department. However, in the scenario where the clinical presentation is consistent with acute coronary syndrome and no culprit lesions are identified on angiography, clinicians and cardiac imagers should be informed of the differential diagnosis and appropriate imaging modalities used to investigate the potential causes. This review describes an imaging-based algorithm that highlights the diagnostic possibilities, their differentiating imaging features, and the important role of cardiovascular magnetic resonance imaging for narrowing the differential diagnosis.

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

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

[Morphological and functional diagnostics of coronary artery disease by computed tomography]

Computed tomography coronary angiography (cCTA) is a safe option for the noninvasive exclusion of significant coronary stenoses in patients with a low or moderate pretest probability for coronary artery disease (CAD). Furthermore, it also allows functional and morphological assessment of coronary stenoses. The European Society of Cardiology (ESC) guidelines on the diagnosis and management of chronic coronary syndrome published in 2019 have strengthened the importance of cCTA in this context and for this reason it has experienced a considerable upgrade. The determination of the Agatston score is a clinically established method for quantifying coronary calcification and influences the initiation of drug treatment. With technologies, such as the introduction of electrocardiography (ECG)-controlled dose modulation and iterative image reconstruction, cCTA can be performed with high image quality and low radiation exposure. Anatomic imaging of coronary stenoses alone is currently being augmented by innovative techniques, such as myocardial CT perfusion imaging or CT-fractional flow reserve (FFR) but the clinical value of these methods merits further investigation. The cCTA could therefore develop into a gatekeeper with respect to the indications for invasive coronary diagnostics and interventions.

Impact of machine-learning-based coronary computed tomography angiography-derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

OBJECTIVES

To evaluate feasibility and diagnostic performance of coronary CT angiography (CCTA)-derived fractional flow reserve (CT-FFR) for detection of significant coronary artery disease (CAD) and decision-making in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR) to potentially avoid additional pre-TAVR invasive coronary angiography (ICA).

METHODS

Consecutive patients with severe AS (n = 95, 78.6 ± 8.8 years, 53% female) undergoing pre-procedural TAVR-CT followed by ICA with quantitative coronary angiography were retrospectively analyzed. CCTA datasets were evaluated using CAD Reporting and Data System (CAD-RADS) classification. CT-FFR measurements were computed using an on-site machine-learning algorithm. A combined algorithm was developed for decision-making to determine if ICA is needed based on pre-TAVR CCTA: [1] all patients with CAD-RADS ≥ 4 are referred for ICA; [2] patients with CAD-RADS 2 and 3 are evaluated utilizing CT-FFR and sent to ICA if CT-FFR ≤ 0.80; [3] patients with CAD-RADS < 2 or CAD-RADS 2-3 and normal CT-FFR are not referred for ICA.

RESULTS

Twelve patients (13%) had significant CAD (≥ 70% stenosis) on ICA and were treated with PCI. Twenty-eight patients (30%) showed CT-FFR ≤ 0.80 and 24 (86%) of those were reported to have a maximum stenosis ≥ 50% during ICA. Using the proposed algorithm, significant CAD could be identified with a sensitivity, specificity, and positive and negative predictive value of 100%, 78%, 40%, and 100%, respectively, potentially decreasing the number of necessary ICAs by 65 (68%).

CONCLUSION

Combination of CT-FFR and CAD-RADS is able to identify significant CAD pre-TAVR and bears potential to significantly reduce the number of needed ICAs.

KEY POINTS

• Coronary CT angiography-derived fractional flow reserve (CT-FFR) using machine learning together with the CAD Reporting and Data System (CAD-RADS) classification safely identifies significant coronary artery disease based on quantitative coronary angiography in patients prior to transcatheter aortic valve replacement. • The combination of CT-FFR and CAD-RADS enables decision-making and bears the potential to significantly reduce the number of needed invasive coronary angiographies.

CT in Transcatheter-delivered Treatment of Valvular Heart Disease

Minimally invasive strategies to treat valvular heart disease have emerged over the past 2 decades. The use of transcatheter aortic valve replacement in the treatment of severe aortic stenosis, for example, has recently expanded from high- to low-risk patients and became an alternative treatment for those with prohibitive surgical risk. With the increase in transcatheter strategies, multimodality imaging, including echocardiography, CT, fluoroscopy, and cardiac MRI, are used. Strategies for preprocedural imaging strategies vary depending on the targeted valve. Herein, an overview of preprocedural imaging strategies and their postprocessing approaches is provided, with a focus on CT. Transcatheter aortic valve replacement is reviewed, as well as less established minimally invasive treatments of the mitral and tricuspid valves. In addition, device-specific details and the goals of CT imaging are discussed. Future imaging developments, such as peri-procedural fusion imaging, machine learning for image processing, and mixed reality applications, are presented.

Optimization of contrast material administration for coronary CT angiography using a software-based test-bolus evaluation algorithm

OBJECTIVES

To evaluate the benefit of a prototype circulation time-based test bolus evaluation algorithm for the individualized optimal timing of contrast media (CM) delivery in patients undergoing coronary CT angiography (CCTA).

METHODS

Thirty-two patients (62 ± 16 years) underwent CCTA using a prototype bolus evaluation tool to determine the optimal time-delay for CM administration. Contrast attenuation, signal-to-noise ratio (SNR), objective, and subjective image quality were evaluated by two independent radiologists. Results were compared to a control cohort (matched for age, sex, body mass index, and tube voltage) of patients who underwent CCTA using the generic test bolus peak attenuation +4 s protocol as scan delay.

RESULTS

In the study group, the mean time delay to CCTA acquisition was significantly longer (26.0 ± 2.9 s) compared to the control group (23.1 ± 3.5 s; p < 0.01). In the study group, SNR improvement was seen in the right coronary artery (17.5 vs 13; p = 0.028), the left main (15.3 vs 12.3; p = 0.027), and the left anterior descending artery (18.5 vs 14.1; p = 0.048). Subjective image quality was rated higher in the study group (4.75 ± 0.7 vs 3.64 ± 0.5; p < 0.001).

CONCLUSIONS

The prototype test bolus evaluation algorithm provided a reliable patient-specific scan delay for CCTA that ensured homogenous vascular attenuation, improvement in objective and subjective image quality, and avoidance of beam hardening artifacts.

ADVANCES IN KNOWLEDGE

The prototype contrast bolus evaluation and optimization tool estimated circulation time-based time-delay improves the overall quality of CCTA.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Computed Tomography Coronary Plaque Characteristics Predict Ischemia Detected by Invasive Fractional Flow Reserve

PURPOSE

Coronary computed tomography angiography (CCTA) plaque quantification has been proposed to be of incremental value in the prediction of ischemia, although prior studies have shown conflicting results. We aimed to determine whether CCTA plaque features assessed on a commercial vendor platform predict invasive fractional flow reserve (FFR)/instantaneous wave-free ratio (IFR).

METHODS

Consecutive patients who underwent CCTA for evaluation of suspected stable coronary artery disease followed by invasive coronary physiology testing within 60 days at a single academic center were identified retrospectively. Semiautomated plaque quantification of the vessel proximal to the location of FFR/IFR measurement was carried out in TeraRecon, along with simple visual assessment for high-risk plaque features of positive remodeling, spotty calcification, low-attenuation plaque (LAP), and lesion length. Ischemia was defined by FFR ≤0.80 or IFR ≤0.89.

RESULTS

A total of 134 patients (62% male, mean age 62±10 y) were included in this study. On univariate logistic regression, the following visual plaque analysis parameters were predictive of ischemia: positive remodeling (odds ratio [OR] with 95% confidence interval [CI]: 4.96; 2.25-10.95; P<0.001), lesion length (OR for every 1 mm with 95% CI: 1.24; 1.14-1.34; P<0.001), spotty calcification (OR with 95% CI: 6.67; 1.67-26.64; P=0.007), and LAP (OR with 95% CI: 30; 3.78-246; P=0.001). None of the semiautomated plaque quantification parameters, such as noncalcified plaque volume or LAP volume, were predictive of ischemia. On stepwise multivariable logistic regression, lesion length (OR with 95% CI: 1.25; 1.14-1.37; P<0.0001) and LAP (OR with 95% CI: 43; 4.4-438; P=0.001) were significant predictors of ischemia, improving the area under the curve of CCTA from 0.53 to 0.87.

CONCLUSIONS

Simple visual plaque assessment for high-risk plaque features improved the performance of CCTA to predict ischemia. Semiautomated plaque quantification performed on a commercial vendor platform was not predictive of ischemia.

Non-invasive fractional flow reserve (FFRCT) in the evaluation of acute chest pain - Concepts and first experiences

OBJECTIVE

To evaluate 30 day rate of major adverse cardiac events (MACE) utilizing cCTA and FFR_CT for evaluation of patients presenting to the Emergency Department (ED) with acute chest pain.

MATERIALS AND METHODS

Patients between the ages of 18-95 years who underwent clinically indicated cCTA and FFR_CT in the evaluation of acute chest pain in the emergency department were retrospectively evaluated for 30 day MACE, repeat presentation/admission for chest pain, revascularization, and additional testing.

RESULTS

A total of 59 patients underwent CCTA and subsequent FFR_CT for the evaluation of acute chest pain in the ED over the enrollment period. 32 out of 59 patients (54 %) had negative FFR_CT (>0.80) out of whom 18 patients (55 %) were discharged from the ED. Out of the 32 patients without functionally significant CAD by FFR_CT, 32 patients (100 %) underwent no revascularization and 32 patients (100 %) had no MACE at the 30-day follow-up period.

CONCLUSION

In this limited retrospective study, patients presenting to the ED with acute chest pain and with CCTA with subsequent FFR_CT of >0.8 had no MACE at 30 days; however, for many of these patients results were not available at time of clinical decision making by the ED physician.

Interobserver Reliability of the Coronary Artery Disease Reporting and Data System in Clinical Practice

PURPOSE

This study aimed to evaluate interobserver reproducibility between cardiothoracic radiologists applying the Coronary Artery Disease Reporting and Data System (CAD-RADS) to describe atherosclerotic burden on coronary computed tomography angiography.

METHODS

Forty clinical computed tomography angiography cases were retrospectively and independently evaluated by 3 attending and 2 fellowship-trained cardiothoracic radiologists using the CAD-RADS lexicon. Radiologists were blinded to patient history and underwent initial training using a practice set of 10 subjects. Interobserver reproducibility was assessed using an intraclass correlation (ICC) on the basis of single-observer scores, absolute agreement, and a 2-way random-effects model. Nondiagnostic studies were excluded. ICC was also performed for CAD-RADS scores grouped by management recommendations for absent (0), nonobstructive (1 to 2), and potentially obstructive (3 to 5) CAD.

RESULTS

Interobserver reproducibility was moderate to good (ICC: 0.748, 95% confidence interval [CI]: 0.639-0.842, P<0.0001), with higher agreement among cardiothoracic radiology fellows (ICC: 0.853, 95% CI: 0.730-0.922, P<0.0001) than attending radiologists (ICC: 0.711, 95% CI: 0.568-0.824, P<0.0001). Interobserver reproducibility for clinical management categories was marginally decreased (ICC: 0.692, 95% CI: 0.570-0.802, P<0.0001). The average percent agreement between pairs of radiologists was 84.74%. Percent observer agreement was significantly reduced in the presence (M=62.22%, SD=15.17%) versus the absence (M=80.91%, SD=17.97%) of modifiers, t(37.95)=3.566, P=0.001.

CONCLUSIONS

Interobserver reliability and agreement with the CAD-RADS terminology are moderate to good in clinical practice. However, further investigations are needed to characterize the causes of interobserver disagreement that may lead to differences in management recommendations.

Prevalence of Abnormal Coronary Findings on Coronary Computed Tomography Angiography Among Young Adults Presenting With Chest Pain

PURPOSE

We evaluated the prevalence of coronary stenosis on coronary computed tomography angiography (CCTA) in patients aged 18 to 30 years, who presented to the emergency department with chest pain. We also examined the risk factors potentially associated with abnormal coronary findings on CCTA in this age group.

MATERIALS AND METHODS

A total of 884 patients were retrospectively evaluated. Indication for CCTA was guided by our hospital's chest pain protocol based on ACC/AHA guidelines. These were performed using the standard technique and interpreted based on CAD-RADS guidelines. Scans were identified as abnormal if atherosclerotic coronary artery disease (CAD), myocardial bridging (MB), or any anatomic coronary artery anomaly were present.

RESULTS

Twenty-two percent of patients had a coronary abnormality on CCTA. The most common abnormality was MB (17.3%), followed by CAD (4.4%) and coronary anomalies (1.5%). A small minority had stenosis (2.8%), most commonly caused by CAD. Most cases with stenosis were minimal to mild (72%) with 0.8% having coronary stenosis ≥50%. Age and male sex were risk factors for both coronary artery stenosis (odds ratio: 1.32 and 4.50, 95% confidence interval: 1.03-1.69, and 1.23-16.46, P=0.028 and 0.023, respectively) and CAD (odds ratio: 1.52 and 3.67, 95% confidence interval: 1.14-2.04, and 1.26-10.66, P=0.005 and 0.017, respectively).

CONCLUSIONS

Epicardial coronary stenosis is rarely the cause of chest pain among young adult patients presenting to the emergency department. Age and male sex were both risk factors for coronary artery stenosis/disease in this age group.

Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography

PURPOSE

The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC) from coronary computed tomography angiography (CCTA) data.

MATERIALS AND METHODS

Under an IRB waiver and in HIPAA compliance, a total of 194 patients who had undergone CCTA were retrospectively included. Two observers independently evaluated the image quality and recorded the presence of CAC in the right (RCA), the combination of left main and left anterior descending (LM-LAD), and left circumflex (LCx) coronary arteries. Noncontrast CACS scans were allowed to be used in cases of uncertainty. Heart and coronary artery centerline detection and labeling were automatically performed. Presence of CAC was assessed by a RNN-LSTM. The algorithm's overall and per-vessel sensitivity, specificity, and diagnostic accuracy were calculated.

RESULTS

CAC was absent in 84 and present in 110 patients. As regards CCTA, the median subjective image quality, signal-to-noise ratio, and contrast-to-noise ratio were 3.0, 13.0, and 11.4. A total of 565 vessels were evaluated. On a per-vessel basis, the algorithm achieved a sensitivity, specificity, and diagnostic accuracy of 93.1% (confidence interval [CI], 84.3%-96.7%), 82.76% (CI, 74.6%-89.4%), and 86.7% (CI, 76.8%-87.9%), respectively, for the RCA, 93.1% (CI, 86.4%-97.7%), 95.5% (CI, 88.77%-98.75%), and 94.2% (CI. 90.2%-94.6%), respectively, for the LM-LAD, and 89.9% (CI, 80.2%-95.8%), 90.0% (CI, 83.2%-94.7%), and 89.9% (CI, 85.0%-94.1%), respectively, for the LCx. The overall sensitivity, specificity, and diagnostic accuracy were 92.1% (CI, 92.1%-95.2%), 88.9% (CI. 84.9%-92.1%), and 90.3% (CI, 88.0%-90.0%), respectively. When accounting for image quality, the algorithm achieved a sensitivity, specificity, and diagnostic accuracy of 76.2%, 87.5%, and 82.2%, respectively, for poor-quality data sets and 93.3%, 89.2% and 90.9%, respectively, when data sets rated adequate or higher were combined.

CONCLUSION

The proposed RNN-LSTM demonstrated high diagnostic accuracy for the detection of CAC from CCTA.

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.

Visually Estimated RESOLVE Score Based on Coronary Computed Tomography to Predict Side Branch Occlusion in Percutaneous Bifurcation Intervention

PURPOSE

The quantitative RESOLVE (Risk prEdiction of Side branch OccLusion in coronary bifurcation interVEntion) score derived from coronary computed tomography angiography (coronary CTA) was developed as a noninvasive and accurate prediction tool for side branch (SB) occlusion in coronary bifurcation intervention. We aimed to determine the ability of a visually estimated CTA-derived RESOLVE score (V-RESOLVE score) to predict SB occlusion in coronary bifurcation intervention.

MATERIALS AND METHODS

The present study included 363 patients with 400 bifurcation lesions. CTA-derived V-RESOLVE score was derived and compared with the quantitative CTA-derived RESOLVE score. The scoring systems were divided into quartiles, and classified as the high-risk and non-high-risk groups. SB occlusion was defined as any decrease in thrombolysis in myocardial infarction flow grade after main vessel stenting.

RESULTS

In total, 28 SB occlusions (7%) occurred. The concordance between visual and quantitative CTA analysis showed poor to excellent agreement (weighted κ range: 0.099 to 0.867). The area under the receiver operating curve for the prediction of SB occlusion was significantly higher for the CTA-derived V-RESOLVE score than for quantitative CTA-derived RESOLVE score (0.792 vs. 0.709, P=0.049). The total net reclassification index was 42.7% (P=0.006), and CTA-derived V-RESOLVE score showed similar capability to discriminate between high-risk group (18.6% vs. 13.8%, P=0.384) and non-high-risk group (3.8% vs. 4.9%, P=0.510) as compared with quantitative CTA-derived RESOLVE score.

CONCLUSIONS

Visually estimated CTA-derived V-RESOLVE score is an accurate and easy-to-use prediction tool for the stratification of SB occlusion in coronary bifurcation intervention.

Prognostic implication of CT-FFR based functional SYNTAX score in patients with de novo three-vessel disease

AIMS

This study was aimed at investigating whether a machine learning (ML)-based coronary computed tomographic angiography (CCTA) derived fractional flow reserve (CT-FFR) SYNTAX score (SS), 'Functional SYNTAX score' (FSSCTA), would predict clinical outcome in patients with three-vessel coronary artery disease (CAD).

METHODS AND RESULTS

The SS based on CCTA (SSCTA) and ICA (SSICA) were retrospectively collected in 227 consecutive patients with three-vessel CAD. FSSCTA was calculated by combining the anatomical data with functional data derived from a ML-based CT-FFR assessment. The ability of each score system to predict major adverse cardiac events (MACE) was compared. The difference between revascularization strategies directed by the anatomical SS and FSSCTA was also assessed. Two hundred and twenty-seven patients were divided into two groups according to the SSCTA cut-off value of 22. After determining FSSCTA for each patient, 22.9% of patients (52/227) were reclassified to a low-risk group (FSSCTA ≤ 22). In the low- vs. intermediate-to-high (>22) FSSCTA group, MACE occurred in 3.2% (4/125) vs. 34.3% (35/102), respectively (P < 0.001). The independent predictors of MACE were FSSCTA (OR = 1.21, P = 0.001) and diabetes (OR = 2.35, P = 0.048). FSSCTA demonstrated a better predictive accuracy for MACE compared with SSCTA (AUC: 0.81 vs. 0.75, P = 0.01) and SSICA (0.81 vs. 0.75, P < 0.001). After FSSCTA was revealed, 52 patients initially referred for CABG based on SSCTA would have been changed to PCI.

CONCLUSION

Recalculating SS by incorporating lesion-specific ischaemia as determined by ML-based CT-FFR is a better predictor of MACE in patients with three-vessel CAD. Additionally, the use of FSSCTA may alter selected revascularization strategies in these patients.

More holes, more contrast? Comparing an 18-gauge non-fenestrated catheter with a 22-gauge fenestrated catheter for cardiac CT

Objective

To compare the performance of an 18-gauge nonfenestrated catheter (18-NFC) with a 22-gauge fenestrated catheter (22-FC) for cardiac CT angiography (CCTA) in patients with suspected coronary heart disease.

Subjects and methods

74 consecutive patients imaged on a 2^nd generation dual-source CT with arterial phase CCTA were included in this retrospective investigation to either an 18-NFC or 22-FC. In comparison to the 18-NFC, the 22-FC has three additional perforations for contrast agent dispersal proximal to the tip. We examined the two groups for differences in their average attenuation in the right and left ventricles (RV, LV) and in the atrium (RA, LA) as well as in the proximal right coronary artery (RCA) and the left main coronary artery (LM). The averages were calculated for both the 18-NFC and 22-FC.

Results

Catheters were successfully placed on the first attempt 97% (36/37) for 18-NFC and 95% (35/37) for the 22-FC. The following enhancement levels were measured: 22-FC (in Hounsfield-Units (HU)): RV = 203±29, LV = 523±36, RA = 198±29, LA = 519±38, RCA = 547±26, LM = 562±25; 18-NFC: RV = 146±26, LV = 464±32, RA = 141±24, LA = 438±35, RCA = 501±23, LM = 523±23; RV (p = 0,03), LV (p = 0.12), RA (p = 0.02), LA (p = 0.04), RCA (p = 0.3), LM (p = 0.33).

Conclusion

No significant differences in attenuation levels as well as in image quality of the coronary arteries were found between NFC and FC. Nevertheless, the 22-gauge FC examinations showed significantly higher attenuation in the left and right atrium as well as the right ventricle. Patients with poor venous access may benefit from a smaller gauge catheter that can deliver sufficiently high flow rates for CCTA.

Prognostic Value of Coronary Computed Tomography Angiography-derived Morphologic and Quantitative Plaque Markers Using Semiautomated Plaque Software

PURPOSE

In this study, we analyzed the prognostic value of coronary computed tomography angiography-derived morphologic and quantitative plaque markers and plaque scores for major adverse cardiovascular events (MACEs).

MATERIALS AND METHODS

We analyzed the data of patients with suspected coronary artery disease (CAD). Various plaque markers were obtained using a semiautomated software prototype or derived from the results of the software analysis. Several risk scores were calculated, and follow-up data concerning MACE were collected from all patients.

RESULTS

A total of 131 patients (65±12 y, 73% male) were included in our study. MACE occurred in 11 patients within the follow-up period of 34±25 months.CAD-Reporting and Data System score (odds ratio [OR]=11.62), SYNTAX score (SS) (OR=1.11), Leiden-risk score (OR=1.37), segment involvement score (OR=1.76), total plaque volume (OR=1.20), and percentage aggregated plaque volume (OR=1.32) were significant predictors for MACE (all P≤0.05). Moreover, the difference of the corrected coronary opacification (ΔCCO) correlated significantly with the occurrence of MACE (P<0.0001). The CAD-Reporting and Data System score, SS, and Leiden-risk score showed substantial sensitivity for predicting MACE (90.9%). The SS and Leiden-risk score displayed high specificities of 80.8% and 77.5%, respectively. These plaque markers and risk scores all provided high negative predictive value (>90%).

CONCLUSION

The coronary computed tomography angiography-derived plaque markers of segment involvement score, total plaque volume, percentage aggregated plaque volume, and ΔCCO, and the risk scores exhibited predictive value for the occurrence of MACE and can likely aid in identifying patients at risk for future cardiac events.

Subtracted Computed Tomography Angiography in the Evaluation of Coronary Arteries With Severe Calcification or Stents Using a 320-Row Computed Tomography Scanner

PURPOSE

Coronary computed tomography angiography (CCTA) has its limitations in evaluating arteries with stents or heavy calcification. This study compares the diagnostic performance of subtracted coronary computed tomography angiography (SCCTA) and nonsubtracted coronary computed tomography angiography (NSCCTA) in evaluating coronary artery disease (CAD) and in-stent restenosis (ISR).

MATERIALS AND METHODS

Twelve patients with stents and 20 patients with heavy coronary calcifications (total Agatston's score >400) underwent both SCCTA and invasive coronary angiography (ICA) with an interval of <3 months. Four subjects in the stented group also had heavy calcifications. Overall, 30 stented segments and 202 calcified segments were assessed to compare the diagnostic performance of SCCTA and NSCCTA in detecting ISR and CAD.

RESULTS

For the 30 stented segments, SCCTA/NSCCTA had a sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) (shown in %) of 66.7/100, 100/55.6, 96.7/60, 100/20, and 96.4/100 in diagnosing ISR, respectively. For the 202 calcified segments, SCCTA/NSCCTA had a sensitivity, specificity, accuracy, PPV, and NPV of 68.8/84.4, 97.6/76.5, 93.1/77.7, 84.6/40.3, and 94.3/96.3 in diagnosing CAD, respectively. For both stented and calcified segments, SCCTA was significantly superior to NSCCTA in specificity and accuracy. For the calcified segments, SCCTA was significantly superior to NSCCTA in PPV. There was no significant difference in the diagnostic performance of SCCTA between the stented and calcified segments.

CONCLUSIONS

The diagnostic accuracy and specificity of SCCTA are significantly superior to those of NSCCTA in evaluating CAD and ISR. SCCTA shows no statistical difference in its diagnostic performance between the stented and calcified segments.