The rationale for the primacy of coronary CT angiography in the National Institute for Health and Care Excellence (NICE) guideline (CG95) for the investigation of chest pain of recent onset

Innovations in cardiac computed tomography: Imaging in coronary artery disease

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool in the non-invasive evaluation of coronary artery disease (CAD). Recent advancements in imaging techniques, quantitative plaque assessment methods, assessment of coronary physiology, and perivascular coronary inflammation have propelled CCTA to the forefront of CAD management, enabling precise risk stratification, disease monitoring, and evaluation of treatment response. However, challenges persist, including the need for cardiovascular outcomes data for therapy modifications based on CCTA findings and the lack of standardized quantitative plaque assessment techniques to establish universal guidelines for treatment strategies. This review explores the current utilization of CCTA in clinical practice, highlighting its clinical impact and discussing challenges and opportunities for future development. By addressing these nuances, CCTA holds promise for revolutionizing coronary imaging and improving CAD management in the years to come. Ultimately, the goal is to provide precise risk stratification, optimize medical therapy, and improve cardiovascular outcomes while ensuring cost-effectiveness for healthcare systems.

Association between coronary artery disease and clinical outcome in cancer patients: A propensity score matching analysis

Objective

The aim of this study was to evaluate the prognostic value of coronary artery disease (CAD) detected by coronary computed tomography angiography (CTA) to predict the risk of all-cause mortality in cancer patients in a propensity score matching (PSM) analysis.

Methods

A total of 331 patients who previously had cancer and underwent coronary CTA from January 2015 to December 2019 were included. Multivariate Cox proportional hazards regression analysis and propensity-score matching analysis were performed. The primary endpoint was all-cause of mortality.

Results

In total, 125 with CAD and 206 with no CAD during a median follow-up of 3.3 years were included in this study. After PSM, age (HR, 1.040; 95%CI, 1.001-1.081; p = 0.014) and CAD (HR, 2.164; 95%CI, 1.057-4.430; p = 0.035) remained significant factors for all-cause mortality.

Conclusion

CAD evaluated by coronary CTA was found to be at higher risk for all-cause mortality in cancer patients. Due to the retrospective design and lack of information on some medical history and treatments, especially immune checkpoint inhibitors, a large-scale prospective study is needed to further determine the prognostic value of coronary CTA in cancer patients.

Imaging biomarkers in cardiac CT: moving beyond simple coronary anatomical assessment

Cardiac computed tomography angiography (CCTA) is considered the standard non-invasive tool to rule-out obstructive coronary artery disease (CAD). Moreover, several imaging biomarkers have been developed on cardiac-CT imaging to assess global CAD severity and atherosclerotic burden, including coronary calcium scoring, the segment involvement score, segment stenosis score and the Leaman-score. Myocardial perfusion imaging enables the diagnosis of myocardial ischemia and microvascular damage, and the CT-based fractional flow reserve quantification allows to evaluate non-invasively hemodynamic impact of the coronary stenosis. The texture and density of the epicardial and perivascular adipose tissue, the hypodense plaque burden, the radiomic phenotyping of coronary plaques or the fat radiomic profile are novel CT imaging features emerging as biomarkers of inflammation and plaque instability, which may implement the risk stratification strategies. The ability to perform myocardial tissue characterization by extracellular volume fraction and radiomic features appears promising in predicting arrhythmogenic risk and cardiovascular events. New imaging biomarkers are expanding the potential of cardiac CT for phenotyping the individual profile of CAD involvement and opening new frontiers for the practice of more personalized medicine.

Performance of machine learning-based coronary computed tomography angiography for selecting revascularization candidates

BACKGROUND

Limited studies have investigated the accuracy of therapeutic decision-making using machine learning-based coronary computed tomography angiography (ML-CCTA) compared with CCTA.

PURPOSE

To investigate the performance of ML-CCTA for therapeutic decision compared with CCTA.

MATERIAL AND METHODS

The study population consisted of 322 consecutive patients with stable coronary artery disease. The SYNTAX score was calculated with an online calculator based on ML-CCTA results. Therapeutic decision-making was determined by ML-CCTA results and the ML-CCTA-based SYNTAX score. The therapeutic strategy and the appropriate revascularization procedure were selected using ML-CCTA, CCTA, and invasive coronary angiography (ICA) independently.

RESULTS

The sensitivity, specificity, positive predictive value, negative predictive value, accuracy of ML-CCTA and CCTA for selecting revascularization candidates were 87.01%, 96.43%, 95.71%, 89.01%, 91.93%, and 85.71%, 87.50%, 86.27%, 86.98%, 86.65%, respectively, using ICA as the standard reference. The area under the receiver operating characteristic curve (AUC) of ML-CCTA for selecting revascularization candidates was significantly higher than CCTA (0.917 vs. 0.866, P = 0.016). Subgroup analysis showed the AUC of ML-CCTA for selecting percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) candidates was significantly higher than CCTA (0.883 vs. 0.777, P < 0.001, 0.912 vs. 0.826, P = 0.003, respectively).

CONCLUSION

ML-CCTA could distinguish between patients who need revascularization and those who do not. In addition, ML-CCTA showed a slightly superior to CCTA in making an appropriate decision for patients and selecting a suitable revascularization strategy.

Saving Contrast Media in Coronary CT Angiography with Photon-Counting Detector CT

RATIONALE AND OBJECTIVES

To determine the optimal virtual monoenergetic image (VMI) energy level and the potential of contrast-media (CM) reduction for coronary computed tomography angiography (CCTA) with photon-counting detector CT (PCD-CT).

MATERIALS AND METHODS

In this institutional review board-approved study, patients who underwent CCTA with dual-source PCD-CT with an identical scan protocol and radiation dose were included. In group 1, CCTA was performed with our standard CM protocol (volume: 72-85.2 mL, 370 mg iodine/mL). VMIs were reconstructed from 40 to 60 keV at 5 keV increments. Objective image quality (IQ) (vascular attenuation, image noise, and contrast-to-noise ratio [CNR]) was measured. Two blinded, independent readers rated subjective IQ (overall IQ, subjective image contrast, and subjective noise using a five-point discrete visual scale). Results of group 1 served to determine the best VMI level for CCTA. In group 2, CM volume was reduced by 20%, and in group 3 by another 20%.

RESULTS

A total of 100 patients were enrolled (45 females, mean age 54 ± 13 years). Inter-reader agreement was good-to-excellent for all comparisons (κ > 0.6). In group 1, the best VMI level regarding objective and subjective IQ was 45 keV, which was selected as the reference for groups 2 and 3. For group 2, mean vascular attenuation was 890 Hounsfield units (HU) and mean CNR was 26, with no differences compared to group 1, 45 keV for both objective and subjective IQ. For group 3, mean vascular attenuation was 676 HU and mean CNR was 21, and all patients were rated as diagnostic except one (severe motion artifacts).

CONCLUSION

Increased IQ of PCD-CT can be used for considerable CM volume reduction while still maintaining a diagnostic IQ of CCTA.

Comparison of prognostic value between CAD-RADS 1.0 and CAD-RADS 2.0 evaluated by convolutional neural networks based CCTA

Objectives

The aim of the present study was to investigate the prognostic value of the novel coronary artery disease reporting and data system (CAD-RADS) 2.0 compared with CAD-RADS 1.0 in patients with suspectedcoronary artery disease (CAD) evaluated by convolutional neural networks (CNN) based coronary computed tomography angiography (CCTA).

Methods

A total of 1796 consecutive inpatients with suspected CAD were evaluated by CCTA for CAD-RADS 1.0 and CAD-RADS 2.0 classifications. Kaplan-Meier and multivariate Cox models were used to estimate major adverse cardiovascular events (MACE) inclusive of all-cause mortality or myocardial infarction (MI). The C-statistic was used to assess the discriminatory ability of the two classifications.

Results

In total, 94 (5.2%) MACE occurred over the median follow-up of 45.25 months (interquartile range 43.53-46.63 months). The annualized MACE rate was 0.014 (95% CI: 0.011-0.017). Kaplan-Meier survival curves indicated that the CAD-RADS classification, segment involvement score (SIS) grade, and Computed Tomography Fractional Flow Reserve (CT-FFR) classification were all significantly associated with the increase in the cumulative MACE (all P < 0.001). CAD-RADS classification, SIS grade, and CT-FFR classification were significantly associated with endpoint in univariate and multivariate Cox analysis. CAD-RADS 2.0 showed a further incremental increase in the prognostic value in predicting MACE (c-statistic 0.702, 95% CI: 0.641-0.763, P = 0.047), compared with CAD-RADS 1.0.

Conclusions

The novel CAD-RADS 2.0 evaluated by CNN-based CCTA showed higher prognostic value of MACE than CAD-RADS 1.0 in patients with suspected CAD.

AI Evaluation of Stenosis on Coronary CTA, Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve: A CREDENCE Trial Substudy

BACKGROUND

Clinical reads of coronary computed tomography angiography (CTA), especially by less experienced readers, may result in overestimation of coronary artery disease stenosis severity compared with expert interpretation. Artificial intelligence (AI)-based solutions applied to coronary CTA may overcome these limitations.

OBJECTIVES

This study compared the performance for detection and grading of coronary stenoses using artificial intelligence-enabled quantitative coronary computed tomography (AI-QCT) angiography analyses to core lab-interpreted coronary CTA, core lab quantitative coronary angiography (QCA), and invasive fractional flow reserve (FFR).

METHODS

Coronary CTA, FFR, and QCA data from 303 stable patients (64 ± 10 years of age, 71% male) from the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia) trial were retrospectively analyzed using an Food and Drug Administration-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination.

RESULTS

Disease prevalence was high, with 32.0%, 35.0%, 21.0%, and 13.0% demonstrating ≥50% stenosis in 0, 1, 2, and 3 coronary vessel territories, respectively. Average AI-QCT analysis time was 10.3 ± 2.7 minutes. AI-QCT evaluation demonstrated per-patient sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 94%, 68%, 81%, 90%, and 84%, respectively, for ≥50% stenosis, and of 94%, 82%, 69%, 97%, and 86%, respectively, for detection of ≥70% stenosis. There was high correlation between stenosis detected on AI-QCT evaluation vs QCA on a per-vessel and per-patient basis (intraclass correlation coefficient = 0.73 and 0.73, respectively; P < 0.001 for both). False positive AI-QCT findings were noted in in 62 of 848 (7.3%) vessels (stenosis of ≥70% by AI-QCT and QCA of <70%); however, 41 (66.1%) of these had an FFR of <0.8.

CONCLUSIONS

A novel AI-based evaluation of coronary CTA enables rapid and accurate identification and exclusion of high-grade stenosis and with close agreement to blinded, core lab-interpreted quantitative coronary angiography. (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia [CREDENCE]; NCT02173275).

National Trends in Coronary Artery Disease Imaging: Associations With Health Care Outcomes and Costs

BACKGROUND

In 2016, the National Institute for Health and Care Excellence Clinical Guideline Number 95 ("Chest pain of recent onset") (CG95) recommended coronary computed tomography angiography (CCTA) as the first-line test for possible angina.

OBJECTIVES

The purpose of this study was to determine the impact of temporal trends in imaging use on outcomes for coronary artery disease (CAD) following the CG95 recommendations.

METHODS

Investigations from 2012 to 2018 were extracted from a national database and linked-hospital admission and mortality registries. Growth rates were adjusted for population size, with image modality use, cardiovascular hospital admissions, and mortality compared using Kendall's rank correlation. The impact of CG95 was assessed using an interrupted time-series analysis.

RESULTS

A total of 1,909,314 investigations for CAD were performed, with an annualized per capita growth of 4.8%. Costs were £0.35 million/100,000 population/year with an increase of 2.8%/year mirroring inflation (2.5%/year). CG95 was associated with a rise in CCTA (exp[β]: 1.10; 95% CI: 1.03-1.18), no change in myocardial perfusion imaging, and a potential modest fall (exp[β]: 0.997; 95% CI: 0.993-1.00]) in invasive coronary angiography. There was an apparent trend between computed tomography angiography growth and invasive catheter angiography reduction across regions (Kendall Tau: -0.19; P = 0.08). CCTA growth was associated with a reduction in cardiovascular mortality (Kendall Tau: -0.21; P = 0.045), and ischemic heart disease deaths (Kendall Tau: -0.22; P = 0.042), with an apparent trend with reduced all-cause mortality (Kendall Tau: -0.19; P = 0.07).

CONCLUSIONS

Imaging investigations for CAD are increasing. Greater regional increases in CCTA were associated with fewer hospitalizations for myocardial infarction and a more rapid decline in CAD mortality.

CAD-RADS™ 2.0 - 2022 Coronary Artery Disease-Reporting and Data System: An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR), and the North America Society of Cardiovascular Imaging (NASCI)

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care.

CAD-RADS™ 2.0 - 2022 Coronary Artery Disease - Reporting and Data System.: An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR) and the North America Society of Cardiovascular Imaging (NASCI)

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in Cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care.

CAD-RADS™ 2.0 - 2022 Coronary Artery Disease-Reporting and Data System: An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR), and the North America Society of Cardiovascular Imaging (NASCI)

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in Cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care.

CAD-RADS™ 2.0 - 2022 Coronary Artery Disease - Reporting and Data System An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR) and the North America Society of Cardiovascular Imaging (NASCI)

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in Cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care. Keywords: Coronary Artery Disease, Coronary CTA, CAD-RADS, Reporting and Data System, Stenosis Severity, Report Standardization Terminology, Plaque Burden, Ischemia Supplemental material is available for this article. This article is published synchronously in Radiology: Cardiothoracic Imaging, Journal of Cardiovascular Computed Tomography, JACC: Cardiovascular Imaging, Journal of the American College of Radiology, and International Journal for Cardiovascular Imaging. © 2022 Society of Cardiovascular Computed Tomography. Published by RSNA with permission.

Identification of pathology-confirmed vulnerable atherosclerotic lesions by coronary computed tomography angiography using radiomics analysis

OBJECTIVES

To explore whether radiomics-based machine learning (ML) models could outperform conventional diagnostic methods at identifying vulnerable lesions on coronary computed tomographic angiography (CCTA).

METHODS

In this retrospective study, 36 heart transplant recipients with coronary heart disease (CAD) and end-stage heart failure were included. Pathological cross-section samples of 350 plaques were collected and coregistered to patients' preoperative CCTA images. A total of 1184 radiomic features were extracted from CCTA images. Through feature selection and stratified fivefold cross-validation, we derived eight radiomics-based ML models for lesion vulnerability prediction. An independent set of 196 plaques from another 8 CAD patients who underwent heart transplants was collected to validate radiomics-based ML models' diagnostic accuracy against conventional CCTA feature-based diagnosis (presence of at least 2 high-risk plaque features). The performance of the prediction models was assessed by the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals (CI).

RESULTS

The training group used to develop radiomics-based ML models contained 200/350 (57.1%) vulnerable plaques and the external validation group was composed of 67.3% (132/196) vulnerable plaques. The radiomics-based ML model based on eight radiomic features showed excellent cross-validation diagnostic accuracy (AUC: 0.900 ± 0.033). In the validation group, diagnosis based on conventional CCTA features demonstrated moderate performance (AUC: 0.656 [95% CI: 0.593 -0.718]), while the radiomics-based ML model showed higher diagnostic ability (0.782 [95% CI: 0.710 -0.846]).

CONCLUSIONS

Radiomics-based ML models showed better diagnostic ability than the conventional CCTA features at assessing coronary plaque vulnerability.

KEY POINTS

• CCTA has great potential in the diagnosis of vulnerable coronary artery lesions. • Radiomics model built through CCTA could discriminate coronary vulnerable lesions in good diagnostic ability. • Radiomics model could improve the ability of vulnerability diagnosis against traditional CCTA method, sensitivity especially.

The Radiologist as a Gatekeeper in Chest Pain

Chest pain is a symptom that can be found in life-threatening conditions such as acute coronary syndrome (ACS). Those patients requiring invasive coronary angiography treatment or surgery should be identified. Often the clinical setting and laboratory tests are not sufficient to rule out a coronary or aortic syndrome. Cardiac radiological imaging has evolved in recent years both in magnetic resonance (MR) and in computed tomography (CT). CT, in particular, due to its temporal and spatial resolution, the quickness of the examination, and the availability of scanners, is suitable for the evaluation of these patients. In particular, the latest-generation CT scanners allow the exclusion of diagnoses such as coronary artery disease and aortic pathology, thereby reducing the patient's stay in hospital and safely selecting patients by distinguishing those who do not need further treatment from those who will need more- or less-invasive therapies. CT additionally reduces costs by improving long-term patient outcome. The limitations related to patient characteristics and those related to radiation exposure are weakening with the improvement of CT technology.

CT ​EvaLuation ​by ​ARtificial ​Intelligence ​For ​Atherosclerosis, Stenosis and Vascular ​MorphologY ​(CLARIFY): ​A ​Multi-center, international study

BACKGROUND

Atherosclerosis evaluation by coronary computed tomography angiography (CCTA) is promising for coronary artery disease (CAD) risk stratification, but time consuming and requires high expertise. Artificial Intelligence (AI) applied to CCTA for comprehensive CAD assessment may overcome these limitations. We hypothesized AI aided analysis allows for rapid, accurate evaluation of vessel morphology and stenosis.

METHODS

This was a multi-site study of 232 patients undergoing CCTA. Studies were analyzed by FDA-cleared software service that performs AI-driven coronary artery segmentation and labeling, lumen and vessel wall determination, plaque quantification and characterization with comparison to ground truth of consensus by three L3 readers. CCTAs were analyzed for: % maximal diameter stenosis, plaque volume and composition, presence of high-risk plaque and Coronary Artery Disease Reporting & Data System (CAD-RADS) category.

RESULTS

AI performance was excellent for accuracy, sensitivity, specificity, positive predictive value and negative predictive value as follows: >70% stenosis: 99.7%, 90.9%, 99.8%, 93.3%, 99.9%, respectively; >50% stenosis: 94.8%, 80.0%, 97.0, 80.0%, 97.0%, respectively. Bland-Altman plots depict agreement between expert reader and AI determined maximal diameter stenosis for per-vessel (mean difference -0.8%; 95% CI 13.8% to -15.3%) and per-patient (mean difference -2.3%; 95% CI 15.8% to -20.4%). L3 and AI agreed within one CAD-RADS category in 228/232 (98.3%) exams per-patient and 923/924 (99.9%) vessels on a per-vessel basis. There was a wide range of atherosclerosis in the coronary artery territories assessed by AI when stratified by CAD-RADS distribution.

CONCLUSIONS

AI-aided approach to CCTA interpretation determines coronary stenosis and CAD-RADS category in close agreement with consensus of L3 expert readers. There was a wide range of atherosclerosis identified through AI.

Advanced measurements of coronary calcium scores: how does it affect current clinical practice?

Coronary artery calcium (CAC) scoring has emerged as a marker of the burden of atheromatous disease and has been included in scoring systems. The practice of myocardial revascularization, considering percutaneous procedures or surgical strategies, is dramatically changing over years and the prognostic significance of CAC scoring is gradually being conceived. In this interdisciplinary scenario, vessel specific calcium scoring, mapping of coronary calcification and its integration with functional assessment of coronary artery disease might change the future decisions in the catheterization lab and operative theaters. This article summarizes CAC evaluation techniques and its implications in clinical practice.

Are Training Programs Ready for the Rapid Adoption of CCTA?: CBME in CCTA

OBJECTIVES

This study sought to assess training volumes and its relationship to learning and identify potential new thresholds for determining expertise.

BACKGROUND

Competency-based medical education (CBME) is being rapidly adopted and therefore training programs will need to adapt and identify new and novel methods of defining, measuring, and assessing clinical skills.

METHODS

Consecutive cardiac computed tomography (CT) studies were interpreted independently by trainees and expert readers, and their interpretations (Agatston score, coronary artery disease severity, and Coronary Artery Disease Reporting and Data System) were collected. Kappa agreements were measured between trainees and experts for every 50 consecutive cases. Agreements between trainees and experts were tracked and compared with the agreement between expert readers.

RESULTS

A total of 36 trainees interpreted 14,432 cardiac CT studies. Agreement between trainees and experts increased with CT case volumes, but trainees learned at different rates. Using a threshold for expertise, skill of measuring coronary calcification was achieved within 50 cases, but expertise for coronary CT angiography appeared to require a mean case volume of 750, comprising 400 abnormal cases.

CONCLUSIONS

Current volume-based training guidelines may be insufficient and higher case volumes may be required. We demonstrate that tracking cardiac CT learners is feasible and that CBME could be incorporated into CT training programs.

Coronary Computed Tomography Angiography for Assesment of Stable Coronary Artery Disease – a Cost-effectiveness Perspective

Patients with chest pain presenting to the emergency room are currently investigated using either invasive coronary angiography (ICA) or noninvasive coronary computed tomography angiography (CCTA). ICA remains an expensive diagnostic tool and exposes patients to a high risk of periprocedural complication. Besides the currently available expansive economic evidence, there is still an important lingering issue: to establish, from the healthcare provider’s point of view, which is the most cost-effective investigation tool for the detection of significant coronary artery disease. The aim of this article is to present the latest developments in the field of imaging tools for the detection of coronary atherosclerosis in patients with chest pain, from the perspective of a cost-effectiveness analysis.

Relationship of Stress Test Findings to Anatomic or Functional Extent of Coronary Artery Disease Assessed by Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve

Background

In the United States, functional stress testing is the primary imaging modality for patients with stable symptoms suspected to represent coronary artery disease (CAD). Coronary computed tomography angiography (CTA) is excellent at identifying anatomic coronary artery disease (CAD). The application of computational fluid dynamics to coronary CTA allows fractional flow reserve (FFR) to be calculated noninvasively (FFR_CT). The relationship of noninvasive stress testing to coronary CTA and FFR_CT in real-world clinical practice has not been studied.

Methods

We evaluated 206 consecutive patients at Loyola University Chicago with suspected CAD who underwent noninvasive stress testing followed by coronary CTA and FFR_CT when indicated. Patients were categorized by stress test results (positive, negative, indeterminate, and equivocal). Duke treadmill score (DTS), METS, exercise duration, and chest pain with exercise were analyzed. Lesions ≥ 50%stenosis were considered positive by coronary CTA. FFR_CT < 0.80 was considered diagnostic of ischemia.

Results

Two hundred and six patients had paired noninvasive stress test and coronary CTA/FFR_CT results. The median time from stress test to coronary CTA was 49 days. Average patient age was 60.3 years, and 42% were male. Of the 206 stress tests, 75% were exercise (70% echocardiographic, 26% nuclear, and 4% EKG). There were no associations of stress test results with CAD > 50% or FFR_CT < 0.80 (p = 0.927 and p = 0.910, respectively). Of those with a positive stress test, only 30% (3/10) had CAD > 50% and only 50% (5/10) had FFR_CT < 0.80. Chest pain with exercise did not correlate with CAD > 50% or FFR_CT < 0.80 (p = 0.66 and p = 0.12, respectively). There were no significant correlations between METS, DTS, or exercise duration and FFR_CT (r = 0.093, p = 0.274; r = 0.012, p = 0.883; and r = 0.034, p = 0.680; respectively).

Conclusion

Noninvasive stress testing, functional capacity, chest pain with exercise, and DTS are not associated with anatomic or functional CAD using a diagnostic strategy of coronary CTA and FFR_CT.

2020 SCCT Guideline for Training Cardiology and Radiology Trainees as Independent Practitioners (Level II) and Advanced Practitioners (Level III) in Cardiovascular Computed Tomography: A Statement from the Society of Cardiovascular Computed Tomography

Cardiovascular computed tomography (CCT) is a well-validated noninvasive imaging tool with an ever-expanding array of applications beyond the assessment of coronary artery disease. These include the evaluation of structural heart diseases, congenital heart diseases, peri-procedural electrophysiology applications, and the functional evaluation of ischemia. This breadth requires a robust and diverse training curriculum to ensure graduates of CCT training programs meet minimum competency standards for independent CCT interpretation. This statement from the Society of Cardiovascular Computed Tomography aims to supplement existing societal training guidelines by providing a curriculum and competency framework to inform the development of a comprehensive, integrated training experience for cardiology and radiology trainees in CCT. This article is being published synchronously in Radiology: Cardiothoracic Imaging, Journal of Cardiovascular Computed Tomography, and JACC: Cardiovascular Imaging. © 2020 Society of Cardiovascular Computed Tomography. Published by RSNA with permission.

2020 SCCT Guideline for Training Cardiology and Radiology Trainees as Independent Practitioners (Level II) and Advanced Practitioners (Level III) in Cardiovascular Computed Tomography: A Statement from the Society of Cardiovascular Computed Tomography

Cardiovascular computed tomography (CCT) is a well-validated non-invasive imaging tool with an ever-expanding array of applications beyond the assessment of coronary artery disease. These include the evaluation of structural heart diseases, congenital heart diseases, peri-procedural electrophysiology applications, and the functional evaluation of ischemia. This breadth requires a robust and diverse training curriculum to ensure graduates of CCT training programs meet minimum competency standards for independent CCT interpretation. This statement from the Society of Cardiovascular Computed Tomography aims to supplement existing societal training guidelines by providing a curriculum and competency framework to inform the development of a comprehensive, integrated training experience for cardiology and radiology trainees in CCT.

2020 SCCT Guideline for Training Cardiology and Radiology Trainees as Independent Practitioners (Level II) and Advanced Practitioners (Level III) in Cardiovascular Computed Tomography: A Statement from the Society of Cardiovascular Computed Tomography

Cardiovascular computed tomography (CCT) is a well-validated non-invasive imaging tool with an ever-expanding array of applications beyond the assessment of coronary artery disease. These include the evaluation of structural heart diseases, congenital heart diseases, peri-procedural electrophysiology applications, and the functional evaluation of ischemia. This breadth requires a robust and diverse training curriculum to ensure graduates of CCT training programs meet minimum competency standards for independent CCT interpretation. This statement from the Society of Cardiovascular Computed Tomography aims to supplement existing societal training guidelines by providing a curriculum and competency framework to inform the development of a comprehensive, integrated training experience for cardiology and radiology trainees in CCT.

The Incremental Role of Coronary Computed Tomography in Chronic Coronary Syndromes

In the context of chronic coronary syndromes (CCS), coronary computed tomography angiography (CCTA) has gained broad acceptance as a noninvasive anatomical imaging tool with ability of excluding coronary stenosis with strong negative predictive value. Atherosclerotic plaque lesions are independent predictors of cardiovascular outcomes in high risk patients with known coronary artery disease (CAD). Calcium detection is commonly expressed through the coronary artery calcium score (CACS), but further research is warranted to confirm the powerness of a CACS-only strategy in both diagnosis and prognosis assessment. Recent studies evidence how defined plaque composition characteristics effectively relate to the risk of plaque instabilization and the overall ischemic burden. Fractional flow reserve from CCTA (FFR-CT) has been demonstrated as a reliable method for noninvasive functional evaluation of coronary lesions severity, while the assessment of perfusion imaging under stress conditions is growing as a useful tool for assessment of myocardial ischemia. Moreover, specific applications in procedural planning of transcatheter valve substitution and follow-up of heart transplantation have gained recent importance. This review illustrates the incremental role of CCTA, which can potentially revolutionize the diagnosis and management pathway within the wide clinical spectrum of CCS.

Coronary artery calcium scoring in individuals at risk for coronary artery disease: current status and future perspectives

The aim of this review is to provide clinicians with an overview of the role of coronary artery calcium (CAC) scoring across the spectrum ranging from asymptomatic individuals to chronic chest pain patients. We will briefly introduce the technical background of CAC scoring, summarize the major guidelines per type of patient at risk and discuss latest research with respect to CAC. Finally, the reader should be able to determine when CAC scoring is indicated or may be of added value.

The effect of on-site CT-derived fractional flow reserve on the management of decision making for patients with stable chest pain (TARGET trial): objective, rationale, and design

Background

The diagnostic accuracy of CT-derived fractional flow reserve (CT-FFR) in clinical application has been well validated. This advanced technology focus on evaluating anatomical stenosis and functional ischemia simultaneously. However, the effect of CT-FFR on the management of decision making has not been fully evaluated in randomized controlled design.

Method/design

TARGET study is a pragmatic, multicenter, prospective, open-label, and randomized controlled trial evaluating the effect of a CCTA/CT-FFR strategy (group A) versus usual care (group B) on intermediate-to-high risk patients with suspected CAD who undergo clinically indicated diagnostic evaluation. A total sample size of 1216 subjects will be enrolled and followed up for 12 months. This study will be performed in 6 Chinese hospitals, and the primary endpoint is the planned ICA without significant obstructive CAD within 90 days. The secondary endpoints include MACE, quality of life, medical expenditure, and cumulative radiation exposure during 1-year follow-up.

Discussion

The study will provide information to patients, health care providers, and other stakeholders in China about which strategy could be more effective in the management of intermediate-to-high risk patients with suspect CAD.

Trial registration

ClinicalTrials.gov NCT03901326. Registered on 3 April 2019.

Comparison of NICE and ESC proposed strategies on new onset chest pain and the contemporary clinical utility of pretest probability risk score

AIMS

Patients with de novo chest pain are usually investigated non-invasively. The new UK-National Institute for Health and Care Excellence (NICE) guidelines recommend CT coronary angiography (CTCA) for all patients, while European Society of Cardiology (ESC) recommends functional tests. We sought to compare the clinical utility and perform a cost analysis of these recommendations in two UK centres with different primary investigative strategies.

METHODSRESULTS

We compared two groups of patients, group A (n=667) and group B (n=654), with new onset chest pain in two neighbouring National Health Service hospitals, each primarily following either ESC (group A) or NICE (group B) guidance. We assessed the clinical utility of each strategy, including progression to invasive coronary angiography (ICA) and revascularisation. We present a retrospective cost analysis in the context of UK tariff for stress echo (£176), CTCA (£220) and ICA (£1001). Finally, we sought to identify predictors of revascularisation in the whole population.Baseline characteristics in both groups were similar. The progression to ICA was comparable (9.9% vs 12.0%, p=0.377), with similar requirement for revascularisation (4.0% vs 5.0%.; p=0.532). The average cost of investigations per investigated patient was lower in group A (£279.66 vs £325.77), saving £46.11 per patient. The ESC recommended risk score (RS) was found to be the only predictor of revascularisation (OR 1.05, 95% CI 1.04 to 1.06; p<0.001).

CONCLUSION

Both NICE and ESC-proposed strategies led to similar rates of ICA and need for revascularisation in discrete, but similar groups of patients. The SE-first approach had a lower overall cost by £46.11 per patient, and the ESC RS was the only variable correlated to revascularisation.

Screening coronary artery disease with computed tomography angiogram should limit normal invasive coronary angiogram, regardless of pretest probability

BACKGOUND

Performing functional testing (FT) or a computed tomography angiogram (CCTA) before invasive coronary angiogram (ICA) is recommended for coronary artery disease (CAD). We aimed to evaluate, in a real life setting, the rate of strictly normal ICA following a positive noninvasive test result.

METHODS

We included all patients who underwent an ICA with a prior positive FT or CCTA. Patients were categorized in 5 subgroups, according to pretest probability (PTP) of having a CAD. Main results of ICA were defined as normal ICA, nonobstructive CAD (non-oCAD), and obstructive CAD (oCAD).

RESULTS

For 4,952 patients who underwent ICA following either a positive FT (3276, 66.2%) or CCTA (1676, 33.8%) result, the PTP was (1) low (<15%; n = 968, 19.5%), (2) lower intermediate (15%-35%; n = 1336, 27.0%), (3) higher intermediate (35%-50%; n = 806, 16.3%), (4) high (50%-65%; n = 806, 17.7%), and (5) very high (> 65%; n = 965, 19.5%). ICA showed no CAD (819 patients, 16.5%), non-oCAD (1,193 patients, 24.1%), or oCAD (2940 patients, 59.4%). Without considering the PTP values, CCTA compared to FT showed less frequently normal ICA (7% vs 16.5%), and more frequently CAD (non-oCAD 27.9% vs 22.2%; oCAD 65.1% vs 56.4%) (all P < .0001). When we considered the different PTP values, CCTA always showed lower rates of normal ICA than the FT. In low- and lower intermediate-risk patients, CCTA detected more frequently oCAD compared to FT (P < .001).

CONCLUSIONS

CCTA is a better alternative than FT to limit unnecessary ICA regardless of PTP value, without missing abnormal ICA.

The ISCHEMIA Trial: Implication for Cardiac Imaging in 2020 and Beyond

Establishing a diagnosis of coronary artery disease (CAD) is more difficult than it would seem. Diagnosis of CAD can be approached in two ways: detection of ischemia (often with stress myocardial perfusion at SPECT, PET, and cardiac MRI) and visualization of the coronary artery anatomy to demonstrate stenosis (noninvasively with cardiac CT). In addition to providing further supportive evidence for the use of coronary CT angiography as the first-line test for the evaluation of CAD, the ISCHEMIA trial also resulted in some interesting findings with regard to imaging; these findings resulted in the open-ended question of "What does this mean for imagers?" © RSNA, 2020.

Latest Advances in Cardiac CT

Recent rapid technological advancements in cardiac CT have improved image quality and reduced radiation exposure to patients. Furthermore, key insights from large cohort trials have helped delineate cardiovascular disease risk as a function of overall coronary plaque burden and the morphological appearance of individual plaques. The advent of CT-derived fractional flow reserve promises to establish an anatomical and functional test within one modality. Recent data examining the short-term impact of CT-derived fractional flow reserve on downstream care and clinical outcomes have been published. In addition, machine learning is a concept that is being increasingly applied to diagnostic medicine. Over the coming decade, machine learning will begin to be integrated into cardiac CT, and will potentially make a tangible difference to how this modality evolves. The authors have performed an extensive literature review and comprehensive analysis of the recent advances in cardiac CT. They review how recent advances currently impact on clinical care and potential future directions for this imaging modality.

Future Directions in Coronary CT Angiography: CT-Fractional Flow Reserve, Plaque Vulnerability, and Quantitative Plaque Assessment

Coronary computed tomography angiography (CCTA) is a well-validated and noninvasive imaging modality for the assessment of coronary artery disease (CAD) in patients with stable ischemic heart disease and acute coronary syndromes (ACSs). CCTA not only delineates the anatomy of the heart and coronary arteries in detail, but also allows for intra- and extraluminal imaging of coronary arteries. Emerging technologies have promoted new CCTA applications, resulting in a comprehensive assessment of coronary plaques and their clinical significance. The application of computational fluid dynamics to CCTA resulted in a robust tool for noninvasive assessment of coronary blood flow hemodynamics and determination of hemodynamically significant stenosis. Detailed evaluation of plaque morphology and identification of high-risk plaque features by CCTA have been confirmed as predictors of future outcomes, identifying patients at risk for ACSs. With quantitative coronary plaque assessment, the progression of the CAD or the response to therapy could be monitored by CCTA. The aim of this article is to review the future directions of emerging applications in CCTA, such as computed tomography (CT)-fractional flow reserve, imaging of vulnerable plaque features, and quantitative plaque imaging. We will also briefly discuss novel methods appearing in the coronary imaging scenario, such as machine learning, radiomics, and spectral CT.

Automated Quantitative Stress Perfusion in a Clinical Routine

Cardiovascular magnetic resonance (CMR) perfusion imaging is a robust noninvasive technique to evaluate ischemia in patients with coronary artery disease (CAD). Although qualitative and semiquantitative methods have shown that CMR has high accuracy in diagnosing flow-obstructing lesions in CAD, quantitative ischemic burden is an important variable used in clinical practice for treatment decisions. Quantitative CMR perfusion techniques have evolved significantly, with accuracy comparable with both PET and microsphere evaluation. Routine clinical use of these quantitative techniques has been facilitated by the introduction of automated methods that accelerate the work flow and rapidly generate pixel-based myocardial blood flow maps.