Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group.

The detection and characterization of coronary artery stenosis and atherosclerosis using imaging tools are key for clinical decision-making in patients with known or suspected coronary artery disease. In this regard, imaging-based quantification can be improved by choosing the most appropriate imaging modality for diagnosis, treatment and procedural planning. In this Consensus Statement, we provide clinical consensus recommendations on the optimal use of different imaging techniques in various patient populations and describe the advances in imaging technology. Clinical consensus recommendations on the appropriateness of each imaging technique for direct coronary artery visualization were derived through a three-step, real-time Delphi process that took place before, during and after the Second International Quantitative Cardiovascular Imaging Meeting in September 2022. According to the Delphi survey answers, CT is the method of choice to rule out obstructive stenosis in patients with an intermediate pre-test probability of coronary artery disease and enables quantitative assessment of coronary plaque with respect to dimensions, composition, location and related risk of future cardiovascular events, whereas MRI facilitates the visualization of coronary plaque and can be used in experienced centres as a radiation-free, second-line option for non-invasive coronary angiography. PET has the greatest potential for quantifying inflammation in coronary plaque but SPECT currently has a limited role in clinical coronary artery stenosis and atherosclerosis imaging. Invasive coronary angiography is the reference standard for stenosis assessment but cannot characterize coronary plaques. Finally, intravascular ultrasonography and optical coherence tomography are the most important invasive imaging modalities for the identification of plaques at high risk of rupture. The recommendations made in this Consensus Statement will help clinicians to choose the most appropriate imaging modality on the basis of the specific clinical scenario, individual patient characteristics and the availability of each imaging modality.

Dynamic Myocardial Perfusion CT for the Detection of Hemodynamically Significant Coronary Artery Disease.

OBJECTIVES: In this international, multicenter study, using third-generation dual-source computed tomography (CT), we investigated the diagnostic performance of dynamic stress CT myocardial perfusion imaging (CT-MPI) in addition to coronary CT angiography (CTA) compared to invasive coronary angiography (ICA) and invasive fractional flow reserve (FFR). BACKGROUND: CT-MPI combined with coronary CTA integrates coronary artery anatomy with inducible myocardial ischemia, showing promising results for the diagnosis of hemodynamically significant coronary artery disease in single-center studies. METHODS: At 9 centers in Europe, Japan, and the United States, 132 patients scheduled for ICA were enrolled; 114 patients successfully completed coronary CTA, adenosine-stress dynamic CT-MPI, and ICA. Invasive FFR was performed in vessels with 25% to 90% stenosis. Data were analyzed by independent core laboratories. For the primary analysis, for each coronary artery the presence of hemodynamically significant obstruction was interpreted by coronary CTA with CT-MPI compared to coronary CTA alone, using an FFR of ≤0.80 and angiographic severity as reference. Territorial absolute myocardial blood flow (MBF) and relative MBF were compared using C-statistics. RESULTS: ICA and FFR identified hemodynamically significant stenoses in 74 of 289 coronary vessels (26%). Coronary CTA with ≥50% stenosis demonstrated a per-vessel sensitivity, specificity, and accuracy for the detection of hemodynamically significant stenosis of 96% (95% CI: 91%-100%), 72% (95% CI: 66%-78%), and 78% (95% CI: 73%-83%), respectively. Coronary CTA with CT-MPI showed a lower sensitivity (84%; 95% CI: 75%-92%) but higher specificity (89%; 95% CI: 85%-93%) and accuracy (88%; 95% CI: 84%-92%). The areas under the receiver-operating characteristic curve of absolute MBF and relative MBF were 0.79 (95% CI: 0.71-0.86) and 0.82 (95% CI: 0.74-0.88), respectively. The median dose-length product of CT-MPI and coronary CTA were 313 mGy·cm and 138 mGy·cm, respectively. CONCLUSIONS: Dynamic CT-MPI offers incremental diagnostic value over coronary CTA alone for the identification of hemodynamically significant coronary artery disease. Generalized results from this multicenter study encourage broader consideration of dynamic CT-MPI in clinical practice. (Dynamic Stress Perfusion CT for Detection of Inducible Myocardial Ischemia [SPECIFIC]; NCT02810795).

Influence of coronary stenosis location on diagnostic performance of machine learning-based fractional flow reserve from CT angiography.

BACKGROUND: Compared with invasive fractional flow reserve (FFR), coronary CT angiography (cCTA) is limited in detecting hemodynamically relevant lesions. cCTA-based FFR (CT-FFR) is an approach to overcome this insufficiency by use of computational fluid dynamics. Applying recent innovations in computer science, a machine learning (ML) method for CT-FFR derivation was introduced and showed improved diagnostic performance compared to cCTA alone. We sought to investigate the influence of stenosis location in the coronary artery system on the performance of ML-CT-FFR in a large, multicenter cohort. METHODS: Three hundred and thirty patients (75.2% male, median age 63 years) with 502 coronary artery stenoses were included in this substudy of the MACHINE (Machine Learning Based CT Angiography Derived FFR: A Multi-Center Registry) registry. Correlation of ML-CT-FFR with the invasive reference standard FFR was assessed and pooled diagnostic performance of ML-CT-FFR and cCTA was determined separately for the following stenosis locations: RCA, LAD, LCX, proximal, middle, and distal vessel segments. RESULTS: ML-CT-FFR correlated well with invasive FFR across the different stenosis locations. Per-lesion analysis revealed improved diagnostic accuracy of ML-CT-FFR compared with conventional cCTA for stenoses in the RCA (71.8% [95% confidence interval, 63.0%-79.5%] vs. 54.8% [45.7%-63.8%]), LAD (79.3 [73.9-84.0] vs. 59.6 [53.5-65.6]), LCX (84.1 [76.0-90.3] vs. 63.7 [54.1-72.6]), proximal (81.5 [74.6-87.1] vs. 63.8 [55.9-71.2]), middle (81.2 [75.7-85.9] vs. 59.4 [53.0-65.6]) and distal stenosis location (67.4 [57.0-76.6] vs. 51.6 [41.1-62.0]). CONCLUSION: In a multicenter cohort with high disease prevalence, ML-CT-FFR offered improved diagnostic performance over cCTA for detecting hemodynamically relevant stenoses regardless of their location.

Lipid-rich Plaques Detected by Near-infrared Spectroscopy Are More Frequently Exposed to High Shear Stress.

High wall shear stress (WSS) and near-infrared spectroscopy (NIRS) detected lipid-rich plaque (LRP) are both known to be associated with plaque destabilization and future adverse cardiovascular events. However, knowledge of spatial co-localization of LRP and high WSS is lacking. This study investigated the co-localization of LRP based on NIRS and high WSS. Fifty-three patients presenting acute coronary syndrome underwent NIRS-intravascular-ultrasound (NIRS-IVUS) imaging of a non-culprit coronary artery. WSS was obtained using WSS profiling in 3D-reconstructions of the coronary arteries based on fusion of IVUS-segmented lumen and CT-derived 3D-centerline. Thirty-eight vessels were available for final analysis and divided into 0.5 mm/45° sectors. LRP sectors, as identified by NIRS, were more often colocalized with high WSS than sectors without LRP. Moreover, there was a dose-dependent relationship between lipid content and high WSS exposure. This study is a first step in understanding the evolution of LRPs to vulnerable plaques. Graphical Abstract.

Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR: Results From MACHINE Registry.

OBJECTIVES: This study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning-based coronary computed tomography (CT) angiography (cCTA)-derived fractional flow reserve (CT-FFR). BACKGROUND: CT-FFR is used reliably to detect lesion-specific ischemia. Novel CT-FFR algorithms using machine-learning artificial intelligence techniques perform fast and require less complex computational fluid dynamics. Yet, influence of CAC score on diagnostic performance of the machine-learning approach has not been investigated. METHODS: A total of 482 vessels from 314 patients (age 62.3 ± 9.3 years, 77% male) who underwent cCTA followed by invasive FFR were investigated from the MACHINE (Machine Learning based CT Angiography derived FFR: a Multi-center Registry) registry data. CAC scores were quantified using the Agatston convention. The diagnostic performance of CT-FFR to detect lesion-specific ischemia was assessed across all Agatston score categories (CAC 0, >0 to <100, 100 to <400, and ≥400) on a per-vessel level with invasive FFR as the reference standard. RESULTS: The diagnostic accuracy of CT-FFR versus invasive FFR was superior to cCTA alone on a per-vessel level (78% vs. 60%) and per patient level (83% vs. 73%) across all Agatston score categories. No statistically significant differences in the diagnostic accuracy, sensitivity, or specificity of CT-FFR were observed across the categories. CT-FFR showed good discriminatory power in vessels with high Agatston scores (CAC ≥400) and high performance in low-to-intermediate Agatston scores (CAC >0 to <400) with a statistically significant difference in the area under the receiver-operating characteristic curve (AUC) (AUC: 0.71 [95% confidence interval (CI): 0.57 to 0.85] vs. 0.85 [95% CI: 0.82 to 0.89], p = 0.04). CT-FFR showed superior diagnostic value over cCTA in vessels with high Agatston scores (CAC ≥ 400: AUC 0.71 vs. 0.55, p = 0.04) and low-to-intermediate Agatston scores (CAC >0 to <400: AUC 0.86 vs. 0.63, p < 0.001). CONCLUSIONS: Machine-learning-based CT-FFR showed superior diagnostic performance over cCTA alone in CAC with a significant difference in the performance of CT-FFR as calcium burden/Agatston calcium score increased. (Machine Learning Based CT Angiography Derived FFR: a Multicenter, Registry [MACHINE] NCT02805621).

Multidirectional wall shear stress promotes advanced coronary plaque development: comparing five shear stress metrics.

AIMS: Atherosclerotic plaque development has been associated with wall shear stress (WSS). However, the multidirectionality of blood flow, and thus of WSS, is rarely taken into account. The purpose of this study was to comprehensively compare five metrics that describe (multidirectional) WSS behaviour and assess how WSS multidirectionality affects coronary plaque initiation and progression. METHODS AND RESULTS: Adult familial hypercholesterolaemic pigs (n = 10) that were fed a high-fat diet, underwent imaging of the three main coronary arteries at three-time points [3 (T1), 9 (T2), and 10-12 (T3) months]. Three-dimensional geometry of the arterial lumen, in combination with local flow velocity measurements, was used to calculate WSS at T1 and T2. For analysis, arteries were divided into 3 mm/45° sectors (n = 3648). Changes in wall thickness and final plaque composition were assessed with near-infrared spectroscopy-intravascular ultrasound, optical coherence tomography imaging, and histology. Both in pigs with advanced and mild disease, the highest plaque progression rate was exclusively found at low time-averaged WSS (TAWSS) or high multidirectional WSS regions at both T1 and T2. However, the eventually largest plaque growth was located in regions with initial low TAWSS or high multidirectional WSS that, over time, became exposed to high TAWSS or low multidirectional WSS at T2. Besides plaque size, also the presence of vulnerable plaque components at the last time point was related to low and multidirectional WSS. Almost all WSS metrics had good predictive values for the development of plaque (47-50%) and advanced fibrous cap atheroma (FCA) development (59-61%). CONCLUSION: This study demonstrates that low and multidirectional WSS promote both initiation and progression of coronary atherosclerotic plaques. The high-predictive values of the multidirectional WSS metrics for FCA development indicate their potential as an additional clinical marker for the vulnerable disease.

Gender differences in the diagnostic performance of machine learning coronary CT angiography-derived fractional flow reserve -results from the MACHINE registry.

PURPOSE: This study investigated the impact of gender differences on the diagnostic performance of machine-learning based coronary CT angiography (cCTA)-derived fractional flow reserve (CT-FFRML) for the detection of lesion-specific ischemia. METHOD: Five centers enrolled 351 patients (73.5% male) with 525 vessels in the MACHINE (Machine leArning Based CT angiograpHy derIved FFR: a Multi-ceNtEr) registry. CT-FFRML and invasive FFR ≤ 0.80 were considered hemodynamically significant, whereas cCTA luminal stenosis ≥50% was considered obstructive. The diagnostic performance to assess lesion-specific ischemia in both men and women was assessed on a per-vessel basis. RESULTS: In total, 398 vessels in men and 127 vessels in women were included. Compared to invasive FFR, CT-FFRML reached a sensitivity, specificity, positive predictive value, and negative predictive value of 78% (95%CI 72-84), 79% (95%CI 73-84), 75% (95%CI 69-79), and 82% (95%CI: 76-86) in men vs. 75% (95%CI 58-88), 81 (95%CI 72-89), 61% (95%CI 50-72) and 89% (95%CI 82-94) in women, respectively. CT-FFRML showed no statistically significant difference in the area under the receiver-operating characteristic curve (AUC) in men vs. women (AUC: 0.83 [95%CI 0.79-0.87] vs. 0.83 [95%CI 0.75-0.89], p = 0.89). CT-FFRML was not superior to cCTA alone [AUC: 0.83 (95%CI: 0.75-0.89) vs. 0.74 (95%CI: 0.65-0.81), p = 0.12] in women, but showed a statistically significant improvement in men [0.83 (95%CI: 0.79-0.87) vs. 0.76 (95%CI: 0.71-0.80), p = 0.007]. CONCLUSIONS: Machine-learning based CT-FFR performs equally in men and women with superior diagnostic performance over cCTA alone for the detection of lesion-specific ischemia.

Effect of Tube Voltage on Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography With Machine Learning: Results From the MACHINE Registry.

OBJECTIVE. Coronary CT angiography (CCTA)-based methods allow noninvasive estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) algorithm (cFFRML). However, attenuation values vary according to the tube voltage used, and it has not been shown whether this significantly affects the diagnostic performance of cFFR and cFFRML. Therefore, the purpose of this study is to retrospectively evaluate the effect of tube voltage on the diagnostic performance of cFFRML. MATERIALS AND METHODS. A total of 525 coronary vessels in 351 patients identified in the MACHINE consortium registry were evaluated in terms of invasively measured FFR and cFFRML. CCTA examinations were performed with a tube voltage of 80, 100, or 120 kVp. For each tube voltage value, correlation (assessed by Spearman rank correlation coefficient), agreement (evaluated by intraclass correlation coefficient and Bland-Altman plot analysis), and diagnostic performance (based on ROC AUC value, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) of the cFFRML in terms of detection of significant stenosis were calculated. RESULTS. For tube voltages of 80, 100, and 120 kVp, the Spearman correlation coefficient for cFFRML in relation to the invasively measured FFR value was ρ = 0.684, ρ = 0.622, and ρ = 0.669, respectively (p < 0.001 for all). The corresponding intraclass correlation coefficient was 0.78, 0.76, and 0.77, respectively (p < 0.001 for all). Sensitivity was 100.0%, 73.5%, and 85.0%, and specificity was 76.2%, 79.0%, and 72.8% for tube voltages of 80, 100, and 120 kVp, respectively. The ROC AUC value was 0.90, 0.82, and 0.80 for 80, 100, and 120 kVp, respectively (p < 0.001 for all). CONCLUSION. CCTA-derived cFFRML is a robust method, and its performance does not vary significantly between examinations performed using tube voltages of 100 kVp and 120 kVp. However, because of rapid advancements in CT and postprocessing technology, further research is needed.

Comparison of the Diagnostic Performance of Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve in Patients With Versus Without Diabetes Mellitus (from the MACHINE Consortium).

Coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) is a noninvasive application to evaluate the hemodynamic impact of coronary artery disease by simulating invasively measured FFR based on CT data. CT-FFR is based on the assumption of a normal coronary microvascular response. We assessed the diagnostic performance of a machine-learning based application for on-site computation of CT-FFR in patients with and without diabetes mellitus with suspected coronary artery disease. The study population included 75 diabetic and 276 nondiabetic patients who were enrolled in the MACHINE consortium. The overall diagnostic performance of coronary CT angiography alone and in combination with CT-FFR were analyzed with direct invasive FFR comparison in 110 coronary vessels of the diabetic group and in 415 coronary vessels of the nondiabetic group. Per-vessel discrimination of lesion-specific ischemia by CT-FFR was assessed by the area under the receiver operating characteristic curves. The overall diagnostic accuracy of CT-FFR in diabetic patients was 83% and in nondiabetic patients 75% (p = 0.088), showing improvement over the diagnostic accuracy of coronary CT angiography, which was 58% and 65% (p = 0.223), respectively. In addition, the diagnostic accuracy of CT-FFR was similar between diabetic and nondiabetic patients per stratified CT-FFR group (CT-FFR < 0.6, 0.6 to 0.69, 0.7 to 0.79, 0.8 to 0.89, ≥0.9). The area under the curves for diabetic and nondiabetic patients were also comparable, 0.88 and 0.82 (p = 0.113), respectively. In conclusion, on-site machine-learning CT-FFR analysis improved the diagnostic performance of coronary CT angiography and accurately discriminated lesion-specific ischemia in both diabetic and nondiabetic patients suspected of coronary artery disease.

Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium.

BACKGROUND: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necessarily imply hemodynamic relevance when fractional flow reserve (FFR) is used as reference. CTA-based FFR (CT-FFR), using computational fluid dynamics (CFD), improves the correlation with invasive FFR results but is computationally demanding. More recently, a new machine-learning (ML) CT-FFR algorithm has been developed based on a deep learning model, which can be performed on a regular workstation. In this large multicenter cohort, the diagnostic performance ML-based CT-FFR was compared with CTA and CFD-based CT-FFR for detection of functionally obstructive coronary artery disease. METHODS AND RESULTS: At 5 centers in Europe, Asia, and the United States, 351 patients, including 525 vessels with invasive FFR comparison, were included. ML-based and CFD-based CT-FFR were performed on the CTA data, and diagnostic performance was evaluated using invasive FFR as reference. Correlation between ML-based and CFD-based CT-FFR was excellent (R=0.997). ML-based (area under curve, 0.84) and CFD-based CT-FFR (0.84) outperformed visual CTA (0.69; P<0.0001). On a per-vessel basis, diagnostic accuracy improved from 58% (95% confidence interval, 54%-63%) by CTA to 78% (75%-82%) by ML-based CT-FFR. The per-patient accuracy improved from 71% (66%-76%) by CTA to 85% (81%-89%) by adding ML-based CT-FFR as 62 of 85 (73%) false-positive CTA results could be correctly reclassified by adding ML-based CT-FFR. CONCLUSIONS: On-site CT-FFR based on ML improves the performance of CTA by correctly reclassifying hemodynamically nonsignificant stenosis and performs equally well as CFD-based CT-FFR.

Comprehensive Cardiac CT With Myocardial Perfusion Imaging Versus Functional Testing in Suspected Coronary Artery Disease: The Multicenter, Randomized CRESCENT-II Trial.

OBJECTIVES: This study sought to assess the effectiveness, efficiency, and safety of a tiered, comprehensive cardiac computed tomography (CT) protocol in comparison with functional testing. BACKGROUND: Although CT angiography accurately rules out coronary artery disease (CAD), incorporation of CT myocardial perfusion imaging as part of a tiered diagnostic approach could improve the clinical value and efficiency of cardiac CT in the diagnostic work-up of patients with angina pectoris. METHODS: Between July 2013 and November 2015, 268 patients (mean age 58 years; 49% female) with stable angina (mean pre-test probability 54%) were prospectively randomized between cardiac CT and standard guideline-directed functional testing (95% exercise electrocardiography). The tiered cardiac CT protocol included a calcium scan, followed by CT angiography if calcium was detected. Patients with ≥50% stenosis on CT angiography underwent CT myocardial perfusion imaging. RESULTS: By 6 months, the primary endpoint, the rate of invasive coronary angiograms without a European Society of Cardiology class I indication for revascularization, was lower in the CT group than in the functional testing group (2 of 130 [1.5%] vs. 10 of 138 [7.2%]; p = 0.035), whereas the proportion of invasive angiograms with a revascularization indication was higher (88% vs. 50%; p = 0.017). The median duration until the final diagnosis was 0 (0 of 0) days in the CT group and 0 (0 of 17) in the functional testing group (p < 0.001). Overall, 13% of patients randomized to CT required further testing, compared with 37% in the functional testing group (p < 0.001). The adverse event rate was similar (3% vs. 3%; p = 1.000), although the median cumulative radiation dose was higher for the CT group (3.1 mSv [interquartile range: 1.6 to 7.8] vs. 0 mSv [interquartile range: 0.0 to 7.1]; p < 0.001). CONCLUSIONS: In patients with suspected stable CAD, a tiered cardiac CT protocol with dynamic perfusion imaging offers a fast and efficient alternative to functional testing. (Comprehensive Cardiac CT Versus Exercise Testing in Suspected Coronary Artery Disease 2 [CRESCENT2]; NCT02291484).

Aberrant coronary artery spasms cause ST-T segment depression during endovascular ablation of atrial flutter.

ST-T segment depression during right-sided endovascular catheter ablation is not only caused by obstructive coronary artery disease or (induced) tachycardia. Clinicians should also consider coronary artery spasms evoked by manipulation of nearby catheters, especially in patients with abnormal coronary artery anatomy.

Transthoracic 3D echocardiographic left heart chamber quantification in patients with bicuspid aortic valve disease.

Integration of volumetric heart chamber quantification by 3D echocardiography into clinical practice has been hampered by several factors which a new fully automated algorithm (Left Heart Model, (LHM)) may help overcome. This study therefore aims to evaluate the feasibility and accuracy of the LHM software in quantifying left atrial and left ventricular volumes and left ventricular ejection fraction in a cohort of patients with a bicuspid aortic valve. Patients with a bicuspid aortic valve were prospectively included. All patients underwent 2D and 3D transthoracic echocardiography and computed tomography. Left atrial and ventricular volumes were obtained using the automated program, which did not require manual contour detection. For comparison manual and semi-automated measurements were performed using conventional 2D and 3D datasets. 53 patients were included, in four of those patients no 3D dataset could be acquired. Additionally, 12 patients were excluded based on poor imaging quality. Left ventricular end-diastolic and end-systolic volumes and ejection fraction calculated by the LHM correlated well with manual 2D and 3D measurements (Pearson's r between 0.43 and 0.97, p < 0.05). Left atrial volume (LAV) also correlated significantly although LHM did estimate larger LAV compared to both 2DE and 3DE (Pearson's r between 0.61 and 0.81, p < 0.01). The fully automated software works well in a real-world setting and helps to overcome some of the major hurdles in integrating 3D analysis into daily practice, as it is user-independent and highly reproducible in a group of patients with a clearly defined and well-studied valvular abnormality.

Combined diagnostic performance of coronary computed tomography angiography and computed tomography derived fractional flow reserve for the evaluation of myocardial ischemia: A meta-analysis.

BACKGROUND: To evaluate the combined diagnostic accuracy of coronary computed tomography angiography (CCTA) and computed tomography derived fractional flow reserve (FFRct) in patients with suspected or known coronary artery disease (CAD). METHODS: PubMed, The Cochrane library, Embase and OpenGray were searched to identify studies comparing diagnostic accuracy of CCTA and FFRct. Diagnostic test measurements of FFRct were either extracted directly from the published papers or calculated from provided information. Bivariate models were conducted to synthesize the diagnostic performance of combined CCTA and FFRct at both "per-vessel" and "per-patient" levels. RESULTS: 7 articles were included for analysis. The combined diagnostic outcomes from "both positive" strategy, i.e. a subject was considered as "positive" only when both CCTA and FFRct were "positive", demonstrated relative high specificity (per-vessel: 0.91; per-patient: 0.81), high positive likelihood ratio (LR+, per-vessel: 7.93; per-patient: 4.26), high negative likelihood ratio (LR-, per-vessel: 0.30; per patient: 0.24) and high accuracy (per-vessel: 0.91; per-patient: 0.81) while "either positive" strategy, i.e. a subject was considered as "positive" when either CCTA or FFRct was "positive", demonstrated relative high sensitivity (per-vessel: 0.97; per-patient: 0.98), low LR+ (per-vessel: 1.50; per-patient: 1.17), low LR- (per-vessel: 0.07; per-patient: 0.09) and low accuracy (per-vessel: 0.57; per-patient: 0.54). CONCLUSION: "Both positive" strategy showed better diagnostic performance to rule in patients with non-significant stenosis compared to "either positive" strategy, as it efficiently reduces the proportion of testing false positive subjects.

Sex Differences in the Performance of Cardiac Computed Tomography Compared With Functional Testing in Evaluating Stable Chest Pain: Subanalysis of the Multicenter, Randomized CRESCENT Trial (Calcium Imaging and Selective CT Angiography in Comparison to Functional Testing for Suspected Coronary Artery Disease).

BACKGROUND: Cardiac computed tomography (CT) represents an alternative diagnostic strategy for women with suspected coronary artery disease, with potential benefits in terms of effectiveness and cost-efficiency. METHODS AND RESULTS: The CRESCENT trial (Calcium Imaging and Selective CT Angiography in Comparison to Functional Testing for Suspected Coronary Artery Disease) prospectively randomized 350 patients with stable angina (55% women; aged 55±10 years), mostly with an intermediate coronary artery disease probability, between cardiac CT and functional testing. The tiered cardiac CT protocol included a calcium scan followed by CT angiography if the Agatston calcium score was between 1 and 400. Patients with test-specific contraindications were not excluded from study participation. Sex differences were studied as a prespecified subanalysis. Enrolled women presented more frequently with atypical chest pain and had a lower pretest probability of coronary artery disease compared with men. Independently of these differences, cardiac CT led in both sexes to a fast final diagnosis when compared with functional testing, although the effect was larger in women (P interaction=0.01). The reduced need for further testing after CT, compared with functional testing, was most evident in women (P interaction=0.009). However, no sex interaction was observed with respect to changes in angina and quality of life, cumulative diagnostic costs, and applied radiation dose (all P interactions≥0.097). CONCLUSIONS: Cardiac CT is more efficient in women than in men in terms of time to reach the final diagnosis and downstream testing. However, overall clinical outcome showed no significant difference between women and men after 1 year. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01393028.

Classification of hemodynamically significant stenoses from dynamic CT perfusion and CTA myocardial territories.

PURPOSE: Myocardial blood flow (MBF) obtained by dynamic CT perfusion (CTP) has been recently introduced to assess hemodynamic significance of coronary stenosis in coronary artery disease. The diagnostic performance of dynamic CTP MBF is limited due to subjective interpretation of MBF maps and MBF variations caused by physiological, methodological, and technical issues. In this paper, we introduce a novel method to quantify the hypoperfused volume (HPV) in myocardial territories derived from CT angiography (CTA) to overcome the limitations of current dynamic CTP MBF analysis methods. METHODS: The diagnostic performance of HPV in classifying significant stenoses was evaluated on 22 patients (57 vessels) that underwent CTA, CTP and invasive fractional flow reserve (FFR). FFR was used as the standard of reference to determine stenosis significance. The diagnostic performance was compared to that of the mean MBF computed in regions manually annotated by an expert (MA-MBF). HPV was derived by thresholding the MBF in myocardial territories constructed from CTA by locating the closest artery. Diagnostic performance was evaluated using leave-one-case out cross-validation. Inter-observer reproducibility was assessed by performing annotations of coronary seeds (HPV) and manual regions (MA-MBF) with two users. In addition, the influence of different parameter settings on the diagnostic performance of HPV was assessed. RESULTS: Leave-one-case out cross-validation showed that HPV has an accuracy of 72% (58-83%) with sensitivity of 72% (47-90%) and specificity of 72% (58-83%). The accuracy of MA-MBF was 70% (57-82%) with a sensitivity of 50% (26-74%) and a specificity of 79% (64-91%). The Spearman correlation and the kappa statistic was (ρ = 0.94, κ = 0.86) for HPV and (ρ = 0.72, κ = 0.82) for MA-MBF. The influence of parameter settings on HPV based diagnostic performance was not significant. CONCLUSIONS: The proposed HPV accurately classifies hemodynamically significant stenoses with a level of accuracy comparable to the mean MBF in regions annotated by an expert. HPV improves inter-observer reproducibility as compared to MA-MBF by providing a more objective criterion to associate the stenotic coronary with the supplied myocardial territory.

Integrating CT Myocardial Perfusion and CT-FFR in the Work-Up of Coronary Artery Disease.

OBJECTIVES: The aim of this study was to investigate the individual and combined accuracy of dynamic computed tomography (CT) myocardial perfusion imaging (MPI) and computed tomography angiography (CTA) fractional flow reserve (FFR) for the identification of functionally relevant coronary artery disease (CAD). BACKGROUND: Coronary CTA has become an established diagnostic test for ruling out CAD, but it does not allow interpretation of the hemodynamic severity of stenotic lesions. Two recently introduced functional CT techniques are dynamic MPI and CTA FFR using computational fluid dynamics. METHODS: From 2 institutions, 74 patients (n = 62 men, mean age 61 years) planned for invasive angiography with invasive FFR measurement in 142 vessels underwent CTA imaging and dynamic CT MPI during adenosine vasodilation. A patient-specific myocardial blood flow index was calculated, normalized to remote myocardial global left ventricular blood flow. CTA FFR was computed using an on-site, clinician-operated application. Using binary regression, a single functional CT variable was created combining both CT MPI and CTA FFR. Finally, stepwise diagnostic work-up of CTA FFR with selective use of CT MPI was simulated. The diagnostic performance of CT MPI, CTA FFR, and CT MPI integrated with CTA FFR was evaluated using C statistics with invasive FFR, with a threshold of 0.80 as a reference. RESULTS: Sensitivity, specificity, and accuracy were 73% (95% confidence interval [CI]: 61% to 86%), 68% (95% CI: 56% to 80%), and 70% (95% CI: 62% to 79%) for CT MPI and 82% (95% CI: 72% to 92%), 60% (95% CI: 48% to 72%), and 70% (63% to 80%) for CTA FFR. For CT MPI integrated with CTA FFR, diagnostic accuracy was 79% (95% CI: 71% to 87%), with improvement of the area under the curve from 0.78 to 0.85 (p < 0.05). Accuracy of the stepwise approach was 77%. CONCLUSIONS: CT MPI and CTA FFR both identify functionally significant CAD, with comparable accuracy. Diagnostic performance can be improved by combining the techniques. A stepwise approach, reserving CT MPI for intermediate CTA FFR results, also improves diagnostic performance while omitting nearly one-half of the population from CT MPI examinations.

The effect of blood pressure on non-invasive fractional flow reserve derived from coronary computed tomography angiography.

OBJECTIVES: The aim of this study is to assess the effect of blood pressure (BP) on coronary computed tomography angiography (CTA) derived computational fractional flow reserve (CTA-FFR). MATERIALS AND METHODS: Twenty-one patients who underwent coronary CTA and invasive FFR were retrospectively identified. Ischemia was defined as invasive FFR ≤0.80. Using a work-in-progress computational fluid dynamics algorithm, CTA-FFR was computed with BP measured before CTA, and simulated BPs of 60/50, 90/60, 110/70, 130/80, 150/90, and 180/100 mmHg respectively. Correlation between CTA-FFR and invasive FFR was assessed using Pearson test. The repeated measuring test was used for multiple comparisons of CTA-FFR values by simulated BP inputs. RESULTS: Twenty-nine vessels (14 with invasive FFR ≤0.80) were assessed. The average CTA-FFR for measured BP (134 ± 20/73 ± 12 mmHg) was 0.77 ± 0.12. Correlation between CTA-FFR by measured BP and invasive FFR was good (r = 0.735, P < 0.001). For simulated BPs of 60/50, 90/60, 110/70, 130/80, 150/90, and 180/100 mmHg, the CTA-FFR increased: 0.69 ± 0.13, 0.73 ± 0.12, 0.75 ± 0.12, 0.77 ± 0.11, 0.79 ± 0.11, and 0.81 ± 0.10 respectively (P < 0.05). CONCLUSION: Measurement of the BP just before CTA is preferred for accurate CTA-FFR simulation. BP variations in the common range slightly affect CTA-FFR. However, inaccurate BP assumptions differing from the patient-specific BP could cause misinterpretation of borderline significant lesions. KEY POINTS: • The blood pressure (BP) affects the CTA-FFR computation. • Measured BP before CT examination is preferable for accurate CTA-FFR simulation. • Inaccurate BP assumptions can cause misinterpretation of borderline significant lesions.

Diagnostic value of transmural perfusion ratio derived from dynamic CT-based myocardial perfusion imaging for the detection of haemodynamically relevant coronary artery stenosis.

OBJECTIVES: To investigate the additional value of transmural perfusion ratio (TPR) in dynamic CT myocardial perfusion imaging for detection of haemodynamically significant coronary artery disease compared with fractional flow reserve (FFR). METHODS: Subjects with suspected or known coronary artery disease were prospectively included and underwent a CT-MPI examination. From the CT-MPI time-point data absolute myocardial blood flow (MBF) values were temporally resolved using a hybrid deconvolution model. An absolute MBF value was measured in the suspected perfusion defect. TPR was defined as the ratio between the subendocardial and subepicardial MBF. TPR and MBF results were compared with invasive FFR using a threshold of 0.80. RESULTS: Forty-three patients and 94 territories were analysed. The area under the receiver operator curve was larger for MBF (0.78) compared with TPR (0.65, P = 0.026). No significant differences were found in diagnostic classification between MBF and TPR with a territory-based accuracy of 77 % (67-86 %) for MBF compared with 70 % (60-81 %) for TPR. Combined MBF and TPR classification did not improve the diagnostic classification. CONCLUSIONS: Dynamic CT-MPI-based transmural perfusion ratio predicts haemodynamically significant coronary artery disease. However, diagnostic performance of dynamic CT-MPI-derived TPR is inferior to quantified MBF and has limited incremental value. KEY POINTS: • The transmural perfusion ratio from dynamic CT-MPI predicts functional obstructive coronary artery disease • Performance of the transmural perfusion ratio is inferior to quantified myocardial blood flow • The incremental value of the transmural perfusion ratio is limited.

Computed Tomography Angiography with a 192-slice Dual-source Computed Tomography System: Improvements in Image Quality and Radiation Dose.

PURPOSE: This study aims to compare image quality, radiation dose, and the influence of the heart rate on image quality of high-pitch spiral coronary computed tomography angiography (CCTA) using 128-slice (second generation) dual-source CT (DSCT) and a 192-slice DSCT (third generation) scanner. MATERIALS AND METHODS: Two consecutive cohorts of fifty patients underwent CCTA by high-pitch spiral scan mode using 128 or 192-slice DSCT. The 192-slice DSCT system has a more powerful roentgen tube (2 × 120 kW) that allows CCTA acquisition at lower tube voltages, wider longitudinal coverage for faster table speed (732 m/s), and the use of iterative reconstruction. Objective image quality was measured as the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Subjective image quality was evaluated using a Likert scale. RESULTS: While the effective dose was lower with 192-slice DSCT (1.2 ± 0.5 vs. 0.6 ± 0.3 mSv; P < 0.001), the SNR (18.9 ± 4.3 vs. 11.0 ± 2.9; P < 0.001) and CNR (23.5 ± 4.8 vs. 14.3 ± 4.1; P < 0.001) were superior to 128-slice DSCT. Although patients scanned with 192-slice DSCT had a faster heart rate (59 ± 7 vs. 56 ± 6; P = 0.045), subjective image quality was scored higher (4.2 ± 0.8 vs. 3.0 ± 0.7; P < 0.001) compared to 128-slice DSCT. CONCLUSIONS: High-pitch spiral CCTA by 192-slice DSCT provides better image quality, despite a higher average heart rate, at lower radiation doses compared to 128-slice DSCT.