Diagnosis and treatment of ischemia-producing coronary stenoses improves 5-year survival of patients undergoing major vascular surgery.

OBJECTIVE: Patients undergoing vascular surgery procedures have poor long-term survival due to coexisting coronary artery disease (CAD), which is often asymptomatic, undiagnosed, and undertreated. We sought to determine whether preoperative diagnosis of asymptomatic (silent) coronary ischemia using coronary computed tomography (CT)-derived fractional flow reserve (FFRCT) together with postoperative ischemia-targeted coronary revascularization can reduce adverse cardiac events and improve long-term survival following major vascular surgery METHODS: In this observational cohort study of 522 patients with no known CAD undergoing elective carotid, peripheral, or aneurysm surgery we compared two groups of patients. Group I included 288 patients enrolled in a prospective Institutional Review Board-approved study of preoperative coronary CT angiography (CTA) and FFRCT testing to detect silent coronary ischemia with selective postoperative coronary revascularization in addition to best medical therapy (BMT) (FFRCT guided), and Group II included 234 matched controls with standard preoperative cardiac evaluation and postoperative BMT alone with no elective coronary revascularization (Usual Care). In the FFRCT group, lesion-specific coronary ischemia was defined as FFRCT ≤0.80 distal to a coronary stenosis, with severe ischemia defined as FFRCT ≤0.75. Results were available for patient management decisions. Endpoints included all-cause death, cardiovascular death, myocardial infarction (MI), and major adverse cardiovascular events (MACE [death, MI, or stroke]) during 5-year follow-up. RESULTS: The two groups were similar in age, gender, and comorbidities. In FFRCT, 65% of patients had asymptomatic lesion-specific coronary ischemia, with severe ischemia in 52%, multivessel ischemia in 36% and left main ischemia in 8%. The status of coronary ischemia was unknown in Usual Care. Vascular surgery was performed as planned in both cohorts with no difference in 30-day mortality. In FFRCT, elective ischemia-targeted coronary revascularization was performed in 103 patients 1 to 3 months following surgery. Usual Care had no elective postoperative coronary revascularizations. At 5 years, compared with Usual Care, FFRCT guided had fewer all-cause deaths (16% vs 36%; hazard ratio [HR], 0.37; 95% confidence interval [CI], 0.22-0.60; P < .001), fewer cardiovascular deaths (4% vs 21%; HR, 0.11; 95% CI, 0.04-0.33; P < .001), fewer MIs (4% vs 24%; HR, 0.13; 95% CI, 0.05-0.33; P < .001), and fewer MACE (20% vs 47%; HR, 0.36; 95% CI, 0.23-0.56; P < .001). Five-year survival was 84% in FFRCT compared with 64% in Usual Care (P < .001). CONCLUSIONS: Diagnosis of silent coronary ischemia with ischemia-targeted coronary revascularization in addition to BMT following major vascular surgery was associated with fewer adverse cardiovascular events and improved 5-year survival compared with patients treated with BMT alone as per current guidelines.

Impact of coronary CT image quality on the accuracy of the FFRCT Planner.

OBJECTIVE: To assess the accuracy of a virtual stenting tool based on coronary CT angiography (CCTA) and fractional flow reserve (FFR) derived from CCTA (FFRCT Planner) across different levels of image quality. MATERIALS AND METHODS: Prospective, multicenter, single-arm study of patients with chronic coronary syndromes and lesions with FFR ≤ 0.80. All patients underwent CCTA performed with recent-generation scanners. CCTA image quality was adjudicated using the four-point Likert scale at a per-vessel level by an independent committee blinded to the FFRCT Planner. Patient- and technical-related factors that could affect the FFRCT Planner accuracy were evaluated. The FFRCT Planner was applied mirroring percutaneous coronary intervention (PCI) to determine the agreement with invasively measured post-PCI FFR. RESULTS: Overall, 120 patients (123 vessels) were included. Invasive post-PCI FFR was 0.88 ± 0.06 and Planner FFRCT was 0.86 ± 0.06 (mean difference 0.02 FFR units, the lower limit of agreement (LLA) - 0.12, upper limit of agreement (ULA) 0.15). CCTA image quality was assessed as excellent (Likert score 4) in 48.3%, good (Likert score 3) in 45%, and sufficient (Likert score 2) in 6.7% of patients. The FFRCT Planner was accurate across different levels of image quality with a mean difference between FFRCT Planner and invasive post-PCI FFR of 0.02 ± 0.07 in Likert score 4, 0.02 ± 0.07 in Likert score 3 and 0.03 ± 0.08 in Likert score 2, p = 0.695. Nitrate dose ≥ 0.8mg was the only independent factor associated with the accuracy of the FFRCT Planner (95%CI - 0.06 to - 0.001, p = 0.040). CONCLUSION: The FFRCT Planner was accurate in predicting post-PCI FFR independent of CCTA image quality. CLINICAL RELEVANCE STATEMENT: Being accurate in predicting post-PCI FFR across a wide spectrum of CT image quality, the FFRCT Planner could potentially enhance and guide the invasive treatment. Adequate vasodilation during CT acquisition is relevant to improve the accuracy of the FFRCT Planner. KEY POINTS: • The fractional flow reserve derived from coronary CT angiography (FFRCT) Planner is a novel tool able to accurately predict fractional flow reserve after percutaneous coronary intervention. • The accuracy of the FFRCT Planner was confirmed across a wide spectrum of CT image quality. Nitrates dose at CT acquisition was the only independent predictor of its accuracy. • The FFRCT Planner could potentially enhance and guide the invasive treatment.

Ischemia-Guided Coronary Revascularization Following Lower-Extremity Revascularization Improves 5-Year Survival of Patients With Chronic Limb-Threatening Ischemia.

PURPOSE: To determine whether diagnosis of asymptomatic (silent) coronary ischemia using coronary computed tomography (CT)-derived fractional flow reserve (FFRCT) together with targeted coronary revascularization of ischemia-producing coronary lesions following lower-extremity revascularization can reduce adverse cardiac events and improve long-term survival of patients with chronic limb-threatening ischemia (CLTI). MATERIALS AND METHODS: Prospective cohort study of CLTI patients with no cardiac history or symptoms undergoing elective lower-extremity revascularization. Patients with pre-operative coronary computed tomography angiography (CTA) and FFRCT evaluation with selective post-operative coronary revascularization (FFRCT group) were compared with patients with standard pre-operative evaluation and no post-operative coronary revascularization (control group). Lesion-specific coronary ischemia was defined as FFRCT≤0.80 distal to a coronary stenosis with FFRCT≤0.75 indicating severe ischemia. Endpoints included all-cause death, cardiac death, myocardial infarction (MI) and major adverse cardiovascular (CV) events (MACE=CV death, MI, stroke, or unplanned coronary revascularization) during 5 year follow-up. RESULTS: In the FFRCT group (n=111), FFRCT analysis revealed asymptomatic (silent) coronary ischemia (FFRCT≤0.80) in 69% of patients, with severe ischemia (FFRCT≤0.75) in 58%, left main ischemia in 8%, and multivessel ischemia in 40% of patients. The status of coronary ischemia in the control group (n=120) was unknown. Following lower-extremity revascularization, 42% of patients in FFRCT had elective coronary revascularization with no elective revascularization in controls. Both groups received guideline-directed medical therapy. During 5 year follow-up, compared with control, the FFRCT group had fewer all-cause deaths (24% vs 47%, hazard ratio [HR]=0.43 [95% confidence interval [CI]=0.27-0.69], p<0.001), fewer cardiac deaths (5% vs 26%, HR=0.18 [95% CI=0.07-0.45], p<0.001), fewer MIs (7% vs 28%, HR=0.21 [95% CI=0.10-0.47], p<0.001), and fewer MACE events (14% vs 39%, HR=0.28 [95% CI=0.15-0.51], p<0.001). CONCLUSIONS: Ischemia-guided coronary revascularization of CLTI patients with asymptomatic (silent) coronary ischemia following lower-extremity revascularization resulted in more than 2-fold reduction in all-cause death, cardiac death, MI, and MACE with improved 5 year survival compared with patients with standard cardiac evaluation and care (76% vs 53%, p<0.001). CLINICAL IMPACT: Silent coronary ischemia in patients with chronic limb-threatening ischemia (CLTI) is common even in the absence of cardiac history or symptoms. FFRCT is a convenient tool to diagnose silent coronary ischemia perioperatively. Our data suggest that post-surgery elective FFRCT-guided coronary revascularization reduces adverse cardiac events and improves long-term survival in this very-high risk patient group. Randomized study is warranted to finally test this concept.

The role of coronary CT angiography in athletes.

The sudden death of a young or high-level athlete or adolescent during recreational sports is one of the events with the greatest impact on public opinion in modern society. Sudden cardiac death (SCD) is the principal medical cause of death in athletes and can be the first and last clinical presentation of underlying disease. To prevent such episodes, pre-participation screening has been introduced in many countries to guarantee cardiovascular safety during sports and has become a common target among medical sports/governing organizations. Different cardiac conditions may cause SCD, with incidence depending on definition, evaluation methods, and studied populations, and a prevalence and etiology changing according to the age of athletes, with CAD most frequent in master athletes, while coronary anomalies and non-ischemic causes prevalent in young. To detect silent underlying causes early would be of considerable clinical value. This review summarizes the pre-participation screening in athletes, the specialist agonistic suitability visit performed in Italy, the anatomical characteristics of malignant coronary anomalies, and finally, the role of coronary CT angiography in such arena. In particular, the anatomical conditions suggesting potential disqualification from sport, the post-treatment follow-up to reintegrate young athletes, the diagnostic workflow to rule-out CAD in master athletes, and their clinical management are analyzed.

Motion artifact removal in coronary CT angiography based on generative adversarial networks.

OBJECTIVES: Coronary motion artifacts affect the diagnostic accuracy of coronary CT angiography (CCTA), especially in the mid right coronary artery (mRCA). The purpose is to correct CCTA motion artifacts of the mRCA using a GAN (generative adversarial network). METHODS: We included 313 patients with CCTA scans, who had paired motion-affected and motion-free reference images at different R-R interval phases in the same cardiac cycle and included another 53 CCTA cases with invasive coronary angiography (ICA) comparison. Pix2pix, an image-to-image conversion GAN, was trained by the motion-affected and motion-free reference pairs to generate motion-free images from the motion-affected images. Peak signal-to-noise ratio (PSNR), structural similarity (SSIM), Dice similarity coefficient (DSC), and Hausdorff distance (HD) were calculated to evaluate the image quality of GAN-generated images. RESULTS: At the image level, the median of PSNR, SSIM, DSC, and HD of GAN-generated images were 26.1 (interquartile: 24.4-27.5), 0.860 (0.830-0.882), 0.783 (0.714-0.825), and 4.47 (3.00-4.47), respectively, significantly better than the motion-affected images (p < 0.001). At the patient level, the image quality results were similar. GAN-generated images improved the motion artifact alleviation score (4 vs. 1, p < 0.001) and overall image quality score (4 vs. 1, p < 0.001) than those of the motion-affected images. In patients with ICA comparison, GAN-generated images achieved accuracy of 81%, 85%, and 70% in identifying no, < 50%, and ≥ 50% stenosis, respectively, higher than 66%, 72%, and 68% for the motion-affected images. CONCLUSION: Generative adversarial network-generated CCTA images greatly improved the image quality and diagnostic accuracy compared to motion-affected images. KEY POINTS: • A generative adversarial network greatly reduced motion artifacts in coronary CT angiography and improved image quality. • GAN-generated images improved diagnosis accuracy of identifying no, < 50%, and ≥ 50% stenosis.

Low-dose coronary artery calcium scoring compared to the standard protocol.

BACKGROUND: We aimed to compare coronary artery calcium scoring (CACS) with computed tomography (CT) with 80 and 120 kVp in a large patient population and to establish whether there is a difference in risk classification between the two scores. METHODS: Patients with suspected CAD undergoing MPS were included. All underwent standard CACS assessment with 120-kVp tube voltage and with 80 kVp. Two datasets (low-dose and standard) were generated and compared. Risk classes (0 to 25, 25 to 50, 50 to 75, 75 to 90, and > 90%) were recorded. RESULTS: 1511 patients were included (793 males, age 69 ± 9.1 years). There was a very good correlation between scores calculated with 120 and 80 kVp (R = 0.94, R2 = 0.88, P < .001), with Bland-Altman limits of agreement of - 563.5 to 871.9 and a bias of - 154.2. The proportion of patients assigned to the < 25% percentile class (P = .03) and with CACS = 0 differed between the two protocols (n = 264 vs 437, P < .001). CONCLUSION: In a large patient population, despite a good correlation between CACS calculated with standard and low-dose CT, there is a systematic underestimation of CACS with the low-dose protocol. This may have an impact especially on the prognostic value of the calcium score, and the established "power of zero" may no longer be warranted if CACS is assessed with low-dose CT.

Frequency, compliance, and yield of cardiac testing after high-sensitivity troponin accelerated diagnostic protocol implementation.

BACKGROUND: Among persons presenting to the emergency department with suspected acute myocardial infarction (MI), cardiac troponin (cTn) testing is commonly used to detect acute myocardial injury. Accelerated diagnostic protocols (ADPs) guide clinicians to integrate cTn results with other clinical information to decide whether to order further diagnostic testing. OBJECTIVE: To determine the change in the rate and yield of stress test or coronary CT angiogram following cTn measurement in patients with chest pain presenting to the emergency department pre- and post-transition to a high-sensitivity (hs-cTn) assay in an updated ADP. METHODS: Using electronic health records, we examined visits for chest pain at five emergency departments affiliated with an integrated academic health system 1-year pre- and post-hs-cTn assay transition. Outcomes included stress test or coronary imaging frequency, ADP compliance among those with additional testing, and diagnostic yield (ratio of positive tests to total tests). RESULTS: There were 7564 patient-visits for chest pain, including 3665 in the pre- and 3899 in the post-period. Following the updated ADP using hs-cTn, 862 (23.5 per 100 patient visits) visits led to subsequent testing versus 1085 (27.8 per 100 patient visits) in the pre-hs-cTn period, (P < 0.001). Among those who were tested, the protocol-compliant rate fell from 80.9% to 46.5% (P < 0.001), but the yield of those tests rose from 24.5% to 29.2% (P = 0.07). Among tests that were noncompliant with ADP guidance, yield was similar pre- and post-updated hs-cTn ADP implementation (pre 13.0%, post 15.4% (P = 0.43). CONCLUSION: Implementation of hs-cTn supported by an updated ADP was associated with a lower rate of stress testing and coronary CT angiogram.

In search of new gatekeepers: coronary CT (Computed Tomography) in acute coronary syndrome.

Coronary computed tomography (CCT) is a non-invasive imaging method that allows visualization of the epicardial coronary arteries. The diagnostic and prognostic role of CCT has been demonstrated by various randomized trials to such an extent that it has been included as a Class I, level of evidence B recommendation in the latest European Society of Cardiology (ESC) guidelines for the diagnosis of chronic coronary syndrome in patients at intermediate-low cardiovascular risk. In addition to the anatomical evaluation, the CCT allows to evaluate the presence of high-risk characteristics of the atherosclerotic plaque (napkin-ring sign, positive remodelling, spotty calcification, and low-attenuation plaque), thus discriminating the stability of the atheromatous pathology. Furthermore, among the potential of cardiac CT in the emergency department, the possibility of making a triple rule-out must be underlined, excluding three potential big killers as the cause of acute chest pain: acute coronary syndrome, pulmonary embolism, and aortic dissection. Various randomized clinical studies have demonstrated that the prognosis of the patient with chronic coronary artery disease (CAD) improves only if a haemodynamically significant stenosis is treated, generally investigated with invasive fractional flow reserve (FFR); CCT technological advances have made it possible to create an algorithm for calculating the FFR-CT, an index of haemodynamic significance of coronary stenosis, whose correlation with the invasive FFR data and, consequently, with the prognosis has been demonstrated of patients with CAD.

Current and Future Applications of Artificial Intelligence in Cardiac CT.

PURPOSE OF REVIEW: In this review, we aim to summarize state-of-the-art artificial intelligence (AI) approaches applied to cardiovascular CT and their future implications. RECENT FINDINGS: Recent studies have shown that deep learning networks can be applied for rapid automated segmentation of coronary plaque from coronary CT angiography, with AI-enabled measurement of total plaque volume predicting future heart attack. AI has also been applied to automate assessment of coronary artery calcium on cardiac and ungated chest CT and to automate the measurement of epicardial fat. Additionally, AI-based prediction models integrating clinical and imaging parameters have been shown to improve prediction of cardiac events compared to traditional risk scores. Artificial intelligence applications have been applied in all aspects of cardiovascular CT - in image acquisition, reconstruction and denoising, segmentation and quantitative analysis, diagnosis and decision assistance and to integrate prognostic risk from clinical data and images. Further incorporation of artificial intelligence in cardiovascular imaging holds important promise to enhance cardiovascular CT as a precision medicine tool.

Screening for Coronary Artery Disease in Patients with Diabetes.

PURPOSE OF REVIEW: The study aims to describe methods for detecting subclinical coronary artery disease (CAD) and their potential implications in asymptomatic patients with diabetes. RECENT FINDINGS: Imaging tools can assess non-invasively the presence and severity of CAD, based on myocardial ischemia, coronary artery calcium score, and coronary computed tomography coronary angiography. Subclinical CAD is common in the general population ageing 50 to 64 years with any coronary atherosclerosis present in 42.1% and obstructive CAD in 5.2%. In patients with diabetes, an even higher prevalence has been noted. The presence of myocardial ischemia, obstructive CAD, and the extent of coronary atherosclerosis provide powerful risk stratification regarding the risk of cardiovascular events. However, randomized trials evaluating systematic screening in the general population or patients with diabetes have demonstrated only moderate impact on management and no significant impact on patient outcomes. Despite providing improved risk stratification, systematic screening of CAD is not recommended in patients with diabetes.

Performance of a Novel CT-Derived Fractional Flow Reserve Measurement to Detect Hemodynamically Significant Coronary Stenosis.

BACKGROUND: Fractional flow reserve (FFR) based on computed tomography (CT) has been shown to better identify ischemia-causing coronary stenosis. However, this current technology requires high computational power, which inhibits its widespread implementation in clinical practice. This prospective, multicenter study aimed at validating the diagnostic performance of a novel simple CT based fractional flow reserve (CT-FFR) calculation method in patients with coronary artery disease. METHODS: Patients who underwent coronary CT angiography (CCTA) within 90 days and invasive coronary angiography (ICA) were prospectively enrolled. A hemodynamically significant lesion was defined as an FFR ≤ 0.80, and the area under the receiver operating characteristic curve (AUC) was the primary measure. After the planned analysis for the initial algorithm A, we performed another set of exploratory analyses for an improved algorithm B. RESULTS: Of 184 patients who agreed to participate in the study, 151 were finally analyzed. Hemodynamically significant lesions were observed in 79 patients (52.3%). The AUC was 0.71 (95% confidence interval [CI], 0.63-0.80) for CCTA, 0.65 (95% CI, 0.56-0.74) for CT-FFR algorithm A (P = 0.866), and 0.78 (95% CI, 0.70-0.86) for algorithm B (P = 0.112). Diagnostic accuracy was 0.63 (0.55-0.71) for CCTA alone, 0.66 (0.58-0.74) for algorithm A, and 0.76 (0.68-0.82) for algorithm B. CONCLUSION: This study suggests the feasibility of automated CT-FFR, which can be performed on-site within several hours. However, the diagnostic performance of the current algorithm does not meet the a priori criteria for superiority. Future research is required to improve the accuracy.

A patient- and acquisition-tailored injection approach for improving consistency of CT enhancement towards a target CT value in coronary CT angiography.

BACKGROUND: Unoptimized coronary CT angiography (CTA) exams typically result in a highly variable arterial enhancement (HUa ) across patients. This study aimed at harmonizing arterial enhancement by implementing a patient-, contrast- and kV-tailored injection protocol. METHODS: First, the optimal body size metric to predict HUa was identified by retrospectively analysing images of 76 patients, acquired with 70 ml contrast media (G1). Second, using phantom experiments, correction factors for the effect of kV and contrast concentration on HUa were determined. Third, a model was developed, prescribing the optimal contrast dose to be injected to obtain a diagnostically appropriate arterial target enhancement HUtarget . The model was then validated on 278 prospectively collected patients, in two groups with two different HUtarget : 525 HU (207 patients, G2A) and 425 HU (71 patients, G2B). The HUa histograms were compared among groups and to the target enhancement through their mean and standard deviation (SD) at 100 kVp reference level. Also, signal-to-noise ratio was obtained and compared among the groups. RESULTS: Fat free mass (FFM) showed the highest correlation with HUa (r = 0.69). KVp correction factors ranged from 0.65 at 70 kVp to 1.22 at 140 kVp. The obtained model reduced the group heterogeneity (SD) from 101HU for reference G1 to 75HU (p < 0.001) for G2A and 68HU (p < 0.001) for G2B. The mean HUa of 506HU in G2A was slightly below HUtarget  = 525HU (p = 0.01) whereas in G2B, the mean HUa of 414HU was not significantly different from HUtarget  = 425HU (p = 0.54). The total iodine dose was lowered from 19.5 g-I to 17.6 g-I and 14.2 g-I from G1 to G2A and G2B, on average. CONCLUSION: A contrast injection model, based on patient's fat free mass and accounting for the contrast agent concentration and the planned CT-scan tube voltage, harmonized arterial enhancement among patients towards a predefined target enhancement in coronary CTA scanning, without affecting the bolus timing.

Diagnostic performance of deep learning-based vessel extraction and stenosis detection on coronary computed tomography angiography for coronary artery disease: a multi-reader multi-case study.

BACKGROUND: Post-processing and interpretation of coronary CT angiography (CCTA) imaging are time-consuming and dependent on the reader's experience. An automated deep learning (DL)-based imaging reconstruction and diagnosis system was developed to improve diagnostic accuracy and efficiency. METHODS: Our study including 374 cases from five sites, inviting 12 radiologists, assessed the DL-based system in diagnosing obstructive coronary disease with regard to diagnostic performance, imaging post-processing and reporting time of radiologists, with invasive coronary angiography as a standard reference. The diagnostic performance of DL system and DL-assisted human readers was compared with the traditional method of human readers without DL system. RESULTS: Comparing the diagnostic performance of human readers without DL system versus with DL system, the AUC was improved from 0.81 to 0.82 (p < 0.05) at patient level and from 0.79 to 0.81 (p < 0.05) at vessel level. An increase in AUC was observed in inexperienced radiologists (p < 0.05), but was absent in experienced radiologists. Regarding diagnostic efficiency, comparing the DL system versus human reader, the average post-processing and reporting time was decreased from 798.60 s to 189.12 s (p < 0.05). The sensitivity and specificity of using DL system alone were 93.55% and 59.57% at patient level and 83.23% and 79.97% at vessel level, respectively. CONCLUSIONS: With the DL system serving as a concurrent reader, the overall post-processing and reading time was substantially reduced. The diagnostic accuracy of human readers, especially for inexperienced readers, was improved. DL-assisted human reader had the potential of being the reading mode of choice in clinical routine.

[Computed tomography in cardiology: history and perspectives].

The review article highlights the main stages of the formation of computed tomography (CT) as a key method used in modern cardiology. The progress of CT scanners is directly related to the increase in the number of detectors, and thus, with an increase in the number of simultaneously collected projections. Modern developments and future technologies in the field of further development of the technique, including CT angiography and other new methods for assessing coronary blood flow, are discussed. The use of artificial intelligence technologies may make it possible to improve and accelerate the interpretation of the resulting images in the future, especially if it is economically justified.

3D computed tomography intravascular endoscopy.

Using coronary computed tomography angiography (CCTA), coronary plaques can be characterized based on both their morphology and composition. Coronary plaques are generally assessed on 2D axial and multiplanar reformatted images. Nevertheless, these visualization tools are limited to observing extraluminal changes in the coronary artery. The presence of plaques prevents them from providing a visual representation of the intraluminal coronary wall. Since its invention in 2000, coronary fly-through or virtual angioscopy (VA) has been extensively studied. However, its application was limited because it required an optimal CT scan and time-consuming post-processing. In recent years, advances in post-processing software have made construction of VA easier, but until recently the quality of the images was insufficient for most patients. Using 3D intravascular endoscopy (3DIE) visualization, we present various intraluminal appearances of the coronary wall and plaque in relation to various types of plaque.

Coronary revascularization of patients with silent coronary ischemia may reduce the risk of myocardial infarction and cardiovascular death after carotid endarterectomy.

BACKGROUND: Major adverse cardiac events (MACEs) are the primary cause of death after carotid endarterectomy (CEA). We sought to determine whether selective coronary revascularization of CEA patients with asymptomatic coronary ischemia can reduce the risk of MACEs, myocardial infarction (MI), and cardiac death after endarterectomy compared with CEA patients receiving standard cardiac evaluation and care. METHODS: Two groups of patients with no cardiac history or symptoms undergoing elective CEA were compared. Group I: patients enrolled in a prospective study of noninvasive preoperative cardiac evaluation using coronary computed tomography (CT)-derived fractional flow reserve (FFRCT) to detect asymptomatic (silent) coronary ischemia with selective postoperative coronary revascularization. Group II: matched Control patients with standard preoperative cardiac evaluation and no postoperative coronary revascularization. Lesion-specific coronary ischemia in group I was defined as FFRCT ≤ 0.80 distal to coronary stenosis with severe ischemia defined as FFRCT ≤ 0.75. End points included MACEs, cardiac death, MI, cardiovascular (CV) death, stroke, and all-cause death through 3-year follow-up. RESULTS: Group I (n = 100) and group II (n = 100) patients were similar in age (68 vs 67 years), gender (65% vs 62% male), comorbidities, and indications for CEA (53% vs 48% symptomatic carotid stenosis). In group I, FFRCT analysis revealed lesion-specific coronary ischemia in 57% of patients, severe coronary ischemia in 44%, left main ischemia in 7%, and multivessel ischemia in 28%. The status of coronary ischemia in group II was unknown. CEA was performed without complications in both groups, and all patients received optimal postoperative medical therapy. In group I, elective coronary revascularization was performed in 33 patients (27 percutaneous coronary intervention; 6 coronary artery bypass grafting) 1 to 3 months after CEA. Group II patients had no elective coronary revascularization. During 3-year follow-up, compared with group II, group I patients had fewer MACEs (4% vs 17%, hazard ratio [HR]: 0.21 [95% confidence interval (CI): 0.07-0.63], P = .004), fewer cardiac deaths (2% vs 9%, HR: 0.20 [95% CI: 0.04-0.95], P = .030), fewer MIs (3% vs 17%, HR: 0.16 [95% CI: 0.05-0.54], P = .001), and fewer CV deaths (2% vs 12%, HR: 0.16 [95% CI: 0.004-0.07], P = .009). There were no significant differences in the rates of stroke or all-cause death. CONCLUSIONS: Preoperative diagnosis of silent coronary ischemia with selective coronary revascularization after CEA may reduce the risk of MACEs, cardiac death, MI, and CV death during 3-year follow-up compared with CEA patients receiving standard cardiac evaluation and care.

Predicting Chronic Myocardial Ischemia Using CCTA-Based Radiomics Machine Learning Nomogram.

BACKGROUND: Coronary computed tomography angiography (CCTA) is a well-established non-invasive diagnostic test for the assessment of coronary artery diseases (CAD). CCTA not only provides information on luminal stenosis but also permits non-invasive assessment and quantitative measurement of stenosis based on radiomics. PURPOSE: This study is aimed to develop and validate a CT-based radiomics machine learning for predicting chronic myocardial ischemia (MIS). METHODS: CCTA and SPECT-myocardial perfusion imaging (MPI) of 154 patients with CAD were retrospectively analyzed and 94 patients were diagnosed with MIS. The patients were randomly divided into two sets: training (n = 107) and test (n = 47). Features were extracted for each CCTA cross-sectional image to identify myocardial segments. Multivariate logistic regression was used to establish a radiomics signature after feature dimension reduction. Finally, the radiomics nomogram was built based on a predictive model of MIS which in turn was constructed by machine learning combined with the clinically related factors. We then validated the model using data from 49 CAD patients and included 18 MIS patients from another medical center. The receiver operating characteristic curve evaluated the diagnostic accuracy of the nomogram based on the training set and was validated by the test and validation set. Decision curve analysis (DCA) was used to validate the clinical practicability of the nomogram. RESULTS: The accuracy of the nomogram for the prediction of MIS in the training, test and validation sets was 0.839, 0.832, and 0.816, respectively. The diagnosis accuracy of the nomogram, signature, and vascular stenosis were 0.824, 0.736 and 0.708, respectively. A significant difference in the number of patients with MIS between the high and low-risk groups was identified based on the nomogram (P < .05). The DCA curve demonstrated that the nomogram was clinically feasible. CONCLUSION: The radiomics nomogram constructed based on the image of CCTA act as a non-invasive tool for predicting MIS that helps to identify high-risk patients with coronary artery disease.

Quantitative myocardial perfusion 82Rb-PET assessed by hybrid PET/coronary-CT: Normal values and diagnostic performance.

PURPOSE: We aimed to assess normal values for quantified myocardial blood flow (MBF) on a hybrid PET/coronary-CT scanner and to test their diagnostic performance in patients with suspected CAD. MATERIALS AND METHODS: Patients underwent 82Rb-PET/CT and integrated CT-based coronary angiography (CCTA) and were classified as normal (no stenosis), with non-obstructive stenosis (< 50%) and with CAD (≥ 50%). Global and regional stress MBF (sMBF), rest MBF and myocardial flow reserve (MFR) were calculated. Ischemia was defined as SDS ≥ 2, severe ischemia as SDS ≥ 7. RESULTS: 357 consecutive patients were included. Global sMBF and MFR were higher in normal patients than in patients with CAD (3.61 ± 0.71 vs 3.04 ± 0.77, P < 0.0001; 3.08 ± 0.84 vs 2.68 ± 0.79, P = 0.0001), but not different compared to patients with non-obstructive stenosis (3.61 ± 0.71 vs 3.43 ± 0.69, P = 0.052; 3.08 ± 0.84 vs 2.99 ± 0.82, P = 0.45). sMBF yielded superior accuracy over MFR in identifying both ischemia (AUC 0.74 vs 0.62, P = 0.003) and severe ischemia (AUC 0.88 vs 0.78, P = 0.012). Optimal threshold for global sMBF to rule out myocardial ischemia was 3.5 mL g-1 min-1. CONCLUSIONS: Normal quantitative values are provided. Global sMBF provided higher diagnostic accuracy than MFR. Using sMBF-threshold of 3.5 mL·g-1·min-1 on 82Rb-PET/CT yielded similar NPV (96%) as CCTA to rule out CAD. Hence, resting scan could be omitted in patients with sMBF values above reference.

Transient ischemic dilation or transient RV visualization in patients with normal SPECT stress myocardial perfusion imaging: Correlation with CT coronary artery calcium scoring and coronary angiography.

BACKGROUND: Ancillary findings on MPI, such as transient ischemic dilation (TID) and transient right ventricular visualization (TRV), are recognized as markers of extensive CAD and predictive of adverse outcomes. They usually occur in association with stress-induced regional MPI abnormalities. However, the clinical significance of these ancillary markers in the presence of normal stress MPI is incompletely understood. METHODS: From a cohort of 564 consecutive patients referred for clinical SPECT stress MPI, 44 patients had normal stress SPECT MPI and either TID (n = 28) or TRV (n = 16). These imaging findings were correlated with CT coronary calcium (CAC), CT coronary angiography (CTA), and invasive coronary angiography (ICA) in patients with severe CAC ≥ 1000 HU. TID and TRV were quantified as stress/rest ratios. Severe CAD was defined as > 70% luminal stenosis on CTA or ICA. RESULTS: The median TID ratio was 1.23, with a range of 1.13-1.48; the median TRV ratio was 1.30, with a range of 1.20-1.48. Of 44 patients with TID or TRV, only 9 patients (20.5%) had severe obstructive > 70% CAD by angiography (6 of 28 patients (21.5%) with TID and 3 of 16 patients (19%) with TRV). Severe multi-vessel CAD occurred in only 2 of 44 patients (4.5%). In contrast, of 9 patients with CAC > 1000 HU, 6 (67%) had severe obstructive CAD. CONCLUSION: In patients with normal stress SPECT MPI and TID or TRV, the incidence of severe obstructive CAD was relatively low and predominantly single-vessel CAD. These findings do not support the concept that TID or TRV with normal stress MPI is predictive of high-risk CAD.

Coronary CTA With AI-QCT Interpretation: Comparison With Myocardial Perfusion Imaging for Detection of Obstructive Stenosis Using Invasive Angiography as Reference Standard.

BACKGROUND. Deep learning frameworks have been applied to interpretation of coronary CTA performed for coronary artery disease (CAD) evaluation. OBJECTIVE. The purpose of our study was to compare the diagnostic performance of myocardial perfusion imaging (MPI) and coronary CTA with artificial intelligence quantitative CT (AI-QCT) interpretation for detection of obstructive CAD on invasive angiography and to assess the downstream impact of including coronary CTA with AI-QCT in diagnostic algorithms. METHODS. This study entailed a retrospective post hoc analysis of the derivation cohort of the prospective 23-center Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) trial. The study included 301 patients (88 women and 213 men; mean age, 64.4 ± 10.2 [SD] years) recruited from May 2014 to May 2017 with stable symptoms of myocardial ischemia referred for nonemergent invasive angiography. Patients underwent coronary CTA and MPI before angiography with quantitative coronary angiography (QCA) measurements and fractional flow reserve (FFR). CTA examinations were analyzed using an FDA-cleared cloud-based software platform that performs AI-QCT for stenosis determination. Diagnostic performance was evaluated. Diagnostic algorithms were compared. RESULTS. Among 102 patients with no ischemia on MPI, AI-QCT identified obstructive (≥ 50%) stenosis in 54% of patients, including severe (≥ 70%) stenosis in 20%. Among 199 patients with ischemia on MPI, AI-QCT identified nonobstructive (1-49%) stenosis in 23%. AI-QCT had significantly higher AUC (all p < .001) than MPI for predicting ≥ 50% stenosis by QCA (0.88 vs 0.66), ≥ 70% stenosis by QCA (0.92 vs 0.81), and FFR < 0.80 (0.90 vs 0.71). An AI-QCT result of ≥ 50% stenosis and ischemia on stress MPI had sensitivity of 95% versus 74% and specificity of 63% versus 43% for detecting ≥ 50% stenosis by QCA measurement. Compared with performing MPI in all patients and those showing ischemia undergoing invasive angiography, a scenario of performing coronary CTA with AIQCT in all patients and those showing ≥ 70% stenosis undergoing invasive angiography would reduce invasive angiography utilization by 39%; a scenario of performing MPI in all patients and those showing ischemia undergoing coronary CTA with AI-QCT and those with ≥ 70% stenosis on AI-QCT undergoing invasive angiography would reduce invasive angiography utilization by 49%. CONCLUSION. Coronary CTA with AI-QCT had higher diagnostic performance than MPI for detecting obstructive CAD. CLINICAL IMPACT. A diagnostic algorithm incorporating AI-QCT could substantially reduce unnecessary downstream invasive testing and costs. TRIAL REGISTRATION. Clinicaltrials.gov NCT02173275.