Diagnostic performance of coronary angiography by 64-row CT

Atherosclerosis quantification and cardiovascular risk: the ISCHEMIA trial

BACKGROUND AND AIMS

The aim of this study was to determine the prognostic value of coronary computed tomography angiography (CCTA)-derived atherosclerotic plaque analysis in ISCHEMIA.

METHODS

Atherosclerosis imaging quantitative computed tomography (AI-QCT) was performed on all available baseline CCTAs to quantify plaque volume, composition, and distribution. Multivariable Cox regression was used to examine the association between baseline risk factors (age, sex, smoking, diabetes, hypertension, ejection fraction, prior coronary disease, estimated glomerular filtration rate, and statin use), number of diseased vessels, atherosclerotic plaque characteristics determined by AI-QCT, and a composite primary outcome of cardiovascular death or myocardial infarction over a median follow-up of 3.3 (interquartile range 2.2-4.4) years. The predictive value of plaque quantification over risk factors was compared in an area under the curve (AUC) analysis.

RESULTS

Analysable CCTA data were available from 3711 participants (mean age 64 years, 21% female, 79% multivessel coronary artery disease). Amongst the AI-QCT variables, total plaque volume was most strongly associated with the primary outcome (adjusted hazard ratio 1.56, 95% confidence interval 1.25-1.97 per interquartile range increase [559 mm3]; P = .001). The addition of AI-QCT plaque quantification and characterization to baseline risk factors improved the model's predictive value for the primary outcome at 6 months (AUC 0.688 vs. 0.637; P = .006), at 2 years (AUC 0.660 vs. 0.617; P = .003), and at 4 years of follow-up (AUC 0.654 vs. 0.608; P = .002). The findings were similar for the other reported outcomes.

CONCLUSIONS

In ISCHEMIA, total plaque volume was associated with cardiovascular death or myocardial infarction. In this highly diseased, high-risk population, enhanced assessment of atherosclerotic burden using AI-QCT-derived measures of plaque volume and composition modestly improved event prediction.

A calcification subtraction method for postmortem coronary computed tomography angiography

Although coronary computed tomography (CT) angiography is a useful tool for evaluating coronary artery lesions both ante- and postmortem, accurate evaluation of the lumen is difficult when highly calcified lesions are present, owing to overestimation of stenosis caused by blooming and partial volume artifacts. In clinical practice, to overcome this diagnostic problem, a subtraction method has been devised to remove calcification by subtracting the precontrast image from the contrast image. In this report, we describe a calcification subtraction method using image analysis software for postmortem coronary CT angiography. This method was devised based on preliminary experimental results showing that the most accurate subtraction was achieved using images reconstructed with a narrower field of view and bone kernel, resulting in higher spatial resolution. This subtraction method allowed evaluation of lumen patency and the degree of stenosis on contrast-enhanced images in a verification using actual specimens where evaluation of the lumen had been difficult because of high calcification. The results were morphologically similar to the macroscopic findings. This method allows more rapid and reliable lesion retrieval and is expected to be useful for postmortem coronary angiography in forensic practice.

Endothelial dysfunction and risk factors for atherosclerosis in psoriatic arthritis: overview and comparison with rheumatoid arthritis

Endothelial dysfunction (ED) is defined as an impairment in the vasodilatory, anti-thrombotic, and anti-inflammatory properties of the cells that make up the lining of blood vessels. ED is considered a key step in the development of atherosclerotic cardiovascular disease. The association between ED and systemic inflammatory diseases is well established. However, the prevalence and clinical significance of ED in psoriatic arthritis (PsA) have been investigated to a lesser extent. This review aims to explore the link between ED and PsA, including ED in macro- and microcirculation, as well as risk factors for its occurrence in PsA and its relationship with atherosclerosis in PsA. Furthermore, the ED in PsA was compared with that of rheumatoid arthritis (RA). Regarding ED in the microcirculation, the coronary flow reserve was found to be significantly reduced in individuals with PsA. The relationship between PsA and macrovascular ED is more pronounced, along with more advanced atherosclerosis detected in patients with PsA. These results are consistent with those obtained in RA studies. On the other hand, arterial stiffness and signs of vascular remodeling were found more frequently in RA than in PsA, with the potential role of efficient anti-TNF treatment in patients with PsA and psoriasis explaining this finding. The impact of ED on cardiovascular diseases and the burden of this risk caused independently by PsA have not yet been precisely established, however, this group of patients requires special attention with regard to cardiovascular events.

Ultra-high-resolution CT vs. invasive angiography for detecting hemodynamically significant coronary artery disease: Rationale and methods of the CORE-PRECISION multicenter study

BACKGROUND

Direct coronary arterial evaluation via computed tomography (CT) angiography is the most accurate noninvasive test for the diagnosis of coronary artery disease (CAD). However, diagnostic accuracy is limited in the setting of severe coronary calcification or stents. Ultra-high-resolution CT (UHR-CT) may overcome this limitation, but no rigorous study has tested this hypothesis.

METHODS

The CORE-PRECISION is an international, multicenter, prospective diagnostic accuracy study testing the non-inferiority of UHR-CT compared to invasive coronary angiography (ICA) for identifying patients with hemodynamically significant CAD. The study will enroll 150 patients with history of CAD, defined as prior documentation of lumen obstruction, stenting, or a calcium score ≥400, who will undergo UHR-CT before clinically prompted ICA. Assessment of hemodynamically significant CAD by UHR-CT and ICA will follow clinical standards. The reference standard will be the quantitative flow ratio (QFR) with <0.8 defined as abnormal. All data will be analyzed in independent core laboratories.

RESULTS

The primary outcome will be the comparative diagnostic accuracy of UHR-CT vs. ICA for detecting hemodynamically significant CAD on a patient level. Secondary analyses will focus on vessel level diagnostic accuracy, quantitative stenosis analysis, automated contour detection, in-depth plaque analysis, and others.

CONCLUSION

CORE-PRECISION aims to investigate if UHR-CT is non-inferior to ICA for detecting hemodynamically significant CAD in high-risk patients, including those with severe coronary calcification or stents. We anticipate this study to provide valuable insights into the utility of UHR-CT in this challenging population and for its potential to establish a new standard for CAD assessment.

Platelets in Vascular Calcification: A Comprehensive Review of Platelet-Derived Extracellular Vesicles, Protein Interactions, Platelet Function Indices, and their Impact on Cellular Crosstalk

Vascular calcification (VC) commonly accompanies the development of atherosclerosis, defined by the accumulation of calcium in the arterial wall, potentially leading to stroke and myocardial infarction. Severe and unevenly distributed calcification poses challenges for interventional procedures, elevating the risks of vascular dissection, acute vascular occlusion, restenosis, and other major adverse cardiovascular events. Platelets promote the development of atherosclerosis by secreting various inflammatory mediators, regulating cell migration, aggregation, adhesion, and initiating and expanding inflammatory responses. There is emerging evidence that platelets play a direct role in VC; however, this novel concept has not yet been critically assessed. This review describes the intricate mechanisms by which platelets promote VC, focusing on three key aspects and the potential opportunities for their therapeutic targeting: extracellular vesicles, platelet-regulatory proteins, and indices related to platelet function.

Challenges and Advances in Interventional Cardiology for Coronary Artery Disease Management

The development of percutaneous coronary intervention (PCI) has been one of the greatest advances in cardiology and has changed clinical practice for patients with coronary artery disease (CAD). Despite continuous improvements in operators' experience, techniques, and the development of new-generation devices, significant challenges remain in improving the efficacy of PCI, including calcification, bifurcation, multivascular disease, stent restenosis, and stent thrombosis, among others. The present review aims to provide an overview of the current status of knowledge of endovascular revascularization in CAD, including relevant trials, therapeutic strategies, and new technologies addressing particular scenarios that can impact the prognosis of this vulnerable population.

STress computed tomogRaphy perfusion and stress cArdiac magnetic resonance for ThE manaGement of suspected or known coronarY artery disease: resources and outcomes impact

BACKGROUND

The aim of this study is to describe resources and outcomes of coronary computed tomography angiography plus Stress CT perfusion (CCTA ​+ ​Stress-CTP) and stress cardiovascular magnetic resonance (Stress-CMR) in symptomatic patients with suspected or known CAD.

METHODS

Six hundred and twenty-four consecutive symptomatic patients with intermediate to high-risk pretest likelihood for CAD or previous history of revascularization referred to our hospital for clinically indicated CCTA ​+ ​Stress-CTP or Stress-CMR were enrolled. Stress-CTP scans were performed in 223 patients while 401 patients performed Stress-CMR. Patient follow-up was performed at 1 year after index test performance. Endpoints were all cardiac events, as a combined endpoint of revascularization, non-fatal MI and death, and hard cardiac events, as combined endpoint of non-fatal MI and death.

RESULTS

Twenty-nine percent of patients who underwent CCTA ​+ ​Stress-CTP received revascularization, 7% of subjects assessed with Stress-CMR were treated invasively, and a low number of non-fatal MI and death was observed with both strategies (hard events in 0.4% of patients that had CCTA ​+ ​Stress-CTP as index test, and in 3% of patients evaluated with Stress-CMR). According to the predefined endpoints, CCTA ​+ ​Stress-CTP group showed high rate of all cardiac events and low rate of hard cardiac events, respectively. The cumulative costs were 1970 ​± ​2506 Euro and 733 ​± ​1418 Euro for the CCTA ​+ ​Stress-CTP group and Stress-CMR group, respectively.

CONCLUSIONS

The use of CCTA ​+ ​Stress-CTP strategy was associated with high referral to revascularization but with a favourable trend in terms of hard cardiac events and diagnostic yield in identifying individuals at lower risk of adverse events despite the presence of CAD.

Hemodynamic influence of mild stenosis morphology in different coronary arteries: a computational fluid dynamic modelling study

Introduction: Mild stenosis [degree of stenosis (DS) < 50%] is commonly labeled as nonobstructive lesion. Some lesions remain stable for several years, while others precipitate acute coronary syndromes (ACS) rapidly. The causes of ACS and the factors leading to diverse clinical outcomes remain unclear. Method: This study aimed to investigate the hemodynamic influence of mild stenosis morphologies in different coronary arteries. The stenoses were modeled with different morphologies based on a healthy individual data. Computational fluid dynamics analysis was used to obtain hemodynamic characteristics, including flow waveforms, fractional flow reserve (FFR), flow streamlines, time-average wall shear stress (TAWSS), and oscillatory shear index (OSI). Results: Numerical simulation indicated significant hemodynamic differences among different DS and locations. In the 20%-30% range, significant large, low-velocity vortexes resulted in low TAWSS (<4 dyne/cm2) around stenoses. In the 30%-50% range, high flow velocity due to lumen area reduction resulted in high TAWSS (>40 dyne/cm2), rapidly expanding the high TAWSS area (averagely increased by 0.46 cm2) in left main artery and left anterior descending artery (LAD), where high OSI areas remained extensive (>0.19 cm2). Discussion: While mild stenosis does not pose any immediate ischemic risk due to a FFR > 0.95, 20%-50% stenosis requires attention and further subdivision based on location is essential. Rapid progression is a danger for lesions with 20%-30% DS near the stenoses and in the proximal LAD, while lesions with 30%-50% DS can cause plaque injury and rupture. These findings support clinical practice in early assessment, monitoring, and preventive treatment.

Optimizing Coronary Computed Tomography Angiography Using a Novel Deep Learning-Based Algorithm

Coronary computed tomography angiography (CCTA) is an essential part of the diagnosis of chronic coronary syndrome (CCS) in patients with low-to-intermediate pre-test probability. The minimum technical requirement is 64-row multidetector CT (64-MDCT), which is still frequently used, although it is prone to motion artifacts because of its limited temporal resolution and z-coverage. In this study, we evaluate the potential of a deep-learning-based motion correction algorithm (MCA) to eliminate these motion artifacts. 124 64-MDCT-acquired CCTA examinations with at least minor motion artifacts were included. Images were reconstructed using a conventional reconstruction algorithm (CA) and a MCA. Image quality (IQ), according to a 5-point Likert score, was evaluated per-segment, per-artery, and per-patient and was correlated with potentially disturbing factors (heart rate (HR), intra-cycle HR changes, BMI, age, and sex). Comparison was done by Wilcoxon-Signed-Rank test, and correlation by Spearman's Rho. Per-patient, insufficient IQ decreased by 5.26%, and sufficient IQ increased by 9.66% with MCA. Per-artery, insufficient IQ of the right coronary artery (RCA) decreased by 18.18%, and sufficient IQ increased by 27.27%. Per-segment, insufficient IQ in segments 1 and 2 decreased by 11.51% and 24.78%, respectively, and sufficient IQ increased by 10.62% and 18.58%, respectively. Total artifacts per-artery decreased in the RCA from 3.11 ± 1.65 to 2.26 ± 1.52. HR dependence of RCA IQ decreased to intermediate correlation in images with MCA reconstruction. The applied MCA improves the IQ of 64-MDCT-acquired images and reduces the influence of HR on IQ, increasing 64-MDCT validity in the diagnosis of CCS.

Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?

PURPOSE OF REVIEW

This review evaluates how Artificial Intelligence (AI) enhances atherosclerotic cardiovascular disease (ASCVD) risk assessment, allows for opportunistic screening, and improves adherence to guidelines through the analysis of unstructured clinical data and patient-generated data. Additionally, it discusses strategies for integrating AI into clinical practice in preventive cardiology.

RECENT FINDINGS

AI models have shown superior performance in personalized ASCVD risk evaluations compared to traditional risk scores. These models now support automated detection of ASCVD risk markers, including coronary artery calcium (CAC), across various imaging modalities such as dedicated ECG-gated CT scans, chest X-rays, mammograms, coronary angiography, and non-gated chest CT scans. Moreover, large language model (LLM) pipelines are effective in identifying and addressing gaps and disparities in ASCVD preventive care, and can also enhance patient education. AI applications are proving invaluable in preventing and managing ASCVD and are primed for clinical use, provided they are implemented within well-regulated, iterative clinical pathways.

Diagnostic Performance of On-Site Automatic Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve

BACKGROUND AND OBJECTIVES

Fractional flow reserve (FFR) is an invasive standard method to identify ischemia-causing coronary artery disease (CAD). With the advancement of technology, FFR can be noninvasively computed from coronary computed tomography angiography (CCTA). Recently, a novel simpler method has been developed to calculate on-site CCTA-derived FFR (CT-FFR) with a commercially available workstation.

METHODS

A total of 319 CAD patients who underwent CCTA, invasive coronary angiography, and FFR measurement were included. The primary outcome was the accuracy of CT-FFR for defining myocardial ischemia evaluated with an invasive FFR as a reference. The presence of ischemia was defined as FFR ≤0.80. Anatomical obstructive stenosis was defined as diameter stenosis on CCTA ≥50%, and the diagnostic performance of CT-FFR and CCTA stenosis for ischemia was compared.

RESULTS

Among participants (mean age 64.7±9.4 years, male 77.7%), mean FFR was 0.82±0.10, and 126 (39.5%) patients had an invasive FFR value of ≤0.80. The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CT-FFR were 80.6% (95% confidence interval [CI], 80.5-80.7%), 88.1% (95% CI, 82.4-93.7%), 75.6% (95% CI, 69.6-81.7%), 70.3% (95% CI, 63.1-77.4%), and 90.7% (95% CI, 86.2-95.2%), respectively. CT-FFR had higher diagnostic accuracy (80.6% vs. 59.1%, p<0.001) and discriminant ability (area under the curve from receiver operating characteristic curve 0.86 vs. 0.64, p<0.001), compared with anatomical obstructive stenosis on CCTA.

CONCLUSIONS

This novel CT-FFR obtained from an on-site workstation demonstrated clinically acceptable diagnostic performance and provided better diagnostic accuracy and discriminant ability for identifying hemodynamically significant lesions than CCTA alone.

Motion robust coronary MR angiography using zigzag centric ky-kz trajectory and high-resolution deep learning reconstruction

PURPOSE

To develop a new MR coronary angiography (MRCA) technique by employing a zigzag fan-shaped centric ky-kz k-space trajectory combined with high-resolution deep learning reconstruction (HR-DLR).

METHODS

All imaging data were acquired from 12 healthy subjects and 2 patients using two clinical 3-T MR imagers, with institutional review board approval. Ten healthy subjects underwent both standard 3D fast gradient echo (sFGE) and centric ky-kz k-space trajectory FGE (cFGE) acquisitions to compare the scan time and image quality. Quantitative measures were also performed for signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as sharpness of the vessel. Furthermore, the feasibility of the proposed cFGE sequence was assessed in two patients. For assessing the feasibility of the centric ky-kz trajectory, the navigator-echo window of a 30-mm threshold was applied in cFGE, whereas sFGE was applied using a standard 5-mm threshold. Image quality of MRCA using cFGE with HR-DLR and sFGE without HR-DLR was scored in a 5-point scale (non-diagnostic = 1, fair = 2, moderate = 3, good = 4, and excellent = 5). Image evaluation of cFGE, applying HR-DLR, was compared with sFGE without HR-DLR. Friedman test, Wilcoxon signed-rank test, or paired t tests were performed for the comparison of related variables.

RESULTS

The actual MRCA scan time of cFGE with a 30-mm threshold was acquired in less than 5 min, achieving nearly 100% efficiency, showcasing its expeditious and robustness. In contrast, sFGE was acquired with a 5-mm threshold and had an average scan time of approximately 15 min. Overall image quality for MRCA was scored 3.3 for sFGE and 2.7 for cFGE without HR-DLR but increased to 3.6 for cFGE with HR-DLR and (p < 0.05). The clinical result of patients obtained within 5 min showed good quality images in both patients, even with a stent, without artifacts. Quantitative measures of SNR, CNR, and sharpness of vessel presented higher in cFGE with HR-DLR.

CONCLUSION

Our findings demonstrate a robust, time-efficient solution for high-quality MRCA, enhancing patient comfort and increasing clinical throughput.

Impact of minimal lumen segmentation uncertainty on patient-specific coronary simulations: A look at FFRCT

We examined the effect of minimal lumen segmentation uncertainty on Fractional Flow Reserve obtained from Coronary Computed Tomography AngiographyFFR CT . A total of 14 patient-specific coronary models with different stenosis locations and degrees of severity were enrolled in this study. The optimal segmented coronary lumens were disturbed using intra± 6 % and inter-operator± 15 % variations on the segmentation threshold.FFR CT was evaluated in each case by 3D-OD CFD simulations. The findings suggest that the sensitivity ofFFR CT to this type of uncertainty increases distally and with the stenosis severity. Cases with moderate or severe distal coronary lesions should undergo either exact and thorough segmentation operations or invasive FFR measurements, particularly if theFFR CT is close to the cutoff (0.80). Therefore, we conclude that it is crucial to consider the lesion's location and degree of severity when evaluatingFFR CT results.

Cardiac CT: Competition, complimentary or confounder

Coronary CT angiography (CCTA) has been gradually adopted into clinical practice over the last two decades. CCTA has high diagnostic accuracy, prognostic value, and unique features such as assessment of plaque composition. CCTA-derived functional assessment techniques such as fractional flow reserve and CT perfusion are also available and can increase the diagnostic specificity of the modality. These properties propound CCTA as a competitor of functional testing in diagnosis of obstructive CAD, however, utilizing CCTA in a concomitant fashion to potentiate the performance of the latter can lead to better patient care and may provide more accurate prognostic information. Although multiple diagnostic challenges such as evaluation of calcified segments, stents, and small distal vessels still exist, the technologic developments in hardware as well as growing incorporation of artificial intelligence to daily practice are all set to augment the diagnostic and prognostic role of CCTA in cardiovascular disorders.

Prognostic value of metabolic dysfunction-associated steatotic liver disease over coronary computed tomography angiography findings: comparison with no-alcoholic fatty liver disease

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the proposed name change for non-alcoholic fatty liver disease (NAFLD). This study aimed to investigate the association of cardiovascular disease risk with MASLD and NAFLD in patients who underwent clinically indicated coronary computed tomography angiography (CCTA).

METHODS

This retrospective study included 2289 patients (60% men; mean age: 68 years) with no history of coronary artery disease who underwent CCTA. The steatotic liver was defined as a hepatic-to-spleen attenuation ratio of < 1.0 on CT just before CCTA. MASLD is defined as the presence of hepatic steatosis along with at least one of the five cardiometabolic risk factors. Adverse CCTA findings were defined as obstructive and/or high-risk plaques. Major adverse cardiac events (MACE) encompassed composite coronary events, including cardiovascular death, acute coronary syndrome, and late coronary revascularization.

RESULTS

MASLD and NAFLD were identified in 415 (18%) and 368 (16%) patients, respectively. Adverse CCTA findings were observed in 40% and 38% of the patients with MASLD and with NAFLD, respectively. Adverse CCTA findings were significantly associated with MASLD (p = 0.007) but not NAFLD (p = 0.253). During a median follow-up of 4.4 years, 102 (4.4%) MACE were observed. MASLD was significantly associated with MACE (hazard ratio 1.82, 95% CI 1.18-2.83, p = 0.007), while its association with NAFLD was not significant (p = 0.070). By incorporating MASLD into a prediction model of MACE, including the risk score and adverse CCTA findings, global chi-squared values significantly increased from 87.0 to 94.1 (p = 0.008).

CONCLUSIONS

Patients with MASLD are likely to have a higher risk of cardiovascular disease than those with NAFLD. Concurrent assessment of MASLD during CCTA improves the identification of patients at a higher risk of cardiovascular disease among those with clinically indicated CCTA.

Value of Dynamic Computed Tomography Myocardial Perfusion in CAD: A Systematic Review and Meta-analysis

AIMS

Dynamic stress computed tomography (CT) perfusion is a non-invasive method for quantifying myocardial ischemia by assessing myocardial blood flow (MBF). In this meta-analysis, we evaluated the diagnostic accuracy of dynamic CT perfusion for the detection of significant coronary artery disease (CAD) across various CT scanners, obese patients, and its prognostic value.

METHODS AND RESULTS

We systematically searched PubMed, Embase, Web of Science, and Cochrane library for published studies evaluating the accuracy of CT myocardial perfusion in diagnosing functional significant ischemia by invasive fractional flow reserve. The diagnostic performance of dynamic CT perfusion in detecting ischemia was evaluated using a summary receiver operating characteristic (sROC) curve. A total of 23 studies underwent meta- analysis. In myocardial region without ischemia, MBF was measured at 1.44 ml/min/g (95% confidence interval [CI]: 1.13-1.75), while in region with ischemia, it was 0.94 ml/min/g (95% CI: 0.80-1.08) (p<0.001). On the patient-based analysis, the area under the sROC curve of CT-MBF was 0.93, with a sensitivity of 0.84 and specificity of 0.88. Differences in CT type (dual source vs. single source), and body mass index (BMI) did not significantly affect the diagnostic performance. The pooled hazard ratio of dynamic CT perfusion for predicting adverse events was 4.98 (95%CI: 2.08-11.93, p=<0.001, I2=61%, p for heterogeneity = 0.07).

CONCLUSIONS

Dynamic CT perfusion has high diagnostic performance in the quantitative assessment of ischemia and detection of functional myocardial ischemia as defined by invasive FFR, and may be useful in risk stratification of CAD patients.

Impact of coronary artery disease in patients with hypertrophic cardiomyopathy

BACKGROUND

Atherosclerotic coronary artery disease (CAD) often occurs concurrently with hypertrophic cardiomyopathy (HCM). However, the influence of concomitant CAD has not been fully assessed in patients with HCM.

METHODS

Invasive or computed tomography coronary angiography was performed in 461 patients with HCM at our hospital to determine the presence and severity of CAD from March 2010 to April 2022. The primary end points were all-cause, cardiovascular, and sudden cardiac deaths. The survival of HCM patients with severe CAD was compared with that of HCM patients without severe CAD.

RESULTS

Of 461 patients with HCM, 235 had concomitant CAD. During the median (interquartile range) follow-up of 49 (31-80) months, 75 patients (16.3%) died. The 5-year survival estimates were 64.3%, 82.5%, and 86.0% for the severe, mild-to-moderate, and no-CAD groups, respectively (log-rank, p = 0.010). Regarding the absence of cardiovascular death, the 5-year survival estimates were 68.5% for patients with severe CAD, 86.4% for patients with mild-to-moderate CAD, and 90.2% for HCM patients with no CAD (log-rank, p = 0.001). In multivariate analyses, severe CAD was associated with all-cause and cardiovascular death after adjusting for age, left ventricular ejection fraction, hypertension, and atrial fibrillation.

CONCLUSIONS

This study showed a worse prognosis among HCM patients with severe CAD than among HCM patients without severe CAD. Therefore, timely recognition of severe CAD in HCM patients and appropriate treatment are important.

IgG4-Related disease with diffuse myopericardial involvement- value of CMR: a case report and literature review of cardiac involvement

BACKGROUND

IgG4-related disease is a fibro-inflammatory disorder with an unknown etiology, which can affect multiple organ systems, including the cardiovascular system. While most reported cases of cardiovascular involvement are primarily associated with the aorta, there have been sporadic reports of isolated cardiac involvement.

CASE PRESENTATION

This paper presents a documented case of IgG4-related systemic disease with symptoms indicative of restrictive cardiomyopathy. Subsequent Cardiac Magnetic Resonance imaging revealed diffuse myopericardial involvement, characterized by pericardial thickening and enhancement, accompanied by subepicardial and myocardial infiltration. Considering the rarity of cardiac involvement in our case, we conducted a thorough review of the existing literature pertaining to various patterns of cardiac involvement in IgG4-related disease, as well as the diagnostic modalities that can be employed for accurate identification and assessment.

CONCLUSIONS

This case report sheds light on the importance of recognizing and evaluating cardiac manifestations in IgG4-related systemic disease to facilitate timely diagnosis and appropriate management.

Halved contrast medium dose coronary dual-layer CT-angiography - phantom study of tube current and patient characteristics

Virtual mono-energetic images (VMI) using dual-layer computed tomography (DLCT) enable substantial contrast medium (CM) reductions. However, the combined impact of patient size, tube voltage, and heart rate (HR) on VMI of coronary CT angiography (CCTA) remains unknown. This phantom study aimed to assess VMI levels achieving comparable contrast-to-noise ratio (CNR) in CCTA at 50% CM dose across varying tube voltages, patient sizes, and HR, compared to the reference protocol (100% CM dose, conventional at 120 kVp). A 5 mm artificial coronary artery with 100% (400 HU) and 50% (200 HU) iodine CM-dose was positioned centrally in an anthropomorphic thorax phantom. Horizontal coronary movement was matched to HR (at 0, < 60, 60-75, > 75 bpm), with varying patient sizes simulated using phantom extension rings. Raw data was acquired using a clinical CCTA protocol at 120 and 140 kVp (five repetitions). VMI images (40-70 keV, 5 keV steps) were then reconstructed; non-overlapping 95% CNR confidence intervals indicated significant differences from the reference. Higher CM-dose, reduced VMI, slower HR, higher tube voltage, and smaller patient sizes demonstrated a trend of higher CNR. Regardless of HR, patient size, and tube voltage, no significant CNR differences were found compared to the reference, with 100% CM dose at 60 keV, or 50% CM dose at 40 keV. DLCT reconstructions at 40 keV from 120 to 140 kVp acquisitions facilitate 50% CM dose reduction for various patient sizes and HR with equivalent CNR to conventional CCTA at 100% CM dose, although clinical validation is needed.

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.

Intra-individual comparison of coronary CT angiography-based FFR between energy-integrating and photon-counting detector CT systems

BACKGROUND

Coronary computed tomography angiography (CCTA)-based fractional flow reserve (CT-FFR) allows for noninvasive determination of the functional severity of anatomic lesions in patients with coronary artery disease. The aim of this study was to intra-individually compare CT-FFR between photon-counting detector (PCD) and conventional energy-integrating detector (EID) CT systems.

METHODS

In this single-center prospective study, subjects who underwent clinically indicated CCTA on an EID-CT system were recruited for a research CCTA on PCD-CT within 30 days. Image reconstruction settings were matched as closely as possible between EID-CT (Bv36 kernel, iterative reconstruction strength level 3, slice thickness 0.5 mm) and PCD-CT (Bv36 kernel, quantum iterative reconstruction level 3, virtual monoenergetic level 55 keV, slice thickness 0.6 mm). CT-FFR was measured semi-automatically using a prototype on-site machine learning algorithm by two readers. CT-FFR analysis was performed per-patient and per-vessel, and a CT-FFR ≤ 0.75 was considered hemodynamically significant.

RESULTS

A total of 22 patients (63.3 ± 9.2 years; 7 women) were included. Median time between EID-CT and PCD-CT was 5.5 days. Comparison of CT-FFR values showed no significant difference and strong agreement between EID-CT and PCD-CT in the per-vessel analysis (0.88 [0.74-0.94] vs. 0.87 [0.76-0.93], P = 0.096, mean bias 0.02, limits of agreement [LoA] -0.14/0.19, r = 0.83, ICC = 0.92), and in the per-patient analysis (0.81 [0.60-0.86] vs. 0.76 [0.64-0.86], P = 0.768, mean bias 0.02, LoA -0.15/0.19, r = 0.90, ICC = 0.93). All included patients were classified into the same category (CT-FFR > 0.75 vs ≤0.75) with both CT systems.

CONCLUSIONS

CT-FFR evaluation is feasible with PCD-CT and it shows a strong agreement with EID-CT-based evaluation when images are similarly reconstructed.

Clinical Outcomes Based on Coronary Computed Tomography-Derived Fractional Flow Reserve and Plaque Characterization

BACKGROUND

Coronary computed tomography angiography (CTA) followed by computed tomography angiography-derived fractional flow reserve (FFRCT) is now commonly used for the management of chronic coronary syndrome (CCS). CTA-verified high-risk plaque (HRP) characteristics have also been reported to be associated with a greater likelihood of adverse cardiac events but have not been used for management decisions.

OBJECTIVES

The aim of this study was to evaluate clinical outcomes based on a combination of point-of-care computed tomography angiography-derived fractional flow reserve (POC-FFRCT) and the presence of HRP in CCS patients initially treated medically or with revascularization based on invasive coronary angiography findings.

METHODS

CTA was performed as the initial test in 5,483 patients presenting with CCS between September 2015 and December 2020 followed by invasive coronary angiography and revascularization as necessary. POC-FFRCT assessment and HRP characterization were obtained subsequently in 745 consecutive patients. We investigated how HRP and POC-FFRCT, which were not available during the original clinical decision making, correlated with the endpoint defined as a composite of cardiac death, acute coronary syndrome, and a need for unplanned revascularization.

RESULTS

Cardiac events occurred in 20 patients (2.7%) during a median follow-up of 744 days. The event rate was significantly higher in patients with POC-FFRCT <0.80 compared with POC-FFRCT ≥0.8 (5.4 vs 0.5 per 100 vessel years; log-rank P < 0.0001) and in patients with HRP compared to those without HRP (3.6 vs 0.8 per 100 vessel years; log-rank P = 0.0001). POC-FFRCT <0.80 and the presence of HRP were the independent predictors of cardiac events (HR: 16.67; 95% CI: 2.63-105.39; P = 0.002) compared with POC-FFRCT ≥0.8 and absent HRP. For the vessels with POC-FFRCT <0.80 and HRP, a significantly higher rate of adverse events was observed in patients who did not undergo revascularization compared with those revascularized (16.4 vs 1.4 per 100 vessel years; log-rank P = 0.006).

CONCLUSIONS

POC-FFRCT <0.80 and the presence of HRP were the independent predictors of cardiac events, and revascularization of HRP lesions with abnormal POC-FFRCT was associated with a lower event rate.

Noninvasive Coronary Physiological Assessment Derived From Computed Tomography

Identifying functional significance using physiological indexes is a standard approach in decision-making for treatment strategies in patients with coronary artery disease. Recently, coronary computed tomography angiography-based physiological assessments, such as computed tomography perfusion and fractional flow reserve derived from coronary computed tomography angiography (FFR-CT), have emerged. These methods have provided incremental diagnostic values for ischemia-causing lesions over anatomical stenosis defined solely by coronary computed tomography angiography. Clinical data have demonstrated their prognostic value in the prediction of adverse cardiovascular events. Several randomized controlled studies have shown that clinical use of FFR-CT can reduce unnecessary invasive procedures compared to usual care. Recent studies have also expanded the role of FFR-CT in defining target lesions for revascularization by acquiring noninvasive lesion-specific hemodynamic indexes like ΔFFR-CT. This review encompasses the current evidence of the diagnostic and prognostic performance of computed tomography-based physiological assessment in defining ischemia-causing lesions and adverse cardiac events, its clinical impact on treatment decision-making, and implications for revascularization.

Frequency of extracardiac findings on "negative" CT coronary angiography studies

AIM

To evaluate the prevalence and nature of extracardiac findings identified on computed tomography (CT) coronary angiography (CTCA) in patients with chest pain but without evidence of coronary artery disease (CAD).

MATERIALS AND METHODS

CTCA studies in patients referred to the hospital between January 2017 to February 2021 with chest pain and a suspected diagnosis of CAD were reviewed retrospectively for the presence of extracardiac findings. Consensus review of CTCA studies was performed by two experienced thoracic radiologists. The presence and severity of extracardiac findings, together with the likelihood that chest pain might be attributed to these, was recorded. Patient records were reviewed to ascertain the recording of extracardiac findings on initial CTCA reports and, where applicable, the nature of the follow-up.

RESULTS

Extracardiac findings (n=210) were present in 110/180 patients (61%) with a mean of 1.9 findings per patient. Extracardiac findings were more prevalent in patients aged ≥65 years compared to those <65 years (p<0.001). At least one extracardiac finding with the potential to cause chest pain was present in 40 patients (22%): degenerative disc disease (n=23 [13%]) and hiatus hernia (n=6 [3.3%]) were the most common extracardiac findings. Only 37.6% (79) of all retrospectively identified findings had been initially reported and, of these, 12.7% (10) required further follow-up.

CONCLUSION

Extracardiac findings are common in patients with no evidence of CAD on CTCA. The entire dataset should be evaluated for the presence of extracardiac findings that could explain chest pain symptoms on wide field of view reconstructions.

On-site CT-derived cFFR in patients with suspected coronary artery disease: Feasibility on a 128-row CT scanner in everyday clinical practice

PURPOSE

 Technical feasibility of CT-based calculation of fractional flow reserve (cFFR) using a 128-row computed tomography scanner in an everyday routine setting. Post-processing and everyday practicability should be analyzed on the scanner on-site in connection with clinical parameters.

MATERIALS AND METHODS

 This single-center retrospective analysis included 230 patients (74 female; mean age 63.8 years) with CCTA within 21 months between 01/2018 and 09/2019 without non-pathological examinations. cFFR values were obtained using a deep learning-based non-commercial research prototype (cFFR Version3.5.0; Siemens Healthineers GmbH, Erlangen). cFFR values were evaluated at two points: at the maximum point of the stenosis and 1.0 cm distal to the stenosis. Comparison with invasive coronary angiography in 57/230 patients (24.7 %) was performed. CT parameters and quality were evaluated. Further subgroup classification concerning criteria of technical postprocessing was performed: no changes necessary, minor corrections necessary, major corrections necessary, and no evaluation was possible. The required time from starting the software to the final result was evaluated.

RESULTS

 A total of 116/448 (25.9 %) mild, 223/448 (49.8 %) moderate, and 109/448 (24.3 %) obstructive stenoses was found. The mean cFFR at the maximum point of the stenosis was 0.92 ± 0.09 and significantly higher than the cFRR value of 0.89 ± 0.13 distal to the stenosis (p < 0.001*). The mean degree of stenosis was 44.02 ± 26.99 % (range: 1-99 %) with an area of 5.39 ± 3.30 mm2. In a total of 45 patients (19.1 %), a relevant reduction in cFFR below 0.80 was determined. Overall, in 57/230 patients (24.8 %), catheter angiography was performed. No significant difference in the degree of maximal stenosis (CAD-RADS 0-2/3/4) was detected between the classification of CCTA and ICA (p = 0.171). The mean post-processing time varied significantly with 8.34 ± 4.66 min. in single-vessel CAD vs. 12.91 ± 3.92 min. in two-vessel CAD vs. 21.80 ± 5.94 min. in three-vessel CAD (each p < 0.001).

CONCLUSION

 Noninvasive onsite quantification of cFFR is feasible with minimal observer interaction in a routine real-world setting on a 128-row scanner. Deep learning-based algorithms allow a robust and semi-automatic on-site determination of cFFR based on data from standard CT scanners.

KEY POINTS

· Non-invasive on-site quantification of cFFR is feasible with minimal observer interaction.. · Deep-learning based algorithms allow robust and semi-automatic on-site determination of cFFR.. · The mean follow-up time varied significantly with the extent of vascular CAD..

Artificial intelligence evaluation of coronary computed tomography angiography for coronary stenosis classification and diagnosis

BACKGROUND

Ruling out obstructive coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) is time-consuming and challenging. This study developed a deep learning (DL) model to assist in detecting obstructive CAD on CCTA to streamline workflows.

METHODS

In total, 2929 DICOM files and 7945 labels were extracted from curved planar reformatted CCTA images. A modified Inception V3 model was adopted. To validate the artificial intelligence (AI) model, two cardiologists labelled and adjudicated the classification of coronary stenosis on CCTA. The model was trained to differentiate the coronary artery into binary stenosis classifications <50% and ≥50% stenosis. Using the quantitative coronary angiography (QCA) consensus results as a reference standard, the performance of the AI model and CCTA radiology readers was compared by calculating Cohen's kappa coefficients at patient and vessel levels. The net reclassification index was used to evaluate the net benefit of the DL model.

RESULTS

The diagnostic accuracy of the AI model was 92.3% and 88.4% at the patient and vessel levels, respectively. Compared with CCTA radiology readers, the AI model had a better agreement for binary stenosis classification at both patient and vessel levels (Cohen kappa coefficient: .79 vs. .39 and .77 vs. .40, p < .0001). The AI model also exhibited significantly improved model discrimination and reclassification (Net reclassification index = .350; Z = 4.194; p < .001).

CONCLUSIONS

The developed AI model identified obstructive CAD, and the model results correlated well with QCA results. Incorporating the model into the reporting system of CCTA may improve workflows.

Artificial Intelligence-based Coronary Stenosis Quantification at Coronary CT Angiography versus Quantitative Coronary Angiography

Purpose To evaluate the performance of a new artificial intelligence (AI)-based tool by comparing the quantified stenosis severity at coronary CT angiography (CCTA) with a reference standard derived from invasive quantitative coronary angiography (QCA). Materials and Methods This secondary, post hoc analysis included 120 participants (mean age, 59.7 years ± 10.8 [SD]; 73 [60.8%] men, 47 [39.2%] women) from three large clinical trials (AFFECTS, P3, REFINE) who underwent CCTA and invasive coronary angiography with QCA. Quantitative analysis of coronary stenosis severity at CCTA was performed using an AI-based coronary stenosis quantification (AI-CSQ) software service. Blinded comparison between QCA and AI-CSQ was measured on a per-vessel and per-patient basis. Results The per-vessel AI-CSQ diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 80%, 88%, 86%, 65%, and 94%, respectively, for diameter stenosis (DS) 50% or greater; and 78%, 92%, 91%, 47%, and 98%, respectively, for DS 70% or greater. The areas under the receiver operating characteristic curve (AUCs) to predict DS of 50% or greater and 70% or greater on a per-vessel basis were 0.92 (95% CI: 0.88, 0.95; P < .001) and 0.93 (95% CI: 0.89, 0.97; P < .001), respectively. The AUCs to predict DS of 50% or greater and 70% or greater on a per-patient basis were 0.93 (95% CI: 0.88, 0.97; P < .001) and 0.88 (95% CI: 0.81, 0.94; P < .001), respectively. Conclusion AI-CSQ at CCTA demonstrated a high diagnostic performance compared with QCA both on a per-patient and per-vessel basis, with high sensitivity for stenosis detection. Keywords: CT Angiography, Cardiac, Coronary Arteries Supplemental material is available for this article. Published under a CC BY 4.0 license.

Machine Learning in Invasive and Noninvasive Coronary Angiography

PURPOSE OF REVIEW

The objective of this review is to shed light on the transformative potential of machine learning (ML) in coronary angiography. We aim to understand existing developments in using ML for coronary angiography and discuss broader implications for the future of coronary angiography and cardiovascular medicine.

RECENT FINDINGS

The developments in invasive and noninvasive imaging have revolutionized diagnosis and treatment of coronary artery disease (CAD). However, CAD remains underdiagnosed and undertreated. ML has emerged as a powerful tool to further improve image analysis, hemodynamic assessment, lesion detection, and predictive modeling. These advancements have enabled more accurate identification of CAD, streamlined workflows, reduced the need for invasive diagnostic procedures, and improved the diagnostic value of invasive procedures when they are needed. Further integration of ML with coronary angiography will advance the prevention, diagnosis, and treatment of CAD. The integration of ML with coronary angiography is ushering in a new era in cardiovascular medicine. We highlight five use cases to leverage ML in coronary angiography: (1) improvement of quality and efficacy, (2) characterization of plaque, (3) hemodynamic assessment, (4) prediction of future outcomes, and (5) diagnosis of non-atherosclerotic coronary disease.

Resting echocardiographic parameters can exclude significant coronary artery disease: A comparison with coronary computed tomography angiography

INTRODUCTION

Coronary computed tomography angiography (CCTA) is known to have a high negative predictive value (NPV) in identifying coronary artery disease (CAD). This study aimed to examine whether resting echocardiographic parameters could exclude significant CAD on CCTA.

METHODS

We recruited 142 patients who had undergone both CCTA and echocardiography within a 3-month window. Based on the CCTA findings, patients were divided into two groups: Group A (non-significant CAD, defined as all coronary segments having <50% stenosis) and Group B (significant CAD). Resting echocardiographic parameters were compared between the two groups to identify predictors of non-significant CAD on CCTA.

RESULTS

A total 92 patients (mean age, 68 ± 13 years; males, 62%) were eligible for this study; 50 in Group A and 42 in Group B. Among the various echo parameters, left atrial volume index (LAVI) and left ventricular (LV) global longitudinal strain (GLS) were significantly lower in Group A (23.5 ± 7.6 vs. 33.6 ± 7.4 mL/m2 , p < .001; -20.2 ± 1.8% vs. -16.8 ± 2.0%, p < .001, respectively). Analysis of the receiver operating characteristic curve revealed that the cutoff value to exclude significant CAD on CCTA was 29.0 mL/m2 for LAVI (NPV 80.8%) and -18.1% for GLS (NPV 80.7%). The NPV increased to 95.0% when these parameters were combined (LAVI < 29.0 mL/m2 and GLS < -18.1%).

CONCLUSION

The combination of resting LAVI and GLS was clinically useful in excluding significant CAD via CCTA.

Deep Learning-based Prediction of Percutaneous Recanalization in Chronic Total Occlusion Using Coronary CT Angiography

Background CT is helpful in guiding the revascularization of chronic total occlusion (CTO), but manual prediction scores of percutaneous coronary intervention (PCI) success have challenges. Deep learning (DL) is expected to predict success of PCI for CTO lesions more efficiently. Purpose To develop a DL model to predict guidewire crossing and PCI outcomes for CTO using coronary CT angiography (CCTA) and evaluate its performance compared with manual prediction scores.

MATERIALS AND METHODS

Participants with CTO lesions were prospectively identified from one tertiary hospital between January 2018 and December 2021 as the training set to develop the DL prediction model for PCI of CTO, with fivefold cross validation. The algorithm was tested using an external test set prospectively enrolled from three tertiary hospitals between January 2021 and June 2022 with the same eligibility criteria. All participants underwent preprocedural CCTA within 1 month before PCI. The end points were guidewire crossing within 30 minutes and PCI success of CTO.

Results A total of 534 participants (mean age, 57.7 years ± 10.8 [SD]; 417 [78.1%] men) with 565 CTO lesions were included. In the external test set (186 participants with 189 CTOs), the DL model saved 85.0% of the reconstruction and analysis time of manual scores (mean, 73.7 seconds vs 418.2-466.9 seconds) and had higher accuracy than manual scores in predicting guidewire crossing within 30 minutes (DL, 91.0%; CT Registry of Chronic Total Occlusion Revascularization, 61.9%; Korean Multicenter CTO CT Registry [KCCT], 68.3%; CCTA-derived Multicenter CTO Registry of Japan (J-CTO), 68.8%; P < .05) and PCI success (DL, 93.7%; KCCT, 74.6%; J-CTO, 75.1%; P < .05). For DL, the area under the receiver operating characteristic curve was 0.97 (95% CI: 0.89, 0.99) for the training test set and 0.96 (95% CI: 0.90, 0.98) for the external test set. Conclusion The DL prediction model accurately predicted the percutaneous recanalization outcomes of CTO lesions and increased the efficiency of noninvasively grading the difficulty of PCI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Pundziute-do Prado in this issue.

Preventative Imaging with Coronary Computed Tomography Angiography

PURPOSE OF REVIEW

Coronary computed tomography angiography (CCTA) is the diagnostic modality of choice for patients with stable chest pain. In this review, we scrutinize the evidence on the use of CCTA for the screening of asymptomatic patients.

RECENT FINDINGS

Clinical evidence suggests that CCTA imaging enhances cardiovascular risk stratification and prompts the timely initiation of preventive treatment leading to reduced risk of major adverse coronary events. Visualization of coronary plaques by CCTA also helps patients to comply with preventive medications. The presence of non-obstructive plaques and total plaque burden are prognostic for cardiovascular events. High-risk plaque features and pericoronary fat attenuation index, enrich the prognostic output of CCTA on top of anatomical information by capturing information on plaque vulnerability and coronary inflammatory burden. Timely detection of atherosclerotic disease or coronary inflammation by CCTA can assist in the deployment of targeted preventive strategies and novel therapeutics to prevent cardiovascular disease.

Predictive value of machine learning algorithm of coronary artery calcium score and clinical factors for obstructive coronary artery disease in hypertensive patients

BACKGROUND

The addition of coronary artery calcium score (CACS) to prediction models has been verified to improve performance. Machine learning (ML) algorithms become important medical tools in an era of precision medicine, However, combined utility by CACS and ML algorithms in hypertensive patients to forecast obstructive coronary artery disease (CAD) on coronary computed tomography angiography (CCTA) is rare.

METHODS

This retrospective study was composed of 1,273 individuals with hypertension and without a history of CAD, who underwent dual-source computed tomography evaluation. We applied five ML algorithms, coupled with clinical factors, imaging parameters, and CACS to construct predictive models. Moreover, 80% individuals were randomly taken as a training set on which 5-fold cross-validation was done and the remaining 20% were regarded as a validation set.

RESULTS

16.7% (212 out of 1,273) of hypertensive patients had obstructive CAD. Extreme Gradient Boosting (XGBoost) posted the biggest area under the receiver operator characteristic curve (AUC) of 0.83 in five ML algorithms. Continuous net reclassification improvement (NRI) was 0.55 (95% CI (0.39-0.71), p < 0.001), and integrated discrimination improvement (IDI) was 0.04 (95% CI (0.01-0. 07), p = 0.0048) when the XGBoost model was compared with traditional Models. In the subgroup analysis stratified by hypertension levels, XGBoost still had excellent performance.

CONCLUSION

The ML model incorporating clinical features and CACS may accurately forecast the presence of obstructive CAD on CCTA among hypertensive patients. XGBoost is superior to other ML algorithms.

Impact of visceral fat on coronary artery disease as defined by quantitative computed tomography angiography

OBJECTIVE

Obesity is associated with all-cause mortality and cardiovascular disease (CVD). Visceral fat (VF) is an important CVD risk metric given its independent correlation with myocardial infarction and stroke. This study aims to clarify the relationship between the presence and severity of VF with the presence and severity of coronary artery plaque.

METHODS

In 145 consecutive asymptomatic patients, atherosclerosis imaging-quantitative computed tomography was performed for total plaque volume (TPV) and percentage atheroma volume, as well as the volume of noncalcified plaque (NCP), calcified plaque, and low-density NCP (LD-NCP), diameter stenosis, and vascular remodeling. This study also included VF analysis and subcutaneous fat analysis, recording of outer waist circumference, and percentage body fat analysis.

RESULTS

The mean age of the patients was 56.1 [SD 8.5] years, and 84.0% were male. Measures of visceral adiposity (mean [SD, Q1-Q3 thresholds]) included estimated body fat, 28.7% (9.0%, 24.1%-33.0%); VF, 169.8 cm2 (92.3, 102.0-219.0 cm2 ); and subcutaneous fat, 223.6 mm2 (114.2, 142.5-288.0 mm2 ). The Spearman correlation coefficients of VF and plaque volume included TPV 0.22 (p = 0.0074), calcified plaque 0.12 (p = 0.62), NCP 0.25 (p = 0.0023), and LD-NCP 0.37 (p < 0.0001). There was a progression of the median coronary plaque volume for each quartile of VF including TPV (Q1: 19.8, Q2: 48.1, Q3: 86.4, and Q4: 136.6 mm3 [p = 0.0098]), NCP (Q1: 15.7, Q2: 35.4, Q3: 86.4, and Q4: 136.6 mm3 [p = 0.0032]), and LD-NCP (Q1: 0.6, Q2: 0.81, Q3: 2.0, and Q4: 5.0 mm3 [p < 0.0001]).

CONCLUSIONS

These findings demonstrate progression with regard to VF and TPV, NCP volume, and LD-NCP volume. Notably, there was a progression of VF and amount of LD-NCP, which is known to be high risk for future cardiovascular events. A consistent progression may indicate the future utility of VF in CVD risk stratification.

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

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

The Relationship between Circulating APOA-1 and Atherosclerosis Initiation and Progression in Psoriasis

APOA-1 is central to the high-density lipoprotein function of reverse cholesterol transport measured by cholesterol efflux capacity. Psoriasis is a systemic inflammatory disease associated with poor cholesterol efflux capacity and accelerated noncalcified coronary burden (NCB) as measured by coronary computed tomographic angiography. In this study, we characterized the relationship between APOA-1, cholesterol efflux capacity, and progression of NCB over 4 years. Consecutively recruited participants with psoriasis underwent coronary computed tomographic angiography for NCB quantification (Medis QAngio, Leiden, The Netherlands) at baseline (n = 310) and at four years (n = 124). Blood was assessed for cardiometabolic biomarkers. The lowest quartile of APOA-1 was associated with cardiometabolic blood markers (insulin, homeostatic model assessment for insulin resistance, and cholesterol efflux capacity) and higher NCB (P < 0.001). The low APOA-1 quartile had higher NCB at 4 years (β = -0.36, P = 0.02) in fully adjusted models. Finally, a 10-unit decrease of APOA-1 was associated with a 16% increase in NCB progression over 4 years (OR = 0.83, 95% confidence interval = 0.70-0.99, P = 0.04). In addition to being associated with cardiometabolic disease, low APOA-1 was associated with more NCB over time. These findings show that low APOA-1 is correlated with initiation and progression of coronary artery disease and may have clinical utility in identifying high-risk populations for development of cardiovascular disease.

Emerging Roles for Artificial Intelligence in Heart Failure Imaging

Artificial intelligence (AI) applications are expanding in cardiac imaging. AI research has shown promise in workflow optimization, disease diagnosis, and integration of clinical and imaging data to predict patient outcomes. The diagnostic and prognostic paradigm of heart failure is heavily reliant on cardiac imaging. As AI becomes increasingly validated and integrated into clinical practice, AI influence on heart failure management will grow. This review discusses areas of current research and potential clinical applications in AI as applied to heart failure cardiac imaging.

Detection of Endoleaks Following Thoracic and Abdominal Aortic Endovascular Aortic Repair-: A Comparison of Standard and Dynamic 4D-Computed Tomography Angiography

PURPOSE

Endoleaks are a common complication after endovascular aortic repair (EVAR) and thoracic endovascular aortic repair (TEVAR). The detection and correct classification of endoleaks is essential for the further treatment of affected patients. However, standard computed tomography angiography (CTA) provides no hemodynamic information on endoleaks, which can result in misclassification in complex cases. The aim of this study was to compare standard CTA (sCTA) with dynamic, dual-energy CTA (dCTA) for detection and classification of endoleaks following EVAR or TEVAR.

MATERIALS AND METHODS

This retrospective evaluation compared 69 sCTA diagnostic examinations performed on 50 different patients with 89 dCTA diagnostic examinations performed on 69 different patients.

RESULTS

In total, 15.9% of sCTA examinations and 49.4% of dCTA examinations led to the detection of endoleaks. With sCTA, 20.0% of patients were diagnosed with endoleaks, while with dCTA, 37.7% of patients were diagnosed with endoleaks. With sCTA, mainly Type 1 endoleaks were detected, whereas, with dCTA, the types of detected endoleaks were more evenly distributed. In comparison with the literature, the frequencies of endoleak types detected with dCTA better reflect the natural distribution than the frequencies detected with standard CTA.

CONCLUSION

Based on the retrospective comparative evaluation, dCTA could pose a valuable supplementary diagnostic tool resulting in a more accurate and realistic detection and classification of suspected endoleaks.

Could Plasma CXCL12 Predict Ventricular Dysfunction in Patients with Severe Myocardial Infarction?

Plasma level of chemokine CXCL12 can predict adverse cardiovascular outcomes in patients with coronary artery disease, but data on its relationship with severity of coronary stenosis in cases of severe myocardial infarction (MI) are scarce and conflicting. The objective of this study was to investigate link between plasma CXCL12 levels and different grades of left ventricular ejection fraction (LVEF) in statin-treated and -untreated patients with severe MI. A total of 198 consecutive patients with first-time severe MI (ST-elevated myocardial infarction [STEMI], n  = 121 and non-ST-elevated myocardial infarction [NSTEMI], n  = 77) were recruited from Coronary Care Unit, King Abdulaziz University Hospital. They have one to two coronary arteries blocked ≥50%, or three arteries blocked 30 to 49%. Demographic and clinical criteria were collected and plasma CXCL12 level was measured. No correlations were detected between demographic and clinical criteria and CXCL12 level. While troponin peaks and LVEF significantly differed between STEMI and NSTEMI patients, CXCL12 level showed nonsignificant changes. Plasma CXCL12 levels decreased significantly in statin-treated patients compared with those untreated. From receiver operating characteristic (ROC) analysis, high CXCL12 levels were associated with no statin therapy. For STEMI and NSTEMI patients, area under the receiver operating characteristic curve for CXCL12 test were 0.685 and 0.820, while sensitivity and specificity values were 75.9 and 54.8%, and 73.1 and 84%, respectively. Plasma CXCL12 levels showed nonsignificant changes with different ranges of LVEF and troponin peaks. In patients with severe MI, irrespective of statin therapy, plasma CXCL12 showed no correlation with different ranges of LVEF suggesting that it cannot predict left ventricular dysfunction in these cases. However, cross-sectional design of this study is a limitation.

Super-Resolution Deep Learning Reconstruction for Improved Image Quality of Coronary CT Angiography

Purpose

To investigate image noise and edge sharpness of coronary CT angiography (CCTA) with super-resolution deep learning reconstruction (SR-DLR) compared with conventional DLR (C-DLR) and to evaluate agreement in stenosis grading using CCTA with that from invasive coronary angiography (ICA) as the reference standard.

Materials and Methods

This retrospective study included 58 patients (mean age, 69.0 years ± 12.8 [SD]; 38 men, 20 women) who underwent CCTA using 320-row CT between April and September 2022. All images were reconstructed with two different algorithms: SR-DLR and C-DLR. Image noise, signal-to-noise ratio, edge sharpness, full width at half maximum (FWHM) of stent, and agreement in stenosis grading with that from ICA were compared. Stenosis was visually graded from 0 to 5, with 5 indicating occlusion.

Results

SR-DLR significantly decreased image noise by 31% compared with C-DLR (12.6 HU ± 2.3 vs 18.2 HU ± 1.9; P < .001). Signal-to-noise ratio and edge sharpness were significantly improved by SR-DLR compared with C-DLR (signal-to-noise ratio, 38.7 ± 8.3 vs 26.2 ± 4.6; P < .001; edge sharpness, 560 HU/mm ± 191 vs 463 HU/mm ± 164; P < .001). The FWHM of stent was significantly thinner on SR-DLR (0.72 mm ± 0.22) than on C-DLR (1.01 mm ± 0.21; P < .001). Agreement in stenosis grading between CCTA and ICA was improved on SR-DLR compared with C-DLR (weighted κ = 0.83 vs 0.77).

Conclusion

SR-DLR improved vessel sharpness, image noise, and accuracy of coronary stenosis grading compared with the C-DLR technique.Keywords: CT Angiography, Cardiac, Coronary Arteries Supplemental material is available for this article. © RSNA, 2023.

Coronary computed tomography in emergencies: The importance of the radiologist's experience

INTRODUCTION

Incorporating coronary computed tomography angiography (CTA) in the hospital workup for suspected acute coronary syndrome requires appropriate skills for interpreting this imaging test. Radiologists' skills can affect the interobserver agreement in evaluating these studies.

OBJECTIVE

To determine the interobserver agreement according to radiologists' experience in the interpretation of coronary CTA studies done in patients who present at the emergency department with acute chest pain and low-to-intermediate probability of acute coronary syndrome.

MATERIALS AND METHODS

We studied the interobserver agreement in the urgent evaluation of coronary CTA studies in which CAD-RADS was used to register the findings. We created pairs of observers among a total of 8 assessors (4 attending radiologists and 4 radiology residents). We used the kappa coefficient to estimate the overall concordance and the concordance between subgroups according to their experience.

RESULTS

The agreement was substantial between experienced radiologists and residents (k=0.627; 95%CI: 0.436-0.826) as well as between all the pairs of observers (k=0.661; 95%CI: 0.506-0.823) for all the CAD-RADS together. The degree of agreement within the group of experienced radiologists was greater than that within the group of residents in all the analyses. The agreement was excellent for the overall CAD-RADS (k=0.950; 95% CI: 0.896-1) and for CAD-RADS ≥ 4 (k=1); the agreement was lower for CAD-RADS ≥ 3 (k=0.754; 95% CI: 0.246-1.255). The agreement for the residents for these categories was k=0.623, k=0.596, and k=0.473, respectively.

CONCLUSION

The agreement among attending radiologists regarding the assessment of urgent coronary CTA studies is excellent. The agreement is lower when residents are paired with attending radiologists. These findings should be taken into consideration when implementing coronary CTA in emergency departments and in the organisation of radiological staff for interpreting and reporting this imaging test.

Prognostic value of coronary CTA-based classifications for predicting major events without obstructive coronary artery disease

We aim to explore the classifications based on coronary computed tomography angiography (CTA) for predicting the risk of major adverse cardiovascular events (MACE) in patients with suspected non-obstructive coronary artery disease (CAD) and compare with traditional non-obstructive CAD (NOCAD) classification, Duke prognostic NOCAD index, Non-obstructive coronary artery disease reporting and data system (NOCAD-RADS). 4378 consecutive non-obstructive CAD patients were assessed by coronary CTA for traditional NOCAD classification, Duke prognostic NOCAD index, NOCAD-RADS and a new classification (stenosis proximal involvement, SPI) from two medical centrals. We defined proximal involvement as any plaque was present in the main or proximal segments of coronary artery (left main, left anterior descending artery, left circumflex artery, or right coronary artery). The main outcome was MACE. During a median follow-up of 3.7 years, a total of 310 patients experienced MACE event. Kaplan-Meier survival curves showed the cumulative events increased significantly associated with traditional NOCAD, Duke NOCAD index, NOCAD-RADS and SPI classifications (all P < 0.001). In multivariate Cox regressions, the risk for the events increased from HR 1.20 (95% CI 0.78-1.83, P = 0.408) for SPI 1 to 1.35 (95% CI 1.05-1.73, P = 0.019) for SPI 2, using SPI 0 as the reference group. Coronary CTA based SPI classification provided important prognostic information for all cause-mortality risk and MACE prediction in patients with non-obstructive CAD, which was non-inferior than traditional NOCAD, Duke NOCAD Index and NOCAD-RADS classifications. The plaque location information by coronary CTA may provide additional risk prediction in patients with non-obstructive CAD.

Deep learning-based prediction for significant coronary artery stenosis on coronary computed tomography angiography in asymptomatic populations

Background

Although coronary computed tomography angiography (CCTA) is currently utilized as the frontline test to accurately diagnose coronary artery disease (CAD) in clinical practice, there are still debates regarding its use as a screening tool for the asymptomatic population. Using deep learning (DL), we sought to develop a prediction model for significant coronary artery stenosis on CCTA and identify the individuals who would benefit from undergoing CCTA among apparently healthy asymptomatic adults.

Methods

We retrospectively reviewed 11,180 individuals who underwent CCTA as part of routine health check-ups between 2012 and 2019. The main outcome was the presence of coronary artery stenosis of ≥70% on CCTA. We developed a prediction model using machine learning (ML), including DL. Its performance was compared with pretest probabilities, including the pooled cohort equation (PCE), CAD consortium, and updated Diamond-Forrester (UDF) scores.

Results

In the cohort of 11,180 apparently healthy asymptomatic individuals (mean age 56.1 years; men 69.8%), 516 (4.6%) presented with significant coronary artery stenosis on CCTA. Among the ML methods employed, a neural network with multi-task learning (19 selected features), one of the DL methods, was selected due to its superior performance, with an area under the curve (AUC) of 0.782 and a high diagnostic accuracy of 71.6%. Our DL-based model demonstrated a better prediction than the PCE (AUC, 0.719), CAD consortium score (AUC, 0.696), and UDF score (AUC, 0.705). Age, sex, HbA1c, and HDL cholesterol were highly ranked features. Personal education and monthly income levels were also included as important features of the model.

Conclusion

We successfully developed the neural network with multi-task learning for the detection of CCTA-derived stenosis of ≥70% in asymptomatic populations. Our findings suggest that this model may provide more precise indications for the use of CCTA as a screening tool to identify individuals at a higher risk, even in asymptomatic populations, in clinical practice.

Non-Contrast and Contrast-Enhanced Cardiac Computed Tomography Imaging in the Diagnostic and Prognostic Evaluation of Coronary Artery Disease

In recent decades, cardiac computed tomography (CT) has emerged as a powerful non-invasive tool for risk stratification, as well as the detection and characterization of coronary artery disease (CAD), which remains the main cause of morbidity and mortality in the world. Advances in technology have favored the increasing use of cardiac CT by allowing better performance with lower radiation doses. Coronary artery calcium, as assessed by non-contrast CT, is considered to be the best marker of subclinical atherosclerosis, and its use is recommended for the refinement of risk assessment in low-to-intermediate risk individuals. In addition, coronary CT angiography (CCTA) has become a gate-keeper to invasive coronary angiography (ICA) and revascularization in patients with acute chest pain by allowing the assessment not only of the extent of lumen stenosis, but also of its hemodynamic significance if combined with the measurement of fractional flow reserve or perfusion imaging. Moreover, CCTA provides a unique incremental value over functional testing and ICA by imaging the vessel wall, thus allowing the assessment of plaque burden, composition, and instability features, in addition to perivascular adipose tissue attenuation, which is a marker of vascular inflammation. There exists the potential to identify the non-obstructive lesions at high risk of progression to plaque rupture by combining all of these measures.

Detecting lesion-specific ischemia in patients with coronary artery disease with computed tomography fractional flow reserve measured at different sites

OBJECTIVES

Whether a stenosis can cause hemodynamic lesion-specific ischemia is critical for the treatment decision in patients with coronary artery disease (CAD). Based on coronary computed tomography angiography (CCTA), CT fractional flow reserve (FFR_CT) can be used to assess lesion-specific ischemia. The selection of an appropriate site along the coronary artery tree is vital for measuring FFR_CT. However the optimal site to measure FFR_CT for a target stenosis remains to be adequately determined. The purpose of this study was to determine the optimal site to measure FFR_CT for a target lesion in detecting lesion-specific ischemia in CAD patients by evaluating the performance of FFR_CT measured at different sites distal to the target lesion in detecting lesion-specific ischemia with FFR measured with invasive coronary angiography (ICA) as reference standard.

METHODS

In this single-center retrospective cohort study, a total of 401 patients suspected of having CAD underwent invasive ICA and FFR between March 2017 and December 2021 were identified. 52 patients having both CCTA and invasive FFR within 90 days were enrolled. Patients with vessels 30%-90% diameter stenosis as determined by ICA were referred to invasive FFR evaluation, which was performed 2-3 cm distal to the stenosis under the condition of hyperemia. For each vessel with 30%-90% diameter stenosis, if only one stenosis was present, this stenosis was selected as the target lesion; if serial stenoses were present, the stenosis most distal to the vessel end was chosen as the target lesion. FFR_CT was measured at four sites: 1 cm, 2 cm, and 3 cm distal to the lower border of the target lesion (FFR_CT-1 cm, FFR_CT-2 cm, FFR_CT-3 cm), and the lowest FFR_CT at the distal vessel tip (FFR_CT-lowest). The normality of quantitative data was assessed using the Shapiro-Wilk test. Pearson's correlation analysis and Bland-Altman plots were used for assessing the correlation and difference between invasive FFR and FFR_CT. Correlation coefficients derived from Chi-suqare test were used to assess the correlation between invasive FFR and the cominbaiton of FFR_CT measred at four sites. The performances of significant obstruction stenosis (diameter stenosis ≥ 50%) at CCTA and FFR_CT measured at the four sites and their combinations in diagnosing lesion-specific ischemia were evaluated by receiver-operating characteristic (ROC) curves using invasive FFR as the reference standard. The areas under ROC curves (AUCs) of CCTA and FFR_CT were compared by the DeLong test.

RESULTS

A total of 72 coronary arteries in 52 patients were included for analysis. Twenty-five vessels (34.7%) had lesion-specific ischemia detected by invasive FFR and 47 vesseles (65.3%) had no lesion-spefifice ischemia. Good correlation was found between invasive FFR and FFR_CT-2 cm and FFR_CT-3 cm (r = 0.80, 95% CI, 0.70 to 0.87, p < 0.001; r = 0.82, 95% CI, 0.72 to 0.88, p < 0.001). Moderate correlation was found between invasive FFR and FFR_CT-1 cm and FFR_CT-lowest (r = 0.77, 95% CI, 0.65 to 0.85, p < 0.001; r = 0.78, 95% CI, 0.67 to 0.86, p < 0.001). FFR_CT-1 cm + FFR_CT-2 cm, FFR_CT-2 cm + FFR_CT-3 cm, FFR_CT-3 cm + FFR_CT-lowest, FFR_CT-1 cm + FFR_CT-2 cm + FFR_CT-3 cm, and FFR_CT-2 cm + FFR_CT-3 cm + FFR_CT-lowest were correatled with invasive FFR (r = 0.722; 0.722; 0.701; 0.722; and 0.722, respectively; p < 0.001 for all). Bland-Altman plots revealed a mild difference between invasive FFR and the four FFR_CT (invasive FFR vs. FFR_CT-1 cm, mean difference -0.0158, 95% limits of agreement: -0.1475 to 0.1159; invasive FFR vs. FFR_CT-2 cm, mean difference 0.0001, 95% limits of agreement: -0.1222 to 0.1220; invasive FFR vs. FFR_CT-3 cm, mean difference 0.0117, 95% limits of agreement: -0.1085 to 0.1318; and invasive FFR vs. FFR_CT-lowest, mean difference 0.0343, 95% limits of agreement: -0.1033 to 0.1720). AUCs of CCTA, FFR_CT-1 cm, FFR_CT-2 cm, FFR_CT-3 cm, and FFR_CT-lowest in detecting lesion-specific ischemia were 0.578, 0.768, 0.857, 0.856 and 0.770, respectively. All FFR_CT had a higher AUC than CCTA (all p < 0.05), FFR_CT-2 cm achieved the highest AUC at 0.857. The AUCs of FFR_CT-2 cm and FFR_CT-3 cm were comparable (p > 0.05). The AUCs were similar between FFR_CT-1 cm + FFR_CT-2 cm, FFR_CT-3 cm + FFR_CT-lowest and FFR_CT-2 cm alone (AUC = 0.857, 0.857, 0.857, respectively; p > 0.05 for all). The AUCs of FFR_CT-2 cm + FFR_CT-3 cm, FFR_CT-1 cm + FFR_CT-2 cm + FFR_CT-3 cm, FFR_CT-and 2 cm + FFR_CT-3 cm + FFR_CT-lowest (0.871, 0.871, 0.872, respectively) were slightly higher than that of FFR_CT-2 cm alone (0.857), but without significnacne differences (p > 0.05 for all).

CONCLUSIONS

FFR_CT measured at 2 cm distal to the lower border of the target lesion is the optimal measurement site for identifying lesion-specific ischemia in patients with CAD.

Clinical Feasibility of Deep Learning-Based Image Reconstruction on Coronary Computed Tomography Angiography

This study evaluated the feasibility of deep-learning-based image reconstruction (DLIR) on coronary computed tomography angiography (CCTA). By using a 20 cm water phantom, the noise reduction ratio and noise power spectrum were evaluated according to the different reconstruction methods. Then 46 patients who underwent CCTA were retrospectively enrolled. CCTA was performed using the 16 cm coverage axial volume scan technique. All CT images were reconstructed using filtered back projection (FBP); three model-based iterative reconstructions (MBIR) of 40%, 60%, and 80%; and three DLIR algorithms: low (L), medium (M), and high (H). Quantitative and qualitative image qualities of CCTA were compared according to the reconstruction methods. In the phantom study, the noise reduction ratios of MBIR-40%, MBIR-60%, MBIR-80%, DLIR-L, DLIR-M, and DLIR-H were 26.7 ± 0.2%, 39.5 ± 0.5%, 51.7 ± 0.4%, 33.1 ± 0.8%, 43.2 ± 0.8%, and 53.5 ± 0.1%, respectively. The pattern of the noise power spectrum of the DLIR images was more similar to FBP images than MBIR images. In a CCTA study, CCTA yielded a significantly lower noise index with DLIR-H reconstruction than with the other reconstruction methods. DLIR-H showed a higher SNR and CNR than MBIR (p < 0.05). The qualitative image quality of CCTA with DLIR-H was significantly higher than that of MBIR-80% or FBP. The DLIR algorithm was feasible and yielded a better image quality than the FBP or MBIR algorithms on CCTA.