Coronary Tomography Research Articles

Image and Clinical Characteristics of the Right Coronary Artery Originating From the Left Coronary Sinus: A Database Review.

This article systematically explores the imaging and clinical characteristics of a relatively rare cardiac anomaly: the right coronary artery originating from the left coronary sinus. Through a comprehensive analysis of existing literature, this study aims to provide a comprehensive understanding of the prevalence, diagnostic methods, and potential clinical implications of this anatomical variation. Anatomical classification is introduced, along with clinical imaging diagnostic methods, including coronary angiography, computed tomography, and magnetic resonance imaging. Additionally, the review delves into the clinical significance of this anomaly, including its potential associations with myocardial ischemia, arrhythmias, and acute cardiac events, outlining clinical approaches to diagnosing myocardial ischemia. The study results consolidate current knowledge about this cardiac variation, emphasizing the importance of recognizing and appropriately managing it in clinical practice.

Invasive coronary imaging of inflammation to further characterize high-risk lesions: what options do we have?

Coronary atherosclerosis remains a leading cause of morbidity and mortality worldwide. The underlying pathophysiology includes a complex interplay of endothelial dysfunction, lipid accumulation and inflammatory pathways. Multiple structural and inflammatory features of the atherosclerotic lesions have become targets to identify high-risk lesions. Various intracoronary imaging devices have been developed to assess the morphological, biocompositional and molecular profile of the intracoronary atheromata. These techniques guide interventional and therapeutical management and allow the identification and stratification of atherosclerotic lesions. We sought to provide an overview of the inflammatory pathobiology of atherosclerosis, distinct high-risk plaque features and the ability to visualize this process with contemporary intracoronary imaging techniques.

Effect of inflammation on association between cancer and coronary artery disease

BackgroundCancer and coronary artery disease (CAD) is reported to often co-exist in same individuals, however, whether cancer is directly associated with anatomical severity of CAD is rarely studied. The present study aimed to observe the relationship between newly diagnosed cancer and anatomical severity of CAD, moreover, to investigate effect of inflammation on the relationship of cancer with CAD.Methods374 patients with newly diagnosed cancer who underwent coronary angiography (CAG) were enrolled. Through 1:3 propensity score matching (PSM) to cancer patients based on the age and gender among 51,106 non-cancer patients who underwent CAG, 1122 non-cancer patients were selected as control patients. Anatomical severity of CAD was assessed using SYNTAX score (SXscore) based on coronary angiographic image. SXscore ≤ 22 (highest quartile) was defined as SX-low, and SXscore > 22 as SX-high. The ratio of neutrophil to lymphocyte count (NLR) was used to describe inflammation level. Association between cancer and the anatomical severity of CAD was investigated using logistic regression.ResultsUnivariate logistic regression analysis showed a correlation between cancer and anatomical severity of CAD (OR: 1.419, 95% CI: 1.083–1.859; P = 0.011). Cancer was associated with increased risk of SX-high after adjusted for common risk factors of CAD (OR: 1.598, 95% CI: 1.172–2.179, P = 0.003). Significant association between cancer and SX-high was revealed among patients with high inflammation (OR: 1.656, 95% CI: 1.099–2.497, P = 0.016), but not among patients with low inflammation (OR: 1.530, 95% CI: 0.973–2.498, P = 0.089).ConclusionsCancer was associated with severity of CAD, however, the association between the two diseases was significant among patients with high inflammation rather than among patients with low inflammation.

Coronary coding in dTGA pre- and post-ASO-verification and necessary corrections following adult CMR.

In adult patients with transposition of the great arteries (dTGA) after arterial switch operation (ASO), the coronary artery circulation after neonatal surgical transfer remains a major culprit for long-term sequelae, including myocardial ischaemia and sudden cardiac death. As coronary imaging in paediatric age is often incomplete and classification mainly relies on the surgeon's description in the operation report, we intended to develop a systematic, understandable pattern of the coronary status for each young patient, combining unambiguous coding with non-invasive imaging. The monocentric prospective study evaluated 89 young adults (mean 23 years) after ASO for dTGA including cardiac magnetic resonance (CMR) coronary angiography. Following 'The Leiden Convention coronary coding system', we describe the systematic transformation process and provide a graphical illustration considering surgical and imaging views for the six main coronary types, followed by a comparison with adult CMR. Discordance between surgeon's and CMR classification is evaluated.In seven (7.9%) patients, a discordance between the surgeon's post-operative and the CMR classification was found; therefore, the initial classification had to be corrected according to adult CMR. Three cases (3.4%) with particularly challenging coronary variants (intramural and interarterial course, functional common ostium) are presented. Considering the risks of a possible neonatal coronary misclassification and of increasing additional acquired coronary artery disease with age, reliable cooperation between surgeons, cardiologists, and imaging specialists must be ensured. Therefore, after completion of growth, a systematic pattern of the coronary artery status, combining unambiguous coding with CMR imaging, should be established for each patient.

Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification.

To prospectively investigate whether fully automated artificial intelligence (FAAI)-based coronary CT angiography (CCTA) image processing is non-inferior to semi-automated mode in efficiency, diagnostic ability, and risk stratification of coronary artery disease (CAD). Adults with indications for CCTA were prospectively and consecutively enrolled at two hospitals and randomly assigned to either FAAI-based or semi-automated image processing using equipment workstations. Outcome measures were workflow efficiency, diagnostic accuracy for obstructive CAD (≥ 50% stenosis), and cardiovascular events at 2-year follow-up. The endpoints included major adverse cardiovascular events, hospitalization for unstable angina, and recurrence of cardiac symptoms. The non-inferiority margin was 3 percentage difference in diagnostic accuracy and C-index. In total, 1801 subjects (62.7 ± 11.1 years) were included, of whom 893 and 908 were assigned to the FAAI-based and semi-automated modes, respectively. Image processing times were 121.0 ± 18.6 and 433.5 ± 68.4 s, respectively (p<0.001). Scan-to-report release times were 6.4 ± 2.7 and 10.5 ± 3.8 h, respectively (p< 0.001). Of all subjects, 152 and 159 in the FAAI-based and semi-automated modes, respectively, subsequently underwent invasive coronary angiography. The diagnostic accuracies for obstructive CAD were 94.7% (89.9-97.7%) and 94.3% (89.5-97.4%), respectively (difference 0.4%). Of all subjects, 779 and 784 in the FAAI-based and semi-automated modes were followed for 589 ± 182 days, respectively, and the C-statistic for cardiovascular events were 0.75 (0.67 to 0.83) and 0.74 (0.66 to 0.82) (difference 1%). FAAI-based CCTA image processing significantly improves workflow efficiency than semi-automated mode, and is non-inferior in diagnosing obstructive CAD and risk stratification for cardiovascular events. Conventional coronary CT angiography image processing is semi-automated. This observation shows that fully automated artificial intelligence-based image processing greatly improves efficiency, and maintains high diagnostic accuracy and the effectiveness in stratifying patients for cardiovascular events. • Coronary CT angiography (CCTA) relies heavily on high-quality and fast image processing. • Full-automation CCTA image processing is clinically non-inferior to the semi-automated mode. • Full automation can facilitate the application of CCTA in early detection of coronary artery disease.

In-Stent Restenosis: Achilles’ Heel of Post-PCI Era

Despite advancements in stent design and polymer coatings over the past two decades, 1% to 2% of patients annually still experience instent restenosis (ISR). ISR reduces myocardial perfusion, may develop symptoms of myocardial ischemia, and thus leads to a high risk of myocardial infarction and cardiac death. Given that millions of drug-eluting stents (DES) are implanted globally every year, ISR remains a prevalent clinical issue with significant public health implications. Coronary intravascular imaging, includes intravascular ultrasound (IVUS) and optical coherence tomography (OCT), can help physicians gain deeper insights into the potential mechanisms of ISR. The preferred treatment strategy hinges on an accurate diagnosis and better understanding of etiology. The mechanism of ISR is multifaceted, and its treatment is challenging. Although the risk of ISR continues to decrease with advancements in DES application, further research is still needed to enrich the treatment options for ISR.

Dataset for Automatic Region-based Coronary Artery Disease Diagnostics Using X-Ray Angiography Images

X-ray coronary angiography is the most common tool for the diagnosis and treatment of coronary artery disease. It involves the injection of contrast agents into coronary vessels using a catheter to highlight the coronary vessel structure. Typically, multiple 2D X-ray projections are recorded from different angles to improve visualization. Recent advances in the development of deep-learning-based tools promise significant improvement in diagnosing and treating coronary artery disease. However, the limited public availability of annotated X-ray coronary angiography image datasets presents a challenge for objective assessment and comparison of existing tools and the development of novel methods. To address this challenge, we introduce a novel ARCADE dataset with 2 objectives: coronary vessel classification and stenosis detection. Each objective contains 1500 expert-labeled X-ray coronary angiography images representing: i) coronary artery segments; and ii) the locations of stenotic plaques. These datasets will serve as a benchmark for developing new methods and assessing existing approaches for the automated diagnosis and risk assessment of coronary artery disease.

Rapid automated lumen segmentation of coronary optical coherence tomography images followed by 3D reconstruction of coronary arteries.

Optical coherence tomography has emerged as an important intracoronary imaging technique for coronary artery disease diagnosis as it produces high-resolution cross-sectional images of luminal and plaque morphology. Precise and fast lumen segmentation is essential for efficient OCT morphometric analysis. However, due to the presence of various image artifacts, including side branches, luminal blood artifacts, and complicated lesions, this remains a challenging task. Our research study proposes a rapid automatic segmentation method that utilizes nonuniform rational B-spline to connect limited pixel points and identify the edges of the OCT lumen. The proposed method suppresses image noise and accurately extracts the lumen border with a high correlation to ground truth images based on the area, minimal diameter, and maximal diameter. We evaluated the method using 3300 OCT frames from 10 patients and found that it achieved favorable results. The average time taken for automatic segmentation by the proposed method is 0.17s per frame. Additionally, the proposed method includes seamless vessel reconstruction following the lumen segmentation. The developed automated system provides an accurate, efficient, robust, and user-friendly platform for coronary lumen segmentation and reconstruction, which can pave the way for improved assessment of the coronary artery lumen morphology.

Coronary artery wall contrast enhancement imaging impact on disease activity assessment in IgG4-RD: a direct marker of coronary involvement

BackgroundCoronary artery wall contrast enhancement (CE) has been applied to non-invasive visualization of changes to the coronary artery wall in systemic lupus erythematosus (SLE). This study investigated the feasibility of quantifying CE to detect coronary involvement in IgG4-related disease (IgG4-RD), as well as the influence on disease activity assessment. MethodsA total of 93 subjects (31 IgG4-RD; 29 SLE; 33 controls) were recruited in the study. Coronary artery wall imaging was performed in a 3.0 T MRI scanner. Serological markers and IgG4-RD Responder Index (IgG4-RD-RI) scores were collected for correlation analysis. ResultsCoronary wall CE was observed in 29 (94 %) IgG4-RD patients and 22 (76 %) SLE patients. Contrast-to-noise ratio (CNR) and total CE area were significantly higher in patient groups compared to controls (CNR: 6.1 ± 2.7 [IgG4-RD] v. 4.2 ± 2.3 [SLE] v. 1.9 ± 1.5 [control], P < 0.001; Total CE area: 3.0 [3.0–6.6] v. 1.7 [1.5–2.6] v. 0.3 [0.3–0.9], P < 0.001). In the IgG4-RD group, CNR and total CE area were correlated with the RI (CNR: r = 0.55, P = 0.002; total CE area: r = 0.39, P = 0.031). RI´ scored considering coronary involvement by CE, differed significantly from RI scored without consideration of CE (RI v. RI´: 15 ± 6 v. 16 ± 6, P < 0.001). ConclusionsVisualization and quantification of CMR coronary CE by CNR and total CE area could be utilized to detect subclinical and clinical coronary wall involvement, which is prevalent in IgG4-RD. The potential inclusion of small and medium-sized vessel involvements in the assessment of disease activity in IgG4-RD is worthy of further investigation.

Rapid three-dimensional quantification of high-intensity plaques from coronary atherosclerosis T1-weighted characterization to predict periprocedural myocardial injury

BackgroundHigh-intensity plaque (HIP) on magnetic resonance imaging (MRI) has been documented as a powerful predictor of periprocedural myocardial injury (PMI) following percutaneous coronary intervention (PCI). Despite the recent proposal of three-dimensional HIP quantification to enhance the predictive capability, the conventional pulse sequence, which necessitates the separate acquisition of anatomical reference images, hinders accurate three-dimensional segmentation along the coronary vasculature. Coronary atherosclerosis T1-weighted characterization (CATCH) enables the simultaneous acquisition of inherently coregistered dark-blood plaque and bright-blood coronary artery images. We aimed to develop a novel HIP quantification approach using CATCH and to ascertain its superior predictive performance compared to the conventional two-dimensional assessment based on plaque-to-myocardium signal intensity ratio (PMR). MethodsIn this prospective study, CATCH MRI was conducted before elective stent implantation in 137 lesions from 125 patients. On CATCH images, dedicated software automatically generated tubular three-dimensional volumes of interest on the dark-blood plaque images along the coronary vasculature, based on the precisely matched bright-blood coronary artery images, and subsequently computed PMR and HIP volume (HIPvol). Specifically, HIPvol was calculated as the volume of voxels with signal intensity exceeding that of the myocardium, weighted by their respective signal intensities. PMI was defined as post-PCI cardiac troponin-T > 5 × the upper reference limit. ResultsThe entire analysis process was completed within 3 min per lesion. PMI occurred in 44 lesions. Based on the receiver operating characteristic curve analysis, HIPvol outperformed PMR for predicting PMI (C-statistics, 0.870 [95% CI, 0.805–0.936] vs. 0.787 [95% CI, 0.706–0.868]; p = 0.001). This result was primarily driven by the higher sensitivity HIPvol offered: 0.886 (95% CI, 0.754–0.962) vs. 0.750 for PMR (95% CI, 0.597–0.868; p = 0.034). Multivariable analysis identified HIPvol as an independent predictor of PMI (odds ratio, 1.15 per 10-μL increase; 95% CI, 1.01–1.30, p = 0.035). ConclusionsOur semi-automated method of analyzing coronary plaque using CATCH MRI provided rapid HIP quantification. Three-dimensional assessment using this approach had a better ability to predict PMI than conventional two-dimensional assessment.

Coronary embolism in left-sided infective endocarditis. A retrospective analysis from a high-volume surgical centre and review of the literature.

Septic embolization is a common and potentially life-threatening complication of infective endocarditis (IE), with a prevalence of 22-50%. While acute coronary syndrome secondary to septic embolism is rare, it poses significant risks. This study examines coronary embolism (CE) in left-sided IE, describing clinical characteristics and outcomes. We retrospectively analysed 649 patients with non-device-related left-sided IE treated between January 2013 and December 2023 in a high-volume surgical centre. CE was diagnosed via ECG, clinical and laboratory signs of acute coronary syndrome, and confirmed by coronary angiography or magnetic resonance imaging. All patients were treated according to current European Society of Cardiology guidelines. A structured follow-up was performed. Among patients included in the study, surgery was performed in 514 (79%) patients. Median follow-up duration was 4.7 years. CE occurred in 8 (1.2%) patients, and 6 (80%) of them were treated surgically. We found no significant differences in overall mortality rate between patients with or without CE (p = 0.65). Finally, cerebral embolism was significantly more frequent in patients with than without CE (75% vs 25%, p = 0.006, post-hoc power 87.8%). CE is a rare but severe complication of IE, significantly associated with cerebral embolism. Early recognition and treatment are crucial to improve patient outcomes. Multicentre studies with larger patient populations are needed to further elucidate risk factors and enhance prognosis for CE in IE patients.

Lesion Classification of Coronary Artery CTA Images Based on CBAM and Transfer Learning

Lesion Classification of Coronary Artery CTA Images Based on CBAM and Transfer Learning

Coronary artery angiography image vessel segmentation method based on feature pyramid network

Coronary artery angiography image vessel segmentation method based on feature pyramid network

Role of intravascular ultrasound and optical coherence tomography in intracoronary imaging for coronary artery disease: a systematic review.

Coronary angiography has long been the standard for coronary imaging, but it has limitations in assessing vessel wall anatomy and guiding percutaneous coronary intervention (PCI). Intracoronary imaging techniques like intravascular ultrasound (IVUS) and optical coherence tomography (OCT) can overcome these limitations. IVUS uses ultrasound and OCT uses near-infrared light to visualize coronary pathology in unique ways due to differences in temporal and spatial resolution. These techniques have evolved to offer clinical utility in plaque characterization and vessel assessment during PCI. Meta-analyses and adjusted observational studies suggest that both IVUS and OCT-guided PCI correlate with reduced cardiovascular risks compared to angiographic guidance alone. While IVUS demonstrates consistent clinical outcome benefits, OCT evidence is less robust. IVUS has progressed from early motion detection to high-resolution systems, with smaller compatible catheters. OCT utilizes near infrared light to achieve unparalleled resolutions, but requires temporary blood clearance for optimal imaging. Enhanced visualization and guidance make IVUS and OCT well-suited for higher risk PCI in patients with diabetes and chronic kidney disease by allowing detailed visualization of complex lesions and ensuring optimal stent deployment and positioning in PCI for patients with type 2 diabetes and chronic kidney disease, improving outcomes. IVUS and recent advancements in zero- and low-contrast OCT techniques can reduce nephrotoxic contrast exposure, thus helping to minimize PCI complications in these high-risk patient groups. IVUS and OCT provide valuable insights into coronary pathophysiology and guide interventions precisely compared to angiography alone. Both have comparable clinical outcomes, emphasizing the need for tailored imaging choices based on clinical scenarios. Continued refinement and integration of intravascular imaging will likely play a pivotal role in optimizing coronary interventions and outcomes. This systematic review aims to delve into the nuances of IVUS and OCT, highlighting their strengths and limitations as PCI adjuncts.

Constraint-Aware Learning for Fractional Flow Reserve Pullback Curve Estimation from Invasive Coronary Imaging.

Estimation of the fractional flow reserve (FFR) pullback curve from invasive coronary imaging is important for the intraoperative guidance of coronary intervention. Machine/deep learning has been proven effective in FFR pullback curve estimation. However, the existing methods suffer from inadequate incorporation of intrinsic geometry associations and physics knowledge. In this paper, we propose a constraint-aware learning framework to improve the estimation of the FFR pullback curve from invasive coronary imaging. It incorporates both geometrical and physical constraints to approximate the relationships between the geometric structure and FFR values along the coronary artery centerline. Our method also leverages the power of synthetic data in model training to reduce the collection costs of clinical data. Moreover, to bridge the domain gap between synthetic and real data distributions when testing on real-world imaging data, we also employ a diffusion-driven test-time data adaptation method that preserves the knowledge learned in synthetic data. Specifically, this method learns a diffusion model of the synthetic data distribution and then projects real data to the synthetic data distribution at test time. Extensive experimental studies on a synthetic dataset and a real-world dataset of 382 patients covering three imaging modalities have shown the better performance of our method for FFR estimation of stenotic coronary arteries, compared with other machine/deep learning-based FFR estimation models and computational fluid dynamics-based model. The results also provide high agreement and correlation between the FFR predictions of our method and the invasively measured FFR values. The plausibility of FFR predictions along the coronary artery centerline is also validated.

Pattern of Endothelialization in Left Atrial Appendage Occluder by Optic Coherence Tomography: A Pilot Study.

Implantation of the left atrial appendage occluder (LAAO) has been proven to prevent stroke effectively in patients with atrial fibrillation who cannot tolerate anticoagulants. Incomplete endothelization of LAAO may cause device-related thrombus, and currently no good image modality exists to clearly see LAAO endothelialization. We aimed to use coronary optic coherence tomography (OCT) to visualize LAAO endothelialization. We enrolled 14 patients (72.8±9.4 years old) undergoing pulmonary vein isolation with a preexisting LAAO implanted more than 1 year ago (5 Watchman and 9 Amulet). After pulmonary vein isolation, we did OCT via steerable sheath and coronary guiding catheter to adjust OCT probe location and injected contrast medium to visualize the LAAO surface. Invitro testing was also performed to see the bare occluder. Invitro OCT showed the surface of the bare device as an interrupted granule pattern, which included the Watchman surface polytetrafluoroethylene membrane string, Amulet disc metal strut, and inner polytetrafluoroethylene membrane string. In the implanted Watchman, OCT showed endothelialization as a smooth surface layer with noninterrupted coarser granules. In the implanted Amulet, OCT showed endothelialization as thin (early) or thick (late) endothelialization layer covering struts with OCT shadows. Among patients with Watchman, 2 showed no, 2 early, and 1 complete endothelialization. Among patients with Amulet, 2 showed no, 3 early, and 4 late endothelialization. We demonstrated the feasibility of OCT to visualize LAAO endothelization with high resolution. Further studies are needed to determine antithrombotic regimens if incomplete endothelization is detected. A new OCT catheter may be designed specifically for LAAO.

Application of Targeted Coronary Angiography in the Diagnosis of Sudden Cardiac Death.

To diagnose coronary artery stenosis by using the postmortem computed tomography angiography (PMCTA), and to explore the diagnostic value of PMCTA in sudden cardiac death. Six death cases were selected, and the contrast medium iohexol was injected under high pressure through femoral artery approach with 5F pigtail catheter to obtain coronary image data and then the data was analyzed. The results of targeted coronary imaging and coronary artery calcium score (CaS) were compared with the results of conventional autopsy and histopathological examination. The autopsy and histopathological examination of cases with coronary artery stenosis obtained similar results in targeted coronary angiography, with a diagnostic concordance rate of 83.3%. Targeted coronary angiography could effectively show coronary artery diseases, and the CaS was consistent with the results of conventional autopsy and histopathological examination. Targeted coronary angiography can be used as an effective auxiliary method for conventional autopsy in cases of sudden cardiac death.

Impact of iodinated contrast shortage on contrast-associated acute kidney injury: a single center experience

Background In March 2022, a COVID-19 outbreak disrupted the global supply of iodine contrast media (ICM). Healthcare systems implemented contrast-saving strategies to maintain their remaining ICM supplies. This study sought to determine the impact of contrast shortage on the incidence of contrast-associated acute kidney injury (CA-AKI). Methods This was a retrospective study of 265 patients undergoing 278 percutaneous coronary interventions (PCI) during 4-month periods prior to (9/1/2021 to 12/31/2021) and during (5/1/2022 to 8/31/2022) contrast shortage at a single center. The primary endpoint was the incidence of CA-AKI between study periods. Results A total of 148 and 130 PCIs were performed before and during contrast shortage, respectively. The incidence of CA-AKI significantly decreased from 11.5% to 4.6% during contrast shortage (P = 0.04). During the shortage, average contrast volume per PCI was significantly lower (123 ± 62 mL vs 88 ± 46 mL, P < 0.001), while coronary imaging was significantly higher (34.3% vs 50%, P = 0.009) compared to preshortage. All-cause mortality at discharge was comparable between study periods (2.8% vs 3.3%, respectively; P = 0.90). Conclusion The scarcity of ICM for PCI procedures in this single-center experience was associated with a significant increase in the utilization of intravascular imaging and a significant reduction in CA-AKI.

Coronary stent imaging in photon counting computed tomography: improved imaging of in-stent stenoses in a phantom with optimized reconstruction kernels.

Coronary CT angiography (CCTA) is becoming increasingly important in the workup of coronary artery disease. Imaging of stents and in-stent stenoses remains a challenge. This work investigates the assessability of in-stent stenoses in photon counting CT (PCCT) using ultra-high-resolution (UHR) imaging and optimized reconstruction kernels. In an established phantom, 6 stents with inserted hypodense stenoses were scanned in both standard resolution (SRM) and UHR in a clinical PCCT scanner (NAEOTOM Alpha, Siemens Healthineers, Germany). Reconstructions were made both with the clinically established and optimized kernels. The visible stent lumen and the extent of stenosis were quantitatively measured and compared with the angiographic reference standard. Also, region-of-interest (ROI)-based measurements and a qualitative assessment of image quality were performed. The visible stent lumen and the extent of stenosis were measured more precisely in UHR compared to SRM (0.11 ± 0.19 vs 0.41 ± 0.22 mm, P < .001). The optimized kernel further improved the accuracy of the measurements and image quality in UHR (0.35 ± 0.23 vs 0.47 ± 0.19 mm, P < .001). Compared to angiography, stenoses were overestimated in PCCT, on average with an absolute difference of 18.20% ± 4.11%. Photon counting CCTA allows improved imaging of in-stent stenoses in a phantom using UHR imaging and optimized kernels. These results support the use of UHR and optimized kernels in clinical practice and further studies. UHR imaging and optimized reconstruction kernels should be used in CCTA in the presence of cardiac stents.

High Inflammation and Coronary Calcification in an Acute Coronary Syndrome Successfully Treated with Cutting Balloon

Abstract Complex coronary atherosclerosis may exhibit different phenotypes of coronary plaques, from non-calcified highly vulnerable atheroma to heavily calcified ones. Computed coronary tomography angiography (CCTA) may identify these different phenotypes and the recently introduced CCTA-based techniques for mapping coronary inflammation along the coronary arteries may provide useful additional information on cardiovascular risk. Here we present the case of a 68-year-old male patient with acute coronary syndrome in whom invasive coronary angiography and CCTA revealed a severe three-vessel disease with a heavily calcified lesion. Mapping of the CT fat attenuation index along the coronary arteries identified a high level of coronary inflammation, especially associated with the non-calcified lesions. All lesions were successfully revascularized by implantation of drug-eluting stents. A cutting balloon was used for the lesion identified by CCTA as heavily calcified, followed by stent implantation, with good results. In conclusion, CCTA, in association with novel techniques for mapping coronary inflammation, may represent an extremely useful tool for preparing complex interventions in multivessel diseases, helping preprocedural planning in high-risk patients.