Coronary Vessel Wall Research Articles

POLYCORE: Polygon-based contour refinement for improved Intravascular Ultrasound Segmentation

Segmentation of the coronary vessel wall in intravascular ultrasound is a fundamental step in guiding coronary intervention. However, it is an challenging task, even for highly skilled cardiologists, due to image artefacts and shadowed regions caused by calcified plaque, guide wires and vessel side branches. Recently, dense-based neural networks have been applied to this task, however, they often fail to predict anatomically plausible contours in these low-signal areas. We propose a novel methodology called Polygon-based Contour Refiner (POLYCORE) that addresses topological error in dense-based segmentation networks using a relational inductive bias through higher-order connections between vertices to learn anatomically rational contours. Our approach remedies the over-smoothing phenomena common in polygon networks by introducing a new vector field refinement module which enables pixel-level detail to be added in an iterative process. POLYCORE is enhanced with augmented polygon aggregation which we show is more effective than typical dense-based test-time augmentation strategies. We achieve state-of-the-art results on two diverse datasets, observing particular improvements when segmenting the lumen structure and in topologically-challenging regions containing shadow artefacts. Our source code is available here: http://orcid.org/https://github.com/kitbransby/POLYCORE.

Development of a patient-specific model of the human coronary system for percutaneous transluminal coronary angioplasty balloon catheter training and testing

BackgroundTo treat stenosed coronary arteries, percutaneous transluminal coronary angioplasty (PTCA) balloon catheters must combine pushability, trackability, crossability, and rewrap behavior. The existing anatomic track model (ASTM F2394) for catheter testing lacks 3D morphology, vessel tortuosity, and compliance, making evaluating performance characteristics difficult. This study aimed to develop a three-dimensional patient-specific phantom (3DPSP) for device testing and safe training for interventional cardiologists.MethodsA range of silicone materials with different shore hardnesses (00–30–45 A) and wall thicknesses (0.5 mm, 1 mm, 2 mm) were tested to determine compliance for creating coronary vessel phantoms. Compliance was assessed using optical coherence tomography (OCT) and compared to values in the literature. Stenosis was induced using multilayer casting and brushing methods, with gypsum added for calcification. The radial tensile properties of the samples were investigated, and the relationship between Young’s modulus and compliance was determined. Various methods have been introduced to approximate the friction between silicone and real coronary vessel walls. Computerized tomography (CT) scans were used to obtain patient-specific anatomy from the femoral artery to the coronary arteries. Artery lumens were segmented from the CT scans to create dissolvable 3D-printed core models.ResultsA 15A shore hardness silicone yielded an experimental compliance of 12.3–22.4 mm2mmHg·103\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\frac{m{m}^{2}}{mmHg}\\cdot {10}^{3}$$\\end{document} for stenosed tubes and 14.7–57.9 mm2mmHg·103\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\frac{m{m}^{2}}{mmHg}\\cdot {10}^{3}$$\\end{document} for uniform tubes, aligning closely with the literature data (6.28–40.88 mm2mmHg·103\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\frac{m{m}^{2}}{mmHg}\\cdot {10}^{3}$$\\end{document}). The Young’s modulus ranged from 43.2 to 75.5 kPa and 56.6–67.9 kPa for the uniform and calcified materials, respectively. The dependency of the compliance on the wall thickness, Young’s modulus, and inner diameter could be shown. Introducing a lubricant reduced the silicone friction coefficient from 0.52 to 0.13. The 3DPSP was successfully fabricated, and comparative analyses were conducted among eight commercially available catheters.ConclusionThis study presents a novel method for crafting 3DPSPs with realistic mechanical and frictional properties. The proposed approach enables the creation of comprehensive and anatomically precise setups spanning the right femoral artery to the coronary arteries, highlighting the importance of such realistic environments for advancing medical device development and fostering safe training conditions.

Coil migration during coronary artery fistula transcatheter embolization

Link of Video Abstract: https://youtu.be/qD-dDYr0m2U Introduction: Coronary artery fistula (CAF) transcatheter coil embolization is very effective in treating symptomatic coronary fistula and has many advantages compared to the surgical approach. Although this procedure is considerably safe, some life-threatening complications, including vessel rupture, coil migration and death, could still happen. We reported an example case of coil migration into the left anterior descending (LAD) artery during transcatheter CAF embolization. Case Description: A 61-year-old man reported recurrent episodes of typical chest pain and a history of inconclusive exercise tests. Computed tomography (CT) angiography revealed a considerable medium size complex coronary fistula from proximal LAD to main pulmonary artery (MPA), which could cause coronary steal syndrome. The patient then underwent CAF transcatheter coil embolization with 3 pushable coils. Upon delivery of the last coil, the coil suddenly migrated into proximal LAD and made the patient feel chest pain with slight ST depression on electrocardiogram (ECG) monitor lead. This coil migration was treated with a coronary stent to pin the coil into the ostial CAF and coronary vessel wall. After the procedure, the chest pain disappeared, and the ST segment on ECG resolved back to baseline. Conclusion: Coil migration is one of the potentially life-threatening complications during transcatheter CAF coil embolization. Careful preparation in choosing the closure technique, selecting coil size, determining the landing zone and using a detachable coil in high-risk CAF anatomy is mandatory to prevent this event.

Intravascular Imaging versus Physiological Assessment versus Biomechanics-Which Is a Better Guide for Coronary Revascularization.

Today, coronary artery disease (CAD) continues to be a prominent cause of death worldwide. A reliable assessment of coronary stenosis represents a prerequisite for the appropriate management of CAD. Nevertheless, there are still major challenges pertaining to some limitations of current imaging and functional diagnostic modalities. The present review summarizes the current data on invasive functional and intracoronary imaging assessment using optical coherence tomography (OCT), and intravascular ultrasound (IVUS). Amongst the functional parameters-on top of fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR)-we point to novel angiography-based measures such as quantitative flow ratio (QFR), vessel fractional flow reserve (vFFR), angiography-derived fractional flow reserve (FFRangio), and computed tomography-derived flow fractional reserve (FFR-CT), as well as hybrid approaches focusing on optical flow ratio (OFR), computational fluid dynamics and attempts to quantify the forces exaggerated by blood on the coronary plaque and vessel wall.

A Two-Species Finite Volume Scalar Model for Modeling the Diffusion of Poly(lactic-co-glycolic acid) into a Coronary Arterial Wall from a Single Half-Embedded Drug Eluting Stent Strut

This paper outlines the methodology and results for a two-species finite volume scalar computational drug transport model developed for simulating the mass transport of Poly(lactic-co-glycolic acid (PLGA)) from a half-embedded single strut implanted in a coronary arterial vessel wall. The mathematical drug transport model incorporates the convection-diffusion equation in scalar form (dimensionless) with a two-species (free-drug and bound-drug) mass transport setup, including reversible equilibrium reaction source terms for the free and bound-drug states to account for the pharmaco-kinetic reactions in the arterial wall. The relative reaction rates of the added source terms control the interconversion of the drug between the free and bound-drug states. The model is solved by a 2D finite-volume method for discretizing and solving the free and bound drug transport equations with anisotropic vascular drug diffusivities. This model is an improvement over previously developed models using the finite-difference and finite element method. A dimensionless characteristic scaling pre-analysis was conducted a priori to evaluate the significance of implementing the reaction source terms in the transport equations. This paper reports the findings of an investigation of the interstitial flow profile into the arterial wall and the free and bound drug diffusion profiles with a parametric study of varying the polymer drug concentration (low and high), tortuosity, porosity, and Peclet and DamKöhler numbers over the course of 400 h (16.67 days). The results also reveal how a single species drug delivery model that neglects both a reversible binding reaction source term and the porosity and tortuosity of the arterial wall cannot accurately predict the distribution of both the free and bound drug.

An observational study assessing the use of Sirolimus-eluting balloons for side-branch treatment in the provisional stenting of coronary bifurcations

BackgroundDrug eluting balloons (DEB) are a feasible method of rapid delivery of drug to a coronary vessel wall. Their efficacy has been established for the treatment of in-stent restenosis and small vessel disease but there is limited data for their use in bifurcation lesions. ObjectiveThe aim of this study was to assess the effectiveness of provisional upfront side-branch DEB use in bifurcation lesions compared to a simple balloon (POBA) or upfront 2 stent bifurcation strategy. MethodsWe conducted an observational study of 625 patients undergoing PCI to bifurcation lesions. All the patients had a DES deployed in the main vessel (MV). Decision on revascularization option for the side branch (SB) was made by the operator. The primary endpoint was target vessel failure. Secondary endpoints were target vessel myocardial infarction and all-cause mortality. Results311 patients had upfront DEB to the SB whilst the remaining were treated with either DES (188) or POBA (126). Baseline characteristics were similar aside from history of previous MI, which were higher in patients treated with DES or POBA, p = 0.009 whereas patients with previous CABG were likely to undergo DEB treatment (p = 0.004). TVF was more likely to occur in the POBA group (7.5 %) compared to the DEB (3.3 %) and DES (3.3 %) groups (p = 0.0019). There was no significant difference in TV-MI (p = 0.62) or death (p = 0.98) between the groups. ConclusionThis study suggests that provisional bifurcation stenting with upfront Sirolimus DEB use in the SB is an effective treatment for non-LMS bifurcation PCI.

Effect of High-Intensity Statin Therapy on Atherosclerosis (IBIS-4): Manual Versus Automated Methods of IVUS Analysis

AimsStandard manual analysis of IVUS to study the impact of anti-atherosclerotic therapies on the coronary vessel wall is done by a core laboratory (CL), the ground truth (GT). Automatic segmentation of IVUS with a machine learning (ML) algorithm has the potential to replace manual readings with an unbiased and reproducible method. The aim is to determine if results from a CL can be replicated with ML methods. MethodsThis is a post-hoc, comparative analysis of the IBIS-4 (Integrated Biomarkers and Imaging Study-4) study (NCT00962416). The GT baseline and 13-month follow-up measurements of lumen and vessel area and percent atheroma volume (PAV) after statin induction were repeated by the ML algorithm. ResultsThe primary endpoint was change in PAV. PAV as measured by GT was 43.95 % at baseline and 43.02 % at follow-up with a change of −0.90 % (p = 0.007) while the ML algorithm measured 43.69 % and 42.41 % for baseline and follow-up, respectively, with a change of −1.28 % (p < 0.001). Along the most diseased 10 mm segments, GT-PAV was 52.31 % at baseline and 49.42 % at follow-up, with a change of −2.94 % (p < 0.001). The same segments measured by the ML algorithm resulted in PAV of 51.55 % at baseline and 47.81 % at follow-up with a change of −3.74 % (p < 0.001). ConclusionsPAV, the most used endpoint in clinical trials, analyzed by the CL is closely replicated by the ML algorithm. ML automatic segmentation of lumen, vessel and plaque effectively reproduces GT and may be used in future clinical trials as the standard.

Non-contrast magnetic resonance angiography for systemic artery evaluation in Kawasaki disease.

Kawasaki disease (KD) is a systemic vasculitis; systemic arteries other than the coronary arteries should therefore also be evaluated. This study investigated the feasibility of evaluating coronary aneurysms, systemic artery aneurysms (SAAs), and cerebrovascular diseases in patients with KD using non-contrast magnetic resonance angiography (NC-MRA). Coronary artery protocols, including coronary magnetic resonance angiography (MRA) and vessel wall imaging, were performed in 57 examinations of 28 patients. Systemic artery protocol, including SAA scans and head MRA, along with coronary artery protocol, were performed in 42 examinations of 42 patients. The image quality of the SAAs was evaluated on a 4-point scale. Examination time and sedation dosage were compared between the protocols. The presence of SAAs and cerebrovascular disease was also evaluated. The image quality score of SAAs was 4 (interquartile range [IQR]: 4-4) for the aorta, 4 (IQR: 3-4) for the subclavian artery, 4 (IQR: 3-4) for the renal artery, and 3 (IQR: 3-4) for the iliac artery. No differences were found between examination time (47.0 [IQR: 43.0-61.0] min vs. 51.0 [IQR: 45.0-60.0] min, p = 0.48) and sedative dose (4.63 [IQR: 3.93-5.79] mg/kg vs. 4.21 [IQR: 3.56-5.71] mg/kg, p = 0.37) between the protocols. Systemic artery protocol detected SAAs in three patients (7.1%), and cerebrovascular disease was not detected. Evaluating the coronary and systemic arteries in patients with KD using NC-MRA on a single examination was possible without compromising examination time or sedation dose. The systemic artery protocol was useful in finding SAAs.

PSUN57 Noninvasive Assessment of the Coronary Artery Vessel Wall in Cushing's Syndrome Patients using 3-T Magnetic Resonance Imaging: Evidence for Increased Atherosclerosis Compared to Risk Matched Controls

Abstract Background Hypercortisolism due to Cushing's Disease (CD), Ectopic ACTH Syndrome (EAS), adrenal adenoma (AA), or Cyclical Cushing's Syndrome (cCS) is associated with increased cardiovascular morbidity and mortality. The mechanism(s) by which hypercortisolism increases coronary artery atherosclerosis is not understood. We previously used Multidetector computerized tomographic coronary angiography (MDCT) to demonstrate significantly increased noncalcified plaque volume in CS patients. Time-Resolved Phase-Sensitive Dual Inversion Recovery technique (TRAPD-3T) magnetic resonance imaging (MRI) is a recently developed noninvasive tool to examine vessel wall thickness (VWT) of coronary arteries. We postulated that TRAPD MRI might be used as an independent biomarker of coronary artery disease burden in CS. Methods 29 CS patients (AA: 1, CD: 14, EAS: 12, cCS: 2) and 29 age, gender, BMI and Framingham score-matched control patients (CPts) underwent TRAPD-3T MRI of the proximal right coronary artery vessel wall thickness. Prior to MRI, 25 CS patients were untreated and 3 were treated. Vessel wall thickness was measured as the average distance between inner and outer boundaries of the vessel wall. Vessel wall thickness variation was calculated as the standard deviation of these measurements. Circularity was the ratio of the mean thickness over the variation in measurement. The larger the circularity ratio, the more consistent the vessel wall thickness and the less eccentric the blood vessel. All measurements given as mean ± SD. Paired t-tests were used to compare the groups. Results Compared to control subjects, CS patients had significantly higher values for coronary VWT (CS: 1.38 ± 0.19mm, CPts: 1.27 ± 0.15mm; p &amp;lt; 0.015) and VWT variation (CS: 0.19 ± 0.072mm, CPts: 0.14 ± 0.045mm; p &amp;lt;0.002). By contrast, control patients had significantly higher vessel wall circularity compared to CS patients (CS: 9.58 ± 2.65mm, CPts: 8.05 ± 2.65mm; p&amp;lt;0.03). CS pts had less vessel wall circularity, thus increased eccentricity, indicating more advanced atherosclerosis. The degree of hypercortisolism was not associated with Framingham risk score, VWT, variability, or circularity. There was also no significant difference in VWT, variability, or circularity between males and females with hypercortisolism. Conclusion The finding of more advanced atherosclerosis in CS patients compared to age-matched controls suggests that excess cortisol may directly or indirectly promote atherosclerotic plaque formation. Adequate treatment of cardiovascular risk factors along with treatment of underlying hypercortisolism is essential to reducing morbidity and mortality. The TRAPD MR technique has promise as a non-invasive and radiation-free technique to monitor CAD and its prevention/treatment in these patients during and after treatment. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.

Association of coronary artery calcification with clinical and physiological characteristics in patients with COPD: Results from COSYCONET

Chronic obstructive pulmonary disease (COPD) is frequently associated with coronary artery disease (CAD). When considering computed tomography (CT) for COPD phenotyping, coronary vessel wall calcification would be a potential marker of cardiac disease. However, non-ECG gated scans as used in COPD monitoring do not comply with established quantitative approaches using ECG-triggered CT and the Agatston score. We studied the diagnostic potential of Agatston scores from non-triggered scans for cardiac disease.The study population was a sub-group of the COPD cohort COSYCONET that underwent CT scanning in addition to comprehensive clinical assessments, echocardiographic data and physician-based diagnoses of comorbidities. Agatston scores from non-contrast enhanced, non-triggered CT were used to identify a cut-off value for CAD via ROC analysis.399 patients were included (152 female, mean age 66.0 ± 8.2 y). In terms of CAD, an Agatston score ≥1500 AU performed best (AUC 0.765; 95% CI: 0.700, 0.831) and was superior to the conventional cut-off value (400 AU). Using this value for defining groups, there were differences (p < 0.05) in lung function, left atrial diameter and left ventricular end-systolic diameter as well as CT-determined central airway wall thickness pointing towards a bronchitis phenotype. In multivariate analysis, BMI, hyperlipidemia, arterial hypertension, GOLD D (p < 0.05) but particularly Agatston score ≥1500 AU (Odds ratio 10.5; 95% CI: 4.8; 22.6)) were predictors of CAD.We conclude that in COPD patients, Agatston scores derived from non-ECG gated CT showed a much higher cut-off value (1500 AU) for actionable coronary artery disease than the score derived from ECG-triggered CT in cardiology patients.

A Deep Learning-based Method to Extract Lumen and Media-Adventitia in Intravascular Ultrasound Images.

Intravascular ultrasound (IVUS) imaging allows direct visualization of the coronary vessel wall and is suitable for assessing atherosclerosis and the degree of stenosis. Accurate segmentation and lumen and median-adventitia (MA) measurements from IVUS are essential for such a successful clinical evaluation. However, current automated segmentation by commercial software relies on manual corrections, which is time-consuming and user-dependent. We aim to develop a deep learning-based method using an encoder-decoder deep architecture to automatically and accurately extract both lumen and MA border. Inspired by the dual-path design of the state-of-the-art model IVUS-Net, our method named IVUS-U-Net++ achieved an extension of the U-Net++ model. More specifically, a feature pyramid network was added to the U-Net++ model, enabling the utilization of feature maps at different scales. Following the segmentation, the Pearson correlation and Bland-Altman analyses were performed to evaluate the correlations of 12 clinical parameters measured from our segmentation results and the ground truth. A dataset with 1746 IVUS images from 18 patients was used for training and testing. Our segmentation model at the patient level achieved a Jaccard measure (JM) of 0.9080 ± 0.0321 and a Hausdorff distance (HD) of 0.1484 ± 0.1584 mm for the lumen border; it achieved a JM of 0.9199 ± 0.0370 and an HD of 0.1781 ± 0.1906 mm for the MA border. The 12 clinical parameters measured from our segmentation results agreed well with those from the ground truth (all p-values are smaller than .01). Our proposed method shows great promise for its clinical use in IVUS segmentation.

Reproducibility between three-dimensional turbo spin-echo and two-dimensional dual inversion recovery turbo spin-echo for coronary vessel wall imaging in Kawasaki disease

Magnetic resonance vessel wall imaging is desirable for evaluating Kawasaki disease (KD)-associated coronary arterial lesions. To evaluate the reproducibility of three-dimensional turbo spin-echo (3D-TSE) and two-dimensional dual inversion-recovery turbo spin-echo (2D-DIR-TSE) for coronary vessel wall imaging in KD. Ten patients were prospectively enrolled. Coronary vessel wall imaging with axial-slice orientation 3D-TSE and 2D-DIR-TSE were acquired for cross-sectional images in aneurysmal and normal regions. Lumen area (LA), wall area (WA), and normalized wall index (NWI) of cross-sectional images were measured in both regions. Reproducibility between 3D-TSE and 2D-DIR-TSE was evaluated via intraclass correlation coefficients (ICCs) and Bland–Altman plots. 48 points (aneurysmal, 27; normal, 21) were evaluated. There were high ICCs between 3D-TSE and 2D-DIR-TSE in LA (0.95) and WA (0.95). In aneurysmal regions, 95% limits of agreement were LA, WA, and NWI of − 29.9 to 30.4 mm2, − 18.8 to 15.0 mm2, and − 0.22 to 0.20, respectively. In normal regions, the 95% limits of agreement were LA, WA, and NWI of − 4.44 to 4.38 mm2, − 3.51 to 4.30 mm2, and − 0.14 to 0.16, respectively. No fixed and proportional biases between 3D-TSE and 2D-DIR-TSE images in aneurysmal and normal regions were noted. 3D-TSE was reproducible with conventional 2D-DIR-TSE for coronary vessel wall assessment on KD.

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

BackgroundClinical reads of coronary computed tomography angiography (CTA), especially by less experienced readers, may result in overestimation of coronary artery disease stenosis severity compared with expert interpretation. Artificial intelligence (AI)-based solutions applied to coronary CTA may overcome these limitations. ObjectivesThis study compared the performance for detection and grading of coronary stenoses using artificial intelligence–enabled quantitative coronary computed tomography (AI-QCT) angiography analyses to core lab–interpreted coronary CTA, core lab quantitative coronary angiography (QCA), and invasive fractional flow reserve (FFR). MethodsCoronary CTA, FFR, and QCA data from 303 stable patients (64 ± 10 years of age, 71% male) from the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia) trial were retrospectively analyzed using an Food and Drug Administration–cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. ResultsDisease prevalence was high, with 32.0%, 35.0%, 21.0%, and 13.0% demonstrating ≥50% stenosis in 0, 1, 2, and 3 coronary vessel territories, respectively. Average AI-QCT analysis time was 10.3 ± 2.7 minutes. AI-QCT evaluation demonstrated per-patient sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 94%, 68%, 81%, 90%, and 84%, respectively, for ≥50% stenosis, and of 94%, 82%, 69%, 97%, and 86%, respectively, for detection of ≥70% stenosis. There was high correlation between stenosis detected on AI-QCT evaluation vs QCA on a per-vessel and per-patient basis (intraclass correlation coefficient = 0.73 and 0.73, respectively; P < 0.001 for both). False positive AI-QCT findings were noted in in 62 of 848 (7.3%) vessels (stenosis of ≥70% by AI-QCT and QCA of <70%); however, 41 (66.1%) of these had an FFR of <0.8. ConclusionsA novel AI-based evaluation of coronary CTA enables rapid and accurate identification and exclusion of high-grade stenosis and with close agreement to blinded, core lab–interpreted quantitative coronary angiography. (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia [CREDENCE]; NCT02173275)

The effect of scan and patient parameters on the diagnostic performance of AI for detecting coronary stenosis on coronary CT angiography

ObjectivesTo determine whether coronary computed tomography angiography (CCTA) scanning, scan preparation, contrast, and patient based parameters influence the diagnostic performance of an artificial intelligence (AI) based analysis software for identifying coronary lesions with ≥50% stenosis. BackgroundCCTA is a noninvasive imaging modality that provides diagnostic and prognostic benefit to patients with coronary artery disease (CAD). The use of AI enabled quantitative CCTA (AI-QCT) analysis software enhances our diagnostic and prognostic ability, however, it is currently unclear whether software performance is influenced by CCTA scanning parameters. MethodsCCTA and quantitative coronary CT (QCT) data from 303 stable patients (64 ± 10 years, 71% male) from the derivation arm of the CREDENCE Trial were retrospectively analyzed using an FDA-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. The algorithm's diagnostic performance measures (sensitivity, specificity, and accuracy) for detecting coronary lesions of ≥50% stenosis were determined based on concordance with QCA measurements and subsequently compared across scanning parameters (including scanner vendor, model, single vs dual source, tube voltage, dose length product, gating technique, timing method), scan preparation technique (use of beta blocker, use and dose of nitroglycerin), contrast administration parameters (contrast type, infusion rate, iodine concentration, contrast volume) and patient parameters (heart rate and BMI). ResultsWithin the patient cohort, 13% demonstrated ≥50% stenosis in 3 vessel territories, 21% in 2 vessel territories, 35% in 1 vessel territory while 32% had <50% stenosis in all vessel territories evaluated by QCA. Average AI analysis time was 10.3 ± 2.7 min. On a per vessel basis, there were significant differences only in sensitivity for ≥50% stenosis based on contrast type (iso-osmolar 70.0% vs non isoosmolar 92.1% p = 0.0345) and iodine concentration (<350 mg/ml 70.0%, 350-369 mg/ml 90.0%, 370–400 mg/ml 90.0%, >400 mg/ml 95.2%; p = 0.0287) in the context of low injection flow rates. On a per patient basis there were no significant differences in AI diagnostic performance measures across all measured scanner, scan technique, patient preparation, contrast, and individual patient parameters. ConclusionThe diagnostic performance of AI-QCT analysis software for detecting moderate to high grade stenosis are unaffected by commonly used CCTA scanning parameters and across a range of common scanning, scanner, contrast and patient variables. Condensed abstractAn AI-enabled quantitative CCTA (AI-QCT) analysis software has been validated as an effective tool for the identification, quantification and characterization of coronary plaque and stenosis through comparison to blinded expert readers and quantitative coronary angiography. However, it is unclear whether CCTA screening parameters related to scanner parameters, scan technique, contrast volume and rate, radiation dose, or a patient's BMI or heart rate at time of scan affect the software's diagnostic measures for detection of moderate to high grade stenosis. AI performance measures were unaffected across a broad range of commonly encountered scanner, patient preparation, scan technique, intravenous contrast and patient parameters.

Patch-based Convolutional Neural Network for Atherosclerotic Carotid Plaque Semantic Segmentation

Atherosclerotic plaque deposition within the coronary vessel wall leads to arterial stenosis and if not adequately treated, it may potentially have deteriorating consequences, such as a debilitating stroke, thus making early detection of the most importance. The manual plaque components annotation process is both time and resource consuming, therefore, an automatic and accurate segmentation tool is necessary. The main aim of this paper is to present the model for identification and segmentation of the atherosclerotic plaque components such as lipid core, fibrous and calcified tissue, by using Convolutional Neural Network on patch-based segments of ultrasound images. There was some research done on the topic of plaque components segmentation, but not in ultrasound imaging data. Due to the size of some plaque components being only a couple of millimeters, we argue that training a neural network on smaller image patches will perform better than a classifier based on the whole image. Besides the size of components, this decision is motivated by the observation that plaque components are not uniformly distributed throughout the whole carotid wall and that a locality-sensitive segmentation is likely to obtain better segmentation accuracy. Our model achieved good results in the segmentation of fibrous tissue but had difficulties in the segmentation of lipid and calcified tissue due to the quality of ultrasound images.

Large Coronary Intramural Hematoma Presenting as Acute Coronay Syndrome

Isolated spontaneous coronary intramural hematoma is characterized by a hemorrhage limited to the media–adventitial layers, causing subsequent hematoma formation without visible intimal flaps. Spontaneous isolated intramural hematoma may occur in the absence of associated intimal dissection. It is an infrequent and serious coronary vessel wall pathology with poorly understood underlying pathogenic mechanisms. Affected individuals may present with a broad spectrum of symptoms ranging from acute coronary syndromes (ACS) to cardiogenic shock or even sudden cardiac death. The disease entity causes challenges in terms of both diagnostic and treatment strategy. We report a case of intramural coronary hematoma in a patient presenting with non ST-segment elevation myocardial infarction.

Oxygen-sensitive Magnetic Resonance Imaging: A Noninvasive Step Forward for Diagnosing Vasculopathy in the Cardiac Allograft.

Oxygen-sensitive Magnetic Resonance Imaging: A Noninvasive Step Forward for Diagnosing Vasculopathy in the Cardiac Allograft.

Coronary Computer Tomography Angiography in 2021-Acquisition Protocols, Tips and Tricks and Heading beyond the Possible.

Recent technological advances, together with an increasing body of evidence from randomized trials, have placed coronary computer tomography angiography (CCTA) in the center of the diagnostic workup of patients with coronary artery disease. The method was proven reliable in the diagnosis of relevant coronary artery stenosis. Furthermore, it can identify different stages of the atherosclerotic process, including early atherosclerotic changes of the coronary vessel wall, a quality not met by other non-invasive tests. In addition, newer computational software can measure the hemodynamic relevance (fractional flow reserve) of a certain stenosis. In addition, if required, information related to cardiac and valvular function can be provided with specific protocols. Importantly, recent trials have highlighted the prognostic relevance of CCTA in patients with coronary artery disease, which helped establishing CCTA as the first-line method for the diagnostic work-up of such patients in current guidelines. All this can be gathered in one relatively fast examination with minimal discomfort for the patient and, with newer machines, with very low radiation exposure. Herein, we provide an overview of the current technical aspects, indications, pitfalls, and new horizons with CCTA, providing examples from our own clinical practice.

Imaging of the Pericoronary Adipose Tissue (PCAT) Using Cardiac Computed Tomography: Modern Clinical Implications.

Modern coronary computed tomography angiography (CTA) is the gold standard to visualize the epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT). The EAT is a metabolic active fat depot enclosed by the visceral pericardium and surrounds the coronary arteries. In disease states with increased EAT volume and dysfunctional adipocytes, EAT secretes an increased amount of adipocytokines and the resulting imbalance of proinflammatory and anti-inflammatory mediators potentially causes atherogenic effects on the coronary vessel wall in a paracrine way ("outside-to-inside" signaling). These EAT-induced atherogenic effects are reported to increase the risk for the development of coronary artery disease, myocardial ischemia, high-risk plaque features, and future major adverse cardiac events. Coronary inflammation plays a key role in the development and progression of coronary artery disease; however, its noninvasive detection remains challenging. In future, this clinical dilemma might be changed by the CTA-derived analysis of the PCAT. On the basis of the concept of an "inside-to-outside" signaling between the inflamed coronary vessel wall and the surrounding PCAT recent evidence demonstrates that PCAT computed tomography attenuation especially around the right coronary artery derived from routine CTA is a promising imaging biomarker and "sensor" to noninvasively detect coronary inflammation. This review summarizes the biological and technical principles of CTA-derived PCAT analysis and highlights its clinical implications to improve modern cardiovascular prevention strategies.

Large Coronary Intramural Hematoma Presenting as Acute Coronay Syndrome

Isolated spontaneous coronary intramural hematoma is a unique subset of spontaneous coronary artery dissection that is characterized by a hemorrhage limited to the medial– adventitial layers, causing subsequent hematoma formation without visible intimal flaps. It is infrequent and serious coronary vessel wall pathology, with poorly understood underlying pathogenic mechanisms. Affected individuals may present with a broad spectrum of symptoms ranging from acute coronary syndromes (ACS) to cardiogenic shock or even sudden cardiac death. The disease entity causes challenges in terms of both diagnostics and treatment strategy. We report a case of intramural coronary hematoma in a patient presenting with non ST- -segment elevation myocardial infarction.