70 research outputs found

    Identification of noncalcified coronary plaque characteristics using machine learning radiomic analysis of non-contrast high-resolution computed tomography

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    Background: Novel imaging and analysis techniques may offer the ability to detect noncalcified or high-risk coronary plaques on a non-contrast computer tomography (CT) scan, advancing cardiovascular diagnostics.Aims: We aimed to explore whether machine learning (ML) radiomic analysis of low-dose high-resolution non-contrast electrocardiographically (ECG) gated cardiac CT scan allows for the identification of noncalcified coronary plaque characteristics.Methods: We prospectively enrolled 125 patients with noncalcified plaques and adverse plaque characteristics (APC) and 25 controls without visible atherosclerosis on coronary CT angiography (CCTA). All patients underwent non-contrast CT exam before CCTA. Four hundred and nineteen radiomic features were calculated to identify the presence of any coronary artery disease (CAD), obstructive CAD (stenosis >50%), plaque with ā‰„2 APC, degree of calcification, and specific APCs. ML models were trained on a training set (917 segmentations) and tested (validation) on a separate set (292 segmentations).Results: Among the radiomic features, 88.3% were associated with a plaque, 0.9% with obstructive CAD, and 76.4% with the presence of at least two APCs. Overall, 80.2%, 88.5%, and 36.5%, of features were associated with calcified, partially calcified, and noncalcified plaques, respectively. Regarding APCs, 61.1%, 61.8%, 84.2%, and 61.3% of features were associated with low attenuation (LAP), napkin-ring sign (NRS), spotty calcification (SC), and positive remodeling (PR), respectively. ML models outperformed conventional methods for the presence of plaque obstructive stenosis, and the presence of 2 APCs, as well as for noncalcified plaques and partially calcified plaques, but not for calcified plaques. ML models also significantly outperformed identification of LAP and PR, but neither NRS nor SC.Conclusion: Radiomic analysis of non-contrast cardiac CT exams may allow for the identification of specific noncalcified coronary plaque characteristics displaying the potential for future clinical applications

    Multimodality imaging:Bird's eye view from The European Society of Cardiology Congress 2018 Munich, August 25-29, 2018

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    At the European Society of Cardiology (ESC) congress of this year 2018, held in Munich from August 25th to 29th, 4594 abstracts were presented. Of those, 423 (10.8%) belonged to an imaging category. Experts in echocardiography (VD), cardiovascular magnetic resonance (CMR) (CBD), nuclear imaging (OG), and cardiac computed tomography (CT) (PMH) have selected the abstracts in their areas of expertise that were of most interest to them and are summarized in this bird's eye view from this ESC meeting. These abstracts were integrated by one of the Editors of the Journal (JB).Cardiolog

    Classification of human coronary atherosclerotic plaques with T1, T2 and Ultrashort TE MRI

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    Multicontrast MRI with T1, T2 and Ultrashort TE (UTE) sequences is used to image atherosclerotic plaque in human coronary arteries. MRI classification of the plaques is compared with their histological classification and found to correlate extremely well. The addition of UTE MRI adds significant value to the imaging of human coronary artery plaque by MRI

    Left ventricular remodeling following myocardial infarction revealed with a quantitative diffusion MRI tractography framework

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    A cardiac-tailored framework for 3D Diffusion Tensor MRI tractography is developed and used to characterize myofiber architecture in normal and remodeled myocardium. We show that myofibers in the subepicardium of the remote infarct zone become less oblique (more circumferential) as the heart dilates and remodels. This fiber realignment may play an important role in the loss of contractile function in the remote zone over time

    Laterality of deep white matter hyperintensities correlates with basilar artery bending and vertebral artery dominance

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    Aim To investigate whether vertebrobasilar geometry contributes to the presence, severity, and laterality of white matter hyperintensities (WMH). Methods We retrospectively reviewed 290 cerebral scans of patients who underwent time-of-flight and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) between 2017 and 2018. WMH were counted, localized, and grouped according to laterality on the FLAIR sequence. A 3D mesh of the posterior circulation was reconstructed (with ITK SNAP software) and the morphology of the vertebrobasilar system analyzed with an in-house software written in Python. Results Patients were assigned into a group with WMH (n=204) and a group without WMH (n=86). The severity of WMH burden was mainly affected by age and hypertension, while the localization of the WMH (or laterality) was mainly affected by the vertebrobasilar system morphology. Basilar artery morphology only affected the parietooccipital region significantly if both posterior communicating arteries were hypoplastic or absent. The dominant vertebral artery and basilar artery curve had an opposite directional relationship. Conclusions An unequal vertebral artery flow is an important hemodynamic contributor to basilar bending. Increased basilar artery curvature and increased infratentorial WMH burden may signal inadequate blood flow and predict cerebrovascular events

    Radiomics of pericardial fat: a new frontier in heart failure discrimination and prediction

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    Objectives: To use pericardial adipose tissue (PAT) radiomics phenotyping to differentiate existing and predict future heart failure (HF) cases in the UK Biobank. Methods: PAT segmentations were derived from cardiovascular magnetic resonance (CMR) studies using an automated quality-controlled model to define the region-of-interest for radiomics analysis. Prevalent (present at time of imaging) and incident (first occurrence after imaging) HF were ascertained using health record linkage. We created balanced cohorts of non-HF individuals for comparison. PyRadiomics was utilised to extract 104 radiomics features, of which 28 were chosen after excluding highly correlated ones (0.8). These features, plus sex and age, served as predictors in binary classification models trained separately to detect (1) prevalent and (2) incident HF. We tested seven modeling methods using tenfold nested cross-validation and examined feature importance with explainability methods. Results: We studied 1204 participants in total, 297 participants with prevalent (60 Ā± 7 years, 21% female) and 305 with incident (61 Ā± 6 years, 32% female) HF, and an equal number of non-HF comparators. We achieved good discriminative performance for both prevalent (voting classifier; AUC: 0.76; F1 score: 0.70) and incident (light gradient boosting machine: AUC: 0.74; F1 score: 0.68) HF. Our radiomics models showed marginally better performance compared to PAT area alone. Increased PAT size (maximum 2D diameter in a given column or slice) and texture heterogeneity (sum entropy) were important features for prevalent and incident HF classification models. Conclusions: The amount and character of PAT discriminate individuals with prevalent HF and predict incidence of future HF. Clinical relevance statement: This study presents an innovative application of pericardial adipose tissue (PAT) radiomics phenotyping as a predictive tool for heart failure (HF), a major public health concern. By leveraging advanced machine learning methods, the research uncovers that the quantity and characteristics of PAT can be used to identify existing cases of HF and predict future occurrences. The enhanced performance of these radiomics models over PAT area alone supports the potential for better personalised care through earlier detection and prevention of HF. Key Points: ā€¢PAT radiomics applied to CMR was used for the first time to derive binary machine learning classifiers to develop models for discrimination of prevalence and prediction of incident heart failure. ā€¢Models using PAT area provided acceptable discrimination between cases of prevalent or incident heart failure and comparator groups. ā€¢An increased PAT volume (increased diameter using shape features) and greater texture heterogeneity captured by radiomics texture features (increased sum entropy) can be used as an additional classifier marker for heart failure

    Photon-counting computed tomography in the assessment of rheumatoid arthritis-associated interstitial lung disease: an initial experience

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    PURPOSEInterstitial lung disease (ILD) accounts for a significant proportion of mortality and morbidity in patients with rheumatoid arthritis (RA). The aim of this cross-sectional study is to evaluate the performance of novel photon-counting detector computed tomography (PCD-CT) in the detection of pulmonary parenchymal involvement.METHODSSixty-one patients with RA without a previous definitive diagnosis of ILD underwent high-resolution (HR) (0.4 mm slice thickness) and ultra-high-resolution (UHR) (0.2 mm slice thickness) PCDCT examination. The extent of interstitial abnormalities [ground-glass opacity (GGO), reticulation, bronchiectasis, and honeycombing] were scored in each lobe using a Likert-type scale. Total ILD scores were calculated as the sum of scores from all lobes.RESULTSReticulation and bronchiectasis scores were higher in the UHR measurements taken compared with the HR protocol [median (quartile 1, quartile 3): 2 (0, 3.5) vs. 0 (0, 3), P < 0.001 and 2 (0, 2) vs. 0 (0, 2), P < 0.001, respectively]; however, GGO and honeycombing scores did not differ [2 (2, 4) vs. 2 (2, 4), P = 0.944 and 0 (0, 0) vs. 0 (0, 0), P = 0.641, respectively]. Total ILD scores from both HR and UHR scans showed a mild negative correlation in diffusion capacity for carbon monoxide (HR: r = ā€“0.297, P = 0.034; UHR: r = ā€“0.294, P = 0.036). The pattern of lung parenchymal involvement did not differ significantly between the two protocols. The HR protocol had significantly lower volume CT dose index [0.67 (0.69, 1.06) mGy], total dose length product [29 (24.48, 33.2) mGy*cm] compared with UHR scans [8.18 (6.80, 9.23) mGy, P < 0.001 and 250 (218, 305) mGy*cm, P < 0.001].CONCLUSIONUHR PCD-CT provides more detailed information on ILD in patients with RA than low-dose HR PCDCT. HR PCD-CT image acquisition with a low effective radiation dose may serve as a valuable, low-radiation screening tool in the selection of patients for further, higher-dose UHR PCD-CT screening

    Standards for quantitative assessments by coronary computed tomography angiography (CCTA)

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    In current clinical practice, qualitative or semi-quantitative measures are primarily used to report coronary artery disease on cardiac CT. With advancements in cardiac CT technology and automated post-processing tools, quantitative measures of coronary disease severity have become more broadly available. Quantitative coronary CT angiography has great potential value for clinical management of patients, but also for research. This document aims to provide definitions and standards for the performance and reporting of quantitative measures of coronary artery disease by cardiac CT.</p
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