Assessment of Remote Myocardium Heterogeneity in Patients with Ventricular Tachycardia Using Texture Analysis of Late Iodine Enhancement (LIE) Cardiac Computed Tomography (cCT) Images

Esposito, Antonio; Palmisano, Anna; Antunes, Sofia; Colantoni, Caterina; Rancoita, Paola Maria Vittoria; Vignale, Davide; Baratto, Francesca; Bella, Paolo Della; Maschio, Alessandro Del; Cobelli, Francesco De

doi:10.1007/s11307-018-1175-1

Cited by 22 publications

(10 citation statements)

References 38 publications

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“…Our results confirmed the feasibility and effectiveness of tissue characterization at CT using LCE (15,16) and ECV (17,18), with good agreement with cardiac MRI (15,31). LCE CT demonstrated a known tendency to underestimate the extension of scar due to the limited LCE CNR compared with that of LGE MRI, in agreement with previous studies (15).…”

Section: Discussionsupporting

confidence: 90%

“…In the past years, technologic development has positively impacted cardiac CT capabilities from a pure angiographic tool to a complete diagnostic modality able to detect wall motion abnormalities (14) and characterize the myocardium, identifying myocardial scars or necrosis (15,16) and quantifying the myocardial extracellular volume fraction (ECV) (17,18). All these features are considered the cornerstones of differential diagnosis among acute infarction, myocarditis, takotsubo cardiomyopathy, and other causes of acute myocardial injury according to the cardiac MRI literature (19).…”

Section: Ct Protocolmentioning

confidence: 99%

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Myocardial Late Contrast Enhancement CT in Troponin-Positive Acute Chest Pain Syndrome

Palmisano¹,

Vignale²,

Tadić³

et al. 2022

Radiology

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cute chest pain or anginal equivalents associated with mild troponin rise remain a diagnostic challenge, particularly in patients at low to intermediate risk for acute coronary syndrome. Coronary CT angiography can be used to safely triage these patients (1,2). In previous large multicenter trials with participants with acute chest pain at low to intermediate pretest risk of acute coronary syndrome, coronary CT angiography was associated with higher detection of coronary artery disease (CAD) (3), shorter length of stay (3,4), and higher rate of discharge (3,4) compared with the standard of care, without an increase in major adverse events at 28 days (4) and at a longer follow-up (5). Acute aortic syndrome, pulmonary embolism, and CAD can be simultaneously ruled out with use of a triple-rule-out (TRO) CT protocol (6,7). However, a TRO CT study cannot help identify nonvascular causes of acute myocardial injury (8). In patients with troponin-positive acute chest pain and unobstructed coronary arteries, cardiac MRI was found to provide a diagnosis in 74%-95% (9-12), identifying myocarditis, takotsubo cardiomyopathy, and myocardial infarction with nonobstructed coronary arteries as the most frequent causes of symptoms and alteration in cardiac biologic markers (10-12). Cardiac MRI was found to change the Background: Acute chest pain with mild troponin rise and inconclusive diagnosis after clinical evaluation represents a diagnostic challenge. Triple-rule-out (TRO) CT may exclude coronary artery disease (CAD), as well as acute aortic syndrome and pulmonary embolism, but cannot help identify other causes of myocardial injury.Purpose: To investigate the diagnostic value of a comprehensive CT protocol including both an angiographic and a late contrast enhancement (LCE) scan in participants with troponin-positive acute chest pain. Materials and Methods:In this prospective study, consecutive patients with troponin-positive acute chest pain or anginal equivalent and inconclusive diagnosis after clinical evaluation (symptoms, markers, electrocardiography, and echocardiography) who underwent TRO CT between June 2018 and September 2020 were enrolled. TRO CT was performed to evaluate the presence of obstructive CAD (stenosis 50%), acute aortic syndrome, and pulmonary embolism. If the findings on the TRO CT scan were negative, an LCE CT scan was acquired after 10 minutes to assess the presence and pattern of scar and quantify the myocardial extracellular volume fraction. CT-based diagnoses were compared with diagnoses obtained with reference standard methods, including invasive coronary angiography, cardiac MRI, and endomyocardial biopsy.Results: Eighty-four patients (median age, 69 years [interquartile range, 50-77 years]; 45 men) were enrolled. TRO CT helped identify obstructive CAD in 35 participants (42%), acute aortic syndrome in one (1.2%), and pulmonary embolism in six (7.1%). LCE CT scans were acquired in the remaining 42 participants. The following diagnoses were reached with use of LCE CT: myocarditis (22 of 42 partici...

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Section: Discussionsupporting

confidence: 90%

Section: Ct Protocolmentioning

confidence: 99%

Myocardial Late Contrast Enhancement CT in Troponin-Positive Acute Chest Pain Syndrome

Palmisano¹,

Vignale²,

Tadić³

et al. 2022

Radiology

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“…They enrolled 161 patients and used logistic regression to create a classification model which proved to have high diagnostic power (AUC = 0.81 in the training set and 0.78 in the testing cohort). Esposito et al used TA to detect extracellular matrix changes in the myocardium of patients with ventricular tachycardia, analyzing late iodine enhancement images and identifying different phenotypes of remodeling [48]. Similarly, the analysis of late iodine enhancement with ML may also be useful in distinguishing cardiac sarcoidosis from non-ischemic cardiomyopathies [49].…”

Section: Coronary Computed Tomography Angiographymentioning

confidence: 99%

Radiomics in Cardiovascular Disease Imaging: from Pixels to the Heart of the Problem

Spadarella

Perillo

Ugga

et al. 2022

Curr Cardiovasc Imaging Rep

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Purpose of Review This review of the literature aims to present potential applications of radiomics in cardiovascular radiology and, in particular, in cardiac imaging. Recent Findings Radiomics and machine learning represent a technological innovation which may be used to extract and analyze quantitative features from medical images. They aid in detecting hidden pattern in medical data, possibly leading to new insights in pathophysiology of different medical conditions. In the recent literature, radiomics and machine learning have been investigated for numerous potential applications in cardiovascular imaging. They have been proposed to improve image acquisition and reconstruction, for anatomical structure automated segmentation or automated characterization of cardiologic diseases. Summary The number of applications for radiomics and machine learning is continuing to rise, even though methodological and implementation issues still limit their use in daily practice. In the long term, they may have a positive impact in patient management.

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“…5 Radiomic texture analysis of late iodine enhancement on CT images reflects left ventricle remodeling and systolic-diastolic function, and may help to identify different patterns of structure remodeling. 6 Coronary plaques are small and have a limited number of voxels, and are therefore very challenging for image analysis. Kolossvary et al demonstrated that the voxels of a coronary plaque were sufficient to perform a radiomic analysis, and found that 21% of radiomic parameters were significantly different between plaques with and without the napkin-ring sign and that radiomic parameters had a higher area under curve (AUC) than conventional parameters (0.92 vs 0.75).…”

Section: Technical Aspects Radiomicsmentioning

confidence: 99%

Development and application of artificial intelligence in cardiac imaging

Jiang

Guo²,

et al. 2020

The British Journal of Radiology

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In this review, we describe the technical aspects of artificial intelligence (AI) in cardiac imaging, starting with radiomics, basic algorithms of deep learning and application tasks of algorithms, until recently the availability of the public database. Subsequently, we conducted a systematic literature search for recently published clinically relevant studies on AI in cardiac imaging. As a result, 24 and 14 studies using CT and MRI, respectively, were included and summarized. From these studies, it can be concluded that AI is widely applied in cardiac applications in the clinic, including coronary calcium scoring, coronary CT angiography, fractional flow reserve CT, plaque analysis, left ventricular myocardium analysis, diagnosis of myocardial infarction, prognosis of coronary artery disease, assessment of cardiac function, and diagnosis and prognosis of cardiomyopathy. These advancements show that AI has a promising prospect in cardiac imaging.

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Assessment of Remote Myocardium Heterogeneity in Patients with Ventricular Tachycardia Using Texture Analysis of Late Iodine Enhancement (LIE) Cardiac Computed Tomography (cCT) Images

Cited by 22 publications

References 38 publications

Myocardial Late Contrast Enhancement CT in Troponin-Positive Acute Chest Pain Syndrome

Myocardial Late Contrast Enhancement CT in Troponin-Positive Acute Chest Pain Syndrome

Radiomics in Cardiovascular Disease Imaging: from Pixels to the Heart of the Problem

Development and application of artificial intelligence in cardiac imaging

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