Automated Three-dimensional Quantification of Noncalcified Coronary Plaque from Coronary CT Angiography: Comparison with Intravascular US

Dey, Damini; Schepis, Tiziano; Marwan, Mohamed; Slomka, Piotr J.; Berman, Daniel S.; Achenbach, Stephan

doi:10.1148/radiol.10100681

Cited by 187 publications

(123 citation statements)

References 29 publications

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“…195 Moreover, plaque quantification software is in development and could further guide accurate detection of atherosclerotic disease burden. 1253 Several new developments in stress nuclear MPI have occurred, including new radioisotopes: 1) an F18 PET perfusion agent (in Phase III trials), which will allow exercise PET testing; 2) 123 I-beta-methyl-iodophenylpentadecanoic acid SPECT, with the unique ability to document metabolic alterations representing prior ischemic episodes (ie, ischemic memory); and 3) 123 I-labeled meta-iodobenzylguanidine SPECT, which could be helpful for assessment of arrhythmic risk in SIHD patients. 1254 Several new SPECT cameras also have been introduced into the marketplace and offer the opportunity for improved image quality within a substantially shorter time period and with a lower radiation dose.…”

Section: Future Developmentsmentioning

confidence: 99%

2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease

Fihn¹,

Gardin²,

Abrams³

et al. 2012

Circulation

722

441

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Section: Future Developmentsmentioning

confidence: 99%

2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease

Fihn¹,

Gardin²,

Abrams³

et al. 2012

Circulation

722

441

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“…[21][22][23][24] Computer-aided coronary plaque quantification from CTA has been reported using plaque attenuation thresholds. [25][26][27][28] A few studies attempted automatic detection of coronary lesions. [29][30][31][32][33] Detection and quantification of coronary artery lesions are particularly challenging due to limited spatial resolution and coronary artery motion, relatively small plaque size, and complex and variable coronary artery anatomy.…”

Section: Introductionmentioning

confidence: 99%

Structured learning algorithm for detection of nonobstructive and obstructive coronary plaque lesions from computed tomography angiography

et al. 2015

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Abstract. Visual identification of coronary arterial lesion from three-dimensional coronary computed tomography angiography (CTA) remains challenging. We aimed to develop a robust automated algorithm for computer detection of coronary artery lesions by machine learning techniques. A structured learning technique is proposed to detect all coronary arterial lesions with stenosis ≥25%. Our algorithm consists of two stages: (1) two independent base decisions indicating the existence of lesions in each arterial segment and (b) the final decision made by combining the base decisions. One of the base decisions is the support vector machine (SVM) based learning algorithm, which divides each artery into small volume patches and integrates several quantitative geometric and shape features for arterial lesions in each small volume patch by SVM algorithm. The other base decision is the formula-based analytic method. The final decision in the first stage applies SVM-based decision fusion to combine the two base decisions in the second stage. The proposed algorithm was applied to 42 CTA patient datasets, acquired with dual-source CT, where 21 datasets had 45 lesions with stenosis ≥25%. Visual identification of lesions with stenosis ≥25% by three expert readers, using consensus reading, was considered as a reference standard. Our method performed with high sensitivity (93%), specificity (95%), and accuracy (94%), with receiver operator characteristic area under the curve of 0.94. The proposed algorithm shows promising results in the automated detection of obstructive and nonobstructive lesions from CTA.

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“…The possible influence of the passage of CM through the specimens should have been minimised by saline flushing. In the future, higher spatial resolution of new CT scanners [29], novel automated software [30] and revolutionary contrast agents [31] may allow improved clinical coronary plaque imaging. The advent of radiation dose-saving CT scanners [32] could also promote the in vivo assessment of the treatment effect on coronary plaques [33].…”

Section: Discussionmentioning

confidence: 99%

Comparison of iodinated contrast media for the assessment of atherosclerotic plaque attenuation values by CT coronary angiography: observations in anex vivomodel

Grutta¹,

Gallucci²,

Gentile³

et al. 2013

BJR

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Objective: To compare the influence of different iodinated contrast media with several dilutions on plaque attenuation in an ex vivo coronary model studied by multislice CT coronary angiography. Methods: In six ex vivo left anterior descending coronary arteries immersed in oil, CT (slices/collimation 6460.625 mm, temporal resolution 210 ms, pitch 0.2) was performed after intracoronary injection of a saline solution, and solutions of a dimeric isosmolar contrast medium (Iodixanol 320 mgI ml 21) and a monomeric high-iodinated contrast medium (Iomeprol 400 mgI ml Invasive conventional coronary angiography is considered the standard method for the evaluation of vascular lumen and stenoses of coronary artery disease (CAD). However, it is a technique that does not allow direct assessment of the coronary artery wall and plaque composition, which is considered to be a pivotal determinant of acute coronary events [1][2][3]. Intravascular ultrasound (IVUS) allows accurate qualitative and quantitative assessment of coronary atherosclerotic plaques [4]. However, IVUS is an invasive and expensive technique. CT coronary angiography (CTCA) is now widely implemented in the clinical routine [5], especially in patients at intermediate pretest probability of CAD [6]. Several studies comparing CTCA with IVUS have demonstrated the high potential of CTCA for coronary plaque imaging purposes [7][8][9]. It has been shown that CTCA has the potential to detect atherosclerotic plaques [10,11], to quantify their volumes [12], to characterise their composition (based on the X-ray attenuating properties of each structure [13]), and to assess positive remodelling of walls [14]. CTCA may non-invasively provide information on the total plaque burden (calcified and non-calcified components) for individual patients with suspected CAD [15].High-iodinated contrast media (CM) are recommended for optimal coronary contrast intensity of CTCA [16]. However, several technical parameters, including CM influence, and intrinsic limitations may affect the attenuation measurements of coronary plaques [17][18][19][20][21][22]. The aim of our study was to compare two different CM with several dilutions of iodine load in the setting of coronary plaque assessment in an ex vivo model by means of CTCA.

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Automated Three-dimensional Quantification of Noncalcified Coronary Plaque from Coronary CT Angiography: Comparison with Intravascular US

Abstract: Automated scan-specific threshold level-based quantification of plaque components from coronary CT angiography allows rapid, accurate measurement of noncalcified plaque volumes, compared with intravascular US, and requires a fraction of the time needed for manual analysis.

Cited by 187 publications

References 29 publications

2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease

2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease

Structured learning algorithm for detection of nonobstructive and obstructive coronary plaque lesions from computed tomography angiography

Comparison of iodinated contrast media for the assessment of atherosclerotic plaque attenuation values by CT coronary angiography: observations in anex vivomodel

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