Assessment of nonstenotic coronary lesions by 64-slice multidetector computed tomography in comparison to intravascular ultrasound: Evaluation of nonculprit coronary lesions

Petranović, Milena; Soni, Anand; Bezzera, Hiram; Loureiro, Ricardo; Sarwar, Ammar; Raffel, Corey; Pomerantsev, Eugene; Jang, Ik–Kyung; Brady, Thomas J.; Achenbach, Stephan; Cury, Ricardo C.

doi:10.1016/j.jcct.2008.12.005

Cited by 80 publications

(26 citation statements)

References 21 publications

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“…3, the cumulative interobserver variability for these noncalcified lesions was less than 28.5%. This interobserver variability of lesion volume was better or comparable to other studies of MDCT-based plaque assessment [4,18]. With regard to the higher interobserver variability associated with quantifying calcified lesions, we feel that those measurements are of limited clinical value given the existence of well validated and readily available software applications for the quantification of coronary calcium [19].…”

Section: Discussionsupporting

confidence: 67%

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Coronary plaque imaging with 256-slice multidetector computed tomography: interobserver variability of volumetric lesion parameters with semiautomatic plaque analysis software

Klass

Kleinhans

Walker

et al. 2010

Int J Cardiovasc Imaging

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The purpose of this study was to evaluate the potential clinical value of coronary plaque imaging with a new generation CT scanner and the interobserver variability of coronary plaque assessment with a new semiautomatic plaque analysis application. Thirty-five isolated plaques of the left anterior descending coronary artery from 35 patients were evaluated with a new semiautomatic plaque analysis application. All patients were scanned with a 256-slice MDCT scanner (Brilliance iCT, Philips Healthcare, Cleveland OH, USA). Two independent observers evaluated lesion volume, maximum plaque burden, lesion CT number mean and standard deviation, and relative lesion composition. We found 10 noncalcified, 16 mixed, and 9 calcified lesions in our study cohort. Relative interobserver bias and variability for lesion volume were -37%, -13%, -49%, -44% and 28%, 16%, 37%, and 90% for all, noncalcified, mixed, and calcified lesions, respectively. Absolute interobserver bias and variability for relative lesion composition were 1.2%, 0.5%, 1.5%, 1.3% and 3.3%, 4.5%, 7.0%, and 4.4% for all, noncalcified, mixed, and calcified lesions, respectively. While mixed and calcified lesions demonstrated a high degree of lesion volume interobserver variability, noncalcified lesions had a lower degree of lesion volume interobserver variability. In addition, relative noncalcified lesion composition had a very low interobserver variability. Therefore, there may a role for MDCT in serial noncalcified plaque assessment with semiautomatic analysis software.

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Section: Discussionsupporting

confidence: 67%

“…Previous studies have shown the reproducibility of MDCT-derived plaque indices with those from intravascular ultrasound (IVUS) [3,4]. At the same time, retrospective studies have shown an association between plaques containing noncalcified components and presentation with acute coronary syndrome [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Coronary plaque imaging with 256-slice multidetector computed tomography: interobserver variability of volumetric lesion parameters with semiautomatic plaque analysis software

Klass

Kleinhans

Walker

et al. 2010

Int J Cardiovasc Imaging

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“…[2][3][4][5][6] Beyond stenosis, CTA also permits noninvasive assessment of atherosclerotic plaque and coronary artery remodeling. [7][8][9] Current clinical assessment of CTA and lesion detection is based on visual analysis, which is time consuming and subject to observer variability, 10 although computer-aided extraction of the coronary arteries is often employed. 11 It was reported that acquiring expertise in CTA interpretation may take more than a year.…”

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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“…Coronary CTA derived information on the presence of CAD provides valuable prognostic information [2][3][4]. Moreover, coronary plaques may be non-invasively characterized by coronary CTA [5][6][7]. Severity of CAD may be estimated by various plaque burden models [3].…”

Section: Introductionmentioning

confidence: 99%

Reproducibility of coronary plaque detection and characterization using low radiation dose coronary computed tomographic angiography in patients with intermediate likelihood of coronary artery disease (ReSCAN study)

Øvrehus

Marwan

Bøtker

et al. 2011

Int J Cardiovasc Imaging

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The purpose of this study is to evaluate the interscan, interobserver and intraobserver agreement for coronary plaque detection, and characterization using low radiation dose high-pitch spiral acquisition coronary CT angiography (CTA). Two experienced observers independently evaluated coronary CTA datasets from 50 consecutive patients undergoing two 128-slice dual source CT scans within 12 days. Mean (±SD) estimated radiation exposure was 1.5 ± 0.2 mSv per scan. Observers recorded the presence and characterization of coronary plaques as non-calcified or calcified. A "segment involvement score" (SIS) was computed by summing the numbers of segments with any coronary plaque per patient. Reproducibility was assessed using kappa (κ) statistics, paired t test and Bland-Altman analyses. Interscan, interobserver, and intraobserver agreement (κ-values) for detection of any or calcified plaques were 83-94% (κ-values 0.57-0.85), and 67-84% (0.31-0.67) for non-calcified plaques on a patient level. No significant difference was observed in mean interscan or interobserver SIS. Mean (95% CI) intraobserver SIS difference was -0.88 (-1.25; -0.51), P < 0.001, with limits of agreement from -4.7 to 2.9. Low radiation dose high-pitch coronary CTA permits detection of any or calcified plaques with high interscan, interobserver, intraobserver agreement. However, variability for the detection of non-calcified plaque is substantial.

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Assessment of nonstenotic coronary lesions by 64-slice multidetector computed tomography in comparison to intravascular ultrasound: Evaluation of nonculprit coronary lesions

Cited by 80 publications

References 21 publications

Coronary plaque imaging with 256-slice multidetector computed tomography: interobserver variability of volumetric lesion parameters with semiautomatic plaque analysis software

Coronary plaque imaging with 256-slice multidetector computed tomography: interobserver variability of volumetric lesion parameters with semiautomatic plaque analysis software

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

Reproducibility of coronary plaque detection and characterization using low radiation dose coronary computed tomographic angiography in patients with intermediate likelihood of coronary artery disease (ReSCAN study)

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