Dataset Information

Non-contrast cardiac CT-based quantitative evaluation of epicardial and intra-thoracic fat in healthy, recently menopausal women: Reproducibility data from the Kronos Early Estrogen Prevention Study.

ABSTRACT:

Background

Cardiac fat is emerging as an important parameter for cardiovascular risk stratification. Accurate and reproducible volumetric measurements can facilitate in the serial assessment of cardiac fat by computed tomography (CT). We assessed the intra- and inter-observer variability of cardiac fat volumetric measurements using a semi-automated CT software.

Methods

We used non-contrast coronary calcium CT scans to quantify epicardial and intra-thoracic fat volumes. Two expert readers analyzed baseline and follow up CT scans of 45 subjects by using a semi-automated CT software (QFAT 2.0, Cedars Sinai-Medical Center). Correlation and Bland-Altman analysis was performed for both intra- and inter-observer comparisons for each cardiac fat type.

Results

The intra-observer correlation coefficients ranged between 0.86 to 0.99 and 0.87 to 0.99 for epicardial (median fat per reader (cm³) 20.9 to 25.7) and intra-thoracic (median fat per reader (cm³) 27.1 to 31.6) fat volumes respectively, with no significant differences between individual data points (all p?>?0.38). The inter-observer correlation coefficient was 0.99 (p?3 with 95% confidence intervals (0.22,1.7) and -1.8?cm³ for inter-observer, with 95% CI (-2.9, -0.69). Bland-Altman plots for intra-thoracic fat measurements were similarly impressive for both inter- and intra-observer reads.

Conclusions

Our data showed that measuring epicardial and intra-thoracic fat volumes by CT using a semi-automated software has excellent intra-observer and inter-observer reliability. Cardiac fat volumes can be obtained easily and reproducibly from routine calcium scoring scans and may help in assessing cardiovascular risk.

Clinical trial registration

URL: https://www.clinicaltrials.gov. Unique identifier: NCT00154180; Keywords: Epicardial fat volume; intra-thoracic fat volume; computed tomography; intra-observer; inter-observer.

SUBMITTER: Jayawardena E

PROVIDER: S-EPMC6829052 | biostudies-literature | 2020 Jan - Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Non-contrast cardiac CT-based quantitative evaluation of epicardial and intra-thoracic fat in healthy, recently menopausal women: Reproducibility data from the Kronos Early Estrogen Prevention Study.

Jayawardena Eranthi E Li Dong D Nakanishi Rine R Dey Damini D Dailing Christopher C Qureshi Assad A Dickens Brooke B Hathiramani Nicolai N Kim Michael M Flores Ferdinand F Kearns Ann E AE Lui Li-Yung LY Black Dennis D Budoff Matthew J MJ

Journal of cardiovascular computed tomography 20190504 1

<h4>Background</h4>Cardiac fat is emerging as an important parameter for cardiovascular risk stratification. Accurate and reproducible volumetric measurements can facilitate in the serial assessment of cardiac fat by computed tomography (CT). We assessed the intra- and inter-observer variability of cardiac fat volumetric measurements using a semi-automated CT software.<h4>Methods</h4>We used non-contrast coronary calcium CT scans to quantify epicardial and intra-thoracic fat volumes. Two expert ...[more]

PMID: 31078511

Similar Datasets

Project description:BackgroundExisting studies have demonstrated that imaging parameters may affect radiomic features. However, the influence of feature calculating parameters has been overlooked. The purpose of this study is to investigate the influence of feature calculating parameters (gray-level range and bin size) on the reproducibility of CT radiomic features.MethodsThirty-six CT scans from an anthropomorphic thoracic phantom were acquired with different imaging parameters including effective dose, pitch, slice thicknesses and reconstruction kernels. The influence of feature calculating parameters was investigated in terms of three gray-level ranges and eleven gray-level bin sizes. Feature reproducibility was assessed by the intraclass correlation coefficient (ICC) with the cutoff value of 0.8 and the coefficient of variation (CV) with the cutoff value of 20%. The agreements of reproducible features in different ranges and bin sizes were analyzed by Kendall's W test and Kappa test. The proportions of reproducible features, in terms of two calculating, four imaging and two segmentation parameters, were evaluated using Cochran's Q test and Dunn's test.ResultsFor the three gray-level ranges, 50% (44/88) of features were reproducible with a perfect agreement (Kendall's W coefficient 0.844, P<0.001). Of the 72 features that may be influenced by gray-level bin size, 33.3% (24/72) were reproducible for 11 bin sizes with a perfect agreement (Kendall's W coefficient 0.879, P<0.001). For the proportions of reproducible features, there was no statistically significant difference among three ranges (P=0.420), but there was among eleven bin sizes (P=0.013). The proportions of reproducible features in feature calculating parameters were statistically significantly lower than those in imaging parameters (adjusted P<0.05).ConclusionsFeature calculating parameters may have a greater influence than imaging parameters on the reproducibility of CT radiomic features, which should be given special attention in clinical applications.

Dataset Information

Non-contrast cardiac CT-based quantitative evaluation of epicardial and intra-thoracic fat in healthy, recently menopausal women: Reproducibility data from the Kronos Early Estrogen Prevention Study.

Background

Methods

Results

Conclusions

Clinical trial registration

Publications

Non-contrast cardiac CT-based quantitative evaluation of epicardial and intra-thoracic fat in healthy, recently menopausal women: Reproducibility data from the Kronos Early Estrogen Prevention Study.

Similar Datasets

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