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.
Adipose Tissue
/ diagnostic imaging
Adiposity
Female
Healthy Volunteers
Humans
Menopause
Middle Aged
Observer Variation
Pericardium
/ diagnostic imaging
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Radiography, Thoracic
Reproducibility of Results
Retrospective Studies
Tomography, X-Ray Computed
United States
Journal
Journal of cardiovascular computed tomography
ISSN: 1876-861X
Titre abrégé: J Cardiovasc Comput Tomogr
Pays: United States
ID NLM: 101308347
Informations de publication
Date de publication:
Historique:
received:
04
02
2019
accepted:
02
05
2019
pubmed:
13
5
2019
medline:
7
7
2020
entrez:
13
5
2019
Statut:
ppublish
Résumé
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. 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. The intra-observer correlation coefficients ranged between 0.86 to 0.99 and 0.87 to 0.99 for epicardial (median fat per reader (cm 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. URL: https://www.clinicaltrials.gov. Unique identifier: NCT00154180; Keywords: Epicardial fat volume; intra-thoracic fat volume; computed tomography; intra-observer; inter-observer.
Sections du résumé
BACKGROUND
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
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
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 (cm
CONCLUSIONS
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
BACKGROUND
URL: https://www.clinicaltrials.gov. Unique identifier: NCT00154180; Keywords: Epicardial fat volume; intra-thoracic fat volume; computed tomography; intra-observer; inter-observer.
Identifiants
pubmed: 31078511
pii: S1934-5925(19)30064-4
doi: 10.1016/j.jcct.2019.05.004
pmc: PMC6829052
mid: NIHMS1529110
pii:
doi:
Banques de données
ClinicalTrials.gov
['NCT00154180']
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
55-59Subventions
Organisme : NHLBI NIH HHS
ID : R01 HL071739
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL133616
Pays : United States
Informations de copyright
Copyright © 2020 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
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