Literature DB >> 18197067

Automated quantitation of pericardiac fat from noncontrast CT.

Damini Dey1, Yasuyuki Suzuki, Shoji Suzuki, Muneo Ohba, Piotr J Slomka, Donna Polk, Leslee J Shaw, Daniel S Berman.   

Abstract

INTRODUCTION: Increased abdominal visceral fat has been shown to be a cardiovascular risk factor. Preliminary studies indicate that pericardiac fat (PF) may provide similar information. We aimed to develop new software (QFAT) for automatic quantitation of PF from noncontrast cardiac CT and compare PF measures to other cardiovascular risk factors.
METHODS: QFAT accepts user-defined range of noncontrast transverse cardiac CT slices, automatically segments the heart, and determines PF volume (PFV) as contiguous pericardial fat voxels. PFV normalized to cardiac volume defines PF ratio (PFR). QFAT and manual processing (MAN) was performed in 105 patients (mean BMI, 27; range, 17-41) by 2 observers.
RESULTS: Mean processing time was 20 +/- 4 seconds for QFAT, and 9 +/- 6 minutes for MAN. There was excellent agreement between QFAT and MAN for PFV (R = 0.98) and PFR (R = 0.98). MAN and QFAT interobserver variability were comparable. Interscan and interscanner variability for PFV and PFR were comparable to corresponding interobserver variability. PFV (R = 0.88, P < 0.0001) and PFR (R = 0.81, P < 0.0001) correlated strongly with abdominal visceral fat area, moderately with BMI (R = 0.58, P < 0.0001 and R = 0.48, P < 0.0001), and weakly with abdominal subcutaneous fat area (R = 0.33, P < 0.0001 and R = 0.32, P = 0.001).
CONCLUSIONS: PFV and PFR can be accurately and automatically quantified from noncontrast CT acquired for coronary calcium screening and may provide complementary information regarding cardiovascular risk.

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Year:  2008        PMID: 18197067     DOI: 10.1097/RLI.0b013e31815a054a

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  40 in total

1.  Interscan reproducibility of computer-aided epicardial and thoracic fat measurement from noncontrast cardiac CT.

Authors:  Ryo Nakazato; Haim Shmilovich; Balaji K Tamarappoo; Victor Y Cheng; Piotr J Slomka; Daniel S Berman; Damini Dey
Journal:  J Cardiovasc Comput Tomogr       Date:  2011-03-21

2.  Increased pericardial fat volume measured from noncontrast CT predicts myocardial ischemia by SPECT.

Authors:  Balaji Tamarappoo; Damini Dey; Haim Shmilovich; Ryo Nakazato; Heidi Gransar; Victor Y Cheng; John D Friedman; Sean W Hayes; Louise E J Thomson; Piotr J Slomka; Alan Rozanski; Daniel S Berman
Journal:  JACC Cardiovasc Imaging       Date:  2010-11

3.  3D-Dixon MRI based volumetry of peri- and epicardial fat.

Authors:  Rami Homsi; Michael Meier-Schroers; Jürgen Gieseke; Darius Dabir; Julian A Luetkens; Daniel L Kuetting; Claas P Naehle; Christian Marx; Hans H Schild; Daniel K Thomas; Alois M Sprinkart
Journal:  Int J Cardiovasc Imaging       Date:  2015-09-30       Impact factor: 2.357

4.  Alterations in plasma non-esterified fatty acid (NEFA) kinetics and relationship with insulin resistance in polycystic ovary syndrome.

Authors:  Uche Ezeh; Zorayr Arzumanyan; Daria Lizneva; Ruchi Mathur; Yen-Hao Chen; Raymond C Boston; Y-D Ida Chen; Ricardo Azziz
Journal:  Hum Reprod       Date:  2019-02-01       Impact factor: 6.918

5.  Threshold for the upper normal limit of indexed epicardial fat volume: derivation in a healthy population and validation in an outcome-based study.

Authors:  Haim Shmilovich; Damini Dey; Victor Y Cheng; Ronak Rajani; Ryo Nakazato; Yuka Otaki; Rine Nakanishi; Piotr J Slomka; Louise E J Thomson; Sean W Hayes; John D Friedman; Heidi Gransar; Nathan D Wong; Leslee J Shaw; Matthew Budoff; Alan Rozanski; Daniel S Berman
Journal:  Am J Cardiol       Date:  2011-08-30       Impact factor: 2.778

6.  The correlation of epicardial adipose tissue on postmortem CT with coronary artery stenosis as determined by autopsy.

Authors:  Damien I Sequeira; Lars C Ebert; Patricia M Flach; Thomas D Ruder; Michael J Thali; Garyfalia Ampanozi
Journal:  Forensic Sci Med Pathol       Date:  2015-02-25       Impact factor: 2.007

7.  Simple quantification of paracardial and epicardial fat dimensions at low-dose chest CT: correlation with metabolic risk factors and usefulness in predicting metabolic syndrome.

Authors:  Chaehun Lim; Myeong-Im Ahn; Jung Im Jung; Kyongmin Sarah Beck
Journal:  Jpn J Radiol       Date:  2018-06-14       Impact factor: 2.374

Review 8.  Epicardial and thoracic fat - Noninvasive measurement and clinical implications.

Authors:  Damini Dey; Ryo Nakazato; Debiao Li; Daniel S Berman
Journal:  Cardiovasc Diagn Ther       Date:  2012-06

9.  Effects of endogenous androgens and abdominal fat distribution on the interrelationship between insulin and non-insulin-mediated glucose uptake in females.

Authors:  Uche Ezeh; Marita Pall; Ruchi Mathur; Damini Dey; Daniel Berman; Ida Y Chen; Daniel A Dumesic; Ricardo Azziz
Journal:  J Clin Endocrinol Metab       Date:  2013-02-28       Impact factor: 5.958

10.  Myocardial Infarction Associates With a Distinct Pericoronary Adipose Tissue Radiomic Phenotype: A Prospective Case-Control Study.

Authors:  Andrew Lin; Márton Kolossváry; Jeremy Yuvaraj; Sebastien Cadet; Priscilla A McElhinney; Cathy Jiang; Nitesh Nerlekar; Stephen J Nicholls; Piotr J Slomka; Pál Maurovich-Horvat; Dennis T L Wong; Damini Dey
Journal:  JACC Cardiovasc Imaging       Date:  2020-08-26
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