Eranthi Jayawardena1, Dong Li2, Rine Nakanishi3, Damini Dey4, Christopher Dailing5, Assad Qureshi6, Brooke Dickens7, Nicolai Hathiramani8, Michael Kim9, Ferdinand Flores10, Ann E Kearns11, Li-Yung Lui12, Dennis Black13, Matthew J Budoff14. 1. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: ejayawardena@labiomed.org. 2. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: dli@labiomed.org. 3. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: rnakanishi@labiomed.org. 4. Qfat CT, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA. Electronic address: damini.dey@cshs.org. 5. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: cdailing@labiomed.org. 6. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: assadbqureshi@gmail.com. 7. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: brookedickens23@gmail.com. 8. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: nicolaihathiramani@gmail.com. 9. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: michaelkim03@gmail.com. 10. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: fflores@labiomed.org. 11. Mayo Clinic, 200 1stAve SW, Rochester, MN, 55902, USA. Electronic address: kearns.ann@mayo.edu. 12. Research Institute, California Pacific Medical Center, San Francisco, CA, USA. Electronic address: llui@sfcc-cpmc.net. 13. Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA. Electronic address: dblack@psg.ucsf.edu. 14. Los Angeles Biomedical Research Institute, 1124 West Carson St, Torrance, CA, 90502, USA. Electronic address: mbudoff@labiomed.org.
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 < 0.0001 for correlation) for both epicardial and intra-thoracic fat. By Bland-Altman analysis for epicardial fat measurements, mean difference of intra-observer was 0.90 cm3 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.
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 < 0.0001 for correlation) for both epicardial and intra-thoracic fat. By Bland-Altman analysis for epicardial fat measurements, mean difference of intra-observer was 0.90 cm3 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.
Authors: Rine Nakanishi; Ronak Rajani; Victor Y Cheng; Heidi Gransar; Ryo Nakazato; Haim Shmilovich; Yuka Otaki; Sean W Hayes; Louise E J Thomson; John D Friedman; Piotr J Slomka; Daniel S Berman; Damini Dey Journal: Atherosclerosis Date: 2011-07-23 Impact factor: 5.162
Authors: S Mitchell Harman; Dennis M Black; Frederick Naftolin; Eliot A Brinton; Matthew J Budoff; Marcelle I Cedars; Paul N Hopkins; Rogerio A Lobo; JoAnn E Manson; George R Merriam; Virginia M Miller; Genevieve Neal-Perry; Nanette Santoro; Hugh S Taylor; Eric Vittinghoff; Mingzhu Yan; Howard N Hodis Journal: Ann Intern Med Date: 2014-08-19 Impact factor: 25.391
Authors: Gary Huang; Dan Wang; Irfan Zeb; Matthew J Budoff; S Mitchell Harman; Virginia Miller; Eliot A Brinton; Samar R El Khoudary; JoAnn E Manson; MaryFran R Sowers; Howard N Hodis; George R Merriam; Marcelle I Cedars; Hugh S Taylor; Frederick Naftolin; Rogerio A Lobo; Nanette Santoro; Rachel P Wildman Journal: Atherosclerosis Date: 2011-12-09 Impact factor: 5.162
Authors: Markus Goeller; Stephan Achenbach; Mohamed Marwan; Mhairi K Doris; Sebastien Cadet; Frederic Commandeur; Xi Chen; Piotr J Slomka; Heidi Gransar; J Jane Cao; Nathan D Wong; Moritz H Albrecht; Alan Rozanski; Balaji K Tamarappoo; Daniel S Berman; Damini Dey Journal: J Cardiovasc Comput Tomogr Date: 2017-11-24
Authors: Amir A Mahabadi; Joseph M Massaro; Guido A Rosito; Daniel Levy; Joanne M Murabito; Philip A Wolf; Christopher J O'Donnell; Caroline S Fox; Udo Hoffmann Journal: Eur Heart J Date: 2009-01-09 Impact factor: 29.983
Authors: Jingzhong Ding; Stephen B Kritchevsky; Fang-Chi Hsu; Tamara B Harris; Gregory L Burke; Robert C Detrano; Moyses Szklo; Michael H Criqui; Matthew Allison; Pamela Ouyang; Elizabeth R Brown; J Jeffrey Carr Journal: Am J Clin Nutr Date: 2008-09 Impact factor: 7.045
Authors: Tomasz Mazurek; LiFeng Zhang; Andrew Zalewski; John D Mannion; James T Diehl; Hwyda Arafat; Lea Sarov-Blat; Shawn O'Brien; Elizabeth A Keiper; Anthony G Johnson; Jack Martin; Barry J Goldstein; Yi Shi Journal: Circulation Date: 2003-10-27 Impact factor: 29.690
Authors: Adam R Baker; Nancy F da Silva; David W Quinn; Alison L Harte; Domenico Pagano; Robert S Bonser; Sudhesh Kumar; Philip G McTernan Journal: Cardiovasc Diabetol Date: 2006-01-13 Impact factor: 9.951
Authors: David M Cordas Dos Santos; Kai Rejeski; Michael Winkelmann; Lian Liu; Paul Trinkner; Sophie Günther; Veit L Bücklein; Viktoria Blumenberg; Christian Schmidt; Wolfgang G Kunz; Michael Von Bergwelt-Baildon; Sebastian Theurich; Marion Subklewe Journal: Haematologica Date: 2022-09-01 Impact factor: 11.047