Short term in vivo precision of whole body composition measurements on the Horizon A densitometer. Issue 2 (29th July 2017)

• Record Type: Journal Article
• Authors: Nowitz, Michael; Monahan, Paula
• Is Part Of: Journal of medical imaging and radiation oncology. Volume 62:Issue 2(2018:Apr.)
• Page Start: 179
• Page End: 182
• Publication Date: 2017-07-29
• Subjects: composition -- fat mass -- lean mass -- least significant change -- precision; Radiology, Medical -- Periodicals; Radiology, Medical -- Australasia -- Periodicals; 616.0757
• DOI: 10.1111/1754-9485.12646
• Languages: English
• ISSNs: 1754-9477

Abstract

Abstract: Introduction: Dual‐energy X‐ray absorptiometry (DXA) is increasingly being used to assess abnormalities in body composition associated with a wide variety of conditions including obesity, sarcopenia, diabetes, anorexia, human immunodeficiency virus lipodystrophy, malabsorption and neuromuscular disorders. The objective of this study was to determine the short‐term in vivo precision and least significant change in serial body composition measurements provided by the Hologic Horizon A densitometer as there is no published, peer reviewed body composition precision data on Horizon scanners in the medical literature. Methods: After acquiring two new Hologic Horizon A densitometers, short term precision scanning was performed on the two scanners using different groups of 30 volunteers, who had duplicate scans with all scans performed by the same operator. Using the International Society of Clinical Densitometry's advanced precision tool, the scan data were recorded and the coefficient of variation (CV) and least significant change (LSC) determined for total fat, lean and bone mineral content (BMC) and bone mineral density (BMD). Results: Coefficients of variation of 0.78% and 0.77% were achieved for total fat (LSC at 95% confidence 2.15%) and 0.52% and 0.40% for total lean (LSC at 95% confidence 1.45% and 1.11%). Conclusions: These results indicate that the two Horizon A scanners in this study exceeded the minimum acceptable precision values by roughly a factor of four and are therefore capable of detecting small differences in lean and fat mass of 1–2% between two measurements at 95% confidence.