S J Warden1,2, Z Liu3,4, R K Fuchs5,3, B van Rietbergen6, S M Moe3,7. 1. Department of Physical Therapy, School of Health and Human Sciences, Indiana University, 1140 W. Michigan St., CF-120, Indianapolis, IN, 46202, USA. stwarden@iu.edu. 2. Indiana Center for Musculoskeletal Health, Indiana University, Indianapolis, IN, USA. stwarden@iu.edu. 3. Indiana Center for Musculoskeletal Health, Indiana University, Indianapolis, IN, USA. 4. Department of Biostatistics, School of Medicine, Indiana University, Indianapolis, IN, USA. 5. Department of Physical Therapy, School of Health and Human Sciences, Indiana University, 1140 W. Michigan St., CF-120, Indianapolis, IN, 46202, USA. 6. Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. 7. Division of Nephrology, Department of Medicine, School of Medicine, Indiana University, Indianapolis, IN, USA.
Abstract
High-resolution peripheral quantitative computed tomography (HR-pQCT) is a powerful tool to assess bone health. To determine how an individual's or population of interest's HR-pQCT outcomes compare to expected, reference data are required. This study provides reference data for HR-pQCT measures acquired in a population of White adults. PURPOSE: To provide age- and sex-specific reference data for high-resolution peripheral quantitative computed tomography (HR-pQCT) measures of the distal and diaphyseal radius and tibia acquired using a second-generation scanner and percent-of-length offsets proximal from the end of the bone. METHODS: Data were acquired in White adults (aged 18-80 years) living in the Midwest region of the USA. HR-pQCT scans were performed at the 4% distal radius, 30% diaphyseal radius, 7.3% distal tibia, and 30% diaphyseal tibia. Centile curves were fit to the data using the LMS approach. RESULTS: Scans of 867 females and 317 males were included. The fitted centile curves reveal HR-pQCT differences between ages, sexes, and sites. They also indicate differences when compared to data obtained by others using fixed length offsets. Excel-based calculators based on the current data were developed and are provided to enable computation of subject-specific percentiles, z-scores, and t-scores and to plot an individual's outcomes on the fitted curves. In addition, regression equations are provided to convert estimated failure load acquired with the conventional criteria utilized with first-generation scanners and those specifically developed for second-generation scanners. CONCLUSION: The current study provides unique data and resources. The combination of the reference data and calculators provide clinicians and investigators an ability to assess HR-pQCT outcomes in an individual or population of interest, when using the described scanning and analysis procedure. Ultimately, the expectation is these data will be expanded over time so the wealth of information HR-pQCT provides becomes increasingly interpretable and utilized.
High-resolution peripheral quantitative computed tomography (HR-pQCT) is a powerful tool to assess bone health. To determine how an individual's or population of interest's HR-pQCT outcomes compare to expected, reference data are required. This study provides reference data for HR-pQCT measures acquired in a population of White adults. PURPOSE: To provide age- and sex-specific reference data for high-resolution peripheral quantitative computed tomography (HR-pQCT) measures of the distal and diaphyseal radius and tibia acquired using a second-generation scanner and percent-of-length offsets proximal from the end of the bone. METHODS: Data were acquired in White adults (aged 18-80 years) living in the Midwest region of the USA. HR-pQCT scans were performed at the 4% distal radius, 30% diaphyseal radius, 7.3% distal tibia, and 30% diaphyseal tibia. Centile curves were fit to the data using the LMS approach. RESULTS: Scans of 867 females and 317 males were included. The fitted centile curves reveal HR-pQCT differences between ages, sexes, and sites. They also indicate differences when compared to data obtained by others using fixed length offsets. Excel-based calculators based on the current data were developed and are provided to enable computation of subject-specific percentiles, z-scores, and t-scores and to plot an individual's outcomes on the fitted curves. In addition, regression equations are provided to convert estimated failure load acquired with the conventional criteria utilized with first-generation scanners and those specifically developed for second-generation scanners. CONCLUSION: The current study provides unique data and resources. The combination of the reference data and calculators provide clinicians and investigators an ability to assess HR-pQCT outcomes in an individual or population of interest, when using the described scanning and analysis procedure. Ultimately, the expectation is these data will be expanded over time so the wealth of information HR-pQCT provides becomes increasingly interpretable and utilized.
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