Reference data and calculators for second-generation HR-pQCT measures of the radius and tibia at anatomically standardized regions in White adults

• Published in: Osteoporosis international Vol. 33; no. 4; pp. 791 - 806
• Main Authors: Warden, S. J., Liu, Z., Fuchs, R. K., van Rietbergen, B., Moe, S. M.
• Format: Journal Article
• Language: English
• Published: London Springer London 01.04.2022; Springer Nature B.V
• Subjects: Adolescent; Adult; Age; Aged; Aged, 80 and over; Bone and Bones; Bone Density; Computed tomography; Endocrinology; Female; Humans; Male; Medicine; Medicine & Public Health; Middle Aged; Original Article; Orthopedics; Radius; Radius - diagnostic imaging; Rheumatology; Tibia; Tibia - diagnostic imaging; Tomography; Tomography, X-Ray Computed - methods; Young Adult; Microarchitecture; High-resolution peripheral quantitative computed tomography; Bone strength; Reference values; Centile curves
• ISSN: 0937-941X; 1433-2965; 1433-2965
• DOI: 10.1007/s00198-021-06164-2

Summary 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.