A Trimodality Comparison of Volumetric Bone Imaging Technologies. Part II: 1-Yr Change, Long-Term Precision, and Least Significant Change

Abstract

The previous article in this 3-part series demonstrated short-term precision and validity for volumetric bone outcome quantification using in vivo peripheral (p) quantitative computed tomography (pQCT) and magnetic resonance imaging (MRI) modalities at resolutions 200 μm or higher. However, 1-yr precision error and clinically significant references are yet to be reported for these modalities. This study examined 59 women with mean age of 75 ± 9 yr and body mass index of 26.84 ± 4.77 kg/m 2 , demonstrating the lowest 1-yr precision error, standard errors of the estimate, and least significant change values for high-resolution (hr) pQCT followed by pQCT, and 1.0-T pMRI for all volumetric bone outcomes except trabecular number. Like short-term precision, 1-yr statistics for trabecular separation were similar across modalities. Excluding individuals with a previous history of fragility fractures, or who were current users of antiresorptives reduced 1-yr change for bone outcomes derived from pQCT and pMR images, but not hr-pQCT images. In Part II of this 3-part series focused on trimodality comparisons of 1-yr changes, hr-pQCT was recommended to be the prime candidate for quantifying change where smaller effect sizes are expected, but pQCT was identified as a feasible alternative for studies expecting larger changes.

Cross-sectional Versus Longitudinal Change in a Prospective HR-pQCT Study

“…Bold values indicate significant difference between cross‐sectional and longitudinal change. *Signifies values higher than the least‐significant change (LSC) over entire study duration (5 years) …”

“…To compare if the changes we observed were clinically meaningful, we compared our results to LSC values previously published in the literature. (18,19,24) These previously published LSC studies used data generated in our laboratory and reflect the age range of the participants in the current study. Polynomial regression was used to determine the effect of age (as a continuous variable) on changes in bone health.…”

“…As with any longitudinal study, being able to determine if the observed change is larger than the error associated with the machine is essential. Short‐ and long‐term HR‐pQCT precision for young and older cohorts are established, and the least‐significant change (LSC) for density, geometry, and architectural parameters are known . Furthermore, recommendations on the required time interval needed to observe changes in area, density, and microarchitectural parameters have been established .…”

“…Short-and long-term HR-pQCT precision for young and older cohorts are established, and the leastsignificant change (LSC) for density, geometry, and architectural parameters are known. (18)(19)(20)(21)(22)(23)(24) Furthermore, recommendations on the required time interval needed to observe changes in area, density, and microarchitectural parameters have been established. (21) A challenge of the current longitudinal HR-pQCT studies is the length of the follow-up time ranging from 1 to 3 years.…”

Effects of a 20-week high-intensity strength and sprint training program on tibial bone structure and strength in middle-aged and older male sprint athletes: a randomized controlled trial

“…The root mean square coefficient of variation (CVRMS) for the BMD, structure and strength index measurements in our laboratory ranges from 0.4 to 1.6% [24]. In terms of least significant change (LSC = 2.77 × CVRMS) [25], which refers to a change greater than the precision error for a single individual, this corresponds to a range of 1.2-4.4%.…”