Related Experiment Video
Updated: Jul 1, 2025
Cortical Bone Assessment Using Ultrasonic Guided Waves: A Reproducibility Study in a Healthy Population
Published on: January 31, 2025
Transferability of bone phenotyping and fracture risk assessment by μFRAC from first-generation high-resolution
Annabel R Bugbird1, Danielle E Whittier1,2, Steven K Boyd1
1McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4Z6, Canada.
Introduction:
The continued development of high-resolution peripheral quantitative computed tomography (HR-pQCT) has led to a second-generation scanner with higher resolution and longer scan region. However, large multicenter prospective cohorts were collected with first-generation HR-pQCT and have been used to develop bone phenotyping and fracture risk prediction (μFRAC) models. This study establishes whether there is sufficient universality of these first-generation trained models for use with second-generation scan data.
Methods:
HR-pQCT data were collected for a cohort of 60 individuals, who had been scanned on both first- and second-generation scanners on the same day to establish the universality of the HR-pQCT models. These data were each used as input to first-generation trained bone microarchitecture models for bone phenotyping and fracture risk prediction, and their outputs were compared for each study participant. Reproducibility of the models were assessed using same-day repeat scans obtained from first-generation (n = 37) and second-generation (n = 74) scanners.
Results:
Across scanner generations, the bone phenotyping model performed with an accuracy of 93.1%. Similarly, the 5-year fracture risk assessment by μFRAC was well correlated with a Pearson's (r) correlation coefficient of r > 0.83 for the three variations of μFRAC (varying inclusion of clinical risk factors, finite element analysis, and dual X-ray absorptiometry). The first-generation reproducibility cohort performed with an accuracy for categorical assignment of 100% (bone phenotyping) and a correlation coefficient of 0.99 (μFRAC), whereas the second-generation reproducibility cohort performed with an accuracy of 96.4% (bone phenotyping) and a correlation coefficient of 0.99 (μFRAC).
Conclusion:
We demonstrated that bone microarchitecture models trained using first-generation scan data generalize well to second-generation scans, performing with a high level of accuracy and reproducibility. Less than 4% of individuals' estimated fracture risk led to a change in treatment threshold, and in general, these dissimilar outcomes using second-generation data tended to be more conservative.
