R M Plett1,2, T D Kemp2,3, L A Burt2, E O Billington2,4, D A Hanley2,4, S K Boyd5,6,7. 1. Biomedical Engineering Graduate Program, Faculty of Graduate Studies, University of Calgary, Calgary, Canada. 2. McCaig Institute for Bone and Joint Health, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4Z6, Canada. 3. Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Canada. 4. Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Canada. 5. McCaig Institute for Bone and Joint Health, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4Z6, Canada. skboyd@ucalgary.ca. 6. Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Canada. skboyd@ucalgary.ca. 7. Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada. skboyd@ucalgary.ca.
Abstract
We developed and validated a finite element (FE) approach for longitudinal high-resolution peripheral quantitative computed tomography (HR-pQCT) studies using 3D image registration to account for misalignment between images. This reduced variability in longitudinal FE estimates and improved our ability to measure in vivo changes in HR-pQCT studies of bone strength. INTRODUCTION: We developed and validated a finite element (FE) approach for longitudinal high-resolution peripheral quantitative computed tomography (HR-pQCT) studies using 3D rigid-body registration (3DR) to maximize reproducibility by accounting for misalignment between images. METHODS: In our proposed approach, we used the full common bone volume defined by 3DR to estimate standard FE parameters. Using standard HR-pQCT imaging protocols, we validated the 3DR approach with ex vivo samples of the distal radius (n = 10, four repeat scans) by assessing whether 3DR can reduce measurement variability from repositioning error. We used in vivo data (n = 40, five longitudinal scans) to assess the sensitivity of 3DR to detect changes in bone strength at the distal radius by the standard deviation of the rate of change (σ), where the ideal value of σ is minimized to define true change. FE estimates by 3DR were compared to estimates by no registration (NR) and slice-matching (SM). RESULTS: Group-wise comparisons of ex vivo variation (CVRMS, %) found that FE measurement precision was improved by SM (CVRMS < 0.80%) and 3DR (CVRMS < 0.62%) compared to NR (CVRMS~2%), and 3DR was advantageous as repositioning error increased. Longitudinal in vivo reproducibility was minimized by 3DR for failure load estimates (σ = 0.008 kN/month). CONCLUSION: Although 3D registration cannot negate motion artifacts, it plays an important role in detecting and reducing variability in FE estimates for longitudinal HR-pQCT data and is well suited for estimating effects of interventions in in vivo longitudinal studies of bone strength.
We developed and validated a finite element (FE) approach for longitudinal high-resolution peripheral quantitative computed tomography (HR-pQCT) studies using 3D image registration to account for misalignment between images. This reduced variability in longitudinal FE estimates and improved our ability to measure in vivo changes in HR-pQCT studies of bone strength. INTRODUCTION: We developed and validated a finite element (FE) approach for longitudinal high-resolution peripheral quantitative computed tomography (HR-pQCT) studies using 3D rigid-body registration (3DR) to maximize reproducibility by accounting for misalignment between images. METHODS: In our proposed approach, we used the full common bone volume defined by 3DR to estimate standard FE parameters. Using standard HR-pQCT imaging protocols, we validated the 3DR approach with ex vivo samples of the distal radius (n = 10, four repeat scans) by assessing whether 3DR can reduce measurement variability from repositioning error. We used in vivo data (n = 40, five longitudinal scans) to assess the sensitivity of 3DR to detect changes in bone strength at the distal radius by the standard deviation of the rate of change (σ), where the ideal value of σ is minimized to define true change. FE estimates by 3DR were compared to estimates by no registration (NR) and slice-matching (SM). RESULTS: Group-wise comparisons of ex vivo variation (CVRMS, %) found that FE measurement precision was improved by SM (CVRMS < 0.80%) and 3DR (CVRMS < 0.62%) compared to NR (CVRMS~2%), and 3DR was advantageous as repositioning error increased. Longitudinal in vivo reproducibility was minimized by 3DR for failure load estimates (σ = 0.008 kN/month). CONCLUSION: Although 3D registration cannot negate motion artifacts, it plays an important role in detecting and reducing variability in FE estimates for longitudinal HR-pQCT data and is well suited for estimating effects of interventions in in vivo longitudinal studies of bone strength.
Entities:
Keywords:
3D registration; Bone strength; Finite element analysis; HR-pQCT; Longitudinal analysis
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