Automated quantitative analysis of peri-articular bone microarchitecture in HR-pQCT knee images.

Journal: Computer methods and programs in biomedicine
Published Date: Jun 13, 2025

Abstract

UNLABELLED: Applying HR-pQCT to image the knee necessitates the development and validation of novel image analysis workflows. Here, we present and validate the first automated workflow for in vivo quantitative assessment of peri-articular bone density and microarchitecture in the knee. Segmentation models were first trained with radius and tibia images (N=2,598) then fine-tuned with knee images (N=131). Atlas-based registration was used to create medial and lateral contact surface masks, which were combined with bone segmentations to generate peri-articular regions of interest masks. The accuracy and precision of the workflow was assessed with an external validation dataset (N=128) and a triple-repeat measures dataset (N=29), respectively. Predicted and reference morphological parameters had linear coefficients of determination between 0.86 and 0.99, with moderate bias present in predictions of subchondral bone plate density and thickness. The average short-term precision RMS%CV estimates across all compartments and all morphological parameters ranged from 1.0 % to 2.9 %.

Authors

  • Nathan J Neeteson
    Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Canada; McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
  • Sasha M Hasick
    McCaig Institute for Bone and Joint Health, University of Calgary, Calgary, Canada.
  • Roberto Souza
    Medical Imaging and Computing Laboratory, Department of Computer Engineering and Industrial Automation, University of Campinas, Campinas, São Paulo, Brazil; Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Calgary Image Processing and Analysis Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Alberta, Canada; Seaman Family Magnetic Resonance Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Alberta, Canada. Electronic address: roberto.medeirosdeso@ucalgary.ca.
  • Steven K Boyd
    Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Canada; McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. Electronic address: skboyd@ucalgary.ca.

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