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Semi-automatic micro-CT segmentation of the midfoot using calibrated thresholds

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Abstract

Purpose

In the field of skeletal research, accurate and reliable segmentation methods are necessary for quantitative micro-CT analysis to assess bone quality. We propose a method of semi-automatic image segmentation of the midfoot, using the cuneiform bones as a model, based on thresholds set by phantom calibration that allows reproducible results in low cortical thickness bones.

Methods

Manual and semi-automatic segmentation methods were compared in micro-CT scans of the medial and intermediate cuneiforms of 24 cadaveric specimens. The manual method used intensity thresholds, hole filling, and manual cleanup. The semi-automatic method utilized calibrated bone and soft tissue thresholds Boolean subtraction to cleanly identify edges before hole filling. Intra- and inter-rater reliability was tested for the semi-automatic method in all specimens. Mask volume and average bone mineral density (BMD) were measured for all masks, and the three-dimensional models were compared to the initial semi-automatic segmentation using an unsigned distance part comparison analysis. Segmentation methods were compared with paired t-tests with significance level 0.05, and reliability was analyzed by calculating intra-class correlation coefficients.

Results

There were statistically significant differences in mask volume and BMD between the manual and semi-automatic segmentation methods in both bones. The intra- and inter-reliability was excellent for mask volume and bone density in both bones. Part comparisons showed a higher maximum distance between surfaces for the manual segmentation than the repeat semi-automatic segmentations.

Conclusion

We developed a semi-automatic micro-CT segmentation method based on calibrated thresholds. This method was designed specifically for use in bones with high rates of curvature and low cortical bone density, such as the cuneiforms, where traditional threshold-based segmentation is more challenging. Our method shows improvement over manual segmentation and was highly reliable, making it appropriate for use in quantitative micro-CT analysis.

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Acknowledgements

This material is the result of work supported with resources and the use of facilities at the Salt Lake City Veterans Affairs Medical Center.

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Authors and Affiliations

  1. Department of Orthopaedics, University of Utah, 590 Wakara Way, Salt Lake City, UT, 84108, USA

    Melissa R. Requist, Yantarat Sripanich, Andrew C. Peterson, Alexej Barg & Amy L. Lenz

  2. Department of Biomedical Engineering, University of Arizona, 1127 E James E Rogers Way, Tucson, AZ, 85721, USA

    Melissa R. Requist

  3. Department of Orthopaedics, Phramongkutklao Hospital and College of Medicine, 315 Rajavithi Road, Tung Phayathai, Ratchathewi, Bangkok, 10400, Thailand

    Yantarat Sripanich

  4. Department of Trauma and Orthopaedic Surgery, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany

    Tim Rolvien & Alexej Barg

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  1. Melissa R. Requist
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Correspondence to Alexej Barg or Amy L. Lenz.

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This study was approved by the Internal Institutional Review Board of the University of Utah (IRB #00071733).

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Submitted to International Journal of Computer Assisted Radiology and Surgery October 2020

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Requist, M.R., Sripanich, Y., Peterson, A.C. et al. Semi-automatic micro-CT segmentation of the midfoot using calibrated thresholds. Int J CARS 16, 387–396 (2021). https://doi.org/10.1007/s11548-021-02318-z

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  • DOI: https://doi.org/10.1007/s11548-021-02318-z

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