JOURNAL ARTICLE

Comparison of Structural Behavior Following Bone Scaffold Implantation in Multi‐Resolution Proximal Femur Images.

  • Published In: International Journal for Numerical Methods in Biomedical Engineering, 2025, v. 41, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Choi, Jun Won; Kim, Jung Jin 3 of 3

Abstract

Bone scaffolds are increasingly regarded as viable alternatives to autografts and allografts in clinical settings. However, their effectiveness can vary based on certain anatomical characteristics, highlighting the importance of image‐based structural analysis. High‐resolution imaging is crucial to accurately assess the performance of bone scaffolds. Despite this, the resolution of current clinical medical images is constrained by concerns regarding radiation exposure. The efficacy of these analyses can be improved by quantitatively evaluating the similarities and differences between low‐ and high‐resolution images. This study quantitatively compared the structural behavior of bone scaffolds using both high‐ and low‐resolution images. This study downscaled a high‐resolution image, implanted a bone scaffold, and conducted finite element analysis. The findings suggest that the resolution needed for accurate structural analysis of skeletal images varies based on the implantation site of the scaffold. Additionally, it was found that the less influence the loading conditions have, the higher the resolution required to accurately assess the structural behavior. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal for Numerical Methods in Biomedical Engineering. 2025/02, Vol. 41, Issue 1, p1
  • Document Type:Article
  • Subject Area:Anatomy and Physiology
  • Publication Date:2025
  • ISSN:2040-7939
  • DOI:10.1002/cnm.70015
  • Accession Number:183919337
  • Copyright Statement:Copyright of International Journal for Numerical Methods in Biomedical Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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