Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Anthony  J. Yosick; Bei Liu; Victor Z. Zhang; Ming Yan; Hani A. Awad

doi:10.3791/67904

JoVE Journal
Bioengineering

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JoVE Journal Bioengineering

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

纵向显微计算机断层扫描图像分析，用于临界尺寸骨缺损中用户定义的感兴趣区域

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08:39 min

June 24, 2025

DOI: 10.3791/67904-v

Anthony J. Yosick^1,2, Bei Liu^2,3, Victor Z. Zhang^1,2, Ming Yan^1,2, Hani A. Awad^1,2,4

¹Department of Biomedical Engineering,University of Rochester, ²Center for Musculoskeletal Research, Department of Orthopaedics,University of Rochester Medical Center, ³Department of Translational Biomedical Science,University of Rochester Medical Center, ⁴Department of Orthopaedics,University of Rochester Medical Center

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我们提出了一种在纵向体内大鼠径向缺陷模型中分析用户定义的感兴趣区域（ROI）的方法。该方法能够在以前受显微计算机断层扫描（μCT）扫描视野变化、标本方向和支架基线存在限制的不同支架之间进行比较分析。

我们开发了纳米颗粒支架，以增强临界缺损的骨再生，并且与传统支架相比，可以提高愈合率。

目前的方法通常跟踪整个骨骼的骨体积变化，缺乏精确度，并且无法始终如一地识别纵向模型中的局部感兴趣区域。我们的协议可以在实体模型中实现一致的局部感兴趣区域跟踪，提高精度和纵向分析，并与全骨量评估进行比较。

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