Geometric Shape Validation of Knee Statistical Shape Model
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    Abstract:

    Objective To obtain the range of anatomical parameters of healthy knee joints in Chinese males and validate a statistical shape model (SSM) based on the geometric shape of a healthy knee to provide references for the design of knee SSM-based prostheses. Methods Computed tomography (CT) images of knee joints from 112 healthy males were acquired to build three-dimensional (3D) knee joint models. Each model was the target model separately, and the remaining models were used as the training set for principal component analysis (PCA). The obtained knee SSM was fitted to the target model to predict the SSM. The exact anatomical measurement points were marked on the sample and SSM prediction models, and 17 linear and 3 angular parameters were derived. The values of the anatomical parameters were statistically tested using an independent samples t-test and Mann-Whitney U-test, and the validity of the SSM in terms of geometric shape was demonstrated if the resulting P-values were all greater than 0.05. Results Qualitative and quantitative comparative analyses of anatomical parameters showed that The mean deviation of linear parameters was less than 6 mm, and that of angular parameters was less than 2.5°. The results of statistical tests showed P>0.05 for all anatomical parameters, proving that the knee SSM prediction model was not statistically different from the true healthy model in terms of geometric shape. Conclusions This study derived a reference range of anatomical parameters for a healthy knee and demonstrated that the knee SSM model was consistent with the real healthy model in terms of shape. The results provide a reference for the design of knee SSM-based prostheses.

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DUAN Huabing, GU Xuelian, LI Xiaohu, ZHOU Jincheng, CHANG Yihao, WANG Jie, GUO Xiaochen. Geometric Shape Validation of Knee Statistical Shape Model[J]. Journal of medical biomechanics,2024,39(2):243-249

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History
  • Received:July 01,2023
  • Revised:September 11,2023
  • Adopted:
  • Online: April 26,2024
  • Published: