Literature DB >> 20177779

Automated method for computing the morphological and clinical parameters of the proximal femur using heuristic modeling techniques.

Pietro Cerveri1, Mario Marchente, Ward Bartels, Kristoff Corten, Jean-Pierre Simon, Alfonso Manzotti.   

Abstract

Bone morphology and morphometric measurements of the lower limb provide significant and useful information for computer-assisted orthopedic surgery planning and intervention, surgical follow-up evaluation, and personalized prosthesis design. Femoral head radius and center, neck axis and size, femoral offset and shaft axis are morphological and functional parameters of the proximal femur utilized both in diagnosis and therapy. Obtaining this information from image data without any operator supervision or manual editing remains a practical objective to avoid variability intrinsic in the manual analysis. In this article, we propose a heuristic method that automatically computes the proximal femur morphological parameters by processing the mesh surface of the femur. The surface data are sequentially processed using geometrical properties such as symmetries, asymmetries, and principal elongation directions. Numerical methods identify the axis of the shaft of femur (least squares cylinder fitting), the head surface and center (least squares sphere fitting), and the femur neck axis and radius (minimal area of the cross section by evolutionary optimization). The repeatability of the method was tested upon 20 femur (10 left + 10 right) surfaces reconstructed from CT scans taken on cadavers. The repeatability error of the automated computation of anatomical landmarks, angles, sizes, and axes was less than 1.5 mm, 2.5 degrees, 1.0 mm, and 3.5 mm, respectively. The computed parameters were in good agreement (landmark difference: <2.0 mm; angle difference: <2.0 degrees; axes difference: <2.5 degrees; size difference: <1.5 mm) with the corresponding reference parameters manually identified in the original CT images by medical experts. In conclusion, the proposed method can improve the degree of automation of model-based hip replacement surgical systems.

Mesh:

Year:  2010        PMID: 20177779     DOI: 10.1007/s10439-010-9965-x

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  4 in total

1.  Predicting the optimal entry point for femoral antegrade nailing using a new measurement approach.

Authors:  Jing-xin Zhao; Xiu-yun Su; Zhe Zhao; Li-cheng Zhang; Zhi Mao; Hao Zhang; Li-hai Zhang; Pei-fu Tang
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-04-01       Impact factor: 2.924

2.  Automated Morphometric Analysis of the Hip Joint on MRI from the German National Cohort Study.

Authors:  Marc Fischer; Sven S Walter; Tobias Hepp; Manuela Zimmer; Mike Notohamiprodjo; Fritz Schick; Bin Yang
Journal:  Radiol Artif Intell       Date:  2021-06-02

3.  Predicting Knee Joint Instability Using a Tibio-Femoral Statistical Shape Model.

Authors:  Pietro Cerveri; Antonella Belfatto; Alfonso Manzotti
Journal:  Front Bioeng Biotechnol       Date:  2020-04-17

4.  A robust method for automatic identification of femoral landmarks, axes, planes and bone coordinate systems using surface models.

Authors:  Maximilian C M Fischer; Sonja A G A Grothues; Juliana Habor; Matías de la Fuente; Klaus Radermacher
Journal:  Sci Rep       Date:  2020-11-30       Impact factor: 4.379

  4 in total

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