Automatic analysis of morphological parameters of the patella based on three-dimensional (3D) surface data

5 pages•Published: October 26, 2019

Abstract

Morphological knowledge about the patella is fundamental to understand normal and pathological knee joint mechanics and guide the design of patellar prosthesis. In literature there are a large number of parameters and measurement methods described to characterize the patellar morphology. However, the majority rely on manual measurements, sample sizes are often small and the number of morphological parameters is limited. The goal of this study was to identify morphological parameters of the patella, develop a standardized and fully automatic workflow for their extraction, and to provide accurate statistical numbers for a large number of patients.

An anonymized dataset of 412 knee geometries from consecutively scheduled total knee arthroplasty patients (gender: 248 female, 164 male) were available. A total number of 8 morphological parameters were identified and later used for the calculation of 3 additional aspect ratios. A fully automatic workflow was developed for parameter extraction based on the three-dimensional surface data. The workflow was applied to all datasets and the results were stored in a database for statistical analysis.

The workflow could process all 412 patellar geometries fully automatic without any algorithmic adjustment or user interaction. The processing time was in the range of 30 s per case. The results of the statistical analysis were in very good agreement with the literature. The numbers clearly demonstrated gender-specific differences, however, it is still unknown whether these are sexual dimorphism or can be eliminated by a scaling. Extensive statistical analysis on gender-specific differences and their normalization is part of future work.

Keyphrases: knee, morphology, patella, patient specific, total knee arthroplasty

In: Patrick Meere and Ferdinando Rodriguez Y Baena (editors). CAOS 2019. The 19th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 3, pages 31-35.

Links:	https://easychair.org/publications/paper/m8Df
	https://doi.org/10.29007/mrjk

BibTeX entry

@inproceedings{CAOS2019:Automatic_analysis_morphological_parameters,
  author    = {Malte Asseln and Klaus Radermacher},
  title     = {Automatic analysis of morphological parameters of the patella based on three-dimensional (3D) surface data},
  booktitle = {CAOS 2019. The 19th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Patrick Meere and Ferdinando Rodriguez Y Baena},
  series    = {EPiC Series in Health Sciences},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {/publications/paper/m8Df},
  doi       = {10.29007/mrjk},
  pages     = {31-35},
  year      = {2019}}

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