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. 2023 Oct 13;10(10):1185.
doi: 10.3390/bioengineering10101185.

Prediction of the Proximal Humerus Morphology Based on a Statistical Shape Model with Two Parameters: Comparison to Contralateral Registration Method

Florianne E van Schaardenburgh  1 , H Chien Nguyen  2   3 , Joëll Magré  2   3 , Koen Willemsen  3 , Bert van Rietbergen  1 , Stefaan Nijs  4
Affiliations

Prediction of the Proximal Humerus Morphology Based on a Statistical Shape Model with Two Parameters: Comparison to Contralateral Registration Method

Florianne E van Schaardenburgh et al. Bioengineering (Basel). .

Abstract

(1) Background: Complex proximal humerus fractures often result in complications following surgical treatment. A better understanding of the full 3D displacement would provide insight into the fracture morphology. Repositioning of fracture elements is often conducted by using the contralateral side as a reconstruction template. However, this requires healthy contralateral anatomy. The purpose of this study was to create a Statistical Shape Model (SSM) and compare its effectiveness to the contralateral registration method for the prediction of the humeral proximal segment; (2) Methods: An SSM was created from 137 healthy humeri. A prediction for the proximal segment of the left humeri from eight healthy patients was made by combining the SSM with parameters. The predicted proximal segment was compared to the left proximal segment of the patients. Their left humerus was also compared to the contralateral (right) humerus; (3) Results: Eight modes explained 95% of the variation. Most deviations of the SSM prediction and the contralateral registration method were below the clinically relevant 2 mm distance threshold.; (4) Conclusions: An SSM combined with parameters is a suitable method to predict the proximal humeral segment when the contralateral CT scan is unavailable or the contralateral humerus is unhealthy, provided that the fracture pattern allows measurements of these parameters.

Keywords: 3D planning; humeral anatomy; proximal humerus fractures; statistical shape modelling.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The steps from CT scan to 3D model.
Figure 2
Figure 2
The steps for creating the SSM.
Figure 3
Figure 3
Illustration of the parameters measured on a humerus: (a) The maximum humerus length; (b) The humeral head radius; (c) The shaft circumference.
Figure 4
Figure 4
The compactness of the SSM. Eight modes explain 95% of the variation.
Figure 5
Figure 5
The first three modes of variation of the SSM of the humerus. Variation in the shape can be visualised by changing the standard deviation (SD), which ranges from −3SD (red coloured) to +3SD (green coloured).
Figure 6
Figure 6
The proximal segment of the SSM prediction and the contralateral registration method have different deviations. The boxplots show the minimum and maximum values.
See this image and copyright information in PMC

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