Radiostereometric Analysis in Unicompartmental Knee Arthroplasty; An Analysis of Marker Placement

Master thesis (2022)

Authors

Contributors

JH Pasma Reinier de Graaf Gasthuis (mentor)

Bart Kaptein Leiden University Medical Center (mentor)

J. Harlaar Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (graduation committee member)

G.A. Kraan Applied Ergonomics and Design - (graduation committee member)

H. Verburg Reinier de Graaf Gasthuis (coach)

Faculty

Mechanical Engineering, Mechanical Engineering

Osteoarthritis RSA Knee implant Markers Unicompartmental knee arthroplasty

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Published Date

02-06-2022

Language

English

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Faculty

Mechanical Engineering

Abstract

Background: Radiostereometric analysis (RSA) is a technique to assess early migration, which has a predictive value for early failure of unicompartmental knee arthroplasty (UKA). To successfully analyze the RSA images it is important to have a sufficient amount of visiblemarkers with an acceptable three-dimensional distribution.
Objective: To provide insights on marker location distribution by developing a method to analyse marker placement based on visibility and accessibility.
Method: Marker locations in RSA scenes of patients (N=25) from a previous study are used to assess marker placement and analyze marker density by performing a voxelization operation to divide the bone in a grid of 3x3x3mm
bins. After spatial smoothing the hotspots with high marker fractions are determined and the four non-adjacent locations with the highest marker fraction are selected as the most favorable locations. Of these locations the distribution is analyzed by calculating the condition number (CN) of 1000 samples.
Results: The locations of a total of 635 3D markers in the femur and 917 3D markers in the tibia were assessed. After voxelization, the average marker density of non-empty bins was respectively 3.1 and 4.3 markers per bin. The four selected locations had a 47 times higher marker fraction compared to the average bin in the femur and 66 times higher for the selected locations in the tibia. Their mean condition number was 49.1 for the femur and 68.2 for the tibia.
Conclusion: The proposed method has proven to be sufficient for marker
placement analysis. Placing the tantalum markers in the selected locations, which have a considerably higher marker contribution to the total amount of
markers, would presumably increase the marker visibility during RSA and decrease patient exclusion due to an insufficient amount and/or distribution of visible markers.

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