Back

A novel approach to determine the micromotion of screw-plate interfaces of a locking-type plating system under axial cyclic loading via synchronized digital image correlation

Halbauer, C.; Paech, A.; Capanni, F.

2025-04-14 orthopedics
10.1101/2025.04.11.25325637 medRxiv
Show abstract

ObjectivesA previously published biomechanical study of axial cyclic testing on a lockingtype plating system presented several failure types of the screw-plate interfaces (SPI). It was assumed that increasing micromotions of SPIs result consequently in initial failure of SPIs during cyclic loading. In conclusion, measurements of SPIs via digital image correlation (DIC) were suggested to detect potential micromotions. MethodsDIC measurements were performed using the ARAMIS Adjustable 3D measurement system to track the surface of the screw-head and bone plate during cyclic testing to determine potential micromotions. The micromotion is thereby described as the change in distance of the screw-head center to a reference point on the bone plate, providing information about the quality of interlocking of the related SPI during cyclic loading. Micromotion analysis was performed on the fracture-adjacent SPIs of the implant system, that were considered as the most relevant interfaces. ResultsMicromotion could be detected for both facture-adjacent SPIs in all test samples with increasing magnitude during cyclic testing, resulting in micromotions up to 587 {micro}m for the proximal and 321 {micro}m for the distal fracture-adjacent SPI after 50k load cycles. The strongest increase in micromotion could thereby be detected within early stages of cyclic loading. ConclusionsThe approach to determine micromotions of SPIs during axial cyclic loading was successful, indicating a reduction of the SPI s quality of interlocking as micromotions increase during cyclic loading of the tested locking-type implant system.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.