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Updated: Mar 6, 2026

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
Published on: April 11, 2018
Introduction of a computer-based method for automated planning of reduction paths under consideration of simulated
Jan Buschbaum1, Rainer Fremd2, Tim Pohlemann3
1Fachbereich Angewandte Ingenieurwissenschaften, Hochschule Kaiserslautern - University of Applied Sciences, Schoenstraße 11, 67659, Kaiserslautern, Germany. jan.buschbaum@hs-kl.de.
Purpose:
Reduction is a crucial step in the surgical treatment of bone fractures. Finding an optimal path for restoring anatomical alignment is considered technically demanding because collisions as well as high forces caused by surrounding soft tissues can avoid desired reduction movements. The repetition of reduction movements leads to a trial-and-error process which causes a prolonged duration of surgery. By planning an appropriate reduction path-an optimal sequence of target-directed movements-these problems should be overcome. For this purpose, a computer-based method has been developed.
Methods:
Using the example of simple femoral shaft fractures, 3D models are generated out of CT images. A reposition algorithm aligns both fragments by reconstructing their broken edges. According to the criteria of a deduced planning strategy, a modified A*-algorithm searches collision-free route of minimal force from the dislocated into the computed target position. Muscular forces are considered using a musculoskeletal reduction model (OpenSim model), and bone collisions are detected by an appropriate method.
Results:
Five femoral SYNBONE models were broken into different fracture classification types and were automatically reduced from ten randomly selected displaced positions. Highest mean translational and rotational error for achieving target alignment is [Formula: see text] and [Formula: see text]. Mean value and standard deviation of occurring forces are [Formula: see text] for M. tensor fasciae latae and [Formula: see text] for M. semitendinosus over all trials. These pathways are precise, collision-free, required forces are minimized, and thus regarded as optimal paths.
Conclusions:
A novel method for planning reduction paths under consideration of collisions and muscular forces is introduced. The results deliver additional knowledge for an appropriate tactical reduction procedure and can provide a basis for further navigated or robotic-assisted developments.
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