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20.03.2017 | Original Article | Ausgabe 8/2017

International Journal of Computer Assisted Radiology and Surgery 8/2017

Introduction of a computer-based method for automated planning of reduction paths under consideration of simulated muscular forces

Zeitschrift:
International Journal of Computer Assisted Radiology and Surgery > Ausgabe 8/2017
Autoren:
Jan Buschbaum, Rainer Fremd, Tim Pohlemann, Alexander Kristen

Abstract

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 \(1.2 \pm 0.9\,\hbox {mm}\) and \(2.6^{\circ } \pm 2.8^{\circ }\). Mean value and standard deviation of occurring forces are \(15.83 \pm 5.05\,\hbox {N}\) for M. tensor fasciae latae and \(3.53 \pm 1.8\,\hbox {N}\) 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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