ArticleBMC musculoskeletal disorders2025
Conditional GAN performs better than orthopedic surgeon in virtual reduction of femoral neck fracture.
Article in BMC musculoskeletal disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveSatisfied reduction of fracture is hard to achieve. The purpose of this study is to develop a virtual fracture reduction technique using conditional GAN (Generative Adversarial Network), and evaluate its performance in simulating and guiding reduction of femoral neck fracture, which is hard to reduce. We compared its reduction quality with manual reduction performed by orthopedic surgeons. It is a pilot study for augmented reality assisted femoral neck fracture surgery.
methodsTo establish the gold standard of reduction, we invited an orthopedic surgeon to perform virtual reduction registration with reference to the healthy proximal femur. The invited orthopedic surgeon also performed manual reduction by Mimics software to represent the capability of human doctor. Then we trained conditional GAN models on our dataset, which consisted 208 images from 208 different patients. For displaced femoral neck fractures, it is not easy to measure the accurate angles, like Pauwels angle, of the fracture line. However, the fracture lines would be clearer after reduction. We compared the results of manual reduction, conditional GAN models and registration by Pauwels angle, Garden index and satisfied reduction rate. We tried different number of downsampling (α) to optimize the performance of conditional GAN models.
resultsThere were 208 pre-surgical CT scans from 208 patients included in our study (age 69.755 ± 13.728, including 88 men). The Pauwles angles of conditional GAN model(α = 0) was 38.519°, which was significantly more stable than manual reduction (44.647°, p < 0.001). The Garden indices of conditional GAN model(α = 0) was 176.726°, which was also significantly more stable than manual reduction (163.590°, p = 0.002). The satisfied reduction rate of conditional GAN model(α = 0) was 88.372%, significantly higher than manual reduction (53.488%, p < 0.001). The Pauwels angles, Garden indices and satisfied reduction rate of conditional GAN model(α = 0) showed no difference to registration.
conclusionConditional GAN model(α = 0) can achieve better performance in the virtual reduction of femoral neck fracture than orthopedic surgeon.
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