Deep learning-based automatic segmentation of lower limb bones and hip-knee-ankle angle measurement using weight-bearing cone-beam CT
LI Han-yu
LIANG Ze-jun
HE Jian-rong
RONG Fan-zhuang
YU Xiao-cheng
XIA Chun-chao
LI Zhen-lin
TANG Jing
Abstract：Objective To develop a deep learning-based automatic segmentation model for the lower limb bones using weight-bearing cone-beam CT(CBCT)and achieve automatic measurement of three-dimensional hip-knee-ankle(HKA)angles.Additionally,to compare and analyze the differences in HKA angles measured by two-dimensional digital X-ray(DR)and three-dimensional CBCT in patients with knee osteoarthritis.Methods 65 patients underwent full lower extremity 3D imaging with CBCT in weight-bearing position.The data were divided into a training set(60 cases)and a test set(5 cases),which were used for the construction of the convolutional neural network(CNN)model for automatic segmentation of bones of the lower limbs and the Dice coefficient accuracy evaluation,respectively.Additionally,56 patients with knee osteoarthritis underwent both bilateral full lower limb DR and weight-bearing CBCT scans.DR images were used for manual measurement of two-dimensional HKA angles,while CBCT images were used for automatic measurement of three-dimensional HKA angles.The differences between the two-dimensional and three-dimensional HKA angles were analyzed for a total of 112 lower limbs using paired t-test.Results In the test set,the Dice coefficients for the automatic segmentation model of each lower limb bone were:femur 0.950,patella 0.928,tibia 0.946,fibula 0.947,and talus 0.946.The accuracy of this segmentation model ensured the precision of the three-dimensional HKA angle measurements.Further analysis showed significant differences between the two-dimensional and three-dimensional HKA angles(MD±SD:-1.23±3.07,MAD±SD:2.05±2.60,P＜0.001).Conclusions There are significant differences between two-dimensional and three-dimensional HKA angles.Additionally,the lower limb bone automatic segmentation model based on weight-bearing CBCT images developed in this study has high segmentation accuracy,providing technical foundation for the automatic measurement of three-dimensional lower limb bone parameters.
Keywords：Cone-beam computed tomographyDeep learningWeight-bearingOsteoarthritiskneeHip-knee-ankle angle
Publication Date：2024-11-19
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 902-907 )