Patient-specific geometrical modeling of orthopedic structures with high efficiency and accuracy for finite element modeling and 3D printing.

ABSTRACT

We improved the geometrical modeling procedure for fast and accurate reconstruction of orthopedic structures. This procedure consists of medical image segmentation, three-dimensional geometrical reconstruction, and assignment of material properties. The patient-specific orthopedic structures reconstructed by this improved procedure can be used in the virtual surgical planning, 3D printing of real orthopedic structures and finite element analysis. A conventional modeling consists of image segmentation, geometrical reconstruction, mesh generation, and assignment of material properties. The present study modified the conventional method to enhance software operating procedures. Patient's CT images of different bones were acquired and subsequently reconstructed to give models. The reconstruction procedures were three-dimensional image segmentation, modification of the edge length and quantity of meshes, and the assignment of material properties according to the intensity of gravy value. We compared the performance of our procedures to the conventional procedures modeling in terms of software operating time, success rate and mesh quality. Our proposed framework has the following improvements in the geometrical modeling (1) processing time (femur 87.16 ± 5.90 %; pelvis 80.16 ± 7.67 %; thoracic vertebra 17.81 ± 4.36 %; P < 0.05); (2) least volume reduction (femur 0.26 ± 0.06 %; pelvis 0.70 ± 0.47, thoracic vertebra 3.70 ± 1.75 %; P < 0.01) and (3) mesh quality in terms of aspect ratio (femur 8.00 ± 7.38 %; pelvis 17.70 ± 9.82 %; thoracic vertebra 13.93 ± 9.79 %; P < 0.05) and maximum angle (femur 4.90 ± 5.28 %; pelvis 17.20 ± 19.29 %; thoracic vertebra 3.86 ± 3.82 %; P < 0.05). Our proposed patient-specific geometrical modeling requires less operating time and workload, but the orthopedic structures were generated at a higher rate of success as compared with the conventional method. It is expected to benefit the surgical planning of orthopedic structures with less operating time and high accuracy of modeling.