Orthopaedic Surgery (Mar 2022)

Flexion Tibial Plateau Fractures: 3‐dimensional CT Simulation‐based Subclassification by Injury Pattern

  • Yaning Hu,
  • Aqin Peng,
  • Shuai Wang,
  • Shuo Pan,
  • Xiao Zhang

DOI
https://doi.org/10.1111/os.13190
Journal volume & issue
Vol. 14, no. 3
pp. 543 – 554

Abstract

Read online

Objective To identify different injury patterns of flexion tibial plateau fractures (FTPFs) with 3D CT simulation technology. The association between these hypothesized injury patterns and concomitant injuries was also investigated. Methods The tibial plateau fracture cases of 297 patients consecutively treated at our trauma center from August 2016 to December 2018 were reviewed retrospectively. A total of 108 patients with FTPFs were enrolled. 3D CT simulation technology was used to reconstruct the position of the knee joint at the time of tibial plateau fracture. The 3D segments for the tibia and femur were created separately, the tibial 3D segment was aligned with the articular surface of the femoral condyle, and then the corresponding injury patterns were deduced. The magnitudes of translation and rotation incurred after the segments were repositioned were calculated by Mimics software. The associations between the hypothesized injury patterns and concomitant injuries were compared. Results FTPFs were classified into two groups according to the fracture region: unicondylar FTPFs (type I) and bicondylar FTPFs (type II). According to the injury patterns simulated in this study, these two types of FTPFs were further subclassified into five subgroups. Type I FTPFs were categorized into two subtypes based on the degree of rotation in the coronal plane (varus 0°): pure flexion‐varus fractures (type IA, −10.23° ± 2.11°, 3.7%, 4/108) and pure flexion‐valgus fractures (type IB, 11.54° ± 2.63°, 26.9%, 29/108). Type II FTPFs were divided into three subgroups based on the degree of rotation in the axial plane (internal rotation >10°; flexion‐neutral −10° to 10°; external rotation <−10°): flexion‐neutral fractures (type IIA, 2.01° ± 3.43°, 13.0%, 14/108), flexion‐internal rotation fractures (type IIB, 23.66° ± 6.17°, 35.2%, 38/108) and flexion‐external rotation fractures (type IIC, −16.23° ± 4.27°, 21.3%, 23/108). The incidence of posterolateral quadrant collapse fractures among type IIB fractures was significantly increased relative to that of type IIC fractures (P < 0.001). The incidence of posterolateral quadrant split fractures, anterolateral quadrant fractures and proximal fibular fractures among type IIC fractures was significantly higher than that among type IIB fractures (P < 0.001). The number of these concomitant injuries significantly differed between type IIB and type IIC fractures (P < 0.001). Conclusion 3D CT simulation‐based subclassification according to the pattern of injury can help surgeons better understand FTPFs and select an appropriate treatment strategy.

Keywords