RESUMO
BACKGROUND: Trochlear dysplasia is known as the primary predisposing factor for patellar dislocation. Current methods to describe trochlear dysplasia are mainly qualitative or based on a limited number of discrete measurements. The purpose of this study is to apply statistical shape analysis to take the full geometrical complexity of trochlear dysplasia into account. METHODS: Statistical shape analysis was applied to 20 normal and 20 trochlear dysplastic distal femur models, including the cartilage. RESULTS: This study showed that the trochlea was anteriorized, proximalized and lateralized and that the mediolateral width and the notch width were decreased in the trochlear dysplastic femur compared to the normal femur. The first three principal components of the trochlear dysplastic femurs, accounting for 79.7% of the total variation, were size, sulcus angle and notch width. Automated classification of the trochlear dysplastic and normal femora achieved a sensitivity of 85% and a specificity of 95%. CONCLUSIONS: This study shows that shape analysis is an outstanding method to visualise the location and magnitude of shape abnormalities. Improvement of automated classification and subtyping within the trochlear dysplastic group are expected when larger training sets are used. CLINICAL RELEVANCE: Classification of trochlear dysplasia, especially borderline cases may be facilitated by automated classification. Furthermore, the identification of a decreased notch width in association with an increased sulcus angle can also contribute to the diagnosis of trochlear dysplasia.
Assuntos
Fêmur/anormalidades , Fêmur/diagnóstico por imagem , Imageamento Tridimensional , Modelos Estatísticos , Adolescente , Adulto , Cartilagem Articular/diagnóstico por imagem , Estudos de Casos e Controles , Análise Discriminante , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Masculino , Pessoa de Meia-Idade , Tomografia Computadorizada Multidetectores , Articulação Patelofemoral/anormalidades , Articulação Patelofemoral/diagnóstico por imagem , Análise de Componente Principal , Adulto JovemRESUMO
The automated extraction of anatomical reference parameters may improve speed, precision and accuracy of surgical procedures. In this study, an automated method for extracting the femoral anatomical axis (FAA) from a 3D surface mesh, based on geometrical entity fitting, is presented. This was applied to conventional total knee arthroplasty, which uses an intramedullary rod (FIR) to orient the femoral prosthesis with respect to the FAA. The orientation and entry point of a FIR with a length of 200 mm are automatically determined from the FAA, as it has been shown that errors in these parameters may lead to malalignment of the mechanical axis. Moreover, the effect of partially scanning the leg was investigated by creating reduced femur models and comparing the results with the full models. Precise measurements are obtained for 50 models by using a central and two outer parts, with lengths of 20 and 120 mm, which correspond to 58% of the mean femoral length. The deviations were less than 2 mm for the FAA, 2.8 mm for the FAA endpoints and 0.7° and 1.3 mm for the FIR orientation and entry point. The computer-based techniques might eventually be used for preoperative planning of total knee arthroplasty.