A framework for three-dimensional statistical shape modeling of the proximal femur in Legg-Calvé-Perthes disease.

Purpose: The pathomorphology of Legg-Calvé-Perthes disease (LCPD) is a key contributor to poor long-term outcomes such as hip pain, femoroacetabular impingement, and early-onset osteoarthritis. Plain radiographs, commonly used for research and in the clinic, cannot accurately represent the full extent of LCPD deformity. The purpose of this study was to develop and evaluate a methodological framework for three-dimensional (3D) statistical shape modeling (SSM) of the proximal femur in LCPD.

Application of statistical shape modeling to the human hip joint: a scoping review.

Objective: The objective of this scoping review was to identify all examples of the application of statistical shape models to the human hip joint, with a focus on applications, population, methodology, and validation.

Introduction: Clinical radiographs are the most common imaging tool for management of hip conditions, but it is unclear whether radiographs can adequately diagnose or predict outcomes of 3D deformity. Statistical shape modeling, a method of describing the variation of a population of shapes using a small number of variables, has been identified as a useful tool to associate 2D images with 3D anatomy.

Application of statistical shape modeling to the human hip joint: a scoping review protocol.

Objective: This review aims to identify all examples of the application of statistical shape models to the human hip joint, with a focus on methodology, validation, and applications.

Introduction: Abnormal hip joint morphology (eg, deformity secondary to Legg-Calvé-Perthes disease) is an important precursor to osteoarthritis. Clinical radiographs are often used to characterize deformity and provide indication for surgical correction, but it is unclear whether radiographs can adequately describe three-dimensional deformity.