Development of a model to predict 3D femur morphology in infants and young children

• NCJ Number: 305265
• Journal: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Dated: 2022
• Date Published: 2022
• Author(s): Keyonna McKinsey; Angela Thompson; Raymond Dsouza; Gina Bertocci
• Grant Number(s): 2015-DN-BX-K018; 2019-R2-CX-0038
• Agencies: NIJ-Sponsored
• Sponsoring Agency: National Institute of Justice (NIJ)
• Corporate Author: University of Louisville
• Publication Format: Article
• Publication Type: Research (Applied/Empirical)
• Country: United States of America

Annotation

The purpose of this study was to develop a predictive model to generate representative 3D pediatric femur models for age 0–3 years based on child characteristics.

 

Abstract

Computed tomography (CT) images of 79 decedent (age 0–3 years) femurs were used to develop a statistical shape model characterising femur shape. A regression model predicted shape parameters from child characteristics (age, height, and weight). The predictive model demonstrated good fit (R2 = 0.976) in predicting femur shape (surface coordinates) in the test set (n = 17) and thus, can be used to generate representative 3D paediatric femur models in the absence of CT imaging. (Publisher abstract provided)