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The femur is the body's longest and strongest bone spanning the thigh region. Its head articulates with the acetabulum of the hip bone to form the hip joint. A minor indentation on the medial side of the femoral head, called the fovea capitis, serves as the site of attachment for the ligament of the head of the femur. This weak ligament spans the femur and acetabulum and supports the hip joint. The narrowed region below the head is the neck of the femur. The inclination angle between the neck...

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Related Experiment Video

Updated: May 14, 2026

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

The aspherical human hip: implication for early osteoarthritis.

Mohamed S Hefny¹, Andrew W L Dickinson, Andrew E Giles

¹School of Computing, Queen's University, Kingston, Ontario, Canada.

Studies in Health Technology and Informatics

|February 13, 2013

Summary

A new computational method accurately quantifies femoral acetabular impingement, a marker for early hip arthritis. This approach reduces errors associated with manual radiographic measurements, improving diagnostic reliability.

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Area of Science:

Orthopedics
Radiology
Biomedical Engineering

Background:

Femoral acetabular impingement (FAI) is a key indicator of early-onset hip arthritis.
Current quantification relies on manual radiographic measurements, which are subjective and error-prone.
The alpha angle is a common radiographic measure for FAI.

Purpose of the Study:

To develop and validate a robust computational method for quantifying FAI.
To offer an objective alternative to manual radiographic measurements.
To assess the correlation of the new method with existing definitions of the alpha angle.

Main Methods:

Applied least-squares fitting of an ellipse to the femoral head contour on radiographs.
Utilized the difference between the ellipse axes as a novel quantification metric for FAI.
Compared the computational results with traditional alpha angle measurements.

Main Results:

The novel computational method demonstrated a good correlation with established definitions of the alpha angle.
The proposed numerical fitting approach provides a more objective quantification of FAI.
This technique offers a reliable alternative to manual measurements.

Conclusions:

A computational approach using ellipse fitting is a viable and accurate method for quantifying FAI.
This technique enhances objectivity and reduces user dependency in hip arthritis assessment.
The findings support the clinical utility of computational analysis in diagnosing early hip joint pathology.