Abstract
Objective: The study aimed to evaluate whether the measurement of Femoral Neck Shaft Angle (FNSA) can be helpful in differentiating femoral head Stress Fracture (SF) from Avascular Necrosis (AVN).
Methods: From September 2019 to April 2022, sixty-four patients [median age 32.0 years, interquartile range (IQR) 23.0–39.0 years] who underwent both hip radiograph and Magnetic Resonance Imaging (MRI) and diagnosed as femoral head SF or AVN were included in our retrospective study. Patients were divided into as having either femoral head SF (n = 34) or AVN (n = 30). The FNSA was measured in anteroposterior hip radiography. Continuous values were compared using the Mann-Whitney U test. The assessment of the predictive value of FNSA for femoral head SF was performed by Receiver Operating Characteristic (ROC) analysis.
Results: The FNSA was significantly higher in patients with SF (median 133.5°, IQR 128.0–136.7°) than those with AVN (median 127.5°, IQR 124.0–132.0°) (p = 0.001). In addition, the FNSA was significantly higher in SF femurs (median 134.8°, IQR 129.2–137.4°) than in contralateral normal femurs (median 127.1°, IQR 124.3–132.5°) in patients with unilateral femoral head SF (n = 30) (p < 0.001). In ROC analysis, the sensitivity, specificity, and Area Under the Curve (AUC) for predicting the femoral head SF were 77.3%, 63.3%, and 0.785 (95% confidence interval: 0.666–0.905), respectively, at a cutoff of 130.2°.
Conclusion: Increased FNSA was associated with femoral head SF; thus, measurement of FNSA could be helpful for differentiating femoral head SF from AVN.
Keywords: Radiography, Femoral neck shaft angle, Stress fracture, Avascular necrosis, Differentiation, Femoral head.
Call for Papers in Thematic Issues
Intelligent Information Retrieval for Multispectral and Hyperspectral Imaging
Multispectral and hyperspectral imaging is an interdisciplinary research area, widely focuses on spectral, spatial, and temporal data. It offers a plethora of opportunities to efficiently analyze the vast area of the earth's surface. However, there are numerous factors such as dimensionality and size of the hyperspectral data, lesser training samples, ...read more
Multimodal Imaging Using Spectroscopic Techniques for Improved Surgical Guidance
The majority of patients with solid malignancies have surgical excision as their primary and most successful method of medical care. On the other hand, patients experience recurrence and subsequent recurrence. Their objective was to provide a simpler and more concise explanation of the obstacles faced by physicians and the ways ...read more
Quantum Machine Learning for Medical Data and Imaging
Quantum computing has promised a significant speedup in certain computationally intensive tasks that are intractable on classical computers. Researchers in quantum machine learning, such as those working in computer vision, image processing, biomedical analysis, and related topics, may play an important role in comprehending and working on complicated medical data, ...read more
8