Machine learning-based estimation of Calcaneus volume using plain radiographic morphometry
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View abstract on PubMed
Summary
This summary is machine-generated.A new formula estimates calcaneus (heel bone) volume using simple radiographic measurements. This method overcomes previous calculation difficulties, offering a practical tool for future anatomical and clinical research.
Area Of Science
- Anatomy
- Biometrics
- Radiology
Background
- Calcaneus volume estimation is challenging, with limited existing studies.
- Accurate volume measurement is crucial for anatomical and clinical applications.
Purpose Of The Study
- To develop a formula for approximating calcaneus volume using plain radiographs.
- To establish a practical method for calcaneus volume calculation.
Main Methods
- Utilized 216 dry adult calcanei from Anatolia.
- Calculated volumes via Archimedes' water displacement method.
- Measured multiple dimensions from lateral and axial radiographs, including lengths, heights, and widths.
- Derived the formula using a multiple linear regression model with Python 3.12.
Main Results
- The mean calcaneus volume was 55.8 mL (SD 11.7 mL).
- A multiple linear regression model yielded the formula: Volume (mL) = 0.96 × max AP l (mm) + 0.40 × max body l (mm) - 0.29 × body h (mm) + 0.76 × min body h (mm) + 0.14 × max post w (mm) + 0.48 × min post w (mm) - 7.49.
- This formula provides an approximate calcaneus volume based on radiographic measurements.
Conclusions
- The derived formula offers a viable method for estimating calcaneus volume.
- The methodology can be applied to similar studies on dry bone specimens.
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