Reliability of tarsal bone segmentation and its contribution to MR kinematic analysis methods

Area of Science:

• Medical Imaging
• Orthopedics
• Biomechanics

Background:

• Tarsal bone segmentation is crucial for accurate kinematic analysis.
• Magnetic resonance (MR) imaging offers detailed anatomical visualization.
• Assessing the reliability of segmentation is vital for clinical and research applications.

Purpose of the Study:

• To evaluate the reliability of tarsal bone segmentation using commercial software and magnetic resonance imaging (MRI).
• To compare the reproducibility of segmentation between different operators.
• To determine the impact of segmentation variability on MR-based kinematic analysis methods.

Main Methods:

• Five subjects underwent manual segmentation of all tarsal bones five times each by two independent operators.
• Morphological parameters (volume, second moment of volume) were calculated to assess intra- and interoperator reproducibility.
• Two kinematic analysis methods (surface point clouds and principal axes) were compared for their sensitivity to segmentation variations.

Main Results:

• Excellent interclass correlation coefficients (>0.997) were achieved for morphological parameters, indicating high intra- and interoperator reproducibility.
• The surface point cloud method demonstrated significantly less sensitivity to segmentation variability (cuboid: up to 0.2°, other tarsal bones: up to 0.1°) compared to the principal axes method (cuboid: up to 6.7°, other tarsal bones: up to 0.8°).

Conclusions:

• Tarsal bone segmentation using MRI and the evaluated software is a reliable and reproducible procedure.
• Operators are interchangeable for this segmentation task.
• The surface point cloud method is recommended for MR-based kinematic analysis due to its robustness against segmentation variations.