Automated volumetric assessment of the Achilles tendon (AVAT) using a 3D T2 weighted SPACE sequence at 3T in healthy and pathologic cases

Purpose

Achilles tendinopathy has been reported to be frequently associated with increasing volume of the tendon. This work aims at reliable and accurate volumetric quantification of the Achilles tendon using a newly developed contour detection algorithm applied on high resolution MRI data sets recorded at 3 T.

Materials and methods

A total of 26 healthy tendons and 4 degenerated tendons were examined for this study. Automated identification (AI) of tendon boundaries was performed in transverse slices with isotropic resolution (0.8 mm) gained with a T2-weighted SPACE sequence at 3 T. For AI a snake algorithm was applied and compared to manual tracing (MT).

Results

AI was feasible in all examined tendons without further correction. AI of both tendons was performed in each participant within 2 min (2 × 37 slices) compared to MT lasting 20 min. MT and AI showed excellent agreement and correlation (R² = 0.99, p < 0.0001). AI provided a reduction of measurement error (0.4 cm³ vs. 0.5 cm³) and coefficient of variation (1% vs. 2%).

Discussion

Compared to MT the AI allows assessment of tendon volumes in highly resolved MRI data in a more accurate and reliable time-saving way. Therefore automated volume detection is seen as a helpful clinical tool for evaluation of small volumetric changes of the Achilles tendon.