Measuring extraocular muscle volume using dynamic contours.

Abstract

The effect of medical treatment on extraocular muscle enlargement in thyroid associated ophthalmopathy (TAO) may be monitored by measuring the change in volume of the extraocular muscles on serial orbital MRI examinations. In theory, 3D image sets offer the opportunity to minimise errors due to poor repositioning and partial volume effects. This study describes an automated technique for estimating extraocular muscle volumes from 3D datasets. Operator input is minimal and the technique is robust. Verification of the technique on both simulated and real datasets is described. For simulated image sets, both automated segmentation and manual outlining produced estimates of volume which were on average 4% less than "true" volume. For real patient data, extraocular muscle volumes measured by the automated technique were 1.6% (SD 13%) less than volumes measured by manual outlining. Coefficient of variation for repeat outlining of the same image dataset for the automated technique was 1.0%, compared with 4% for manual outlining. The manual technique took an experienced operator approximately 20 min to perform, compared to 7 min for the automated technique. The automated method is therefore rapid, reproducible and at least as accurate as other available methods.