Correlation of Automated Computed Tomography Volumetric Analysis Metrics With Motility Disturbances in Thyroid Eye Disease

Abstract

Purpose: The authors sought to examine relationships between CT metrics derived via an automated method and clinical parameters of extraocular muscle changes in thyroid eye disease (TED). Methods: CT images of 204 orbits in the setting of TED were analyzed with an automated segmentation tool developed at the institution. Labels were applied to orbital structures of interest on the study images, which were then registered against a previously established atlas of manually indexed orbits derived from 35 healthy individuals. Point-wise correspondences between study and atlas images were then compared via a fusion algorithm to highlight metrics of interest where TED orbits differed from healthy orbits. Results: Univariate analysis demonstrated several correlations between CT metrics and clinical data. Metrics pertaining to the extraocular muscles—including average diameter, maximum diameter, and muscle volume—were strongly correlated (p < 0.05) with the presence of ocular motility deficits with regards to the superior, inferior, and lateral recti (with exception of superior rectus motility deficits being mildly correlated with muscle volume [p = 0.09]). Motility defects of the medial rectus were strongly correlated with muscle volume, and only weakly correlated with average and maximum muscle diameter. Conclusions: The novel method of automated imaging metrics may provide objective, rapid clinical information which may have utility in prevention and recognition of visual impairments in TED before they reach an advanced or irreversible stage and while they are able to be improved with immunomodulatory treatments.

Reply Re: “Correlation of Automated Computed Tomography Volumetric Analysis Metrics With Motility Disturbances in Thyroid Eye Disease”

“…We thank Li et al for their comments on our thyroid eye disease research. 1 We agree with the authors that additional validation of automated segmentation in thyroid eye disease is needed. Validation of any measurement tool is important, and we have done it.…”

“…We demonstrate that Kalman filters provide a simple, yet fast and efficient solution to improving muscle segmentation in thyroid eye disease. 1,6,10…”

Re: “Correlation of Automated Computed Tomography Volumetric Analysis Metrics With Motility Disturbances in Thyroid Eye Disease”

“…We read with great interest the article “Correlation of Automated Computed Tomography Volumetric Analysis Metrics With Motility Disturbances in Thyroid Eye Disease” wherein Law et al 1 employ an automated segmentation method developed using normal orbital CT images to characterize relationships between CT metrics and clinical findings in patients with thyroid eye disease. Using this automated method, the authors concluded that ocular motility deficits were correlated with superior, inferior, and lateral recti average diameter, maximum diameter, and volume, and medial rectus volume.…”

“…Using this automated method, the authors concluded that ocular motility deficits were correlated with superior, inferior, and lateral recti average diameter, maximum diameter, and volume, and medial rectus volume. 1…”

“…2 Accuracy was assessed using intersection over union and Dice coefficient, which is standard for analyzing such imaging algorithms. 2,3 As the automated segmentation method described by Law et al 1 was developed using normal orbit CT images, further validation must be presented to describe the accuracy of this new method as applied to thyroid eye disease orbits before clinical associations can be meaningfully analyzed.…”