Abstract:
Objective Full-thickness macular holes (MH) are classified principally by size, which is one of the
strongest predictors of anatomical and visual success. Using a three-dimensional (3D) automated
image processing algorithm, we analysed optical coherence tomography (OCT) images of 104 MH
of patients, comparing MH dimensions and morphology with clinician-acquired two-dimensional
measurements.
Methods and Analysis All patients underwent a high-density central horizontal scanning OCT
protocol. Two independent clinicians measured the minimum linear diameter (MLD) and maximum
base diameter. OCT images were also analysed using an automated 3D segmentation algorithm
which produced key parameters including the respective maximum and minimum diameter of the
minimum area (MA) of the MH, as well as volume and surface area.
Results Using the algorithm-derived values, MH were found to have significant asymmetry in all
dimensions. The minima of the MA were typically approximately 90° to the horizontal, and differed
from their maxima by 55 μm. The minima of the MA differed from the human-measured MLD by a m. The minima of the MA differed from the human-measured MLD by a
mean of nearly 50 μm. The minima of the MA differed from the human-measured MLD by a m, with significant interobserver variability. The resultant differences led to
reclassification using the International Vitreomacular Traction Study Group classification in a
quarter of the patients (p=0.07).
Conclusion MH are complex shapes with significant asymmetry in all dimensions. We have shown
how 3D automated analysis of MH describes their dimensions more accurately and repeatably than
human assessment. This could be used in future studies investigating hole progression and outcome
to help guide optimum treatments.
