  Purpose: To evaluate Pegasus-OCT, a clinical decision support software for
the identification of features of retinal disease from macula OCT scans, across
heterogenous populations involving varying patient demographics, device
manufacturers, acquisition sites and operators.
  Methods: 5,588 normal and anomalous macular OCT volumes (162,721 B-scans),
acquired at independent centres in five countries, were processed using the
software. Results were evaluated against ground truth provided by the dataset
owners.
  Results: Pegasus-OCT performed with AUROCs of at least 98% for all datasets
in the detection of general macular anomalies. For scans of sufficient quality,
the AUROCs for general AMD and DME detection were found to be at least 99% and
98%, respectively.
  Conclusions: The ability of a clinical decision support system to cater for
different populations is key to its adoption. Pegasus-OCT was shown to be able
to detect AMD, DME and general anomalies in OCT volumes acquired across
multiple independent sites with high performance. Its use thus offers
substantial promise, with the potential to alleviate the burden of growing
demand in eye care services caused by retinal disease.
