Purpose: To validate and evaluate the accuracy of an algorithm for the identification of nonmetallic intraocular foreign body composition based on computed tomography and magnetic resonance imaging.
Methods: An algorithm for the identification of 10 nonmetallic materials based on computed tomography and magnetic resonance imaging has been previously determined in an ex vivo porcine model. Materials were classified into 4 groups (plastic, glass, stone, and wood). The algorithm was tested by 40 ophthalmologists, which completed a questionnaire including 10 sets of computed tomography and magnetic resonance images of eyes with intraocular foreign bodies and were asked to use the algorithm to identify their compositions. Rates of exact material identification and group identification were measured.
Results: Exact material identification was achieved in 42.75% of the cases, and correct group identification in 65%. Using the algorithm, 6 of the materials were exactly identified by over 50% of the participants, and 7 were correctly classified according to their groups by over 75% of the materials.
Discussion: The algorithm was validated and was found to enable correct identification of nonmetallic intraocular foreign body composition in the majority of cases. This is the first study to report and validate a clinical tool allowing intraocular foreign body composition based on their appearance in computed tomography and magnetic resonance imaging, which was previously impossible.