PURPOSE: To highlight changing features over time within a single static image through the auto-alignment and subtraction of serial optic nerve photographs. METHODS: Subtraction maps were generated from auto-aligned (EyeIC, Narbeth, PA) baseline and follow-up images using Adobe Photoshop software. They demonstrated progressive retinal nerve fibre layer (RNFL) defects, optic disc haemorrhage (DH), neuroretinal rim loss (RL) and peripapillary atrophy (PPA). A masked glaucoma specialist identified features of progression on subtraction map first, then assessed feature strength by comparison with original images using alternation flicker. Control images with no progression and parallax-only images (as determined by flicker) were included. RESULTS: Eighty eyes of 67 patients were used to generate subtraction maps that detected glaucoma progression in 87% of DH (n = 28, sensitivity (Se) 82%, specificity (Sp) 98%) and 84% of PPA (n = 30, Se 80%, Sp 98%) cases. The lowest rate of detection was seen with RL at 67% (n = 31, Se 65%, Sp 100%). The subtraction technique was most sensitive for detecting parallax (n = 39, Se 98%, Sp 94%). Features of glaucoma progression appeared equally strong in flicker and subtraction images, but parallax was often enhanced on subtraction maps. Among control images selected for absence of features of glaucomatous change (n = 9) in original flicker images, no features were detected on subtraction maps. CONCLUSIONS: Auto-alignment and subtraction of serial optic nerve photographs reliably detects features of glaucoma progression with a single static image. Parallax identification may also be facilitated. Auto-alignment and subtraction of serial optic nerve photographs may prove especially useful in education and printed publications when dynamic imaging is not feasible.
PURPOSE: To highlight changing features over time within a single static image through the auto-alignment and subtraction of serial optic nerve photographs. METHODS: Subtraction maps were generated from auto-aligned (EyeIC, Narbeth, PA) baseline and follow-up images using Adobe Photoshop software. They demonstrated progressive retinal nerve fibre layer (RNFL) defects, optic disc haemorrhage (DH), neuroretinal rim loss (RL) and peripapillary atrophy (PPA). A masked glaucoma specialist identified features of progression on subtraction map first, then assessed feature strength by comparison with original images using alternation flicker. Control images with no progression and parallax-only images (as determined by flicker) were included. RESULTS: Eighty eyes of 67 patients were used to generate subtraction maps that detected glaucoma progression in 87% of DH (n = 28, sensitivity (Se) 82%, specificity (Sp) 98%) and 84% of PPA (n = 30, Se 80%, Sp 98%) cases. The lowest rate of detection was seen with RL at 67% (n = 31, Se 65%, Sp 100%). The subtraction technique was most sensitive for detecting parallax (n = 39, Se 98%, Sp 94%). Features of glaucoma progression appeared equally strong in flicker and subtraction images, but parallax was often enhanced on subtraction maps. Among control images selected for absence of features of glaucomatous change (n = 9) in original flicker images, no features were detected on subtraction maps. CONCLUSIONS: Auto-alignment and subtraction of serial optic nerve photographs reliably detects features of glaucoma progression with a single static image. Parallax identification may also be facilitated. Auto-alignment and subtraction of serial optic nerve photographs may prove especially useful in education and printed publications when dynamic imaging is not feasible.