OCT-derived GCIPL Color Code Indicates Progression in NTG Suspects

Interpreting OCT results can be especially challenging in patients with high myopia. Retinal nerve fiber layer (RNFL) and macular ganglion cel–inner plexiform layer (GCIPL) measurements in these eyes frequently yield values that fall outside normal limits. True glaucomatous thinning in these layers may be underestimated or overlooked, particularly when global retinal thinning masks localized loss. This presents a diagnostic dilemma in differentiating high myopia from early glaucoma, particularly in patients without elevated intraocular pressure (IOP). This scan from the study shows a representative case of a stable NTG suspect with preserved inferotemporal and average GCIPL thickness. The macular cube scan shows borderline (yellow-coded) thinning in selected sectors, but both the inferotemporal and average GCIPL thicknesses remain within normal limits (green-coded) in both eyes. Initial Humphrey VF test in 2016 (figure E-1) reveals no glaucomatous visual field defects and follow-up in 2024 (figure E-2) confirms continued functional stability with no signs of progression. This case highlights the long-term clinical relevance of preserved inferotemporal and average GCIPL thickness, suggesting that even in highly myopic eyes, a green color code in these sectors is associated with sustained visual field stability. Photo: Shin HJ, et al. Sci Rep. February 22, 2026. Click image to enlarge.  Researchers based in South Korea aimed to find out whether the predictive color coding on OCT could predict glaucomatous conversion in normal-tension glaucoma (NTG) suspects and whether this approach retains its predictive value in highly myopic eyes. The study found that color-coded inferotemporal GCIPL thinning at baseline was significantly associated with visual field (VF) progression over time. In particular, GCIPL color code abnormalities maintained clinical relevance even in the high myopia subgroup, where RNFL-based interpretations were less informative.“The clinical strength of this parameter lies not in its ability to confirm disease, but in its ability to rule out progression,” the study authors wrote in their paper, which was published in Scientific Reports.A total of 307 eyes underwent baseline spectral-domain OCT imaging, with RNFL and GCIPL thicknesses categorized by device-generated color codes (green: normal, yellow: borderline, red: abnormal). Glaucoma conversion was defined by the emergence of reproducible visual field defects over a mean follow-up of 76.0 months, during which 23.8% of eyes progressed.Inferotemporal GCIPL thickness showed the strongest discriminative capacity (area under the curve [AUC] = 0.68, cutoff = 62.0μm), with further improvement in highly myopic eyes (AUC = 0.85). Red color coding in the inferotemporal sector was associated with a significantly increased risk of conversion (hazard ratio: 2.47), while eyes with green coding in both inferotemporal and average GCIPL sectors demonstrated high negative predictive values (85.0% overall, 90.2% in the myopic subgroup).“The high negative predictive value associated with these parameters supports their use as conservative decision-making tools in settings where overtreatment is a concern,” the researchers noted. “While the inferotemporal GCIPL thickness demonstrated the strongest predictive value among GCIPL sectors, the AUC values and corresponding sensitivity and positive predictive value remained modest.”A low positive predictive value and sensitivity highlight the need for supplementary diagnostic tools when evaluating high-risk patients. Therefore, the research team believes that a multimodal assessment combining structural, functional, and potentially perfusion-based metrics remains essential for accurate risk stratification in clinical practice.Click here for the journal source. Shin HJ, Park HL, Ryu HK, Park CK. GCIPL color coding on OCT predicts glaucoma conversion in normal-tension glaucoma suspects, including a high myopia subgroup. Sci Rep. February 22, 2026. [Epub ahead of print]. This article was developed by the editorial staff in conjunction with experts in the field. In the process, AI may have been among the editorial tools used to meet the goals of human editors, who approved all content.