Purpose
The Laguna ONhE program divides conventional color images of the optic nerve head (ONH) into 24 sectors using two ellipses, approximately parallel to its edge, and four diametrical lines. It notes the differences between its red and green components and compensates the diversities of spectral composition of the illumination light, the absorption of the lens and the spectral response of the detector used by means a relative measure: the values of the tissue are divided by those obtained in the central vessels.
Previous experience in 700 normal and 494 glaucoma images obtained with Nidek, Kowa and Topcon fundus cameras was used to optimize the Laguna ONhE index “Glaucoma Discriminant Function, GDF“.
Methods
96 healthy subjects and 82 confirmed and suspect glaucoma were examined twice with the Laguna ONhE method (INSOFT, Spain), using images obtained with the Horus DEC- 200 portable fundus camera (MiiS, Taiwan), and once with the Spectralis OCT (Heidelberg, Germany). The images were divided into two groups of better and worst contrast, comparing vessels Vs tissue, using the red and green channels in the optic nerve image. Differences between outcomes were analyzed with the MedCalc 17.9.7 program.
Results
Both series respectively had contrasts of 1.58±0.33 and 1.95±0.60 (p<0.0001). The Pearson correlation coefficient between GDF and BMO-MRW was 0.827-0.831 in the two groups of images (p<0.0001, Fig 1), between GDF and RNFLT was 0.763-0.766 (p<0.0001) and between BMO-MRW and RNFLT was 0.848 (p<0.0001, Fig 2). Intra-class correlation coefficient between the GDF values of the two exams was 0.957. Using ROC analysis, we calculated the confidence intervals (5%-95%) of the area under the curve, the specificity closest to 95%, and the corresponding sensitivity.
Conclusion
Using a simple manual fundus camera to study the distribution of hemoglobin in the optic nerve achieves a diagnostic capacity of glaucoma almost equivalent, or minimally different, to an OCT, even using images of sub-optimal quality.