Abstract
PURPOSE: To extend wavelet analysis of pattern electroretinography (PERG) from macular cone to retinal ganglion cell (RGC) dysfunction in optic nerve disease (OND) by validating Symlet-2 (sym2) discrete wavelet transform (DWT) features.
METHODS: From the open access PERG-Institute of Applied Ophthalmobiology (IOBA) dataset, 58 recordings from OND subjects and 262 recordings from healthy volunteers (HVs) were analyzed. Five pre-selected sym2 coefficients (D5-2, D6-2, D6-3, A6-3, A6-4) were quantified. Their correlations with canonical amplitudes (|P50-N35|, |N95-P50|) and group separation (rank-biserial effect size, |rrb|) were analyzed. We also assessed a previously defined DWT energy index based on the Daubechies 8 mother wavelet (7N), capturing RGC activity.
RESULTS: The macular cone-specific sym2-D6-2 correlated tightly with |P50-N35| in HVs (rcorr = 0.95) and OND subjects (rcorr = 0.97). In contrast, sym2-A6-4 (112-150 ms, 0-13 Hz) was best suited to capture differences between the HV and OND groups (|rrb| = 0.549), compared to |N95-P50| (|rrb| = 0.358). Bootstrap benchmarking confirmed that sym2-A6-4 outperformed |P50-N35| and |N95-P50| (Δ|rrb| = 0.362 and 0.187; Pboot = 0.005 and 0.036, respectively). The 7N feature failed to yield effective results on all measures (|rrb| = 0.084).
CONCLUSIONS: Sym2 DWT features provide compartment-specific, multidimensional biomarkers that outperform traditional canonical peaks for both macular cone (sym2-D6-2) and RGC (sym2-A6-4) assessment. Future work should validate these biomarkers in a large, diverse, genetically and phenotypically characterized external cohort to confirm generalizability and clinical utility.
TRANSLATIONAL RELEVANCE: Sym2 wavelet indices provide robust and sensitive PERG biomarkers that could serve as quantitative endpoints in clinical trials.