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Multidimensional Quantification of Macular Cone Activity in Pattern Electroretinography Using Discrete Wavelet

Yousif J Shwetar1,2, Melissa A Haendel3,4

  • 1Joint Department of Biomedical Engineering, University of North Carolina and North Carolina State University, Chapel Hill, NC, USA.

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Discrete Wavelet Transform (DWT) features offer new quantitative biomarkers for macular cone function in inherited retinal diseases. The sym2-D6-2 index shows promise for monitoring disease progression and therapeutic evaluation in clinical trials.

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Area of Science:

  • Ophthalmology
  • Biomedical Engineering
  • Signal Processing

Background:

  • Macular-predominant inherited retinal diseases (mpIRDs) impact cone photoreceptors, necessitating reliable biomarkers for monitoring.
  • Pattern electroretinography (PERG) assesses macular function, but quantitative feature extraction remains an area for advancement.

Purpose of the Study:

  • To evaluate discrete wavelet transform (DWT) features as quantitative biomarkers for macular cone function.
  • To assess the utility of these DWT features in the context of pattern electroretinography (PERG) for macular-predominant inherited retinal diseases (mpIRDs).

Main Methods:

  • Analyzed 486 PERG recordings from 123 participants using DWT.
  • Screened 20 mother wavelets, retaining six for feature generation, followed by cleaning and correlation pruning to yield 141 features.
  • Utilized inverse-DWT signal reconstruction with the sym2 wavelet to identify time-frequency indices preserving key PERG peaks (N35, P50, N95).

Main Results:

  • The sym2-D6-2 index (38-75 ms, 13-27 Hz) emerged as the top discriminative feature, showing strong correlation with the clinical macular cone marker |P50-N35| (rcorr = 0.95).
  • This DWT-derived index demonstrated superior group separation with a higher diagnostic area under the curve (0.875 vs. 0.835) and larger effect size (res = 0.644 vs. 0.576) compared to |P50-N35|.
  • Sym2-D6-2 provided tighter, nonoverlapping group distributions, indicating enhanced diagnostic capability.

Conclusions:

  • DWT-derived time-frequency features, specifically sym2-D6-2, serve as robust, multidimensional biomarkers of macular cone function.
  • These quantitative endpoints show significant potential for monitoring disease progression and evaluating therapeutic interventions in mpIRDs.
  • The sym2-D6-2 index offers an objective metric for macular cone function, suitable as a quantitative endpoint in mpIRD clinical trials.