Effect of Intensity Discretization on Radiomic Features in En Face EDI-OCT of Choroidal Nevi

Background/Objectives: Intensity discretization influences radiomic measurements, but its effects in optical coherence tomography (OCT) of choroidal lesions remain insufficiently characterized. We evaluated fixed bin width (FBW) and fixed bin number (FBN) strategies with different parameters to inform discretization choices for en face enhanced-depth imaging OCT (EDI-OCT) of stable choroidal nevi. Methods: Ninety-three original-domain radiomic features were extracted from 64 eyes across 11 discretization settings (FBW 2 - 64; FBN 8 - 64). We assessed feature values, eye rankings, observer reproducibility, slab-depth dependence, redundancy, and feature-set overlap. Primary absolute-agreement intraclass correlation coefficients (ICCs) used per-eye feature values averaged across six numeric slabs. Histogram entropy and an approximate co-occurrence sampling-density proxy characterized the discretized intensity representation. Results: Seventy-seven features depended on discretization. Median occupied gray levels decreased with increasing bin width from 54 at FBW 2 to five at FBW 25. Eye rankings were similar between neighboring settings (median Spearman ρ 0.97 - 0.99), but less concordant in selected FBW - FBN comparisons. Median observer ICCs ranged from 0.84 to 0.91, without clear evidence of differences between settings. Feature sets overlapped less after redundancy reduction. FBW 4 and FBN 32 provided intermediate gray-level resolution and sampling-density proxies, retaining at least 16 occupied gray levels in approximately 99% and 100% of observations, respectively. Conclusions: Intensity discretization substantially alters radiomic texture values, eye rankings, and feature selection. Observer reproducibility alone is insufficient to guide discretization choice. Intensity representation, gray-level compression, and slab depth should also be considered. FBW 4 and FBN 32 emerged as exploratory candidate settings within the evaluated pipeline. External validation and assessment of clinical utility remain necessary.

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Journal
medRxiv
Published
2026-11-02
DOI
https://doi.org/10.64898/2026.11.01.26367028
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
preprint
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preprint

Effect of Intensity Discretization on Radiomic Features in En Face EDI-OCT of Choroidal Nevi

Hugo Alexandre Ferreira, Helena Rico Pereira, Marco Dutra-Medeiros, Duarte Oliveira-Saraiva et al.
medRxiv
Radiomics and Machine Learning in Medical Imaging
preprint

Effect of Intensity Discretization on Radiomic Features in En Face EDI-OCT of Choroidal Nevi

Hugo Alexandre Ferreira, Helena Rico Pereira, Marco Dutra-Medeiros, Duarte Oliveira-Saraiva, Maria Luz Cachulo, João Pedro Nobre, Marta Vila Franca
preprint en

Abstract

Background/Objectives: Intensity discretization influences radiomic measurements, but its effects in optical coherence tomography (OCT) of choroidal lesions remain insufficiently characterized. We evaluated fixed bin width (FBW) and fixed bin number (FBN) strategies with different parameters to inform discretization choices for en face enhanced-depth imaging OCT (EDI-OCT) of stable choroidal nevi. Methods: Ninety-three original-domain radiomic features were extracted from 64 eyes across 11 discretization settings (FBW 2 - 64; FBN 8 - 64). We assessed feature values, eye rankings, observer reproducibility, slab-depth dependence, redundancy, and feature-set overlap. Primary absolute-agreement intraclass correlation coefficients (ICCs) used per-eye feature values averaged across six numeric slabs. Histogram entropy and an approximate co-occurrence sampling-density proxy characterized the discretized intensity representation. Results: Seventy-seven features depended on discretization. Median occupied gray levels decreased with increasing bin width from 54 at FBW 2 to five at FBW 25. Eye rankings were similar between neighboring settings (median Spearman ρ 0.97 - 0.99), but less concordant in selected FBW - FBN comparisons. Median observer ICCs ranged from 0.84 to 0.91, without clear evidence of differences between settings. Feature sets overlapped less after redundancy reduction. FBW 4 and FBN 32 provided intermediate gray-level resolution and sampling-density proxies, retaining at least 16 occupied gray levels in approximately 99% and 100% of observations, respectively. Conclusions: Intensity discretization substantially alters radiomic texture values, eye rankings, and feature selection. Observer reproducibility alone is insufficient to guide discretization choice. Intensity representation, gray-level compression, and slab depth should also be considered. FBW 4 and FBN 32 emerged as exploratory candidate settings within the evaluated pipeline. External validation and assessment of clinical utility remain necessary.

medRxiv
University of Lisbon (PT), University of Coimbra (PT), Universidade Nova de Lisboa (PT)
Radiomics and Machine Learning in Medical Imaging
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