Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage

Gábor M. Somfai, Erika Tátrai, Lenke Laurik, Boglárka E. Varga, Vera Ölvedy, William E Smiddy, Robert Tchitnga, Anikó Somogyi, Delia Cabrera DeBuc

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Background: The sensitivity of Optical Coherence Tomography (OCT) images to identify retinal tissue morphology characterized by early neural loss from normal healthy eyes is tested by calculating structural information and fractal dimension. OCT data from 74 healthy eyes and 43 eyes with type 1 diabetes mellitus with mild diabetic retinopathy (MDR) on biomicroscopy was analyzed using a custom-built algorithm (OCTRIMA) to measure locally the intraretinal layer thickness. A power spectrum method was used to calculate the fractal dimension in intraretinal regions of interest identified in the images. ANOVA followed by Newman-Keuls post-hoc analyses were used to test for differences between pathological and normal groups. A modified p value of <0.001 was considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between eyes of pathological patients and normal healthy eyes.Results: Fractal dimension was higher for all the layers (except the GCL + IPL and INL) in MDR eyes compared to normal healthy eyes. When comparing MDR with normal healthy eyes, the highest AUROC values estimated for the fractal dimension were observed for GCL + IPL and INL. The maximum discrimination value for fractal dimension of 0.96 (standard error =0.025) for the GCL + IPL complex was obtained at a FD ≤ 1.66 (cut off point, asymptotic 95% Confidence Interval: lower-upper bound = 0.905-1.002). Moreover, the highest AUROC values estimated for the thickness measurements were observed for the OPL, GCL + IPL and OS. Particularly, when comparing MDR eyes with control healthy eyes, we found that the fractal dimension of the GCL + IPL complex was significantly better at diagnosing early DR, compared to the standard thickness measurement.Conclusions: Our results suggest that the GCL + IPL complex, OPL and OS are more susceptible to initial damage when comparing MDR with control healthy eyes. Fractal analysis provided a better sensitivity, offering a potential diagnostic predictor for detecting early neurodegeneration in the retina.

Original languageEnglish
Article number295
JournalBMC Bioinformatics
Volume15
Issue number1
DOIs
StatePublished - Sep 1 2014

Fingerprint

Optical Coherence Tomography
Fractals
Optical tomography
Fractal dimension
Fractal Dimension
Fractal
Quantify
Damage
Tissue
Diabetic Retinopathy
Thickness measurement
Fractal Analysis
Diabetes Mellitus
Retina
Receiver Operating Characteristic Curve
p-Value
Standard error
Medical problems
Region of Interest
Analysis of variance (ANOVA)

Keywords

  • Diabetic retinopathy
  • Fractal analysis
  • Fractal dimension
  • Ophthalmology
  • Optical coherence tomography
  • Wavelet algorithm

ASJC Scopus subject areas

  • Applied Mathematics
  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications

Cite this

Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage. / Somfai, Gábor M.; Tátrai, Erika; Laurik, Lenke; Varga, Boglárka E.; Ölvedy, Vera; Smiddy, William E; Tchitnga, Robert; Somogyi, Anikó; Cabrera DeBuc, Delia.

In: BMC Bioinformatics, Vol. 15, No. 1, 295, 01.09.2014.

Research output: Contribution to journalArticle

Somfai, Gábor M. ; Tátrai, Erika ; Laurik, Lenke ; Varga, Boglárka E. ; Ölvedy, Vera ; Smiddy, William E ; Tchitnga, Robert ; Somogyi, Anikó ; Cabrera DeBuc, Delia. / Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage. In: BMC Bioinformatics. 2014 ; Vol. 15, No. 1.
@article{06c40a2e94f74ff4b04a9a982fedc867,
title = "Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage",
abstract = "Background: The sensitivity of Optical Coherence Tomography (OCT) images to identify retinal tissue morphology characterized by early neural loss from normal healthy eyes is tested by calculating structural information and fractal dimension. OCT data from 74 healthy eyes and 43 eyes with type 1 diabetes mellitus with mild diabetic retinopathy (MDR) on biomicroscopy was analyzed using a custom-built algorithm (OCTRIMA) to measure locally the intraretinal layer thickness. A power spectrum method was used to calculate the fractal dimension in intraretinal regions of interest identified in the images. ANOVA followed by Newman-Keuls post-hoc analyses were used to test for differences between pathological and normal groups. A modified p value of <0.001 was considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between eyes of pathological patients and normal healthy eyes.Results: Fractal dimension was higher for all the layers (except the GCL + IPL and INL) in MDR eyes compared to normal healthy eyes. When comparing MDR with normal healthy eyes, the highest AUROC values estimated for the fractal dimension were observed for GCL + IPL and INL. The maximum discrimination value for fractal dimension of 0.96 (standard error =0.025) for the GCL + IPL complex was obtained at a FD ≤ 1.66 (cut off point, asymptotic 95{\%} Confidence Interval: lower-upper bound = 0.905-1.002). Moreover, the highest AUROC values estimated for the thickness measurements were observed for the OPL, GCL + IPL and OS. Particularly, when comparing MDR eyes with control healthy eyes, we found that the fractal dimension of the GCL + IPL complex was significantly better at diagnosing early DR, compared to the standard thickness measurement.Conclusions: Our results suggest that the GCL + IPL complex, OPL and OS are more susceptible to initial damage when comparing MDR with control healthy eyes. Fractal analysis provided a better sensitivity, offering a potential diagnostic predictor for detecting early neurodegeneration in the retina.",
keywords = "Diabetic retinopathy, Fractal analysis, Fractal dimension, Ophthalmology, Optical coherence tomography, Wavelet algorithm",
author = "Somfai, {G{\'a}bor M.} and Erika T{\'a}trai and Lenke Laurik and Varga, {Bogl{\'a}rka E.} and Vera {\"O}lvedy and Smiddy, {William E} and Robert Tchitnga and Anik{\'o} Somogyi and {Cabrera DeBuc}, Delia",
year = "2014",
month = "9",
day = "1",
doi = "10.1186/1471-2105-15-295",
language = "English",
volume = "15",
journal = "BMC Bioinformatics",
issn = "1471-2105",
publisher = "BioMed Central",
number = "1",

}

TY - JOUR

T1 - Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage

AU - Somfai, Gábor M.

AU - Tátrai, Erika

AU - Laurik, Lenke

AU - Varga, Boglárka E.

AU - Ölvedy, Vera

AU - Smiddy, William E

AU - Tchitnga, Robert

AU - Somogyi, Anikó

AU - Cabrera DeBuc, Delia

PY - 2014/9/1

Y1 - 2014/9/1

N2 - Background: The sensitivity of Optical Coherence Tomography (OCT) images to identify retinal tissue morphology characterized by early neural loss from normal healthy eyes is tested by calculating structural information and fractal dimension. OCT data from 74 healthy eyes and 43 eyes with type 1 diabetes mellitus with mild diabetic retinopathy (MDR) on biomicroscopy was analyzed using a custom-built algorithm (OCTRIMA) to measure locally the intraretinal layer thickness. A power spectrum method was used to calculate the fractal dimension in intraretinal regions of interest identified in the images. ANOVA followed by Newman-Keuls post-hoc analyses were used to test for differences between pathological and normal groups. A modified p value of <0.001 was considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between eyes of pathological patients and normal healthy eyes.Results: Fractal dimension was higher for all the layers (except the GCL + IPL and INL) in MDR eyes compared to normal healthy eyes. When comparing MDR with normal healthy eyes, the highest AUROC values estimated for the fractal dimension were observed for GCL + IPL and INL. The maximum discrimination value for fractal dimension of 0.96 (standard error =0.025) for the GCL + IPL complex was obtained at a FD ≤ 1.66 (cut off point, asymptotic 95% Confidence Interval: lower-upper bound = 0.905-1.002). Moreover, the highest AUROC values estimated for the thickness measurements were observed for the OPL, GCL + IPL and OS. Particularly, when comparing MDR eyes with control healthy eyes, we found that the fractal dimension of the GCL + IPL complex was significantly better at diagnosing early DR, compared to the standard thickness measurement.Conclusions: Our results suggest that the GCL + IPL complex, OPL and OS are more susceptible to initial damage when comparing MDR with control healthy eyes. Fractal analysis provided a better sensitivity, offering a potential diagnostic predictor for detecting early neurodegeneration in the retina.

AB - Background: The sensitivity of Optical Coherence Tomography (OCT) images to identify retinal tissue morphology characterized by early neural loss from normal healthy eyes is tested by calculating structural information and fractal dimension. OCT data from 74 healthy eyes and 43 eyes with type 1 diabetes mellitus with mild diabetic retinopathy (MDR) on biomicroscopy was analyzed using a custom-built algorithm (OCTRIMA) to measure locally the intraretinal layer thickness. A power spectrum method was used to calculate the fractal dimension in intraretinal regions of interest identified in the images. ANOVA followed by Newman-Keuls post-hoc analyses were used to test for differences between pathological and normal groups. A modified p value of <0.001 was considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between eyes of pathological patients and normal healthy eyes.Results: Fractal dimension was higher for all the layers (except the GCL + IPL and INL) in MDR eyes compared to normal healthy eyes. When comparing MDR with normal healthy eyes, the highest AUROC values estimated for the fractal dimension were observed for GCL + IPL and INL. The maximum discrimination value for fractal dimension of 0.96 (standard error =0.025) for the GCL + IPL complex was obtained at a FD ≤ 1.66 (cut off point, asymptotic 95% Confidence Interval: lower-upper bound = 0.905-1.002). Moreover, the highest AUROC values estimated for the thickness measurements were observed for the OPL, GCL + IPL and OS. Particularly, when comparing MDR eyes with control healthy eyes, we found that the fractal dimension of the GCL + IPL complex was significantly better at diagnosing early DR, compared to the standard thickness measurement.Conclusions: Our results suggest that the GCL + IPL complex, OPL and OS are more susceptible to initial damage when comparing MDR with control healthy eyes. Fractal analysis provided a better sensitivity, offering a potential diagnostic predictor for detecting early neurodegeneration in the retina.

KW - Diabetic retinopathy

KW - Fractal analysis

KW - Fractal dimension

KW - Ophthalmology

KW - Optical coherence tomography

KW - Wavelet algorithm

UR - http://www.scopus.com/inward/record.url?scp=84907986145&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84907986145&partnerID=8YFLogxK

U2 - 10.1186/1471-2105-15-295

DO - 10.1186/1471-2105-15-295

M3 - Article

C2 - 25178846

AN - SCOPUS:84907986145

VL - 15

JO - BMC Bioinformatics

JF - BMC Bioinformatics

SN - 1471-2105

IS - 1

M1 - 295

ER -