Development of an automated system for the detection of genotype in polypoidal choroidal vasculopathy using retinal image phenotype

Lakshmi Priyankka Alagappan; Joel En Wei Koh; Jahmunah V; Adhithi Ramesh; Muna Bhende; Rajiv Raman; U Rajendra Acharya; Sinnakaruppan Mathavan

doi:10.1016/j.cmpb.2020.105460

Development of an automated system for the detection of genotype in polypoidal choroidal vasculopathy using retinal image phenotype

Comput Methods Programs Biomed. 2020 Aug:192:105460. doi: 10.1016/j.cmpb.2020.105460. Epub 2020 Mar 19.

Authors

Lakshmi Priyankka Alagappan¹, Joel En Wei Koh², Jahmunah V², Adhithi Ramesh³, Muna Bhende⁴, Rajiv Raman⁴, U Rajendra Acharya⁵, Sinnakaruppan Mathavan³

Affiliations

¹ SN ONGC Department of Genetics and Molecular Biology, Vision Research Foundation, Sankara Nethralaya campus, Chennai-600006, India; School of Chemical and Biotechnology, SASTRA University, Tanjore-613401, India.
² School of Engineering, Ngee Ann Polytechnic, Singapore.
³ SN ONGC Department of Genetics and Molecular Biology, Vision Research Foundation, Sankara Nethralaya campus, Chennai-600006, India.
⁴ Shri Bhagwan Mahavir Department of Vitreo Retinal Services, Medical Research Foundation, Sankara Nethralaya, Chennai-600006, India.
⁵ School of Engineering, Ngee Ann Polytechnic, Singapore; Department of Biomedical Engineering, School of Science and Technology, Singapore University of Social Sciences, Singapore; Department of Bioinformatics and Medical Engineering, Asia University, Taiwan. Electronic address: aru@np.edu.sg.

PMID: 32276189
DOI: 10.1016/j.cmpb.2020.105460

Abstract

Background and objectives: Polypoidal choroidal vasculopathy (PCV) is a retinal disorder characterized by the presence of aneurismal polypoidal lesions in the choroidal vasculature. A single nucleotide polymorphism (SNP) is a common genetic variant which may be associated with the disease. This study is to investigate the association of HERPUD1 (rs2217332) gene with PCV in the Indian population and develop an automated system for genotype and phenotype correlation using fundus images and machine learning methods.

Methods: A cohort of 54 PCV patients and 120 control subjects were recruited for the study. Genotyping of SNP (HERPUD1, rs2217332) was performed by following polymerase chain reaction and direct sequencing method. Statistical association of SNP to PCV was determined using chi-square analysis. The acquired GG and AG images were preprocessed using an adaptive histogram. 19 and 18 texture features were extracted from the images in the PCV naïve cases and PCV patients on treatment, respectively. Student's independent t-test was then employed for the selection of significant features, which were input to the ensemble tree for automated classification. Leave-one-out validation was used to evaluate the system.

Results: HERPUD1 rs2217332 SNP is significantly associated in PCV patients compared to control (P = 0.0296, odds ratio [OD] = 2.297, 95% confidence interval [CI] = 1.087-4.856) in the Indian population. High F1 and precision values of 85.71%, 86.84% and 85.71%, 93.75% were achieved in the pre and post- treatment phases, respectively.

Conclusion: Our results suggest that the HERPUD1 polymorphism is associated in PCV patients. Based on our analysis, it may be possible to predict the genotype and disease status of PCV patients using fundus images in assistance with a machine learning algorithm.

Keywords: Adaptive synthetic sampling; Ensemble classifier; Fundus images; Leave-one-out validation; Machine learning technique; Polypoidal choroidal vasculopathy; Single nucleotide polymorphism; Texture features; t-test.

Publication types

Comparative Study

MeSH terms

Choroid Diseases / diagnosis*
Choroid Diseases / genetics*
Cohort Studies
Diagnosis, Computer-Assisted*
Genotype*
Humans
Phenotype*
Retina / physiopathology*
Vascular Diseases / diagnosis*
Vascular Diseases / genetics*