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Prediction of Causative Genes in Inherited Retinal Disorders from Spectral-Domain Optical Coherence Tomography Utilizing Deep Learning Techniques
- Source :
- Journal of Ophthalmology, Journal of Ophthalmology, Vol 2019 (2019)
- Publication Year :
- 2019
- Publisher :
- Hindawi, 2019.
-
Abstract
- Purpose. To illustrate a data-driven deep learning approach to predicting the gene responsible for the inherited retinal disorder (IRD) in macular dystrophy caused by ABCA4 and RP1L1 gene aberration in comparison with retinitis pigmentosa caused by EYS gene aberration and normal subjects. Methods. Seventy-five subjects with IRD or no ocular diseases have been ascertained from the database of Japan Eye Genetics Consortium; 10 ABCA4 retinopathy, 20 RP1L1 retinopathy, 28 EYS retinopathy, and 17 normal patients/subjects. Horizontal/vertical cross-sectional scans of optical coherence tomography (SD-OCT) at the central fovea were cropped/adjusted to a resolution of 400 pixels/inch with a size of 750 × 500 pix2 for learning. Subjects were randomly split following a 3 : 1 ratio into training and test sets. The commercially available learning tool, Medic mind was applied to this four-class classification program. The classification accuracy, sensitivity, and specificity were calculated during the learning process. This process was repeated four times with random assignment to training and test sets to control for selection bias. For each training/testing process, the classification accuracy was calculated per gene category. Results. A total of 178 images from 75 subjects were included in this study. The mean training accuracy was 98.5%, ranging from 90.6 to 100.0. The mean overall test accuracy was 90.9% (82.0–97.6). The mean test accuracy per gene category was 100% for ABCA4, 78.0% for RP1L1, 89.8% for EYS, and 93.4% for Normal. Test accuracy of RP1L1 and EYS was not high relative to the training accuracy which suggests overfitting. Conclusion. This study highlighted a novel application of deep neural networks in the prediction of the causative gene in IRD retinopathies from SD-OCT, with a high prediction accuracy. It is anticipated that deep neural networks will be integrated into general screening to support clinical/genetic diagnosis, as well as enrich the clinical education.
- Subjects :
- Retinal Disorder
Article Subject
medicine.diagnostic_test
biology
business.industry
Random assignment
Deep learning
ABCA4
Pattern recognition
Overfitting
medicine.disease
Ophthalmology
lcsh:Ophthalmology
Optical coherence tomography
lcsh:RE1-994
Retinitis pigmentosa
medicine
biology.protein
Artificial intelligence
business
Retinopathy
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 20900058 and 2090004X
- Volume :
- 2019
- Database :
- OpenAIRE
- Journal :
- Journal of Ophthalmology
- Accession number :
- edsair.doi.dedup.....d5cfbcead030b329dcb3df9933de6c04