Assessment of patient specific information in the wild on fundus photography and optical coherence tomography.

Munk, Marion R.; Kurmann, Thomas; Márquez-Neila, Pablo; Zinkernagel, Martin S.; Wolf, Sebastian; Sznitman, Raphael (2021). Assessment of patient specific information in the wild on fundus photography and optical coherence tomography. Scientific reports, 11(1), p. 8621. Springer Nature 10.1038/s41598-021-86577-5

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In this paper we analyse the performance of machine learning methods in predicting patient information such as age or sex solely from retinal imaging modalities in a heterogeneous clinical population. Our dataset consists of N = 135,667 fundus images and N = 85,536 volumetric OCT scans. Deep learning models were trained to predict the patient's age and sex from fundus images, OCT cross sections and OCT volumes. For sex prediction, a ROC AUC of 0.80 was achieved for fundus images, 0.84 for OCT cross sections and 0.90 for OCT volumes. Age prediction mean absolute errors of 6.328 years for fundus, 5.625 years for OCT cross sections and 4.541 for OCT volumes were observed. We assess the performance of OCT scans containing different biomarkers and note a peak performance of AUC = 0.88 for OCT cross sections and 0.95 for volumes when there is no pathology on scans. Performance drops in case of drusen, fibrovascular pigment epitheliuum detachment and geographic atrophy present. We conclude that deep learning based methods are capable of classifying the patient's sex and age from color fundus photography and OCT for a broad spectrum of patients irrespective of underlying disease or image quality. Non-random sex prediction using fundus images seems only possible if the eye fovea and optic disc are visible.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Medical Imaging Laboratory
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology

UniBE Contributor:

Munk, Marion; Kurmann, Thomas Kevin; Márquez Neila, Pablo; Zinkernagel, Martin Sebastian; Wolf, Sebastian and Sznitman, Raphael

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

2045-2322

Publisher:

Springer Nature

Language:

English

Submitter:

Marion Munk

Date Deposited:

11 May 2021 11:08

Last Modified:

16 May 2021 03:04

Publisher DOI:

10.1038/s41598-021-86577-5

PubMed ID:

33883573

BORIS DOI:

10.48350/156003

URI:

https://boris.unibe.ch/id/eprint/156003

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