LensAge to Reveal Biological Age

Recruiting

• Conditions: Biological Age; Ophthalmology; Lens Opacities

• Registration Number: NCT05588921
• Lead Sponsor: Sun Yat-sen University

Brief Summary

Assessment of aging is central to health management. Compared to chronological age, biological age can better reflect the aging process and health status; however, an effective indicator of biological age in clinical practice is lacking. Human lens accumulates biological changes during aging and is amenable to a rapid and objective assessment. Therefore, the investigators will develop LensAge as an innovative indicator to reveal biological age based on deep learning using lens photographs.

Detailed Description

Not available

Study Timeline

• Study Start: 2020-01-01
• Status Verified: 2022-10
• Study First Submitted: 2022-10-17
• Study First Submitted QC: 2022-10-17
• Last Update Submitted: 2022-10-19
• Study First Posted: 2022-10-20
• Last Update Posted: 2022-10-21
• Primary Completion: 2022-12-30
• Study Completion: 2022-12-30

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 6000

Inclusion Criteria

• ages from 20 to 100 years
• have anterior segment photographs
• have ophthalmic and physical examination records

Exclusion Criteria

• have a history of previous eye surgery, eye trauma, or ocular diseases that can cause complicated cataracts
• baseline information missing

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
The difference between LensAge and chronological age	Baseline	The age estimation models based on a convolutional neural network (CNN) using lens photographs will be used to generate LensAge. LensAge at the individual level will be calculated by averaging the results of all images corresponding to one individual. The difference between LensAge at the individual level and chronological age will be used to unveil an individual's aging process. A difference above 0 indicates an individual with a faster pace of aging than their peers of the same chronological age, while a difference below 0 indicates a slower pace of aging.

Secondary Outcome Measures

Name	Time	Method
Correlation between the LensAge difference and age-related health parameters	Baseline	Age-corrected LensAge differences will be used to investigate the odds ratios (ORs) with age-related health parameters.
Mean error (ME) of the DL age estimation model.	Baseline	Mean error (ME) in terms of both image level and individual level will be used to evaluate the performance of the DL age estimation model.
Mean absolute error (MAE) of the DL age estimation model.	Baseline	Mean absolute error (MAE) in terms of both image level and individual level will be used to evaluate the performance of the DL age estimation model.
R-squared (R2) of the DL age estimation model.	Baseline	R-squared (R2) in terms of both image level and individual level will be used to evaluate the performance of the DL age estimation model.

Trial Locations

Locations (1)

Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity; 🇨🇳 Guangzhou, Guangdong, China