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LensAge to Reveal Biological Age

Sponsor
Sun Yat-sen University (Other)
Overall Status
Recruiting
CT.gov ID
NCT05588921
Collaborator
(none)
6,000
Enrollment
1
Location
35.9
Anticipated Duration (Months)
166.9
Patients Per Site Per Month

Study Details

Study Description

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.

Condition or Disease Intervention/Treatment Phase

    Study Design

    Study Type:
    Observational
    Anticipated Enrollment :
    6000 participants
    Observational Model:
    Cohort
    Time Perspective:
    Retrospective
    Official Title:
    A Deep Learning-based Indicator to Reveal Biological Age Using Lens Photographs
    Actual Study Start Date :
    Jan 1, 2020
    Anticipated Primary Completion Date :
    Dec 30, 2022
    Anticipated Study Completion Date :
    Dec 30, 2022

    Arms and Interventions

    Arm Intervention/Treatment
    Aging group

    Participants with baseline information, medical history of diseases, and lens photographs

    Outcome Measures

    Primary Outcome Measures

    1. 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

    1. 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.

    2. 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.

    3. 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.

    4. 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.

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    20 Years to 100 Years
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    Yes
    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

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity Guangzhou Guangdong China 510060

    Sponsors and Collaborators

    • Sun Yat-sen University

    Investigators

    • Principal Investigator: Haotian Lin, M.D., Ph.D., Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    Haotian Lin, Professor, Sun Yat-sen University
    ClinicalTrials.gov Identifier:
    NCT05588921
    Other Study ID Numbers:
    • LA-2022
    First Posted:
    Oct 20, 2022
    Last Update Posted:
    Oct 21, 2022
    Last Verified:
    Oct 1, 2022
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Additional relevant MeSH terms:
    Cataract

    Study Results

    No Results Posted as of Oct 21, 2022