Scientists have developed an AI tool that estimates someone's biological age from photographs of their face.
It predicted that patients with cancer who aged rapidly between photos taken over the course of their treatment had lower chances of survival.
The American research team behind the artificial intelligence (AI) tool, called FaceAge, showed it can estimate a person's biological age from a single photo.
The latest study suggests that estimating biological age from multiple photos taken over time can provide extra information about how well a person with cancer will do with treatment.
The findings, published in the journal Nature Communications, suggest that Face Aging Rate (FAR) — which uses photos to measure changes in biological age over time — can serve as a non-invasive biomarker for cancer prognosis.
The study involved analyzing two photographs from each of 2,279 patients with cancer, taken at different time points over the course of treatment.
The research team found that higher FAR was "significantly associated" with decreased survival probability.
Study co-senior author Dr. Raymond Mak, a radiation oncologist at Mass General Brigham Cancer Institute, Boston, said: "Deriving a Face Aging Rate from multiple, routine facial photographs allows for near real-time tracking of an individual's health.
"Our study suggests that measuring FaceAge over time may refine personalized treatment planning, improve patient counseling, and help guide the frequency and intensity of follow-up in oncology."
He explained that FaceAge is an AI tool that uses deep learning technologies to determine biological age from a photo of a person's face.
They also found that older FaceAge estimates correlated with worse survival outcomes after cancer treatment.
In the new study, the research team sought to learn what information FaceAge could provide when applied to multiple photos of the same person taken over time.
They inspected facial photos from a group of patients with varying types of cancer who received at least two courses of radiation therapy at Brigham and Women's Hospital in Boston between 2012 and 2023.
The photos were taken as part of the routine clinical workflow at each separate radiation therapy course.
FAR was calculated as the change in FaceAge between the two time points, divided by the time interval.
The research team also calculated FaceAge Deviation (FAD), which estimates how biologically old or young the patient looked in a single face photo relative to chronological age.
Average FAR results indicated that patients' facial aging outpaced their chronological aging by 40%.
Higher FAR — or accelerated aging — was associated with lower survival, and the effect was strongest when the interval between photos was two years or more.
Patients with both high FAD and FAR values were also significantly more likely to have poorer survival probabilities.
But FAR was more likely to predict survival outcomes stably over longer intervals than FAD — indicating that dynamic measurements might be more reliable than single timepoint readings.
The research team suggest that integrating FAR with original FAD could provide a more informative measure of a patient's evolving health status.
In another recent study, published in the Journal of the National Cancer Institute, FaceAge was tested on more than 24,500 cancer patients over the age of 60 who received radiation therapy.
FaceAge was older than chronological age in 65% of the patients.
Those with a FaceAge estimate 10 or more years older than their chronological age had significantly worse survival outcomes, while those with an estimate of five or fewer years had better outcomes.
Study co-author Hugo Aerts, of Mass General Brigham, said: "Tracking FaceAge over time from simple photos offers a non-invasive, cost-effective biomarker with potential to inform individuals of their health."
He added: "We hope with continued study we can learn how FaceAge may provide prognostic information for patients with other chronic diseases and for healthy individuals."
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