By Elodie Vaz | Published on May 6, 2026 |
4 min read
In oncology, predicting
disease progression and treatment response remains a major challenge. While
tumor biomarkers, imaging, and clinical parameters already guide therapeutic
decisions, they do not always capture a patient’s overall biological state. Yet
biological aging, which reflects physiological frailty, strongly influences
treatment tolerance and survival.
With this in mind, a team
from Mass General Brigham is exploring a novel approach: using the face as a
health indicator. In a study published on April 28 in Nature Communications,
researchers show that the “rate of facial aging” measured by artificial
intelligence could serve as a non-invasive prognostic biomarker in cancer.
FaceAge: estimating biological
age from a face
The tool, called FaceAge,
relies on deep learning algorithms capable of estimating an individual’s
apparent biological age from a simple facial photograph.
A previous study had
already shown that cancer patients appeared, according to FaceAge, on average
five years older than their chronological age. The higher the estimated facial age,
the poorer the prognosis after treatment.
In this new work, the
objective was no longer just to measure a “snapshot” facial age, but to assess
its dynamics over time.
Turning a series of
photos into a prognostic tool
The researchers sought to
determine whether changes in facial age over time could provide additional
clinical insight into the health status and survival of cancer patients.
“Calculating the rate of
facial aging from multiple facial photographs taken regularly allows near
real-time monitoring of an individual’s health,” explains Dr. Raymond Mak,
co-senior author and corresponding author, a radiation oncologist at the Mass
General Brigham Cancer Institute, in a press release.
“Our study suggests that
tracking facial age over time could refine personalized treatment planning,
improve patient counseling, and help guide the frequency and intensity of
oncology follow-up.”
The study included 2,279
patients with various cancers treated with radiotherapy at Brigham and Women’s
Hospital between 2012 and 2023.
All patients had received
at least two cycles of radiotherapy and had at least two facial photographs,
taken as part of standard clinical protocol at each treatment cycle.
The researchers
calculated two parameters:
- The Facial Aging Rate (FAR), obtained
by dividing the change in estimated facial age between two images by the
time interval;
- The Facial Age Difference (FAD),
defined as the difference between estimated facial age and chronological
age at a given time point.
FAR thus reflects the
speed of apparent biological aging, while FAD provides a static measure of
“over-aging” or apparent “rejuvenation.”
Accelerated facial
aging linked to poorer survival
The results showed that
patients’ median facial aging was approximately 40% faster than their
chronological aging.
A high FAR—indicating
accelerated aging—was significantly associated with reduced survival. This
association was particularly strong when the interval between the two
photographs reached or exceeded two years.
Patients with both a high
FAD and a high FAR also had significantly lower survival.
However, FAR proved more
robust than FAD in predicting long-term survival, suggesting that a dynamic
measure is more informative than a single time-point assessment.
The authors therefore
propose that combining FAR with baseline FAD could provide a more refined view
of changes in a patient’s overall condition.
Toward a non-invasive,
low-cost biomarker ?
For Professor Hugo Aerts,
co-author of the study and director of the Artificial Intelligence in Medicine
(AIM) program, this approach opens broader perspectives. “Tracking facial age
over time using simple photographs offers a non-invasive and cost-effective
biomarker that could inform individuals about their health,” he notes. “We hope
that further research will allow us to determine how facial age can provide
prognostic information for patients with other chronic diseases and even for
healthy individuals,” he adds.
These findings reinforce
data from another recent study published in the Journal of the National
Cancer Institute, conducted in more than 24,500 patients over the age of 60
treated with radiotherapy. In 65% of them, FaceAge-estimated age exceeded
chronological age, with significantly lower survival when the gap reached 10
years or more.
Prospective trials are
underway to validate FaceAge in other cancers and chronic conditions. The team
has also launched a public web portal to collect additional data and further
refine the algorithm.
Ultimately, this
technology could become part of the predictive and personalized medicine
toolkit: a simple photograph, repeated over time, could serve as a clinical
indicator of frailty, complementing biological and imaging biomarkers. A
promising prospect—provided its robustness is confirmed across more diverse
populations and clinical settings.
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About the Author – Elodie Vaz
Health journalist, CFPJ graduate (2023).
Élodie explores the marks diseases leave on bodies and, more broadly, on
human life. A registered nurse since 2010, she spent twelve years at patients’
bedsides before exchanging her stethoscope for a notebook. She now investigates
the links between environment and health, convinced that the vitality of life
cannot be reduced to that of humans
