The Mass General Brigham research team behind FaceAge, an artificial intelligence (AI) tool that can estimate a person’s biological age from a single photo, is reporting in a new study that estimating biological age from multiple photos taken over time can provide even more information about how well a person with cancer will do with treatment.
Their results, published in 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 new study analyzed two photographs from each of 2,279 patients with cancer, taken at different time points over the course of treatment. The researchers found that higher FAR was significantly associated with decreased survival probability.
“Deriving a Face Aging Rate from multiple, routine facial photographs allows for near real-time tracking of an individual’s health,” said co-senior and corresponding author Raymond Mak, MD , a radiation oncologist at Mass General Brigham Cancer Institute and a faculty member in the Artificial Intelligence in Medicine (AIM) program at Mass General Brigham. “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.”
FaceAge is an AI tool that uses deep learning technologies to determine biological age from a person’s face photo. In a study published last year , the investigators determined that patients with cancer were likely to appear about five years older than their chronological age per FaceAge, and that older FaceAge estimates correlated with worse survival outcomes after cancer treatment.
In the new study, the researchers 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 cohort of patients with varying types of cancer who received at least two courses of radiation therapy at Brigham and Women’s Hospital 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 these two time points, divided by the time interval. The researchers also calculated FaceAge Deviation (FAD), which estimates how biologically old or young the patient looked in a single face photo relative to chronological age.
Median 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.
Additionally, patients with both high FAD and FAR values were significantly more likely to have poorer survival probabilities. However, 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 authors suggest that integrating FAR with baseline FAD could provide a more nuanced and informative measure of an individual’s evolving health status. Further research is needed to evaluate FaceAge and FAR in more diverse populations.
“Tracking FaceAge over time from simple photos offers a non-invasive, cost-effective biomarker with potential to inform individuals of their health,” said study co-author Hugo Aerts, PhD , director of the AIM program at Mass General Brigham. “We hope with continued study we can learn how FaceAge may provide prognostic information for patients with other chronic diseases and for healthy individuals.”
This research provides additional demonstrations of the potential clinical utility of FaceAge. In another recent study published in JNCI: 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.
Ongoing and future studies, including prospective trials, will continue to investigate FaceAge outcomes in patients with different cancers and other diseases. The research team has now also launched an institutional review board-approved web portal that allows the general public to submit their own face photographs to get a FaceAge assessment and participate in research to advance this technology at faceage.bwh.harvard.edu .
Authorship: In addition to Mak and Aerts, Mass General Brigham study authors included Fridolin Haugg (first author), Grace Lee, John He, Andrew Warrington, Dennis Bontempi, Danielle S. Bitterman, Vasco Prudente, Suraj Pai, Christian Guthier, and Benjamin Kann, in addition to Paul J. Catalano of DFCI.
Disclosures: Mak reports being on an Advisory Board for ViewRay and AstraZeneca; Consulting for AstraZeneca, Pfizer, Varian Medical Systems, and Sio Capital Management; Honorarium from Novartis and Springer Nature; and Research Funding from the National Institute of Health, ViewRay, AstraZeneca, Siemens Medical Solutions USA, Inc., and Varian Medical Systems; Patents pending for FaceAge and related technologies. Additional disclosures unrelated to this work can be found in the paper.
Funding: This research was partly funded by a philanthropic gift from George Denny.
Paper cited: Haugg, F. et al. “Face aging rate quantifies change in biological age to predict cancer outcomes” Nature Communications DOI: 10.1038/s41467-025-66758-w
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Nature Communications
Computational simulation/modeling
People
Face aging rate quantifies change in biological age to predict cancer outcomes
28-Apr-2026
Mak reports being on an Advisory Board for ViewRay and AstraZeneca; Consulting for AstraZeneca, Pfizer, Varian Medical Systems, and Sio Capital Management; Honorarium from Novartis and Springer Nature; and Research Funding from the National Institute of Health, ViewRay, AstraZeneca, Siemens Medical Solutions USA, Inc., and Varian Medical Systems; Patents pending for FaceAge and related technologies. Additional disclosures unrelated to this work can be found in the paper.