Medical-AI trial: protecting the ovaries with AI adaptive radiotherapy (OvAR-Y) — pelvic cancer in young women and oncofertility (in-silico) (NCT06904365)
An observational study using in-silico (computer simulation on real data) to test the feasibility of ovarian-sparing adaptive radiotherapy for women under 50 who need pelvic radiation for cancers such as uterine and rectal. It addresses the unmet need to reduce the risk of premature ovarian failure. 10 cases.
Trial overview (primary data)
- StatusActive, not recruiting
- ConditionsUterine Cancer, Rectal Cancer, Colon Cancer, Breast Cancer, Lung Cancer, Sarcoma, Cervix Cancer, Head and Neck Cancer, Anal Cancer, Liver Cancer, Gastric Cancer, Bladder Cancer
- InterventionsDEVICE: HyperSight cone beam computed tomography (CBCT) scan, DEVICE: ETHOS 2.0
- SponsorWashington University School of Medicine
- Target enrollment10 participants
- Period2025-04-08 〜 2026-08-31
Key points
- An observational study using in-silico methods to test the feasibility of ovarian-sparing adaptive radiotherapy for women under 50 needing pelvic radiation.
- Background: premenopausal patients face high risk of premature ovarian failure from radiation, with cardiac, musculoskeletal, sexual, and psychosocial morbidity.
- Existing ovarian transposition has variable success, limited access, and residual dose. This addresses an unmet need.
- Adaptive radiotherapy re-creates the plan to match each session imaging, with AI increasingly supporting automated planning.
- 10 cases; in-silico (no actual irradiation, checked on computer) feasibility, not an establishment of effectiveness or safety in real patients.
Treating pelvic cancers such as uterine or rectal cancer often means directing radiation at the pelvis. But radiation affects not only the targeted tumor but also the nearby ovaries, and in young, premenopausal women it can cause premature ovarian failure, when the ovaries stop working earlier than they should.
Through the loss of hormones, this has lasting effects on the heart, bones, sexual function, and psychosocial well-being. Surgery to move the ovaries out of the radiation field (ovarian transposition) exists, but its success varies, it is not accessible to everyone, and a meaningful dose can still reach the ovaries. Here lies an unmet need for new ways to protect the ovaries.
What this study examines is ovarian-sparing adaptive radiotherapy. Adaptive radiotherapy re-creates the treatment plan to match imaging taken at each session, improving precision in hitting the target while sparing normal tissue, and AI increasingly supports the automated creation of these plans.
Per the registry summary, the study evaluates this ovarian sparing in-silico (planning and checking doses on a computer using real data, without actually irradiating patients) as a feasibility study in 10 cases.
As cancer outcomes improve, quality of life after treatment, and oncofertility (cancer and reproductive medicine) in younger patients in particular, matters more. If AI-supported adaptive radiotherapy can hold down the dose to the ovaries, it might preserve future fertility and hormone function while maintaining treatment effect.
That said, this is a small in-silico feasibility evaluation; it does not establish effectiveness or safety in actual patients.
Why it matters
As cancer outcomes improve, oncofertility (cancer and reproductive medicine) in younger patients matters more. Using AI-supported adaptive radiotherapy to reduce ovarian dose is a useful reference for balancing treatment effect with fertility and hormone function (this trial is a small in-silico feasibility study, not an establishment of effectiveness).
FAQ
What is adaptive radiotherapy?
What does in-silico mean?
Sources (primary)
Source: ClinicalTrials.gov (U.S. NIH/NLM, public domain). This site does not provide medical advice. Verify the latest and exact details with the official source. This site is not endorsed or certified by the NIH/NLM.
- ClinicalTrials.gov (study record, original)
- NCT ID: NCT06904365