Evaluating breast appearance after cancer treatment using AI

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational study aims to assess the aesthetic outcomes of breast cancer treatments by analyzing post-treatment photographs with a deep neural network algorithm. The algorithm processes images to identify key points on the breast, allowing for a detailed classification of changes in appearance from baseline. By automating this assessment, the study seeks to reduce the time physicians spend evaluating breast cosmesis in clinical settings. The approach combines advanced image processing techniques with machine learning to enhance the accuracy of aesthetic evaluations.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* Confirmed diagnosis of primary breast cancer (invasive or in situ)
* Patient undergone breast conservation / Whole breast reconstruction
* Patient received breast RT
* Already provided written informed consent on earlier projects
* Patient provided photographs of both breasts
* Non-metastatic disease or oligometastatic
* Age \> 18 years
* Reconsent given

Exclusion Criteria:

* Mastectomy without whole breast reconstruction
* Bilateral breast cancer
* Partial breast irradiation
* Male patient
* Limited life expectancy due to co-morbidity
* Patients undergoing brachy boost

Where it's running

• Tata Memorial Centre
  Mumbai, Maharashtra, India Recruiting

Study contacts

• Principal investigator: Tabassum Wadasadwala, MD — Tata Memorial Centre
• Study coordinator: Tabassum Wadasadawala, MD
• Email: twadasadwala@actrec.gov.in
• Phone: 9324445303

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.