Evaluating breast cancer treatment effectiveness using artificial intelligence
Prospective Validation and Application of an Artificial Intelligence-based Model for Evaluating the Efficacy of Breast Cancer Patients After Neoadjuvant Therapy
This study is testing whether an artificial intelligence tool can help doctors better predict how well neoadjuvant therapy works for breast cancer patients using MRI images and clinical data.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 300 (estimated) |
| Ages | 18 Years and up |
| Sex | Female |
| Sponsor | Cancer Institute and Hospital, Chinese Academy of Medical Sciences Academic / other |
| Locations | 2 sites (Beijing, Beijing Municipality and 1 other locations) |
| Trial ID | NCT06649565 on ClinicalTrials.gov |
What this trial studies
This study aims to validate an artificial intelligence-based model designed to non-invasively evaluate the efficacy of neoadjuvant therapy in breast cancer patients. It involves the prospective collection of MRI images and clinical data from multiple centers, which will be processed and analyzed using AI techniques to enhance the prediction of treatment outcomes. The goal is to improve the accuracy and versatility of efficacy assessments, potentially reducing the need for surgical interventions. By integrating imaging genomics and clinical characteristics, the study seeks to establish a robust model for predicting pathological complete response in breast cancer patients.
Who should consider this trial
Good fit: Ideal candidates are female patients aged 18 and older with confirmed invasive breast cancer who are scheduled for neoadjuvant therapy and subsequent surgery.
Not a fit: Patients with bilateral breast cancer, multiple lesions, or those who have received prior anti-tumor treatments may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to more accurate non-invasive evaluations of treatment efficacy, potentially sparing patients from unnecessary surgeries.
How similar studies have performed: While there have been studies exploring AI in medical imaging, this specific multi-center approach for breast cancer efficacy evaluation is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients who were treated in the above research centers between January 1, 2024 and October 31, 2025; * ≥18 years old, female, ECOG score ≤2; * Pathological biopsy confirmed invasive breast cancer; * AJCC (8th edition) stage I-III; * MRI imaging data before and after neoadjuvant therapy; * Planned mastectomy or breast-conserving surgery after neoadjuvant therapy, and postoperative pathological information obtained. Exclusion Criteria: * Bilateral breast cancer, multiple lesions, or occult breast cancer; * Poor MRI data quality; * Patients who had received other anti-tumor treatments before enrollment; * Patients with other malignant tumors
Where this trial is running
Beijing, Beijing Municipality and 1 other locations
- Sanhuan Cancer Hospital, Chaoyang District, Beijing(Cancer Hospital, Chinese Academy of Medical Sciences, close medical alliance) — Beijing, Beijing Municipality, China (Recruiting)
- Cancer Hospital, Chinese Academy of Medical Sciences — Beijing, Beijing Municipality, China (Recruiting)
Study contacts
- Study coordinator: peng yuan, doctor
- Email: yuanpengyp01@163.com
- Phone: 01087787242
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.