Construction and Validation of an Assessment Model of PCR After NAT on Breast Cancer Patients With AI Technology

Breast cancer is a major cause of survival for women worldwide. Neoadjuvant therapy as an important treatment for locally advanced breast cancer has had many positive effects for breast cancer patients. As drug therapy for breast cancer continues to evolve, the percentage of pathologic complete responses continues to increase. However, at present, pCR can only be judged by pathological testing of surgically resected specimens, and the question of whether pCR can be accurately judged preoperatively has become an urgent issue.Therefore, this project plans to establish and validate a model for determining pCR after NAT in breast cancer based on clinical information, imaging and pathological information of breast cancer patients in multiple centers using artificial intelligence technology in accordance with international guidelines and domestic expert consensus on breast cancer NAT, in order to solve the problem of surgical decision making for patients after NAT, by combining experts from breast medicine, surgery, pathology and imaging departments in several tertiary care hospitals across China. The model will be validated to solve the problem of surgical decision making for post-NAT patients.

Sex

Female

Minimum age

18 Years

Inclusion Criteria:

1. patients admitted to each study center between January 1, 2010 and December 31, 2021.
2. ≥18 years of age, female, with an ECOG score ≤2.
3. pathological biopsy confirmed invasive breast cancer.
4. were initially treated with neoadjuvant therapy.
5. have MRI imaging data prior to radical surgery after neoadjuvant treatment.
6. underwent surgery as planned after neoadjuvant therapy and obtained postoperative pathology information.

Exclusion Criteria:

1. Bilateral breast cancer, multiple lesions or occult breast cancer.
2. no data related to breast MRI.
3. no surgery after neoadjuvant therapy, no postoperative pathology results.