Prediction of Non-sentinel Lymph Node Metastatic Status of Breast Cancer Based on Pathology-MRI Images

NCT06510738 | Not Yet Recruiting

• 1 other identifier: KYLX2024-128
• Study Type: observational
• Target: 700
• Locations: 0 countries
• Sites: N/A

Brief Summary

The goal of this observational study is to develop an artificial intelligence model based on pathology and magnetic resonance imaging (MRI) images to predict the metastatic status of non-sentinel lymph nodes in patients with breast cancer sentinel lymph node metastasis. The main questions it aims to answer are: Can an artificial intelligence model based on MRI images of breast cancer patients predict the non-sentinel lymph node metastatic status in patients with breast cancer sentinel lymph node metastasis? Can an artificial intelligence model based on intraoperative frozen section images of sentinel lymph nodes in breast cancer patients predict the non-sentinel lymph node metastasis status in patients with sentinel lymph node metastasis from breast cancer? Can artificial intelligence models based on preoperative MRI and intraoperative frozen section images of sentinel lymph nodes in breast cancer patients predict the non-sentinel lymph node metastatic status in patients with sentinel lymph node metastasis from breast cancer? Researchers will retrospectively and prospectively collect preoperative MRI and intraoperative sentinel lymph node section images from breast cancer patients.

Conditions

Breast Cancer; Artificial Intelligence; Lymph Node Metastasis; Digital Pathology

Outcome Measures

Primary Outcomes (3)

• Non-sentinel lymph node metastatic status

  metastasis or non-metastasis

  2024-2025

• Accuracy, Sensitivity, Specificity，Area under the curve

  The performance of predicting non-sentinel lymph node metastatic status

  2024-2025

• Positive predictive value，Negative predictive value

  The performance of predicting non-sentinel lymph node metastatic status

  2024-2025

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The investigators plan to retrospective collect 700 patients with breast cancer and prospective collect 150 patients with breast cancer

You may qualify if:

• Patients with primary breast cancer
• Positive sentinel lymph node biopsy and axillary lymph node dissection.
• No neoadjuvant chemotherapy, radiotherapy or ablation prior to surgery.
• MRI within 3 weeks prior to surgery.

You may not qualify if:

• recurrent breast cancer or history of surgery or radiation therapy in the axilla
• Inflammatory breast cancer
• Bilateral breast cancer or metastatic breast cancer
• previous or current history of other malignant tumors
• Sentinel lymph node count \> 5

Sponsors & Collaborators

• Yunnan Cancer Hospital: lead
• Affiliated Cancer Hospital of Shantou University Medical College: collaborator

MeSH Terms

Conditions

Breast Neoplasms; Lymphatic Metastasis

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases; Neoplasm Metastasis; Neoplastic Processes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 14, 2024
• First Posted: July 19, 2024
• Study Start: August 1, 2024
• Primary Completion: June 1, 2025
• Study Completion: December 1, 2025
• Last Updated: August 13, 2024

Record last verified: 2024-07