Evaluation of Axillary Lymph Node Metastasis Status of Breast Cancer Based on Pathological Images and Virtual Staining

The goal of this observational study is to develop an artificial intelligence model to transform unstained lymph node tissue slice images directly into stained images. The main questions it aims to answer are:

Can the virtual staining model generate hematoxylin and eosin (H&E) and immunohistochemistry (IHC) images suitable for clinical diagnosis from unstained paraffin-embedded lymph node slice images, including those from breast axillary lymph nodes and other tumor lymph nodes?

Can the virtual staining model generate H&E and IHC images suitable for clinical diagnosis from unstained frozen sentinel lymph node slice images from breast cancer patients?

Researchers will retrospectively collect paraffin-embedded lymph node slices from tumor patients and prospectively collect frozen sentinel lymph node slices from breast cancer patients.

Study Overview

• Status: Not yet recruiting
• Conditions: Breast Cancer; Lymph Node Metastasis; Digital Pathology; Virtual Staining

• Study Type: Observational
• Enrollment (Estimated): 2200

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Part 1:

The investigators plan to collect 1000 patients with breast cancer.

Part 2:

The investigators plan to collect 100 patients with each of the following cancers: thyroid, lung, esophagus, stomach, colorectal, prostate, bladder, and cervix. The total number of patients will be 800.

Part 3:

The investigators plan to prospectively collect 400 patients with breast cancer.

Description

Inclusion Criteria:

Part 1:

Female patients aged 18-75 with breast cancer; Undergoing surgical excision of breast cancer and sentinel lymph node biopsy/axillary lymph node dissection; Lymph nodes with clear postoperative paraffin pathological results.

Part 2:

Patients aged 18-75 with one of the following cancers: thyroid, lung, esophagus, stomach, colorectal, prostate, bladder, or cervix; Undergoing surgical resection of lymph nodes; Lymph nodes with clear postoperative paraffin pathological results.

Part 3:

Female patients aged 18-75 with breast cancer; Undergoing surgical excision of breast cancer and sentinel lymph node biopsy; Sentinel lymph nodes with clear postoperative paraffin pathological results.

Exclusion Criteria:

Part 1 / Part 2:

Lymph node diagnosis is missing; Absence of lymph node component in the slice.

Part 3:

Sentinel lymph node diagnosis is missing; Absence of lymph node component in the frozen slice.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Accuracy, Sensitivity, Specificity，Area under the curve，	The performance of pathologists diagnosing the lymph node metastasis status by virtual and real staining whole slide images	2024-2025
Positive predictive value，Negative predictive value	The performance of pathologists diagnosing the lymph node metastasis status by virtual and real staining whole slide images	2024-2025
Lymph node metastasis status	Lymph node metastasis status: metastasis or non-metastasis	2024-2025

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Peak Signal-to-Noise Ratio(PSNR)	Scores of the similarity between virtual and real staining of lymph nodes, with values ranging from 0 to infinity, the higher scores mean the better outcomes	2024-2025
Multi-Scale Structural Similarity (MS-SSIM)	Scores of the similarity between virtual and real staining of lymph nodes, with values ranging from 0 to 1, the higher scores mean the better outcomes	2024-2025
Pearson correlation coefficient	Scores of the similarity between virtual and real staining of lymph nodes, with values ranging from 0 to 1, the higher scores mean the better outcomes	2024-2025

Collaborators and Investigators

• Sponsor: Yunnan Cancer Hospital
• Collaborators: Affiliated Cancer Hospital of Shantou University Medical College

Study record dates

Study Major Dates

• Study Start (Estimated): August 1, 2024
• Primary Completion (Estimated): June 1, 2025
• Study Completion (Estimated): December 1, 2025

Study Registration Dates

• First Submitted: June 26, 2024
• First Submitted That Met QC Criteria: June 26, 2024
• First Posted (Actual): July 3, 2024

Study Record Updates

• Last Update Posted (Actual): August 13, 2024
• Last Update Submitted That Met QC Criteria: August 10, 2024
• Last Verified: June 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Skin Diseases; Neoplasms; Neoplasms by Site; Breast Diseases; Neoplastic Processes; Breast Neoplasms; Neoplasm Metastasis; Lymphatic Metastasis
• Other Study ID Numbers: KYLX2024-129

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No