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| Name | Class |
|---|---|
| Affiliated Cancer Hospital of Shantou University Medical College | OTHER |
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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.
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| Measure | Description | Time Frame |
|---|---|---|
| Lymph node metastasis status | Lymph node metastasis status: metastasis or non-metastasis | 2024-2025 |
| 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 |
| 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) |
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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.
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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.
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| ID | Term |
|---|---|
| D008207 | Lymphatic Metastasis |
| D001943 | Breast Neoplasms |
| ID | Term |
|---|---|
| D009362 | Neoplasm Metastasis |
| D009385 | Neoplastic Processes |
| D009369 | Neoplasms |
| D010335 | Pathologic Processes |
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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 |
| D013568 |
| Pathological Conditions, Signs and Symptoms |
| D009371 | Neoplasms by Site |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |