Invasive breast carcinoma of no special type - Female, 81 - Tissue image [2270630026311221] - Open Research Data - Bridge of Knowledge

Your account

login

Search

Invasive breast carcinoma of no special type - Female, 81 - Tissue image [2270630026311221]

Description

This is the histopathological image of LYMPH NODES tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

The detailed information about the patient, sample, and diagnosis are as follows:

Patient:

Age: 81

Clinical description: Ulcerated tumor of right breast, diameter 10 cm. Enlarged axillary lymph node. Core needle biopsy: breast invasive carcinoma.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: DUCTAL AND LOBULAR NEOPLASMS

Diagnosis: Invasive breast carcinoma of no special type

Result of the histopathological examination: Invasive breast carcinoma NOS: NHG 3 (3+3+3: 86 mitoses per 10HPF). Skin of breast with carcinoma infiltration. Ulceration is present. Metastasis of carcinoma to axillary lymph node (1/5 lymph nodes). ER-, PR-, HER2-, Ki67 100%.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: LYMPH NODES

Organ: LYMPH NODES

Tissue: Axillary lymph node

Type of staining: positive/HE

Staining: Not applicable

Antibody: Not applicable

Technology:

Equipment: Pannoramic 250 3DHistech

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

e32bf227-be64-4966-8781-fa9d25e46baf
8.4 GB, S3 ETag , downloads: 0
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5

File details

License:
Creative Commons: by-nc-sa 4.0 open in new tab
CC BY-NC-SA
Non-commercial - Share-alike
Raw data:
Data contained in dataset was not processed.
Software:
CaseViewer 2.3

Details

Year of publication:
2022
Verification date:
2021-03-05
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/jfdv-br83 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

Keywords

Cite as

Authors

seen 13 times