Invasive breast carcinoma of no special type - Female, 67 - Tissue image [7100730013393931] - Open Research Data - Bridge of Knowledge

Search

Invasive breast carcinoma of no special type - Female, 67 - Tissue image [7100730013393931]

Description

This is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: VS200 Olympus slide scanner (20x magnification) and saved to DICOM format.

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

Patient:

Age: 67

Clinical description: Breast tumor.

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 cancer of no special type G1. Gland formation: 2, Pleomorphism: 2, Mitotic activity: 1. IHC - Estrogen receptors: TS=8/8 (3+ in about 90% of tumor cells). - Progesterone receptors: TS=8/8 (3+ in about 80% of tumor cells) - Her2: 2+ - Ki67: (+) in about 10% of tumor cells (hot spot) - CK14: (-) - E-cadherin: (+)

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: BREAST

Organ: BREAST

Tissue: Upper-outer quadrant of breast

Type of staining: positive/IHC

Staining: Not applicable

Antibody: CK 14

Technology:

Equipment: VS200 Olympus

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

164ad97e-de80-4de6-a120-991a63d9a011
583.5 MB, S3 ETag , downloads: 1
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:
2022-03-24
Creation date:
2022
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/z02w-6m70 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

Keywords

Cite as

seen 15 times