Invasive breast carcinoma of no special type - Female, 56 - Tissue image [5040730020276751] - Open Research Data - Bridge of Knowledge

Your account

login

Search

Invasive breast carcinoma of no special type - Female, 56 - Tissue image [5040730020276751]

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: 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: 56

Clinical description: Diagnosis of invasive carcinoma of right breast. Additional hypoechoic tumor on ultrasound.

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- NHG2. Tumor composed of nests and trabeculae of atypical neoplastic cells and abundant desmoplastic stroma. E-cadherin+, ER+, PR+ (in some carcinoma cells), HER2 +, Ki-67 20%.

Sample:

Material: FFPE

Collecting method: Core-needle biopsy

Topography: BREAST

Organ: BREAST

Tissue: Lower-outer quadrant of breast

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

50f945dd-b5af-463c-84ee-659ee522b071
1.9 GB, S3 ETag , downloads: 22
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:
2021
Verification date:
2021-02-03
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/hxga-ze75 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

Keywords

Cite as

Authors

seen 95 times