Invasive breast carcinoma of no special type - Female, 68 - Tissue image [4190730010775781] - Open Research Data - Bridge of Knowledge

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Invasive breast carcinoma of no special type - Female, 68 - Tissue image [4190730010775781]

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: 68

Clinical description: Mobile, palpable mass of right breast, 5 cm diameter. Core needle biopsy: Invasive breast 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 of no special type- NHG3. 36 mitoses per 10 HPF. Ductal carcinoma in situ (DCIS)- NG3. Solid cancer nests, marked cellular pleomorphism, prominent nucleoli. TILs are present. ER-, PR-, HER2-, Ki-67 80%.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: BREAST

Organ: BREAST

Tissue: Upper-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

84f7e969-ef6e-4908-81c6-a40ceeb95e3c
10.1 GB, S3 ETag , downloads: 19
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:
2021-03-04
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/f41c-r287 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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