Invasive breast carcinoma of no special type - Female, 81 - Tissue image [227063002631241] - Open Research Data - Bridge of Knowledge

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Invasive breast carcinoma of no special type - Female, 81 - Tissue image [227063002631241]

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: 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: BREAST

Organ: BREAST

Tissue: Outer breast

Type of staining: positive/IHC

Staining: Not applicable

Antibody: Ki-67

Technology:

Equipment: Pannoramic 250 3DHistech

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

77aecfa8-d530-4bac-aa15-e7dcbd191e9a
11.3 GB, S3 ETag , downloads: 17
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/gp99-fj48 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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