Angiosarcoma - Female, 67 - Tissue image [614072959901651] - Open Research Data - Bridge of Knowledge

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Angiosarcoma - Female, 67 - Tissue image [614072959901651]

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: 67

Clinical description: History of breast carcinoma, chemotherapy, radiotherapy and brachytherapy. Ulcerated tumor of left breast. 27 x 13 mm tumor on MRI. Core needle biopsy: suspicion of angiosarcoma.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: BLOOD VESSEL TUMORS

Diagnosis: Angiosarcoma

Result of the histopathological examination: Angiosarcoma. High grade tumor with solid growth pattern. Cells with marked atypia and pleomorphism. Numerous mitoses and apoptoses. Extravasation of blood from malignant vessels forming blood lakes. Ulceration of skin is present. CD31+, CKAE1/AE3-, S100-, Ki-67 90%.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: BREAST

Organ: BREAST

Tissue: Upper-inner 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

67b72d62-f404-41ba-b3ae-267d8536849e
7.1 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:
2021-03-16
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/bwnq-yj51 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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