Endometrial stromal sarcoma, low grade - Female, 64 - Tissue image [1270630012698451] - Open Research Data - Bridge of Knowledge

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Endometrial stromal sarcoma, low grade - Female, 64 - Tissue image [1270630012698451]

Description

This is the histopathological image of OTHER AND ILL-DEFINED SITES 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: 64

Clinical description: History of endometrial stromal sarcoma low grade. History of chemotherapy,. Numerous nodules in pelvis, abdominal cavity, ligaments of uterus.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: COMPLEX MIXED AND STROMAL NEOPLASMS

Diagnosis: Endometrial stromal sarcoma, low grade

Result of the histopathological examination: Endometrial stromal sarcoma, low grade- recurrence: CD10+, SMA singular cells +, ER focally +, PR focally +, Cyclin D1 (weak expression in some cells), Ki-67 10%.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: OTHER AND ILL-DEFINED SITES

Organ: OTHER AND ILL-DEFINED SITES

Tissue: Pelvis, NOS

Type of staining: positive/IHC

Staining: Not applicable

Antibody: Cyclin D1

Technology:

Equipment: Pannoramic 250 3DHistech

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

4955c5cb-b7f1-4a9c-9394-86e65f1979d1
7.7 GB, S3 ETag , downloads: 21
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:
2021-11-05
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/fd7v-c626 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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