Mullerian mixed tumor - Female, 60 - Tissue image [5280730021738421] - Open Research Data - Bridge of Knowledge

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Mullerian mixed tumor - Female, 60 - Tissue image [5280730021738421]

Description

This is the histopathological image of CORPUS UTERI 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: 60

Clinical description: Endometrial polyp.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: COMPLEX MIXED AND STROMAL NEOPLASMS

Diagnosis: Mullerian mixed tumor

Result of the histopathological examination: Malignant mixed Mullerian tumor (carcinosarcoma). IHC epithelial component: CK AE1/3 (+), vimentin (+/-), PAX 8 (+), ER(+), p53- negative status, WT1 (-), EMA (+), napsin A (-), CD10-, p40; mesenchymal component: CK AE1/3- focal (+), vimentin (+), S100- focal (+), PAX 8 (+), ER (+), desmin-, SMA(+), CD117 (+), CD99 (+), cyclin D1 (+), CD34 (-), p53- negative status, WT1 (+), EMA (+), napsin A (-), CD10 (+), p40 (-).

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: FEMALE GENITAL ORGANS

Organ: CORPUS UTERI

Tissue: Corpus uteri

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

ffd22224-9159-4398-b060-8310bfa47669
2.9 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:
2022-05-25
Creation date:
2022
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/15vj-jp60 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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