Teratoma, malignant, NOS - Female, 39 - Tissue image [3300730069393831] - Open Research Data - Bridge of Knowledge

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Teratoma, malignant, NOS - Female, 39 - Tissue image [3300730069393831]

Description

This is the histopathological image of OVARY 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: 39

Clinical description: A cyst 15 cm in diameter with a smooth outer surface and a fallopian tube 6 cm long. The cyst filled with brown fluid. The internal surface is smooth, with a polypoid mass measuring 5x3x2.5cm. On cross-section the mass is solid.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: GERM CELL NEOPLASMS

Diagnosis: Teratoma, malignant, NOS

Result of the histopathological examination: Immature teratoma G3. Multiple foci of immature neuroepithelium and necrosis are seen. IHC: CD56(+), GFAP(+), CKAE1/AE3(+), synaptophysin(+, chromogranin(-), NSE(-). Ki-67 high.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: FEMALE GENITAL ORGANS

Organ: OVARY

Tissue: Ovary

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

3789e5c1-5d3b-449c-aaa5-1842bec09a93
1.3 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:
2020-10-09
Creation date:
2020
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/5e8n-ez28 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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