Severe cervical dysplasia, not elsewhere classified - Female, 33 - Tissue image [9160729581059751] - Open Research Data - Bridge of Knowledge

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Severe cervical dysplasia, not elsewhere classified - Female, 33 - Tissue image [9160729581059751]

Description

This is the histopathological image of CERVIX 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: 33

Clinical description: Histerectomy with bilateral fallopian tubes due to HSIL dysplasia confirmed by histopathological examination (colposcopy biopsy)

Gender: Female

Diagnosis:

Classification: ICD-10_10-20

Classification code: Chapter XIV - Diseases of the genitourinary system

Diagnosis: Severe cervical dysplasia, not elsewhere classified

Result of the histopathological examination: A fragment of the exocervix covered with a paraepidermal epithelium with high grade dysplasia (CIN3/ CIS) with infiltration of the glands in the transformation zone.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: FEMALE GENITAL ORGANS

Organ: CERVIX UTERI

Tissue: Exocervix

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

831f860d-9107-40d9-95a8-b0a2d5e6a411
4.6 GB, S3 ETag , downloads: 25
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:
2020-09-26
Creation date:
2020
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/cyq1-2b97 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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