Classical Hodgkin lymphoma, nodular sclerosis, NOS - Female, 25 - Tissue image [5300730025876441] - Open Research Data - Bridge of Knowledge

Your account

login

Search

Classical Hodgkin lymphoma, nodular sclerosis, NOS - Female, 25 - Tissue image [5300730025876441]

Description

This is the histopathological image of LYMPH NODES tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 1000 slide scanner (20x magnification) and saved to DICOM format.

The detailed information about the patient, sample, and diagnosis are as follows:

Patient:

Age: 25

Clinical description: Enlarged cervical and supraclavicular lymph nodes on the left side. Suspicion of lymphoma.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: CHOROBA HODGKINA

Diagnosis: Classical Hodgkin lymphoma, nodular sclerosis, NOS

Result of the histopathological examination: Hodgkin lymphoma, nodular sclerosis: lymph node with nodules separated by collagen bands. Numerous Hodgkin Reed-Sternberg (HRS). HRS cells: CD30+, CD15+, MUM1+, Pax5 (weak)+, CD3-, CD20-, Ki-67+, EBVLMP1-, ALK1-.

Sample:

Material: FFPE

Collecting method: Excision of lesions

Topography: LYMPH NODES

Organ: LYMPH NODES

Tissue: Supraclavicular lymph node

Type of staining: positive/IHC

Staining: Not applicable

Antibody: Epstein-Barr Virus

Technology:

Equipment: Pannoramic 1000

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

aaf0893d-df29-4cc3-ba86-362af048dbe5
164.8 MB, S3 ETag , downloads: 22
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:
2022-04-06
Creation date:
2022
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/gk4a-0970 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

Keywords

Cite as

Authors

seen 56 times