EBV positive diffuse large B-cell lymphoma - Female, 70 - Tissue image [5190730046657521] - Open Research Data - Bridge of Knowledge

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EBV positive diffuse large B-cell lymphoma - Female, 70 - Tissue image [5190730046657521]

Description

This is the histopathological image of HEMATOPOIETIC AND RETICULOENDOTHELIAL SYSTEMS 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: 70

Clinical description: Splenomegaly.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: MATURE B-CELL LYMPHOMAS

Diagnosis: EBV positive diffuse large B-cell lymphoma

Result of the histopathological examination: Diffuse large B-cell lymphoma, EBV+ (EBV+ DLBCL). IHC : LCA weak+,CD20+, CD79a+,bcl2+,bcl6+,CD10 ( - ),CD 3 ( - ), CD2 ( - ), CD4 ( - ),CD7 ( - ), CD8( - ), ALK1 ( - ), tdT( - ), CD56 ( - ), CD23( - ), CD30( - ) CD5 ( - ), desmin ( - ), CK ( - ), CD34 ( - ), PAX5+/-, c myc(-), EBER(+)

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: HEMATOPOIETIC AND RETICULOENDOTHELIAL SYSTEMS

Organ: HEMATOPOIETIC AND RETICULOENDOTHELIAL SYSTEMS

Tissue: Spleen

Type of staining: positive/IHC

Staining: Not applicable

Antibody: CD 45 (LCA)

Technology:

Equipment: Pannoramic 250 3DHistech

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

97ce48c5-6823-4268-832c-ddea66f66732
2.0 GB, S3 ETag , downloads: 4
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:
2022-05-09
Creation date:
2022
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/2eqk-0y66 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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