Diffuse large B-cell lymphoma, germinal center B-cell subtype - Female, 67 - Tissue image [914073001413901] - Open Research Data - Bridge of Knowledge

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Diffuse large B-cell lymphoma, germinal center B-cell subtype - Female, 67 - Tissue image [914073001413901]

Description

This is the histopathological image of RETROPERITONEUM AND PERITONEUM 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: 67

Clinical description: Abdominal pains. 9 cm tumor of mesentery on ultrasound.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: MATURE B-CELL LYMPHOMAS

Diagnosis: Diffuse large B-cell lymphoma, germinal center B-cell subtype

Result of the histopathological examination: DLBCL GCB subtype: LCA+, CD20+, CD79a+, CD30+ focally, CD10+, BCL2+, BCL6 + focally (>30% cells), MUM1+, CD3-, CD5-, CD15-, CyklinD1-, cmyc focally (<40% cells), EMA-, CKAE1/AE3-, Ki-67 80%.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: RETROPERITONEUM AND PERITONEUM

Organ: RETROPERITONEUM AND PERITONEUM

Tissue: Mesentery

Type of staining: positive/IHC

Staining: Not applicable

Antibody: CD 10

Technology:

Equipment: Pannoramic 250 3DHistech

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

5f0a2b1f-e1a3-49ff-b76c-dfdb56ea9623
6.0 GB, 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:
2021
Verification date:
2021-08-28
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/x21f-6g49 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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