Diffuse large B-cell lymphoma, NOS - Male, 55 - Tissue image [5040730020289681] - Open Research Data - Bridge of Knowledge

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Diffuse large B-cell lymphoma, NOS - Male, 55 - Tissue image [5040730020289681]

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 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: 55

Clinical description: Suspicion of the lymphoma

Gender: Male

Diagnosis:

Classification: ICD-O_3.2

Classification code: MATURE B-CELL LYMPHOMAS

Diagnosis: Diffuse large B-cell lymphoma, NOS

Result of the histopathological examination: In submitted samples a B-cell lymphoma was found, immunophenotype: CD20 (+), CD3 (-), bcl2 (+), bcl6 (+) and CD10 (+) partly, CD5 (-), cyklin D1 (-), mum1 (-), CD138 (-), CD30 (-), ALK1 (-), cMyc (-), Ki67 ca 85%. CKAE 1/3 (-), CD117 (-), synaptophysin (-), chromogranin (-). Conclusion: Malignant B-cell lymphoma high-grade (DLBCL). Ki 67 staining.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: LYMPH NODES

Organ: LYMPH NODES

Tissue: Lymph node, NOS

Type of staining: positive/IHC

Staining: Not applicable

Antibody: Ki-67

Technology:

Equipment: Pannoramic 250 3DHistech

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

5a91cd5e-a2aa-4f74-aad8-ca7dbf53e50e
10.3 GB, S3 ETag , downloads: 16
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:
2020-08-07
Creation date:
2020
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/806t-p160 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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