Discordant ventriculoarterial connection - Male, 1 - Tissue image [3070630010195701] - Open Research Data - Bridge of Knowledge

Search

Discordant ventriculoarterial connection - Male, 1 - Tissue image [3070630010195701]

Description

This is the histopathological image of HEART, MEDIASTINUM, AND PLEURA 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: 1

Clinical description: Transposition of the great arteries (TGA). After cardiac surgery. Survived 6 days.

Gender: Male

Diagnosis:

Classification: ICD-10_10-20

Classification code: Chapter XVII - Congenital malformations, deformations and chromosomal abnormalities

Diagnosis: Discordant ventriculoarterial connection

Result of the histopathological examination: Cardiac muscle with areas of interstitial haemorrhages within the interventricular sept and epicardial haemorrhages in other sections.

Sample:

Material: FFPE

Collecting method: Autopsy specimen

Topography: RESPIRATORY SYSTEM AND INTRATORACIC ORGANS

Organ: HEART, MEDIASTINUM, AND PLEURA

Tissue: Heart

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

904299f8-513e-494b-bfd4-9d34c4363adb
8.0 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:
2022
Verification date:
2021-09-18
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/6m4n-gf51 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

Keywords

Cite as

seen 51 times