Adenocarcinoma, intestinal type - Female, 71 - Tissue image [5310730015836351] - Open Research Data - Bridge of Knowledge

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Adenocarcinoma, intestinal type - Female, 71 - Tissue image [5310730015836351]

Description

This is the histopathological image of COLON tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: VS200 Olympus slide scanner (20x magnification) and saved to DICOM format.

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

Patient:

Age: 71

Clinical description: Colorectal cancer

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: ADENOMAS AND ADENOCARCINOMAS

Diagnosis: Adenocarcinoma, intestinal type

Result of the histopathological examination: In colorectal tumor samples invasive adenocarcinoma G2 is found. The cancer infiltration covers the entire thickness of the intestinal wall (border of the sigmoid colon) as well as the mesorectal adipose tissue and the sigmoid mesenteric adipose tissue. There is perforation within the tumor. Foci of angioinvasion and neuroinvasion by cancer infiltration have been identified.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: DIGESTIVE ORGANS

Organ: COLON

Tissue: Colon, NOS

Type of staining: positive/HE

Staining: Not applicable

Antibody: Not applicable

Technology:

Equipment: VS200 Olympus

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

d87a2927-c77d-4aa0-b651-a32effe0e4e2
1.9 GB, S3 ETag , downloads: 23
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:
2022-04-04
Creation date:
2022
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/daqa-2z12 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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