Low grade serous carcinoma - Female, 58 - Tissue image [10010729534339021] - Open Research Data - Bridge of Knowledge

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Low grade serous carcinoma - Female, 58 - Tissue image [10010729534339021]

Description

This is the histopathological image of OVARY 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: 58

Clinical description: Cystic tumor of the left ovary, 11 cm in diameter On the cross-section cysts from 0.5 cm to 5.5 cm in diameter, filled with serous contents.

Gender: Female

Diagnosis:

Classification: ICD-O_3.2

Classification code: CYSTIC, MUCINOUS AND SEROUS NEOPLASMS

Diagnosis: Low grade serous carcinoma

Result of the histopathological examination: Low-grade serous carcinoma of left ovary Tumor with growth patterns: micropapillary or complex papillae, inverted macropapillae Uniform / homogeneous population of small cells with scant cytoplasm Mild to moderate nuclear atypia at mos

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: FEMALE GENITAL ORGANS

Organ: OVARY

Tissue: Ovary

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

5ed67c7e-88a0-4823-bd76-3c7be3bc08ec
9.8 GB, S3 ETag , downloads: 1
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:
2021-08-18
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/y9ya-an63 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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