Between Dec 19, 2024 and Jan 2, 2025, datasets can be submitted to DRUM but will not be processed until after the break. Staff will not be available to answer email during this period, and will not be able to provide DOIs until after Jan 2. If you are in need of a DOI during this period, consider Dryad or OpenICPSR. Submission responses to the UDC may also be delayed during this time.
 

CT radiomic features for canine primary lung tumors

Wolf-Ringwall, Amber
Rendahl, Aaron
Seelig, Davis
Ober, Chris
Able, Hannah
Wilke, Chris
Lawrence, Jessica
2021-07-20
Thumbnail Image

Persistent link to this item

https://doi.org/10.13020/mkez-rd57
 https://hdl.handle.net/11299/221999
Statistics
View Statistics

Keywords

Collection period

2007-01-01
2018-11-30

Date completed

2019-10-01

Date updated

Time period coverage

Geographic coverage

Source information

Journal Title

Journal ISSN

Volume Title

Title

CT radiomic features for canine primary lung tumors

Published Date

2021-07-20

Authors

Group

University of Minnesota Veterinary Oncology

Author Contact

Lawrence, Jessica
jlawrenc@umn.edu

Type

Dataset

Abstract

Quantitative analysis of computed tomography (CT) radiomic features is an indirect measure of tumor heterogeneity, which has been associated with prognosis in human lung carcinoma. Canine lung tumors share similar features to human lung tumors and may serve as a model in which to investigate the utility of radiomic features in differentiating tumor type and prognostication. The purpose of this study was to correlate first-order radiomic features from canine primary lung tumors to histopathologic characteristics and outcome. Sixty-seven tumors from 65 dogs were evaluated in this study.

Description

Datasets used for statistical analyses from the 65 dogs included in the study are available for review. Data include clinical data, CT review, histopathologic review, and first order radiomic features extracted from postcontrast thoracic CT images.

Referenced by

Related to

Replaces

item.page.isreplacedby

License

CC0 1.0 Universal
 http://creativecommons.org/publicdomain/zero/1.0/

Publisher

Collections

Data Repository for U of M (DRUM)

Funding information

University of Minnesota CVM Resident and Graduate Student Research Grants

item.page.sponsorshipfunderid

item.page.sponsorshipfundingagency

item.page.sponsorshipgrant

Previously Published Citation

Other identifiers

Suggested citation

Wolf-Ringwall, Amber; Rendahl, Aaron; Seelig, Davis; Ober, Chris; Able, Hannah; Wilke, Chris; Lawrence, Jessica. (2021). CT radiomic features for canine primary lung tumors. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/mkez-rd57.

View/Download File

File View/Open
Description
Size
Canine lung CT data_PLoS One2021.csv
Canine lung CT data
(4.65 KB)

Canine Lung histopathology data_PLoS One2021.csv
Canine lung tumor histopathology data
(10.2 KB)

Canine lung tumor_Clinical data_PLoS One 2021.csv
Canine lung tumor clinical data
(17.2 KB)

Canine lung tumor_first order radiomic features_PLoS One2021.csv
Canine lung tumor radiomic statistics
(14.93 KB)

Readme_Lawrence_DRUM.txt
Readme File
(4.47 KB)

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.