Description
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.
Funding information
Sponsorship: University of Minnesota CVM Resident and Graduate Student Research Grants
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.
Funding information
Sponsorship: University of Minnesota CVM Resident and Graduate Student Research Grants
| Date made available | Jul 20 2021 |
|---|---|
| Publisher | Data Repository for the University of Minnesota |
| Date of data production | Jan 1 2007 - Nov 30 2018 |