{"id":5800,"date":"2023-09-04T03:38:47","date_gmt":"2023-09-04T03:38:47","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-analysis-result\/radiomic-feature-standards\/"},"modified":"2023-09-13T12:11:13","modified_gmt":"2023-09-13T12:11:13","slug":"radiomic-feature-standards","status":"publish","type":"tcia_analysis_result","link":"https:\/\/cm.vastapps.dev\/tcia-analysis-result\/radiomic-feature-standards\/","title":{"rendered":"RADIOMIC-FEATURE-STANDARDS"},"featured_media":8754,"template":"","cancer_types":["Lung"],"citations":[4811,4812,2925,4813,4814,4815,4816,4817,4818,4819,4820,4821,4822,4823],"full_export":"

Summary<\/h2>

This dataset was used by the NCI's Quantitative Imaging Network (QIN) PET-CT Subgroup for their project titled: Multi-center Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Datasets<\/strong>.\u00a0 The purpose of this project was to assess the agreement among radiomic features when computed by several groups by using different software packages under very tightly controlled conditions, which included common image data sets and standardized feature definitions.\u00a0<\/p>

The image datasets (and Volumes of Interest \u2013 VOIs) provided here are the same ones used in that project and reported in the publication listed below (ISSN 2379-1381\u00a0<\/span>https:\/\/doi.org\/10.18383\/j.tom.2019.00031<\/a>)<\/span>.\u00a0 In addition, we have provided detailed information about the software packages used (Table 1 in that publication) as well as the individual feature value results for each image dataset and each software package that was used to create the summary tables (Tables 2, 3 and 4) in that publication.\u00a0<\/p>

For that project, nine common quantitative imaging features were selected for comparison including features that describe morphology, intensity, shape, and texture and that are described in detail in the International Biomarker Standardisation Initiative (IBSI,\u00a0<\/span>https:\/\/arxiv.org\/abs\/1612.07003<\/span>\u00a0<\/span><\/a>\u00a0<\/span>and recent publication (Zwanenburg A. Valli\u00e8res M, et al, The Image Biomarker\u00a0Standardization\u00a0Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping<\/strong>. Radiology. 2020 May;295(2):328-338. doi: https:\/\/doi.org\/10.1148\/radiol.2020191145<\/a>).<\/span><\/p>

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Acknowledgements\u00a0<\/strong> <\/span><\/p>

The authors gratefully acknowledge the following sources of support:\u00a0\u00a0<\/span><\/p>