{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Lu H"],"funding":["Cancer Center Support Grant at the H. Lee Moffitt Cancer Center and Research Institute","National Cancer Institute","NCI NIH HHS","NCI designated Comprehensive Cancer Center"],"pagination":["45"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6599273"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["19(1)"],"pubmed_abstract":["<h4>Background</h4>We retrospectively evaluated the capability of radiomic features to predict tumor growth in lung cancer screening and compared the performance of multi-window radiomic features and single window radiomic features.<h4>Methods</h4>One hundred fifty lung nodules among 114 screen-detected, incident lung cancer patients from the National Lung Screening Trial (NLST) were investigated. Volume double time (VDT) was calculated as the difference between continuous two scans and used to define indolent and aggressive lung cancers. Lung nodules were semi-automatically segmented using lung and mediastinal windows separately, and subtracting the mediastinal window region from the lung window region generated the difference region. 364 radiomic features were separately exacted from nod"],"journal":["Cancer imaging : the official publication of the International Cancer Imaging Society"],"pubmed_title":["Multi-window CT based Radiomic signatures in differentiating indolent versus aggressive lung cancers in the National Lung Screening Trial: a retrospective study."],"pmcid":["PMC6599273"],"funding_grant_id":["P30-CA76292","U01-CA143062; U01-CA200464; U01-CA 186145; U01- CA196405","U01 CA186145","U01 CA200464","CCSG","U01 CA143062"],"pubmed_authors":["Abdalah MA","Gillies RJ","Balagurunathan Y","Qi J","Lu H","Mu W","Garcia AL","Ye Z","Schabath MB"],"additional_accession":[]},"is_claimable":false,"name":"Multi-window CT based Radiomic signatures in differentiating indolent versus aggressive lung cancers in the National Lung Screening Trial: a retrospective study.","description":"<h4>Background</h4>We retrospectively evaluated the capability of radiomic features to predict tumor growth in lung cancer screening and compared the performance of multi-window radiomic features and single window radiomic features.<h4>Methods</h4>One hundred fifty lung nodules among 114 screen-detected, incident lung cancer patients from the National Lung Screening Trial (NLST) were investigated. Volume double time (VDT) was calculated as the difference between continuous two scans and used to define indolent and aggressive lung cancers. Lung nodules were semi-automatically segmented using lung and mediastinal windows separately, and subtracting the mediastinal window region from the lung window region generated the difference region. 364 radiomic features were separately exacted from nod","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Jun","modification":"2025-04-04T21:28:10.708Z","creation":"2019-07-25T07:00:18Z"},"accession":"S-EPMC6599273","cross_references":{"pubmed":["31253194"],"doi":["10.1186/s40644-019-0232-6"]}}