Radial gradient and radial deviation radiomic features from pre-surgical CT scans are associated with survival among lung adenocarcinoma patients

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dc.authorid0000-0003-3241-3216
dc.authorid0000-0003-0490-5184
dc.authorid0000-0002-5598-4727
dc.authorid0000-0002-2565-4030
dc.authorid0000-0001-7961-0191
dc.authorscopusid55293294500
dc.authorscopusid56677757700
dc.authorscopusid6507754227
dc.authorscopusid55937209500
dc.authorscopusid55742304400
dc.authorscopusid6601964766
dc.authorscopusid35242663400
dc.authorwosidTunali, Ilke/AAG-7120-2020
dc.authorwosidBalagurunathan, Yoganand/AAH-9139-2021
dc.authorwosidGuvenis, Albert/Q-2710-2015
dc.authorwosidSchabath, Matthew B./J-3763-2016
dc.authorwosidBalagurunathan, Yoganand/AAF-9163-2020
dc.authorwosidGuvenis, Albert/T-8866-2019
dc.contributor.authorTunalı, İlke
dc.contributor.authorStringfield, Olya
dc.contributor.authorGüveniş, Albert
dc.contributor.authorWang, Hua
dc.contributor.authorLiu, Ying
dc.contributor.authorBalagurunathan, Yoganand
dc.contributor.authorSchabath, Matthew B.
dc.date.accessioned2022-05-11T14:16:04Z
dc.date.available2022-05-11T14:16:04Z
dc.date.issued2017
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Biyomedikal Mühendisliği Bölümü
dc.description.abstractThe goal of this study was to extract features from radial deviation and radial gradient maps which were derived from thoracic CT scans of patients diagnosed with lung adenocarcinoma and assess whether these features are associated with overall survival. We used two independent cohorts from different institutions for training (n= 61) and test (n= 47) and focused our analyses on features that were non-redundant and highly reproducible. To reduce the number of features and covariates into a single parsimonious model, a backward elimination approach was applied. Out of 48 features that were extracted, 31 were eliminated because they were not reproducible or were redundant. We considered 17 features for statistical analysis and identified a final model containing the two most highly informative features that were associated with lung cancer survival. One of the two features, radial deviation outside-border separation standard deviation, was replicated in a test cohort exhibiting a statistically significant association with lung cancer survival (multivariable hazard ratio = 0.40; 95% confidence interval 0.17-0.97). Additionally, we explored the biological underpinnings of these features and found radial gradient and radial deviation image features were significantly associated with semantic radiological features.
dc.description.sponsorshipJames & Esther King Biomedical Research Program-Team Science Project [2KT01]; National Cancer Institute (NCI)United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Cancer Institute (NCI) [U01-CA143062]; NCI Early Detection Research NetworkUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Cancer Institute (NCI) [U01-CA200464]; Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and Research Institute; NCI designated Comprehensive Cancer Center [P30-CA76292]; NATIONAL CANCER INSTITUTEUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Cancer Institute (NCI) [U01CA196405, U01CA200464, U01CA186145, P30CA076292, U01CA143062] Funding Source: NIH RePORTER
dc.description.sponsorshipFunding support came from the James & Esther King Biomedical Research Program-Team Science Project (2KT01 to Dr. Gillies); the National Cancer Institute (NCI) (U01-CA143062 to Dr. Gillies); and the NCI Early Detection Research Network (U01-CA200464 to Drs. Gillies and Schabath). This work has also been supported in part by a Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and Research Institute; an NCI designated Comprehensive Cancer Center (grant number P30-CA76292).
dc.identifier.doi10.18632/oncotarget.21629
dc.identifier.endpage96026
dc.identifier.issn1949-2553
dc.identifier.issue56en_US
dc.identifier.pmid29221183
dc.identifier.scopus2-s2.0-85033390910
dc.identifier.scopusqualityQ2
dc.identifier.startpage96013
dc.identifier.urihttps://doi.org/10.18632/oncotarget.21629
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6167
dc.identifier.volume8
dc.identifier.wosWOS:000414937900076
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorTunalı, İlke
dc.language.isoen
dc.publisherImpact Journals Llc
dc.relation.ispartofOncotarget
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectradiomics
dc.subjectradial gradient
dc.subjectradial deviation
dc.subjectlung adenocarcinoma
dc.subjectquantitative imaging
dc.subjectGrowth-Factor Receptor
dc.subjectPrognostic-Factors
dc.subjectCancer Patients
dc.subjectCell
dc.subjectMutations
dc.subjectSegmentation
dc.subjectExpression
dc.subjectNodules
dc.subjectTrends
dc.subjectImages
dc.titleRadial gradient and radial deviation radiomic features from pre-surgical CT scans are associated with survival among lung adenocarcinoma patients
dc.typeArticle

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