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A diagnostic tree for differentiation of adult pilocytic astrocytomas from high-grade gliomas

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dc.contributor.author강석구-
dc.contributor.author김세훈-
dc.contributor.author김의현-
dc.contributor.author문주형-
dc.contributor.author박예원-
dc.contributor.author안성수-
dc.contributor.author이승구-
dc.contributor.author장종희-
dc.date.accessioned2021-10-21T00:18:38Z-
dc.date.available2021-10-21T00:18:38Z-
dc.date.issued2021-10-
dc.identifier.issn0720-048X-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/185469-
dc.description.abstractBackground: To develop a diagnostic tree analysis (DTA) model based on demographical information and conventional MRI for differential diagnosis of adult pilocytic astrocytomas (PAs) and high-grade gliomas (HGGs; World Health Organization grade III-IV). Methods: A total of 357 adult patients with pathologically confirmed PA (n = 65) and HGGs (n = 292) who underwent conventional MRI were included. The patients were randomly divided into training (n = 250) and validation (n = 107) datasets to assess the diagnostic performance of the DTA model. The DTA model was created using a classification and regression tree algorithm on the basis of demographical and MRI findings. Results: In the DTA model, tumor location (on cerebellum, brainstem, hypothalamus, optic nerve, or ventricle), cystic mass with mural nodule appearance, presence of infiltrative growth, and major axis (cutoff value, 2.9 cm) were significant predictors for differential diagnosis of adult PAs and HGGs. The AUC, accuracy, sensitivity, and specificity were 0.94 (95% confidence interval 0.86-1.00), 96.2%, 89.5%, and 97.7%, respectively, in the test set. The accuracy of the DTA model was significantly higher than the no-information rate in the test (96.2 % vs 85.0%, P < 0.001) set. Conclusion: The DTA model based on MRI findings may be useful for differential diagnosis of adult PA and HGGs.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherElsevier Science Ireland Ltd-
dc.relation.isPartOfEUROPEAN JOURNAL OF RADIOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAdult-
dc.subject.MESHAlgorithms-
dc.subject.MESHAstrocytoma* / diagnostic imaging-
dc.subject.MESHBrain Neoplasms* / diagnostic imaging-
dc.subject.MESHDiagnosis, Differential-
dc.subject.MESHGlioma* / diagnostic imaging-
dc.subject.MESHHumans-
dc.subject.MESHMagnetic Resonance Imaging-
dc.titleA diagnostic tree for differentiation of adult pilocytic astrocytomas from high-grade gliomas-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Neurosurgery (신경외과학교실)-
dc.contributor.googleauthorYae Won Park-
dc.contributor.googleauthorDain Kim-
dc.contributor.googleauthorJihwan Eom-
dc.contributor.googleauthorSung Soo Ahn-
dc.contributor.googleauthorJu Hyung Moon-
dc.contributor.googleauthorEui Hyun Kim-
dc.contributor.googleauthorSeok-Gu Kang-
dc.contributor.googleauthorJong Hee Chang-
dc.contributor.googleauthorSe Hoon Kim-
dc.contributor.googleauthorSeung-Koo Lee-
dc.identifier.doi10.1016/j.ejrad.2021.109946-
dc.contributor.localIdA00036-
dc.contributor.localIdA00610-
dc.contributor.localIdA00837-
dc.contributor.localIdA01383-
dc.contributor.localIdA05330-
dc.contributor.localIdA02234-
dc.contributor.localIdA02912-
dc.contributor.localIdA03470-
dc.relation.journalcodeJ00845-
dc.identifier.eissn1872-7727-
dc.identifier.pmid34534909-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0720048X21004277-
dc.subject.keywordDecision tree-
dc.subject.keywordGlioma-
dc.subject.keywordMagnetic resonance imaging-
dc.subject.keywordPilocytic astrocytoma-
dc.contributor.alternativeNameKang, Seok Gu-
dc.contributor.affiliatedAuthor강석구-
dc.contributor.affiliatedAuthor김세훈-
dc.contributor.affiliatedAuthor김의현-
dc.contributor.affiliatedAuthor문주형-
dc.contributor.affiliatedAuthor박예원-
dc.contributor.affiliatedAuthor안성수-
dc.contributor.affiliatedAuthor이승구-
dc.contributor.affiliatedAuthor장종희-
dc.citation.volume143-
dc.citation.startPage109946-
dc.identifier.bibliographicCitationEUROPEAN JOURNAL OF RADIOLOGY, Vol.143 : 109946, 2021-10-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurosurgery (신경외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Pathology (병리학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers

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