Cited 2 times in
Dynamic contrast-enhanced MRI radiomics model predicts epidermal growth factor receptor amplification in glioblastoma, IDH-wildtype
DC Field | Value | Language |
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dc.contributor.author | 강석구 | - |
dc.contributor.author | 김세훈 | - |
dc.contributor.author | 박예원 | - |
dc.contributor.author | 손범석 | - |
dc.contributor.author | 안성수 | - |
dc.contributor.author | 이승구 | - |
dc.contributor.author | 장종희 | - |
dc.date.accessioned | 2024-01-03T01:11:26Z | - |
dc.date.available | 2024-01-03T01:11:26Z | - |
dc.date.issued | 2023-09 | - |
dc.identifier.issn | 0167-594X | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/197487 | - |
dc.description.abstract | Purpose: To develop and validate a dynamic contrast-enhanced (DCE) MRI-based radiomics model to predict epidermal growth factor receptor (EGFR) amplification in patients with glioblastoma, isocitrate dehydrogenase (IDH) wildtype. Methods: Patients with pathologically confirmed glioblastoma, IDH wildtype, from January 2015 to December 2020, with an EGFR amplification status, were included. Patients who did not undergo DCE or conventional brain MRI were excluded. Patients were categorized into training and test sets by a ratio of 7:3. DCE MRI data were used to generate volume transfer constant (Ktrans) and extracellular volume fraction (Ve) maps. Ktrans, Ve, and conventional MRI were then used to extract the radiomics features, from which the prediction models for EGFR amplification status were developed and validated. Results: A total of 190 patients (mean age, 59.9; male, 55.3%), divided into training (n = 133) and test (n = 57) sets, were enrolled. In the test set, the radiomics model using the Ktrans map exhibited the highest area under the receiver operating characteristic curve (AUROC), 0.80 (95% confidence interval [CI], 0.65-0.95). The AUROC for the Ve map-based and conventional MRI-based models were 0.74 (95% CI, 0.58-0.90) and 0.76 (95% CI, 0.61-0.91). Conclusion: The DCE MRI-based radiomics model that predicts EGFR amplification in glioblastoma, IDH wildtype, was developed and validated. The MRI-based radiomics model using the Ktrans map has higher AUROC than conventional MRI. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Springer | - |
dc.relation.isPartOf | JOURNAL OF NEURO-ONCOLOGY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Brain Neoplasms* / diagnostic imaging | - |
dc.subject.MESH | Brain Neoplasms* / genetics | - |
dc.subject.MESH | Brain Neoplasms* / metabolism | - |
dc.subject.MESH | ErbB Receptors / genetics | - |
dc.subject.MESH | Glioblastoma* / diagnostic imaging | - |
dc.subject.MESH | Glioblastoma* / genetics | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Isocitrate Dehydrogenase / genetics | - |
dc.subject.MESH | Magnetic Resonance Imaging | - |
dc.subject.MESH | Male | - |
dc.subject.MESH | Middle Aged | - |
dc.subject.MESH | Retrospective Studies | - |
dc.title | Dynamic contrast-enhanced MRI radiomics model predicts epidermal growth factor receptor amplification in glioblastoma, IDH-wildtype | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Neurosurgery (신경외과학교실) | - |
dc.contributor.googleauthor | Beomseok Sohn | - |
dc.contributor.googleauthor | Kisung Park | - |
dc.contributor.googleauthor | Sung Soo Ahn | - |
dc.contributor.googleauthor | Yae Won Park | - |
dc.contributor.googleauthor | Seung Hong Choi | - |
dc.contributor.googleauthor | Seok-Gu Kang | - |
dc.contributor.googleauthor | Se Hoon Kim | - |
dc.contributor.googleauthor | Jong Hee Chang | - |
dc.contributor.googleauthor | Seung-Koo Lee | - |
dc.identifier.doi | 10.1007/s11060-023-04435-y | - |
dc.contributor.localId | A00036 | - |
dc.contributor.localId | A00610 | - |
dc.contributor.localId | A05330 | - |
dc.contributor.localId | A04960 | - |
dc.contributor.localId | A02234 | - |
dc.contributor.localId | A02912 | - |
dc.contributor.localId | A03470 | - |
dc.relation.journalcode | J01629 | - |
dc.identifier.eissn | 1573-7373 | - |
dc.identifier.pmid | 37689596 | - |
dc.identifier.url | https://link.springer.com/article/10.1007/s11060-023-04435-y | - |
dc.subject.keyword | Epidermal growth factor receptor | - |
dc.subject.keyword | Glioblastoma | - |
dc.subject.keyword | Glioma | - |
dc.subject.keyword | Magnetic resonance image | - |
dc.subject.keyword | Perfusion weighted imaging | - |
dc.contributor.alternativeName | Kang, Seok Gu | - |
dc.contributor.affiliatedAuthor | 강석구 | - |
dc.contributor.affiliatedAuthor | 김세훈 | - |
dc.contributor.affiliatedAuthor | 박예원 | - |
dc.contributor.affiliatedAuthor | 손범석 | - |
dc.contributor.affiliatedAuthor | 안성수 | - |
dc.contributor.affiliatedAuthor | 이승구 | - |
dc.contributor.affiliatedAuthor | 장종희 | - |
dc.citation.volume | 164 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 341 | - |
dc.citation.endPage | 351 | - |
dc.identifier.bibliographicCitation | JOURNAL OF NEURO-ONCOLOGY, Vol.164(2) : 341-351, 2023-09 | - |
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