Cited 0 times in
Diffuse glioma, not otherwise specified: imaging-based risk stratification achieves histomolecular-level prognostication
DC Field | Value | Language |
---|---|---|
dc.date.accessioned | 2023-07-06T00:31:39Z | - |
dc.date.available | 2023-07-06T00:31:39Z | - |
dc.date.issued | 2022-05 | - |
dc.identifier.issn | 0938-7994 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/194850 | - |
dc.description.abstract | Objectives: To determine whether imaging-based risk stratification enables prognostication in diffuse glioma, NOS (not otherwise specified). Methods: Data from 220 patients classified as diffuse glioma, NOS, between January 2011 and December 2020 were retrospectively included. Two neuroradiologists analyzed pre-surgical CT and MRI to assign gliomas to the three imaging-based risk types considering well-known imaging phenotypes (e.g., T2/FLAIR mismatch). According to the 2021 World Health Organization classification, the three risk types included (1) low-risk, expecting oligodendroglioma, isocitrate dehydrogenase (IDH)-mutant, and 1p/19q-codeleted; (2) intermediate-risk, expecting astrocytoma, IDH-mutant; and (3) high-risk, expecting glioblastoma, IDH-wildtype. Progression-free survival (PFS) and overall survival (OS) were estimated for each risk type. Time-dependent receiver operating characteristic analysis using 10-fold cross-validation with 100-fold bootstrapping was used to compare the performance of an imaging-based survival model with that of a historical molecular-based survival model published in 2015, created using The Cancer Genome Archive data. Results: Prognostication according to the three imaging-based risk types was achieved for both PFS and OS (log-rank test, p < 0.001). The imaging-based survival model showed high prognostic value, with areas under the curves (AUCs) of 0.772 and 0.650 for 1-year PFS and OS, respectively, similar to the historical molecular-based survival model (AUC = 0.74 for PFS and 0.87 for OS). The imaging-based survival model achieved high long-term performance in both 3-year PFS (AUC = 0.806) and 5-year OS (AUC = 0.812). Conclusion: Imaging-based risk stratification achieved histomolecular-level prognostication in diffuse glioma, NOS, and could aid in guiding patient referral for insufficient or unsuccessful molecular diagnosis. Key points: • Three imaging-based risk types enable distinct prognostication in diffuse glioma, NOS (not otherwise specified). • The imaging-based survival model achieved similar prognostic performance as a historical molecular-based survival model. • For long-term prognostication of 3 and 5 years, the imaging-based survival model showed high performance. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Springer International | - |
dc.relation.isPartOf | EUROPEAN RADIOLOGY | - |
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 | Glioma* / diagnostic imaging | - |
dc.subject.MESH | Glioma* / genetics | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Isocitrate Dehydrogenase / genetics | - |
dc.subject.MESH | Mutation | - |
dc.subject.MESH | Retrospective Studies | - |
dc.subject.MESH | Risk Assessment | - |
dc.title | Diffuse glioma, not otherwise specified: imaging-based risk stratification achieves histomolecular-level prognostication | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Radiology (영상의학교실) | - |
dc.contributor.googleauthor | Eun Bee Jang | - |
dc.contributor.googleauthor | Ho Sung Kim | - |
dc.contributor.googleauthor | Ji Eun Park | - |
dc.contributor.googleauthor | Seo Young Park | - |
dc.contributor.googleauthor | Yeo Kyung Nam | - |
dc.contributor.googleauthor | Soo Jung Nam | - |
dc.contributor.googleauthor | Young-Hoon Kim | - |
dc.contributor.googleauthor | Jeong Hoon Kim | - |
dc.identifier.doi | 10.1007/s00330-022-08850-z | - |
dc.relation.journalcode | J00851 | - |
dc.identifier.eissn | 1432-1084 | - |
dc.identifier.pmid | 35587830 | - |
dc.identifier.url | https://link.springer.com/article/10.1007/s00330-022-08850-z | - |
dc.subject.keyword | Diagnostic molecular pathology | - |
dc.subject.keyword | Glioma | - |
dc.subject.keyword | Imaging genomics | - |
dc.subject.keyword | Prognosis | - |
dc.citation.volume | 32 | - |
dc.citation.number | 11 | - |
dc.citation.startPage | 7780 | - |
dc.citation.endPage | 7788 | - |
dc.identifier.bibliographicCitation | EUROPEAN RADIOLOGY, Vol.32(11) : 7780-7788, 2022-05 | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.