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Diffuse glioma, not otherwise specified: imaging-based risk stratification achieves histomolecular-level prognostication

Authors
 Eun Bee Jang  ;  Ho Sung Kim  ;  Ji Eun Park  ;  Seo Young Park  ;  Yeo Kyung Nam  ;  Soo Jung Nam  ;  Young-Hoon Kim  ;  Jeong Hoon Kim 
Citation
 EUROPEAN RADIOLOGY, Vol.32(11) : 7780-7788, 2022-05 
Journal Title
EUROPEAN RADIOLOGY
ISSN
 0938-7994 
Issue Date
2022-05
MeSH
Brain Neoplasms* / diagnostic imaging ; Brain Neoplasms* / genetics ; Glioma* / diagnostic imaging ; Glioma* / genetics ; Humans ; Isocitrate Dehydrogenase / genetics ; Mutation ; Retrospective Studies ; Risk Assessment
Keywords
Diagnostic molecular pathology ; Glioma ; Imaging genomics ; Prognosis
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.
Full Text
https://link.springer.com/article/10.1007/s00330-022-08850-z
DOI
10.1007/s00330-022-08850-z
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/194850
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