Neuroimaging-Based Classification Algorithm for Predicting 1p/19q-Codeletion Status in IDH-Mutant Lower Grade Gliomas. AJNR Am J Neuroradiol 2019 Mar;40(3):426-432
Date
02/02/2019Pubmed ID
30705071Pubmed Central ID
PMC7028667DOI
10.3174/ajnr.A5957Scopus ID
2-s2.0-85063012799 (requires institutional sign-in at Scopus site) 65 CitationsAbstract
BACKGROUND AND PURPOSE: Isocitrate dehydrogenase (IDH)-mutant lower grade gliomas are classified as oligodendrogliomas or diffuse astrocytomas based on 1p/19q-codeletion status. We aimed to test and validate neuroradiologists' performances in predicting the codeletion status of IDH-mutant lower grade gliomas based on simple neuroimaging metrics.
MATERIALS AND METHODS: One hundred two IDH-mutant lower grade gliomas with preoperative MR imaging and known 1p/19q status from The Cancer Genome Atlas composed a training dataset. Two neuroradiologists in consensus analyzed the training dataset for various imaging features: tumor texture, margins, cortical infiltration, T2-FLAIR mismatch, tumor cyst, T2* susceptibility, hydrocephalus, midline shift, maximum dimension, primary lobe, necrosis, enhancement, edema, and gliomatosis. Statistical analysis of the training data produced a multivariate classification model for codeletion prediction based on a subset of MR imaging features and patient age. To validate the classification model, 2 different independent neuroradiologists analyzed a separate cohort of 106 institutional IDH-mutant lower grade gliomas.
RESULTS: Training dataset analysis produced a 2-step classification algorithm with 86.3% codeletion prediction accuracy, based on the following: 1) the presence of the T2-FLAIR mismatch sign, which was 100% predictive of noncodeleted lower grade gliomas, (n = 21); and 2) a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation of the classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers. The metrics used in the algorithm were associated with moderate-substantial interreader agreement (κ = 0.56-0.79).
CONCLUSIONS: We have validated a classification algorithm based on simple, reproducible neuroimaging metrics and patient age that demonstrates a moderate prediction accuracy of 1p/19q-codeletion status among IDH-mutant lower grade gliomas.
Author List
Batchala PP, Muttikkal TJE, Donahue JH, Patrie JT, Schiff D, Fadul CE, Mrachek EK, Lopes MB, Jain R, Patel SHAuthor
Edward Kelly S. Mrachek MD Assistant Professor in the Pathology department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AdultAged
Algorithms
Astrocytoma
Brain Neoplasms
Chromosomes, Human, Pair 1
Cohort Studies
Female
Glioma
Humans
Isocitrate Dehydrogenase
Magnetic Resonance Imaging
Male
Middle Aged
Mutation
Neuroimaging
Oligodendroglioma
Retrospective Studies
Young Adult
