Dataset Information

Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas.

ABSTRACT: High-grade gliomas with mutations in the isocitrate dehydrogenase (IDH) gene family confer longer overall survival relative to their IDH-wild-type counterparts. Accurate determination of the IDH genotype preoperatively may have both prognostic and diagnostic value. The current study used a machine-learning algorithm to generate a model predictive of IDH genotype in high-grade gliomas based on clinical variables and multimodal features extracted from conventional MRI.Preoperative MRIs were obtained for 120 patients with primary grades III (n = 35) and IV (n = 85) glioma in this retrospective study. IDH genotype was confirmed for grade III (32/35, 91%) and IV (22/85, 26%) tumors by immunohistochemistry, spectrometry-based mutation genotyping (OncoMap), or multiplex exome sequencing (OncoPanel). IDH1 and IDH2 mutations were mutually exclusive, and all mutated tumors were collapsed into one IDH-mutated cohort. Cases were randomly assigned to either the training (n = 90) or validation cohort (n = 30). A total of 2970 imaging features were extracted from pre- and postcontrast T1-weighted, T2-weighted, and apparent diffusion coefficient map. Using a random forest algorithm, nonredundant features were integrated with clinical data to generate a model predictive of IDH genotype.Our model achieved accuracies of 86% (area under the curve [AUC] = 0.8830) in the training cohort and 89% (AUC = 0.9231) in the validation cohort. Features with the highest predictive value included patient age as well as parametric intensity, texture, and shape features.Using a machine-learning algorithm, we achieved accurate prediction of IDH genotype in high-grade gliomas with preoperative clinical and MRI features.

SUBMITTER: Zhang B

PROVIDER: S-EPMC5193019 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas.

Zhang Biqi B Chang Ken K Ramkissoon Shakti S Tanguturi Shyam S Bi Wenya Linda WL Reardon David A DA Ligon Keith L KL Alexander Brian M BM Wen Patrick Y PY Huang Raymond Y RY

Neuro-oncology 20160626 1

<h4>Background</h4>High-grade gliomas with mutations in the isocitrate dehydrogenase (IDH) gene family confer longer overall survival relative to their IDH-wild-type counterparts. Accurate determination of the IDH genotype preoperatively may have both prognostic and diagnostic value. The current study used a machine-learning algorithm to generate a model predictive of IDH genotype in high-grade gliomas based on clinical variables and multimodal features extracted from conventional MRI.<h4>Method ...[more]

PMID: 27353503

Similar Datasets

Project description:Background and purposeIsocitrate dehydrogenase (IDH) wild-type lower-grade gliomas (histologic grades II and III) with epidermal growth factor receptor (EGFR) amplification or telomerase reverse transcriptase (TERT) promoter mutation are reported to behave similar to glioblastoma. We aimed to evaluate whether MR imaging features could identify a subset of IDH wild-type lower-grade gliomas that carry molecular features of glioblastoma.Materials and methodsIn this multi-institutional retrospective study, pathologically confirmed IDH wild-type lower-grade gliomas from 2 tertiary institutions and The Cancer Genome Atlas constituted the training set (institution 1 and The Cancer Genome Atlas, 64 patients) and the independent test set (institution 2, 57 patients). Preoperative MRIs were analyzed using the Visually AcceSAble Rembrandt Images and radiomics. The molecular glioblastoma status was determined on the basis of the presence of EGFR amplification and TERT promoter mutation. Molecular glioblastoma was present in 73.4% and 56.1% in the training and test sets, respectively. Models using clinical, Visually AcceSAble Rembrandt Images, and radiomic features were built to predict the molecular glioblastoma status in the training set; then they were validated in the test set.ResultsIn the test set, a model using both Visually AcceSAble Rembrandt Images and radiomic features showed superior predictive performance (area under the curve = 0.854) than that with only clinical features or Visually AcceSAble Rembrandt Images (areas under the curve = 0.514 and 0.648, respectively; P < . 001, both). When both Visually AcceSAble Rembrandt Images and radiomics were added to clinical features, the predictive performance significantly increased (areas under the curve = 0.514 versus 0.863, P < .001).ConclusionsMR imaging features integrated with machine learning classifiers may predict a subset of IDH wild-type lower-grade gliomas that carry molecular features of glioblastoma.

Project description:BACKGROUND:Mutations in the isocitrate dehydrogenase 1 (IDH1) and IDH2 genes are important for both the integrated diagnosis and the prognosis of diffuse gliomas. The p.R132H mutation of IDH1 is the most frequently observed IDH mutation, while IDH2 mutations were relatively rarely studied. The aim of the study was to determine the pathological and genetic characteristics of lower-grade gliomas that carry IDH2 mutations. METHODS:Data from 238 adult patients with lower-grade gliomas were retrospectively analyzed. The status of IDH1/2 gene mutations, telomerase reverse transcriptase (TERT) promoter mutations, O-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, 1p/19q co-deletion and the expressions of IDH1 R132H, alpha-thalassemia X-linked mental retardation, and p53 were evaluated. Progression-free survival (PFS) and overall survival (OS) were calculated via Kaplan-Meier estimation using the log-rank test. RESULTS:Totally, 71% (169/238) of patients were positive for IDH mutations, including 12 patients harboring mutations in IDH2. Among the 12 patients with IDH2 mutations, ten patients harbored the R172K mutation, one patient harbored the R172S mutation and one harbored the R172W mutation. Of these, 11 tumors occurred in the frontal lobe and showed morphology typical of oligodendroglioma. The proportion of grade II tumors was higher than that of grade III tumors in IDH2 mutant-gliomas. IDH2 mutations were frequently associated with TERT promoter mutations, 1p/19q co-deletion and MGMT promoter methylation. IDH2 mutations were associated with better outcomes compared with IDH wild-type gliomas (P?<?0.05). However, the PFS and OS did not differ from that of IDH1 mutant patients (P?=?0.95 and P?=?0.60, respectively). CONCLUSIONS:IDH2 mutations are more frequent in oligodendrogliomas and associated with a better prognosis. IDH2 mutations may segregate in distinct clinico-pathological and genetic subtypes of gliomas, and therefore may merit routine investigation.

Project description:Isocitrate dehydrogenase 1 gene mutations are found in most World Health Organization grade II and III gliomas and secondary glioblastomas. Isocitrate dehydrogenase 1 mutations are known to have prognostic value in high-grade gliomas. However, their prognostic significance in low-grade gliomas remains controversial. We determined the predictive and prognostic value of isocitrate dehydrogenase 1 status in low-grade gliomas. The association of isocitrate dehydrogenase 1 status with clinicopathological and genetic factors was also evaluated. Clinical information and genetic data including isocitrate dehydrogenase 1 mutation, O 6-methylguanine DNA methyltransferase promoter methylation, 1p/19q chromosome loss, and TP53 mutation of 417 low-grade gliomas were collected from the Chinese Glioma Genome Atlas database. Kaplan-Meier and Cox proportional hazards regression analyses were performed to evaluate the prognostic effect of clinical characteristics and molecular biomarkers. Isocitrate dehydrogenase 1 mutation was identified as an independent prognostic factor for overall, but not progression-free, survival. Notably, isocitrate dehydrogenase 1 mutation was found to be a significant prognostic factor in patients with oligodendrogliomas, but not in patients with astrocytomas. Furthermore, O 6-methylguanine DNA methyltransferase promoter methylation (p = 0.017) and TP53 mutation (p < 0.001), but not 1p/19q loss (p = 0.834), occurred at a higher frequency in isocitrate dehydrogenase 1-mutated tumors than in isocitrate dehydrogenase 1 wild-type tumors. Younger patient age (p = 0.041) and frontal lobe location (p = 0.010) were significantly correlated with isocitrate dehydrogenase 1 mutation. Chemotherapy did not provide a survival benefit in patients with isocitrate dehydrogenase 1-mutated tumors. Isocitrate dehydrogenase 1 mutation was an independent prognostic factor in low-grade gliomas, whereas it showed no predictive value for chemotherapy response. Isocitrate dehydrogenase 1 mutation was highly associated with O 6-methylguanine DNA methyltransferase promoter methylation and TP53 mutation.

Dataset Information

Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas.

Publications

Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets