Volume 51, Issue 6 pp. 1799-1809
Original Research

Identification of IDH and TERTp mutation status using 1H-MRS in 112 hemispheric diffuse gliomas

Esin Ozturk-Isik PhD

Corresponding Author

Esin Ozturk-Isik PhD

Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey

Brain Tumor Research Group, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Address reprint requests to: E.O.-I., Bogazici University, Institute of Biomedical Engineering, Rasathane Cad, Kandilli Campus, Kandilli Mah, 34684 Istanbul, Turkey. E-mail: [email protected]Search for more papers by this author
Sevim Cengiz MSc

Sevim Cengiz MSc

Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey

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Alpay Ozcan PhD

Alpay Ozcan PhD

Brain Tumor Research Group, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Department of Medical Device Technologies, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Biomedical Imaging Research and Development Center, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Center for Neuroradiological Applications and Research, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

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Cengiz Yakicier MD, PhD

Cengiz Yakicier MD, PhD

Department of Molecular Biology and Genetics, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

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Ayca Ersen Danyeli MD

Ayca Ersen Danyeli MD

Brain Tumor Research Group, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Department of Pathology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

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M. Necmettin Pamir MD

M. Necmettin Pamir MD

Brain Tumor Research Group, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Department of Neurosurgery, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Center for Neuroradiological Applications and Research, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

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Koray Özduman MD

Koray Özduman MD

Brain Tumor Research Group, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Department of Neurosurgery, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Center for Neuroradiological Applications and Research, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

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Alp Dincer MD

Alp Dincer MD

Brain Tumor Research Group, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Department of Radiology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

Center for Neuroradiological Applications and Research, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

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First published: 30 October 2019
Citations: 26
Contract grant sponsor: TUBITAK 1003; Contract grant number: 216S432.

Abstract

Background

There is a growing interest in noninvasively defining molecular subsets of hemispheric diffuse gliomas based on the isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) mutation status, which correspond to distinct tumor entities, and differ in demographics, natural history, treatment response, recurrence, and survival patterns.

Purpose

To investigate whether metabolite levels detected with short echo time (TE) proton MR spectroscopy (1H-MRS) at 3T can be used for noninvasive molecular classification of IDH and TERTp mutation-based subsets of gliomas.

Study Type

Retrospective.

Subjects

In all, 112 hemispheric diffuse gliomas (70 males/42 females, mean age: 42.1 ± 13.9 years).

Field Strength/Sequence

Short-TE 1H-MRS (repetition time (TR) = 2000 msec, TE = 30 msec, number of signal averages = 192) and routine clinical brain tumor MR protocols were acquired at 3T.

Assessment

1H-MRS data were quantified using LCModel software. TERTp and IDH1 or IDH2 (IDH1/2) mutations in the tissue were determined by either minisequencing or Sanger sequencing.

Statistical Tests

Metabolic differences between IDH mutant and IDH wildtype gliomas were assessed by a Mann–Whitney U-test. A Kruskal–Wallis test followed by a Tukey–Kramer test was used to analyze metabolic differences between IDH and TERTp mutational molecular subsets of gliomas. A Spearman rank correlation coefficient was used to assess the correlations of metabolite intensities with the Ki-67 index. Furthermore, machine learning was employed to classify the IDH and TERTp mutational status of gliomas, and the accuracy, sensitivity, and specificity values were estimated.

Results

Short-TE 1H-MRS classified the presence of an IDH mutation with 88.39% accuracy, 76.92% sensitivity, and 94.52% specificity, and a TERTp mutation within primary IDH wildtype gliomas with 92.59% accuracy, 83.33% sensitivity, and 95.24% specificity.

Data Conclusion

Short-TE 1H-MRS could be used to identify molecular subsets of hemispheric diffuse gliomas corresponding to IDH and TERTp mutations.

Level of Evidence: 3

Technical Efficacy Stage: 2

J. Magn. Reson. Imaging 2020;51:1799–1809.

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