Validation Study for Non-Invasive Prediction of IDH Mutation Status in Patients with Glioma Using In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

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Abstract

The isocitrate dehydrogenase (IDH) mutation status is an indispensable prerequisite for diagnosis of glioma (astrocytoma and oligodendroglioma) according to the WHO classification of brain tumors 2021 and is a potential therapeutic target. Usually, immunohistochemistry followed by sequencing of tumor tissue is performed for this purpose. In clinical routine, however, non-invasive determination of IDH mutation status is desirable in cases where tumor biopsy is not possible and for monitoring neuro-oncological therapies. In a previous publication, we presented reliable prediction of IDH mutation status employing proton magnetic resonance spectroscopy (1H-MRS) on a 3.0 Tesla (T) scanner and machine learning in a prospective cohort of 34 glioma patients. Here, we validated this approach in an independent cohort of 67 patients, for which 1H-MR spectra were acquired at 1.5 T between 2002 and 2007, using the same data analysis approach. Despite different technical conditions, a sensitivity of 82.6% (95% CI, 61.2-95.1%) and a specificity of 72.7% (95% CI, 57.2-85.0%) could be achieved. We concluded that our 1H-MRS based approach can be established in a routine clinical setting with affordable effort and time, independent of technical conditions employed. Therefore, the method provides a non-invasive tool for determining IDH status that is well-applicable in an everyday clinical setting.
Original languageEnglish
Article number2762
Pages (from-to)2762
Number of pages14
JournalCancers
Volume14
Issue number11
DOIs
Publication statusPublished - 02 Jun 2022

Fields of science

  • 301101 General pathology
  • 301108 Molecular pathology
  • 302013 Medical diagnostics
  • 302071 Radiology
  • 303039 Radiological technology
  • 302075 Sonography
  • 302043 Magnetic resonance imaging (MRI)
  • 302010 Computed tomography (CT)
  • 302070 Radiodiagnostics
  • 301901 Blood group serology
  • 302040 Laboratory diagnostics
  • 304007 Tissue engineering

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