Cancers (Jun 2022)

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

  • Elisabeth Bumes,
  • Claudia Fellner,
  • Franz A. Fellner,
  • Karin Fleischanderl,
  • Martina Häckl,
  • Stefan Lenz,
  • Ralf Linker,
  • Tim Mirus,
  • Peter J. Oefner,
  • Christian Paar,
  • Martin Andreas Proescholdt,
  • Markus J. Riemenschneider,
  • Katharina Rosengarth,
  • Serge Weis,
  • Christina Wendl,
  • Sibylle Wimmer,
  • Peter Hau,
  • Wolfram Gronwald,
  • Markus Hutterer

DOI
https://doi.org/10.3390/cancers14112762
Journal volume & issue
Vol. 14, no. 11
p. 2762

Abstract

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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.

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