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Validation Study for Non-Invasive Prediction of IDH Mutation Status in Patients with Glioma Using In Vivo$ ^{1}$H-Magnetic Resonance Spectroscopy and Machine Learning
| Content Provider | MDPI |
|---|---|
| Author | Martina, Häckl Bumes, Elisabeth Fellner, Claudia Fellner, Franz A. Fleischanderl, Karin Lenz, Stefan Linker, Ralf Mirus, Tim Oefner, Peter J. Paar, Christian Proescholdt, Martin Andreas Riemenschneider, Markus J. Rosengarth, Katharina Weis, Serge Wendl, Christina Wimmer, Sibylle Hau, Peter Gronwald, Wolfram Hutterer, Markus |
| Copyright Year | 2022 |
| Description | 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 $(^{1}$H-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$ ^{1}$H-MR spectra were acquired at 1.5 T between 2002 and 2007, using the same data analysis approach. Despite different technical conditions, a sensitivity of 82.6% (95% CI, 61.2–95.1%) and a specificity of 72.7% (95% CI, 57.2–85.0%) could be achieved. We concluded that our$ ^{1}$H-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. |
| Starting Page | 2762 |
| e-ISSN | 20726694 |
| DOI | 10.3390/cancers14112762 |
| Journal | Cancers |
| Issue Number | 11 |
| Volume Number | 14 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-06-02 |
| Access Restriction | Open |
| Subject Keyword | Cancers Radiology, Nuclear Medicine and Imaging Glioma Idh Mutation 1h-mrs 2-hydroxyglutarate Linear Support Vector Machine Independent Validation |
| Content Type | Text |
| Resource Type | Article |
