Validation Study for Non-Invasive Prediction of IDH Mutation Status in Patients with Glioma Using In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning
by
, , , , and
Elisabeth Bumes
1,*
,
Claudia Fellner
2,
Franz A. Fellner
3,
Karin Fleischanderl
4,
Martina Häckl
5,
Stefan Lenz
4,
Ralf Linker
1,
Tim Mirus
5,
Peter J. Oefner
5, 
Christian Paar
6,
Martin Andreas Proescholdt
7,
Markus J. Riemenschneider
8,
Katharina Rosengarth
7,
Serge Weis
9
,
Christina Wendl
2,
Sibylle Wimmer
10,
Peter Hau
1
,
Wolfram Gronwald
5,†
and
Markus Hutterer
1,11,† 1
Department of Neurology and Wilhelm Sander-NeuroOncology Unit, Regensburg University Hospital, 93055 Regensburg, Germany
2
Department of Radiology and Division of Neuroradiology, Regensburg University Hospital, 93055 Regensburg, Germany
3
Central Institute of Radiology, Kepler University Hospital, 4021 Linz, Austria
4
Division of Molecular Pathology, Neuromed Campus, Kepler University Hospital, 4020 Linz, Austria
5
Institute of Functional Genomics, University of Regensburg, 93053 Regensburg, Germany
6
Institute of Laboratory Medicine, Kepler University Hospital, 4021 Linz, Austria
7
Department of Neurosurgery, Regensburg University Hospital, 93053 Regensburg, Germany
8
Department of Neuropathology, Regensburg University Hospital, 93053 Regensburg, Germany
9
Division of Neuropathology, Neuromed Campus, Kepler University Hospital, 4020 Linz, Austria
10
Institute of Neuroradiology, Neuromed Campus, Kepler University Hospital, 4020 Linz, Austria
11
Department of Neurology with Acute Geriatrics, Saint John of God Hospital Linz, 4021 Linz, Austria
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2022, 14(11), 2762; https://doi.org/10.3390/cancers14112762
Submission received: 30 April 2022
/
Revised: 24 May 2022
/
Accepted: 31 May 2022
/
Published: 2 June 2022
(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)
Simple Summary
The enzyme isocitrate dehydrogenase (IDH) affects glioma cell metabolism in multiple ways. Mutation of IDH is not only indicative of the presence of astrocytoma or oligodendroglioma but it also comes with a better prognosis and constitutes a promising therapeutic target. Therefore, determination of IDH mutation status is essential in clinical practice. In most patients, tissue can be obtained by resection or biopsy to determine IDH status histologically. However, in some cases, this is not possible for technical reasons. We recently showed in a small cohort of patients that non-invasive determination of IDH mutation status using proton magnetic resonance spectroscopy (1H-MRS) at 3.0 Tesla (T) together with machine learning techniques is feasible in a standard clinical setting and with acceptable effort. Here, we demonstrate that our approach showed comparably good results in sensitivity (82.6%) and specificity (72.7%) in a larger validation cohort employing 1H-MRS at 1.5 T in a retrospective, distinct setting. We concluded that our method works well regardless of the magnetic field strength and scanner used, and thus, may improve patient care.
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.
