Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

Isocitrate dehydrogenase (IDH)-1 mutation is an important prognostic factor and a potential therapeutic target in glioma. Immunohistological and molecular diagnosis of IDH mutation status is invasive. To avoid tumor biopsy, dedicated spectroscopic techniques have been proposed to detect D-2-hydroxyglutarate (2-HG), the main metabolite of IDH, directly in vivo. However, these methods are technically challenging and not broadly available. Therefore, we explored the use of machine learning for the non-invasive, inexpensive and fast diagnosis of IDH status in standard 1H-magnetic resonance spectroscopy (1H-MRS). To this end, 30 of 34 consecutive patients with known or suspected glioma WHO grade II-IV were subjected to metabolic positron emission tomography (PET) imaging with O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) for optimized voxel placement in 1H-MRS. Routine 1H-magnetic resonance (1H-MR) spectra of tumor and contralateral healthy brain regions were acquired on a 3 Tesla magnetic resonance (3T-MR) scanner, prior to surgical tumor resection and molecular analysis of IDH status. Since 2-HG spectral signals were too overlapped for reliable discrimination of IDH mutated (IDHmut) and IDH wild-type (IDHwt) glioma, we used a nested cross-validation approach, whereby we trained a linear support vector machine (SVM) on the complete spectral information of the 1H-MRS data to predict IDH status. Using this approach, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2–99.9%) and a specificity of 75.0% (95% CI, 42.9–94.5%), respectively. The area under the curve (AUC) amounted to 0.83. Subsequent ex vivo 1H-nuclear magnetic resonance (1H-NMR) measurements performed on metabolite extracts of resected tumor material (eight specimens) revealed myo-inositol (M-ins) and glycine (Gly) to be the major discriminators of IDH status. We conclude that our approach allows a reliable, non-invasive, fast and cost-effective prediction of IDH status in a standard clinical setting.

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OS08.4.A Retrospective analysis of in vivo 1H-magnetic resonance spectroscopy based on a machine learning approach enables reliable prediction of IDH mutation in patients with glioma

Neuro-Oncology ◽

10.1093/neuonc/noab180.034 ◽

2021 ◽

Vol 23 (Supplement_2) ◽

pp. ii11-ii11

Author(s):

E Bumes ◽

C Fellner ◽

S Lenz ◽

R Linker ◽

S Weis ◽

...

Keyword(s):

Machine Learning ◽

Validation Cohort ◽

Resonance Spectroscopy ◽

Learning Approach ◽

Idh Mutation ◽

1H Mrs ◽

1H Magnetic Resonance Spectroscopy ◽

Mutation Status ◽

Machine Learning Approach

Abstract BACKGROUND Mutation of isocitrate dehydrogenase (IDH) is not only an important landmark in the development of low-grade gliomas, but also has prognostic significance and is a potential therapeutic target. There is a high need to determinate IDH mutation status at diagnosis and during the course of therapy in a non-invasive and reliable manner. We established a machine learning approach based on a support vector machine to detect IDH mutation status in in vivo standard 1H-magnetic resonance spectroscopy (1H-MRS) at 3T with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2–99.9%), and a specificity of 75% (95% CI, 42.85–94.5%) in a prospective monocentric clinical trial. Here, the same method is applied in a retrospective cohort at 1.5T and tested for transferability. MATERIAL AND METHODS Validation cohort. The validation cohort comprised 100 patients with glioma for which standard in vivo 1H-MRS spectra had been acquired between 2002 and 2007. Standard single voxel spectroscopy had been measured at 1.5T using a PRESS sequence with a TR of 1500ms and a TE of 30ms. One sample had to be excluded due to non-malignant histology and for 15 samples the IDH mutation status was not available. Therefore, the validation cohort comprised 84 samples, of which 35 were bearing an IDH mutation in immunohistochemistry (sequencing for confirmation is outstanding). Machine learning. To transfer our method to an independent validation cohort our previously established machine learning approach was first trained on all samples of the 3T group. The trained algorithm was then applied to the data of the validation cohort. Here, among other factors the different field strengths, with which the spectra were acquired (3T vs. 1.5T) had to be considered. RESULTS 27 samples of the validation cohort had to be excluded due to poor spectra quality. Our approach correctly detected IDH mutation status in 47 of 62 patients (75.8%), although the technical conditions were significantly different from our published prospective cohort. 17 of 30 patients bearing an IDH mutation were correctly identified, while 30 of 32 wild type patients were determined successfully. CONCLUSION Our approach to detect IDH mutation status has promising application in an unselected retrospective cohort, demonstrating transferability across different technical conditions. Further investigations to improve our technique and an advanced neuropathological processing of the samples are planned.

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P5-13-05: Non-Invasive In Vivo 1H Magnetic Resonance Spectroscopy (MRS) Monitoring of Breast Tumor Response to IGF1R Targeted Therapy.

10.1158/0008-5472.sabcs11-p5-13-05 ◽

2011 ◽

Author(s):

D Sachdev ◽

JE Lin ◽

C Lunzer ◽

M Marjanska ◽

M Garwood ◽

...

Keyword(s):

Targeted Therapy ◽

Magnetic Resonance ◽

Magnetic Resonance Spectroscopy ◽

Breast Tumor ◽

Tumor Response ◽

Resonance Spectroscopy ◽

1H Magnetic Resonance Spectroscopy ◽

Non Invasive

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Non-invasive intramyocellular lipid determination by 1H magnetic resonance spectroscopy (1H MRS)

Journal of Science and Medicine in Sport ◽

10.1016/s1440-2440(02)80085-8 ◽

2002 ◽

Vol 5 (4) ◽

pp. 25

Keyword(s):

Magnetic Resonance ◽

Magnetic Resonance Spectroscopy ◽

Resonance Spectroscopy ◽

Intramyocellular Lipid ◽

1H Mrs ◽

1H Magnetic Resonance Spectroscopy ◽

Non Invasive

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Non-invasive analysis of gallbladder bile composition in cynomolgus monkeys using in vivo 1H magnetic resonance spectroscopy

Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids ◽

10.1016/j.bbalip.2007.01.006 ◽

2007 ◽

Vol 1771 (4) ◽

pp. 544-549 ◽

Cited By ~ 12

Author(s):

B KUNNECKE ◽

A BRUNS ◽

M VONKIENLIN

Keyword(s):

Magnetic Resonance ◽

Magnetic Resonance Spectroscopy ◽

Gallbladder Bile ◽

Resonance Spectroscopy ◽

1H Magnetic Resonance Spectroscopy ◽

Cynomolgus Monkeys ◽

Bile Composition ◽

Non Invasive

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BIMG-08. DEUTERIUM MAGNETIC RESONANCE SPECTROSCOPY USING 2H-PYRUVATE ALLOWS NON-INVASIVE IN VIVO IMAGING OF TERT EXPRESSION IN BRAIN TUMORS

Neuro-Oncology Advances ◽

10.1093/noajnl/vdab024.007 ◽

2021 ◽

Vol 3 (Supplement_1) ◽

pp. i2-i2

Author(s):

Georgios Batsios ◽

Celine Taglang ◽

Meryssa Tran ◽

Anne Marie Gillespie ◽

Joseph Costello ◽

...

Keyword(s):

Magnetic Resonance ◽

Magnetic Resonance Spectroscopy ◽

In Vivo Imaging ◽

Lactate Production ◽

Telomere Maintenance ◽

Resonance Spectroscopy ◽

Low Grade ◽

Non Invasive ◽

Tert Expression

Abstract Telomere shortening constitutes a natural barrier to uncontrolled proliferation and all tumors must find a mechanism of maintaining telomere length. Most human tumors, including high-grade primary glioblastomas (GBMs) and low-grade oligodendrogliomas (LGOGs) achieve telomere maintenance via reactivation of the expression of telomerase reverse transcriptase (TERT), which is silenced in normal somatic cells. TERT expression is, therefore, a driver of tumor proliferation and, due to this essential role, TERT is also a therapeutic target. However, non-invasive methods of imaging TERT are lacking. The goal of this study was to identify magnetic resonance spectroscopy (MRS)-detectable metabolic biomarkers of TERT expression that will enable non-invasive visualization of tumor burden in LGOGs and GBMs. First, we silenced TERT expression by RNA interference in patient-derived LGOG (SF10417, BT88) and GBM (GS2) models. Our results linked TERT silencing to significant reductions in steady-state levels of NADH in all models. NADH is essential for the conversion of pyruvate to lactate, suggesting that measuring pyruvate flux to lactate could be useful for imaging TERT status. Recently, deuterium (2H)-MRS has emerged as a novel, clinically translatable method of monitoring metabolic fluxes in vivo. However, to date, studies have solely examined 2H-glucose and the use of [U-2H]pyruvate for non-invasive 2H-MRS has not been tested. Following intravenous injection of a bolus of [U-2H]pyruvate, lactate production was higher in mice bearing orthotopic LGOG (BT88 and SF10417) and GBM (GS2) tumor xenografts relative to tumor-free mice, suggesting that [U-2H]pyruvate has the potential to monitor TERT expression in vivo. In summary, our study, for the first time, shows the feasibility and utility of [U-2H]pyruvate for in vivo imaging. Importantly, since 2H-MRS can be implemented on clinical scanners, our results provide a novel, non-invasive method of integrating information regarding a fundamental cancer hallmark, i.e. TERT, into glioma patient management.

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