Differentiation of Astrocytoma Between Grades II and III Using a Combination of Methionine Positron Emission Tomography and Magnetic Resonance Spectroscopy

Overview

Journal World Neurosurg X

Date 2023 May 1

PMID 37123626

Authors

Hirohito Yano

Kazuhiro Miwa

Noriyuki Nakayama

Takashi Maruyama

Naoyuki Ohe

Soko Ikuta

Yuka Ikegame

Tetsuya Yamada

Hiroaki Takei

Etsuko Owashi

Kazufumi Ohmura

Kazutoshi Yokoyama

Morio Kumagai

Yoshihiro Muragaki

Toru Iwama

Jun Shinoda

Affiliations

Soon will be listed here.

Abstract

Objective: This study aimed to establish a method for differentiating between grades II and III astrocytomas using preoperative imaging.

Methods: We retrospectively analyzed astrocytic tumors, including 18 grade II astrocytomas (isocitrate dehydrogenase (IDH)-mutant: IDH-wildtype = 8:10) and 56 grade III anaplastic astrocytomas (37:19). We recorded the maximum methionine (MET) uptake ratios (tumor-to-normal: T/N) on positron emission tomography (PET) and three MRS peak ratios: choline (Cho)/creatine (Cr), N-acetyl aspartate (NAA)/Cr, and Cho/NAA, between June 2015 and June 2020. We then evaluated the cut-off values to differentiate between grades II and III. We compared the grading results between contrast enhancement effects on MR and combinational diagnostic methods (CDM) on a scatter chart using the cutoff values of the T/N ratio and MRS parameters.

Results: The IDH-mutant group showed significant differences in the Cho/NAA ratio between grades II and III using univariate analysis; however, multiple regression analysis results negated this. The IDH-wildtype group showed no significant differences between the groups. Contrast enhancement effects also showed no significant differences in IDH status. Accordingly, regardless of the IDH status, no statistically independent factors differentiated between grades II and III. However, CDMs showed higher sensitivity and negative predictive value in distinguishing them than MRI contrast examinations for both IDH statuses. We demonstrated a significantly higher diagnostic rate of grade III than of grade II with CDM, which was more striking in the IDH-mutant group than in the wild-type group.

Conclusions: CDM could be valuable in differentiating between grade II and III astrocytic tumors.

References

Kim D, Chun J, Kim S, Moon J, Kang S, Chang J . Re-evaluation of the diagnostic performance of C-methionine PET/CT according to the 2016 WHO classification of cerebral gliomas. Eur J Nucl Med Mol Imaging. 2019; 46(8):1678-1684. DOI: 10.1007/s00259-019-04337-0. View

Nafe R, Herminghaus S, Raab P, Wagner S, Pilatus U, Schneider B . Preoperative proton-MR spectroscopy of gliomas--correlation with quantitative nuclear morphology in surgical specimen. J Neurooncol. 2003; 63(3):233-45. DOI: 10.1023/a:1024249232454. View

Kudulaiti N, Qiu T, Lu J, Zhang H, Zhang Z, Guan Y . Combination of Magnetic Resonance Spectroscopy and ¹¹C-Methionine Positron Emission Tomography for the Accurate Diagnosis of Non-Enhancing Supratentorial Glioma. Korean J Radiol. 2019; 20(6):967-975. PMC: 6536785. DOI: 10.3348/kjr.2018.0690. View

Londono A, Castillo M, Armao D, Kwock L, Suzuki K . Unusual MR spectroscopic imaging pattern of an astrocytoma: lack of elevated choline and high myo-inositol and glycine levels. AJNR Am J Neuroradiol. 2003; 24(5):942-5. PMC: 7975769. View

Bulik M, Jancalek R, Vanicek J, Skoch A, Mechl M . Potential of MR spectroscopy for assessment of glioma grading. Clin Neurol Neurosurg. 2012; 115(2):146-53. DOI: 10.1016/j.clineuro.2012.11.002. View

Takei H, Shinoda J, Ikuta S, Maruyama T, Muragaki Y, Kawasaki T . Usefulness of positron emission tomography for differentiating gliomas according to the 2016 World Health Organization classification of tumors of the central nervous system. J Neurosurg. 2019; 133(4):1010-1019. DOI: 10.3171/2019.5.JNS19780. View

Likavcanova K, Dobrota D, Liptaj T, Pronayova N, Mlynarik V, Belan V . In vitro study of astrocytic tumour metabolism by proton magnetic resonance spectroscopy. Gen Physiol Biophys. 2005; 24(3):327-35. View

Lopci E, Riva M, Olivari L, Raneri F, Soffietti R, Piccardo A . Prognostic value of molecular and imaging biomarkers in patients with supratentorial glioma. Eur J Nucl Med Mol Imaging. 2017; 44(7):1155-1164. DOI: 10.1007/s00259-017-3618-3. View

Riva M, Lopci E, Castellano A, Olivari L, Gallucci M, Pessina F . Lower Grade Gliomas: Relationships Between Metabolic and Structural Imaging with Grading and Molecular Factors. World Neurosurg. 2019; 126:e270-e280. DOI: 10.1016/j.wneu.2019.02.031. View

10.

Qi C, Li Y, Fan X, Jiang Y, Wang R, Yang S . A quantitative SVM approach potentially improves the accuracy of magnetic resonance spectroscopy in the preoperative evaluation of the grades of diffuse gliomas. Neuroimage Clin. 2019; 23:101835. PMC: 6487359. DOI: 10.1016/j.nicl.2019.101835. View

11.

Okita Y, Shofuda T, Kanematsu D, Yoshioka E, Kodama Y, Mano M . The association between C-methionine uptake, IDH gene mutation, and MGMT promoter methylation in patients with grade II and III gliomas. Clin Radiol. 2020; 75(8):622-628. DOI: 10.1016/j.crad.2020.03.033. View

12.

Nakajo K, Uda T, Kawashima T, Terakawa Y, Ishibashi K, Tsuyuguchi N . Diagnostic Performance of [C]Methionine Positron Emission Tomography in Newly Diagnosed and Untreated Glioma Based on the Revised World Health Organization 2016 Classification. World Neurosurg. 2021; 148:e471-e481. DOI: 10.1016/j.wneu.2021.01.012. View

13.

Harada M, Tanouchi M, Nishitani H, Miyoshi H, Bandou K, Kannuki S . Non-invasive characterization of brain tumor by in-vivo proton magnetic resonance spectroscopy. Jpn J Cancer Res. 1995; 86(3):329-32. PMC: 5920808. DOI: 10.1111/j.1349-7006.1995.tb03059.x. View

14.

Delgado A, Delgado A . Discrimination between Glioma Grades II and III Using Dynamic Susceptibility Perfusion MRI: A Meta-Analysis. AJNR Am J Neuroradiol. 2017; 38(7):1348-1355. PMC: 7959917. DOI: 10.3174/ajnr.A5218. View

15.

Suh C, Kim H, Jung S, Gon Choi C, Kim S . 2-Hydroxyglutarate MR spectroscopy for prediction of isocitrate dehydrogenase mutant glioma: a systemic review and meta-analysis using individual patient data. Neuro Oncol. 2018; 20(12):1573-1583. PMC: 6231199. DOI: 10.1093/neuonc/noy113. View

16.

Moller-Hartmann W, Herminghaus S, Krings T, Marquardt G, Lanfermann H, Pilatus U . Clinical application of proton magnetic resonance spectroscopy in the diagnosis of intracranial mass lesions. Neuroradiology. 2002; 44(5):371-81. DOI: 10.1007/s00234-001-0760-0. View

17.

Verger A, Stoffels G, Bauer E, Lohmann P, Blau T, Fink G . Static and dynamic F-FET PET for the characterization of gliomas defined by IDH and 1p/19q status. Eur J Nucl Med Mol Imaging. 2017; 45(3):443-451. DOI: 10.1007/s00259-017-3846-6. View

18.

Zhou W, Zhou Z, Wen J, Xie F, Zhu Y, Zhang Z . A Nomogram Modeling C-MET PET/CT and Clinical Features in Glioma Helps Predict IDH Mutation. Front Oncol. 2020; 10:1200. PMC: 7396495. DOI: 10.3389/fonc.2020.01200. View

19.

Park Y, Han K, Ahn S, Bae S, Choi Y, Chang J . Prediction of -Mutation and 1p/19q-Codeletion Status Using Preoperative MR Imaging Phenotypes in Lower Grade Gliomas. AJNR Am J Neuroradiol. 2017; 39(1):37-42. PMC: 7410710. DOI: 10.3174/ajnr.A5421. View

20.

Kato T, Shinoda J, Nakayama N, Miwa K, Okumura A, Yano H . Metabolic assessment of gliomas using 11C-methionine, [18F] fluorodeoxyglucose, and 11C-choline positron-emission tomography. AJNR Am J Neuroradiol. 2008; 29(6):1176-82. PMC: 8118839. DOI: 10.3174/ajnr.A1008. View