Asian Journal of Research and Reports in Neurology

Sensitivity and Specificity of Magnetic Resonance Spectroscopy (MRS) in the Diagnosis of Meningiomas

Zonaid Kabir *

National Institute of Kidney Diseases and Urology (NIKDU), Dhaka, Bangladesh.

Momotaj Sohely

Department of Community Medicine, Sheikh Hasina Medical College, Tangail, Bangladesh.

*Author to whom correspondence should be addressed.

---

Abstract

Background: Meningiomas are the most common extra axial tumors of brain accounting 13-26% of primary intracranial neoplasm. They are the most common non glial tumor of central nervous system (CNS). Meningiomas arise from the arachnoid cells called meningothelial cell and appear as extra axial, sharply demarcated, solid mushroom imaging pattern with dense homogenous contrast enhancement on CT and MRI.

Objective: To determine the sensitivity and specificity of Magnetic Resonance Spectroscopy (MRS) in the Diagnosis of Meningiomas.

Methods and Materials: This cross-sectional study was conducted on 45 patients with suspected meningioma who were referred to the Radiology and Imaging Department of Bangabandhu Sheikh Mujib Medical University (BSMMU) from the Department of Neurology and Neurosurgery during period from October 2019 to September 2021. Magnetic Resonance Spectroscopy (MRS) findings were evaluated taking into account the histopathology as a gold standard. Statistical analyses were carried out by using SPSS version 23.0. The quantitative observations were indicated by frequencies. Receiver operating characteristic (ROC) curve was generated to determine the cutoff value for the best sensitivity, specificity, negative and positive predictive values of choline /N-acetyl aspartate ratio with regard to diagnosis and characterization of meningiomas.

Results: In MRS out of 45 patients 36(80%) patients were diagnosed as meningioma among them 30(67%) patients had increased alanine, 38(84%) patients had increased choline, 22(49%) patients NAA had not detected, 20(44%) patients NAA were minimally detected. Remaining 9(20%) patients had non-meningioma. In histopathology out of 45 patients 38(84%) patients had meningioma and 7(16%) patients had non meningioma. Histopathology showed 27(71%) patients was grade I, 3(8%) was grade II and 8(21%) was grade III. Increased lactate was detected in 11 patients, out of which 9(82%) patients were found high grade and 2(18%) patients were low grade meningiomas. The validity of meningioma by MRS was represented by calculating sensitivity, specificity, accuracy, positive and negative predictive values taking into account histopathology as gold standard. Sensitivity was 89.47%, specificity was 71.43%, accuracy was 86.67%, PPV was 94.44% and NPV was 55.56%. Based on the receiver-operator characteristic (ROC) curve choline/N-acetyl aspartate ratio had area under curve 0.850. Receiver-operator characteristic (ROC) was constructed by using choline /N-acetyl aspartate ratio, which gave a cut off value ≥2.99, with 80.0% sensitivity and 62.5% specificity for prediction of high grade.

Conclusion: The study suggested that MRS findings were consistent with low specificity in the diagnosis of meningiomas but MRS can characterize the types of meningiomas keeping histopathology as a gold standard. Increased alanine, decreased or absent NAA, increased choline, decreased creatine could be the spectroscopic parameters for the diagnosis of meningiomas and by using choline/N-acetyl aspartate ratio more sensitivity was found to predicted high grade along with lactate peak.

Keywords: MRI, MRS, histopathology, choline/creatine ratio, choline /N-acetyl aspartate ratio

---

---

---

References

Kleihues P, Cavenee WK. Pathology and genetics of tumors of the nervous system. IARC; 2000.

Toh CH, Castillo M, Wong AC, Wei KC, Wong HF, Ng SH, Wan YL. Differentiation between classic and atypical meningiomas with use of diffusion tensor imaging. American Journal of Neuroradiology. 2008; 29(9):1630-1635.

Buetow MP, Buetow PC, Smirniotopoulos JG. Typical, atypical, and misleading features in meningioma. Radiographics. 1991;11(6):1087-1106.

Haaga JR, Boll DT. CT and MRI of the whole body. 6th edition, Elsevire. 2017;212-526.

D’Ambrosio AL, Bruce JN. Treatment of meningioma: An update. Current Neurology and Neuroscience Reports. 2003;3(3):206-214.

Stefanovic J, Stojanov D, Bosnjakovic P, Stojanov NI. Magnetic resonance presentation of intracranial meningiomas. Global Journal of Medical Research. 2011;4:33-8.

Majos C, Alonso J, Aguilera C, Serrallonga M, Coll S, Acebes JJ, et al. Utility of proton MR spectroscopy in the diagnosis of radiologically atypical intracranial meningiomas. Neuroradiology. 2003; 45(3):129-136.

Tamrazi B, Shiroishi MS, Liu CSJ. Advanced imaging of intracranial meningiomas. Neurosurgery clinics of North America. 2016;27(2):137-43.

Yue Q, Isobe T, Shibata Y, Anno I, Kawamura H, Yamamoto Y, et al. New observations concerning the interpretation of magnetic resonance spectroscopy of meningioma. European Radiology. 2008; 18(12):2901-2911.

Castillo M, Kwock L. Clinical applications of proton magnetic resonance spectroscopy in the evaluation of common intracranial tumors. Topics in Magnetic Resonance Imaging. 1999;10(2):104-113.

Kinoshita Y, Kajiwara H, Yokota A, Koga Y. Proton magnetic resonance spectroscopy of brain tumors: An in vitro study. Neurosurgery. 1994;35(4):606-614.

Lin MC, Li CZ, Hsieh CC, Hong KT, Lin BJ, Lin C, et al. Preoperative grading of intracranial meningioma by magnetic resonance spectroscopy (1H-MRS). Plos One. 2018;13(11):e0207612.

Server A, Josefsen R, Kulle B, Mæhlen J, Schellhorn T, Gadmar Ø, et al. Proton magnetic resonance spectroscopy in the distinction of high-grade cerebral gliomas from single metastatic brain tumors. Acta Radiologica. 2010;51(3):316-325.

Majos C, Julià-Sapé M, Alonso J, Serrallonga M, Aguilera C, Acebes JJ, et al. Brain tumor classification by proton MR spectroscopy: Comparison of diagnostic accuracy at short and long TE. American Journal of Neuroradiology. 2004;25(10): 1696-1704.

Watts J, Box G, Galvin A, Brotchie P, Trost N, Sutherland T. Magnetic resonance imaging of meningiomas: A pictorial review. Insights into Imaging. 2014;5(1): 113-122.

Chavhan GB. MRI made easy (for beginners). 2nd edition, Jaypee Brothers Medical Publishers, India. 2013;158-171.

Matsusue E, Inoue C, Tabuchi S, Yoshioka H, Nagao Y, Matsumoto K, et al. Utility of 3T single-voxel proton MR spectroscopy for differentiating intracranial meningiomas from intracranial enhanced mass lesions. Acta Radiologica Open. 2021;10(4):1-10.

Jaskólski DJ, Fortuniak J, Stefańczyk L, Majos A, Gajewicz W, Papierz W, et al. Differential diagnosis of intracranial meningiomas based on magnetic resonance spectroscopy. Neurologia i Neurochirurgia Polska. 2013;47(3):247-255.

Liu J, Chen J, Zha Y, Huang Y, Zeng F. Magnetic Resonance Imaging (MRI) Differential Diagnosis of Meningiomas Using ANOVA. Contrast Media & Molecular Imaging. 2021;2021:1-8.

Buhl R, Nabavi A, Wolff S, Hugo HH, Alfke K, Jansen O, et al. MR spectroscopy in patients with intracranial meningiomas. Neurological Research. 2007;29(1):43-46.

Demir MK, Iplikcioglu AC, Dincer A, Arslan M, Sav A. Single voxel proton MR spectroscopy findings of typical and atypical intracranial meningiomas. European Journal of Radiology. 2006; 60(1):48-55.

Domingo Z, Rowe G, Blamire AM, Cadoux-Hudson TAD. Role of ischaemia in the genesis of oedema surrounding meningiomas assessed using magnetic resonance imaging and spectroscopy. British Journal of Neurosurgery. 1998; 12(5):414-418.