Diagnostic Value of Diffusion Weighted Imaging & MR Spectroscopy in Characterisation of Intracranial Neoplasms with Histopathological Correlation

Abstract

Introduction: Intracranial neoplasms represent a heterogeneous group of lesions with varied biological behaviour, prognosis, and management strategies. Accurate preoperative characterization remains a diagnostic challenge, as conventional magnetic resonance imaging (MRI) often shows overlapping features among different tumor types.

Aim & Objective: This study aimed to evaluate the diagnostic utility of diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) in the characterization of intracranial neoplasms, with histopathological examination as the reference standard. 

Material & Methods: A prospective observational study was conducted on 35 patients with suspected intracranial tumors. All patients underwent comprehensive MRI, including DWI with apparent diffusion coefficient (ADC) mapping and multivoxel MRS for metabolite analysis.

Results: Quantitative parameters such as tumor and peritumoral ADC values, along with metabolite ratios (Cho/Cr, Cho/NAA, NAA/Cr), were analysed and correlated with histopathological findings. The mean tumor ADC value was 1.03 ± 0.30 ×10⁻³ mm²/s, with significantly lower values observed in high-grade tumors and lymphoma compared to low-grade tumors (p < 0.001). MRS demonstrated elevated choline and reduced NAA in neoplastic lesions, with higher Cho/Cr and Cho/NAA ratios in high-grade tumors. MRI showed high specificity (95.7%) and overall diagnostic accuracy of 85.7% in identifying high-grade gliomas, though sensitivity was moderate (66.7%).

Conclusion: The combined use of DWI and MRS improved diagnostic confidence in tumor characterization, grading, and differentiation from other intracranial lesions. These advanced imaging techniques provide valuable non-invasive insights into tumor cellularity and metabolism, complementing conventional MRI and aiding in clinical decision-making. In conclusion, integration of DWI and MRS significantly enhances the diagnostic performance of MRI in intracranial neoplasms, with strong correlation to histopathology.

REFERENCES:

1. Maier S, Baur A, Flügel D, Lüdemann L, Knopp MV. Diffusion imaging of brain tumors. Eur J Radiol. 2010;76(3):376-387.
2. Aydın ZB, Selek K, Erol FS, Demir MK, Öner YA. Diagnostic value of diffusion-weighted magnetic resonance imaging and proton MR spectroscopy in brain lesions: correlation with histopathology. Eur J Radiol. 2019;116:34-40. https://doi.org/10.7759/cureus.6409
3. Dawoud MA, Sherif MF, Eltomey MA. Apparent diffusion coefficient and magnetic resonance spectroscopy in grading of malignant brain neoplasms. Egypt J Radiol Nucl Med. 2014;45(4):1215-1222. https://doi.org/10.1016/j.ejrnm.2014.08.003
4. Gupta K, Jain N, Saggar K. Role of diffusion weighted imaging and MR spectroscopy in characterisation of intracranial neoplasms. Indian J Radiol Imaging. 2018;28(3):324-33.
5. Calvar JA, Meli FJ, Romero C, Calcagno ML, Yánez PY, Martinez AR, et al. Characterization of brain tumors by MRS, DWI and Ki-67 labeling index. J Neurooncol. 2005;72(3):273-80. https://doi.org/10.1007/s11060-004-3342-2
6. Horská A, Barker PB. Imaging of brain tumors: MR spectroscopy and metabolic imaging. Neuroimaging Clin N Am. 2010;20(3):293-310. https://doi.org/10.1016/j.nic.2010.04.003
7. Elshafey R, Hassanien A, et al. 1H proton MR spectroscopy and diffusion-weighted imaging in discrimination between pyogenic brain abscesses and necrotic tumors. Egypt J Radiol Nucl Med. 2014;45(3):889-896. https://doi.org/10.1016/j.ejrnm.2014.01.010
8. Hirschler L, Sollmann N, Schmitz-Abecassis B, et al. Advanced MR techniques for preoperative glioma characterization: Part 1. J Magn Reson Imaging. 2023;57(6):1655-1675.
9. Provenzale JM, Mukundan S Jr, Barboriak DP. Diffusion-weighted and perfusion MR imaging for brain tumor characterization and grading. Radiology. 2006;239(3):632-649. https://doi.org/10.1148/radiol.2393042031
10. Gujar SK, Maheshwari S, Björkman-Burtscher I, Sundgren PC. Magnetic resonance spectroscopy. J Neuroophthalmol. 2005;25(3):217-226.
11. McKnight TR. Proton magnetic resonance spectroscopic evaluation of brain tumor metabolism. In: Perry MC, editor. Semin Oncol. 2004;31(5):605-617.
12. Sugahara T, Korogi Y, Kochi M, Ikushima I, Hirai T, Okuda T, et al. Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas. J Magn Reson Imaging. 1999;9(1):53-60. https://doi.org/10.1002/(sici)1522-2586(199901)9:1<53::aid-jmri7>3.0.co;2-2
13. Weinberg BD, Kuruva M, Shim H, Mullins ME. Clinical applications of magnetic resonance spectroscopy in brain tumors: from diagnosis to treatment. Radiol Clin North Am. 2021;59(3):349-362.
14. Wang QP, Lei DQ, Yuan Y, Xiong NX. Accuracy of ADC derived from DWI for differentiating high-grade from low-grade gliomas: a systematic review and meta-analysis. Medicine (Baltimore). 2020;99(8):1-9. https://doi.org/10.1097/md.0000000000019254
15. Zhang L, Min Z, Tang M, Chen S, Lei X, Zhang X. The utility of diffusion MRI with quantitative ADC measurements for differentiating high-grade from low-grade cerebral gliomas: evidence from a meta-analysis. J Neurol Sci. 2017;373:9-15. https://doi.org/10.1016/j.jns.2017.01.049
16. Kono K, Inoue Y, Nakayama K, Shakudo M, Morino M, Ohata K, et al. The role of diffusion-weighted imaging in patients with brain tumors. AJNR Am J Neuroradiol. 2001;22(6):1081-1088.
17. Ko CC, Tai MH, Li CF, Chang HY, Chang YH, Chen TY, et al. Differentiation between glioblastoma multiforme and primary cerebral lymphoma: additional benefits of quantitative diffusion-weighted MR imaging. PLoS One. 2016;11(9):1-15. https://doi.org/10.1371/journal.pone.0162565
18. Suh CH, Kim HS, Jung SC, Kim SJ. Diffusion-weighted imaging and diffusion tensor imaging for differentiating high-grade glioma from solitary brain metastasis: a systematic review and meta-analysis. AJNR Am J Neuroradiol. 2018;39(7):1208-1214. https://doi.org/10.3174/ajnr.a5650
19. Guzman R, Altrichter S, El-Koussy M, et al. Contribution of the apparent diffusion coefficient in perilesional edema for the assessment of brain tumors. J Neuroradiol. 2008;35(4):224-229. https://doi.org/10.1016/j.neurad.2008.02.003
20. Lu S, Ahn D, Johnson G, Cha S. Peritumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors. AJNR Am J Neuroradiol. 2003;24(5):937-941.
21. Demir MK, Iplikcioglu AC, Dincer A, Arslan M, Sav A. Single voxel proton MR spectroscopy findings of typical and atypical intracranial meningiomas. Eur J Radiol. 2006;60(1):48-55. https://doi.org/10.1016/j.ejrad.2006.06.002
22. Chawla S, Zhang Y, Wang S, Poptani H, Melhem ER, Sehgal CM, et al. Proton magnetic resonance spectroscopy in differentiating glioblastomas from primary cerebral lymphomas and brain metastases. J Comput Assist Tomogr. 2010;34(6):836-841. https://doi.org/10.1097/rct.0b013e3181ec554e