Diffusion tensor imaging in evaluation of posterior fossa tumors in children on a 3T MRI scanner

Abstract

Context: Primary intracranial tumors in children are commonly located in the posterior fossa. Conventional MRI offers limited information regarding the histopathological type of tumor which is essential for better patient management. Aims: The purpose of the study was to evaluate the usefulness of advanced MR imaging techniques like diffusion tensor imaging (DTI) in distinguishing the various histopathological types of posterior fossa tumors in children. Settings and Design: DTI was performed on a 3T MRI scanner in 34 untreated children found to have posterior fossa lesions. Materials and Methods: Using third party software, various DTI parameters [apparent diffusion coefficient (ADC), fractional anisotropy (FA), radial diffusivity, planar index, spherical index, and linear index] were calculated for the lesion. Statistical Analysis Used: Data were subjected to statistical analysis [analysis of variance (ANOVA)] using SPSS 15.0 software. Results: We observed significant correlation (P < 0.01) between ADC mean and maximum, followed by radial diffusivity (RD) with the histopathological types of the lesions. Rest of the DTI parameters did not show any significant correlation in our study. Conclusions: The results of our study support the hypothesis that most cellular tumors and those with greater nuclear area like medulloblastoma would have the lowest ADC values, as compared to less cellular tumors like pilocytic astrocytoma.

Keywords

Apparent diffusion coefficient - children - diffusion tensor imaging - fractional anisotropy - linear index - planar index - posterior fossa tumors - radial diffusivity - spherical index

Publication History

Article published online:
30 July 2021

• References

• 1 Poretti A, Meoded A, Huisman TA. Neuroimaging of pediatric posterior fossa tumors including review of the literature. J Magn Reson Imaging 2012;35:32-47.
• 2 Bahn MM. Invariant and orthonormal scalar measures derived from magnetic resonance diffusion tensor imaging. J Magn Reson 1999;141:68-77.
• 3 Chen X, Weigel D, Ganslandt O, Buchfelder M, Nimsky C. Diffusion tensor imaging and white matter tractography in patients with brainstem lesions. Acta Neurochir (Wien) 2007;149:1117-31.
• 4 Gauvain KM, McKinstry RC, Mukherjee P, Perry A, Neil JJ, Kaufman BA, et al. Evaluating pediatric brain tumor cellularity diffusion-tensor imaging. AJR Am J Roentgenol 2001;177:449-54.
• 5 Pauleit D, Langen KJ, Floeth F, Hautzel H, Riemenschneider MJ, Reifenberger G, et al. Can the apparent diffusion coefficient be used as a noninvasive parameter to distinguish tumor tissue from peritumoral tissue in cerebral gliomas? J Magn Reson Imaging 2004;20:758-64.
• 6 Tzika AA, Zarifi MK, Goumnerova L, Astrakas LG, Zurakowski D, Young-Poussaint T, et al. Neuroimaging in pediatric brain tumors: Gd-DTPA-enhanced, hemodynamic, and diffusion MR imaging compared with MR spectroscopic imaging. AJNR Am J Neuroradiol 2002;23:322-33.
• 7 Mardor Y, Roth Y, Ochershvilli A, Spiegelmann R, Tichler T, Daniels D, et al. Pretreatment prediction of brain tumors&#39; response to radiation therapy using high b-value diffusion-weighted MRI. Neoplasia 2004;6:136-42.
• 8 Guo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high-grade astrocytomas: Comparison of water diffusibility and histologic characteristics. Radiology 2002;224:177-83.
• 9 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;22:1081-8.
• 10 Beppu T, Inoue T, Shibata Y, Yamada N, Kurose A, Ogasawara K, et al. Fractional anisotropy value by diffusion tensor magnetic resonance imaging as a predictor of cell density and proliferation activity of glioblastomas. Surg Neurol 2005;63:56-61.
• 11 Price SJ, Burnet NG, Donovan T, Green HA, Peña A, Antoun NM, et al. Diffusion tensor imaging of brain tumours at 3T: A potential tool for assessing white matter tract invasion? Clin Radiol 2003;58:455-62.
• 12 Ellison D. Classifying the medulloblastoma: Insights from morphological and molecular genetics. Neuropathol Appl Neurobiol 2002;28:257-82.
• 13 Kleihues P, Louis DN, Scheithauer BW, Rorke LB, Reifenberger G, Burger PC, et al. The WHO classification of tumours of the nervous system. J Neuropathol Exp Neurol 2002;61:215-29.
• 14 Tlili-Graiess K, Mhiri Souei M, Mlaiki B, Arifa N, Moulahi H, Jemni Gharbi H, et al. Imaging of acute cerebellitis in children. Report of 4 cases. J Neuroradiol 2006;33:38-44.
• 15 Rumboldt Z, Camacho DL, Lake D, Welsh CT, Castillo M. Apparent diffusion coefficients for differentiation of cerebellar tumors in children. AJNR Am J Neuroradiol 2006;27:1362-9.
• 16 Jaremko JL, Jans LB, Coleman LT, Ditchfield MR. Value and limitations of diffusion-weighted imaging in grading and diagnosis of pediatric posterior fossa tumors. AJNR Am J Neuroradiol 2010;31:1613-6.
• 17 Stadlbauer A, Ganslandt O, Buslei R, Hammen T, Gruber S, Moser E, et al. Gliomas: Histopathologic evaluation of changes in directionality and magnitude of water diffusion at diffusion-tensor MR imaging. Radiology 2006;240:803-10.
• 18 Jolapara M, Kesavadas C, Radhakrishnan VV, Saini J, Patro SN, Gupta AK, et al. Diffusion tensor mode in imaging of intracranial epidermoid cysts: One step ahead of fractional anisotropy. Neuroradiology 2009;51:123-9.
• 19 Jolapara M, Patro SN, Kesavadas C, Saini J, Thomas B, Gupta AK, et al. Can diffusion tensor metrics help in preoperative grading of diffusely infiltrating astrocytomas? A retrospective study of 36 cases. Neuroradiology 2011;53:63-8.