Evaluation of the Role of Diffusion Tensor Imaging in Grading of Glial Tumors based on Relative Anisotropy

Document Type : Original Article (s)

Authors

1 Department of Radiology, School of Paramedicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran

2 Assistant Professor, Department of Radiology, School of Paramedicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran

3 Professor, Research Center for Neurosurgery and Functional Nerves, Shohadaye Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran

4 Department of Radiology, School of Paramedicine, Shiraz University of Medical Sciences, Shiraz, Iran

Abstract

Background: The most common primary tumors of the brain are gliomas. Despite improvements in treatment strategy, the prognosis for patients with high-grade gliomas has stayed poor, while it is relatively good for low-grade gliomas. The main and gold standard way for grading glial tumor is biopsy. Accurate assessment of tumor grade is vital for the determination of best treatment plan. The purpose of this study was to evaluate the role of diffusion tensor imaging (as a noninvasive method) using relative anisotropy (RA) in glial tumor grading.Methods: A total of 20 histologically confirmed gliomas patients were scanned using a 1.5-Tesla magnetic resonance scanner. We described two regions of interest (ROIs), white matter adjacent to the tumor and the homologous fiber tracts to first ROI in the contralateral hemisphere.Findings: The relative anisotropy values and ratio of the low-grade gliomas tended to be higher than those of the high-grade gliomas in the peritumoral fibers (P = 0.008, for RAt and P = 0.039 for RAt/n).Conclusion: Our findings prove that the relative anisotropy was different between low- and high-grade gliomas, which may be helpful in grading.

Keywords

References

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Journal of Isfahan Medical School
Volume 33, Issue 359 - Serial Number 359
September and October 2016
Pages 1994-1998

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History

  • Receive Date: 20 July 2015
  • Revise Date:
  • Accept Date: 06 April 2022

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