Evaluating the Possibility of Defining Cut-Off Points for Δfa% in Order to Differentiate Four Major Types of Peri-Tumoral White Matter Tract Involvement Publisher



Deilami T¹ ; Kharrazi HH¹ ; Seddighi AS² ; Tanzifi P³ ; Tayebivaljouzi R⁴ ; Zamani F¹ ; Tafti AC⁵
Source: Iranian Journal of Radiology Published:2015

Abstract

Background: Diffusion tensor imaging (DTI) and its different scalar values such as fractional anisotropy (FA) have recently been used for evaluation of peri-tumoral white matter (WM) involvement to help define safer surgical excision margins. Objectives: The purpose of this study is to evaluate the possibility of defining diagnostic cut-off points for differentiating four major types of peri-tumoral WM involvement using FA. Patients and Methods: DTI was performed in 12 patients with high presumption of having brain tumors, on a 1.5 T MRI scanner. DTI data was processed by MedINRIA software. Two-hundred region of interests (ROI) were evaluated: 100 in the lesion zone and the rest in the normal WM in the contralateral hemisphere. FA value related to each ROI was measured, and the percentage of FA decrement (ΔFAs%) was calculated. Results: Of the 100 ROIs on the lesion side, 74 were related to high-grade lesions, 23 to low-grade ones, and three to “gliosis”. There were 54 “infiltrated”, 22 “displaced”, 15 “disrupted”, and 9 “edematous” tracts. The major type of fiber involvement, both in low-grade and high-grade tumors was “infiltrated, whereas “edematous” fibers comprised the minority. ΔFA% was more than-35 for “displaced” and “edematous” fibers, and less than-35 for the majority of “disrupted” ones, but “infiltrated” fibers had scattered distribution. Mean ΔFA% was the least for “disrupted”, followed by “infiltrated”, “edematous” and “displaced” parts. Conclusion: Introducing definite diagnostic cut-points was not possible, due to overlap. Based on the fact that “disruption” is the most aggressive process, a sensitivity analysis was carried out for “disrupted” fibers for several presumptive cut-off points. © 2015, Tehran University of Medical Sciences and Iranian Society of Radiology.