Relative fractional anisotropy value using DTI: Can it help as a prognostic tool in anticipating the recovery of stroke patients?

Abdeldayem, Emad H.; Ahmed Osman; Roushdy, Tamer M.;

Abstract


Objective: To evaluate the use of diffusion tensor imaging (DTI) and fractional anisotropy (FA) as prognostic tools in anticipating the recovery of stroke patients. Patients and methods: 40 patients were included in our study after exclusion of 23 patients. All patients admitted in Neurology Department with stroke. The patients subjected to National Institute of Health Stroke Scale (NIHSS) followed by MRI with DTI and FA calculation. Follow up after three months was done based on the Modified Rankin Score (MRS). The results were compared and statistically analyzed. Results: There was a statistical significant between the NIHSS and DTI pattern at the time of admission (p value < 0.05) reflecting the severity of the stroke with 22 patients showed disrupted fibers (55%), of which 16 patients were categorized as moderate NIHSS and 19 patients showed poor outcome. Relative FA equal 0.8 was found to be the cut off value in predicting the poor or good prognosis using MRS as a reference with 94.4% sensitivity, 90.9% specificity and 0.833 area under curve. Conclusion: DTI is a prognostic tool in anticipating the recovery of the stroke patients. Moreover, the relative FA score works as more additive value in evaluation of the patient improvement.


Other data

Title Relative fractional anisotropy value using DTI: Can it help as a prognostic tool in anticipating the recovery of stroke patients?
Authors Abdeldayem, Emad H. ; Ahmed Osman ; Roushdy, Tamer M.
Keywords Diffusion tensor imaging (DTI);Fractional anisotropy (FA);Modified Rankin Score (MRS);National Institute of Health Stroke Scale (NIHSS);Region of interest (ROI)
Issue Date 1-Dec-2017
Publisher ELSEVIER SCIENCE BV
Journal Egyptian Journal of Radiology and Nuclear Medicine 
Volume 48
Issue 4
Start page 1019
End page 1025
ISSN 0378603X
DOI 10.1016/j.ejrnm.2017.04.007
Scopus ID 2-s2.0-85037627189
Web of science ID WOS:000425307700036

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