Objectives: Diffuse axonal injury is one of the major causes of unconsciousness, profound neurologic deficits and persistent vegetative state after head trauma. In recent years, MR imaging has been gaining popularity as an adjunctive imaging method in patients with DAI. Our study aims to assess the relative diagnostic and prognostic capability of various MRI sequences.

Patients And Methods: Retrospective observational study done in 1 year duration on 30 DAI patients. Clinical assessment done with GCS at admission and GOS at 6 month. MRI Brain FLAIR, DWI, T2*GRE AND SWI sequences taken. DAI grade were evaluated for different MRI sequences. Prognosis was correlated to total number of lesion/locations and DAI grade of patients. Statistical analysis was done using SPSS Statistical software (ver.20.0.0) and XL-Stat and ANOVA one way test, test (Turkey test) and Chi square test.

Result: We studied 30 male patients, mean age 32.57±8.72 ranges. The commonest mode of injury is RTA-80%, fall-16% followed by assault-3.33%. Out of 30 patients, 17 patients (56.67%) had GCS <=8, 13 patients (43.33%) had GCS between 9 and 12 and no patient had a GCS score between 13 and 15. The mean GCS score was 8.47±1.50. At a 6 month follow up, out of a total of 30 patients, 2 patients (6.66%) expired (GOS-1), 3 patients (10%) remained in persistent vegetative state (GOS-2), 11 patients (36.67%) and 10 patients (33.33%) were found to be severely (GOS-3) and moderately (GOS-4) disabled respectively and 4 patients (13.33%) showed good recovery (GOS-5). Mean GOS is 3.37+/-1.06. Newer imaging -SWI able to detects lesion better (diagnosis of DAI) as compared to other older sequences like FLAIR,DWI,T2*GRE. But no statistically significant found between total number of lesion/locations to the outcome and also newer imaging do not change the grade of DAI patients.

Conclusion: Although advanced imaging in head injury, SWI helps in diagnosing the diffuse axonal injury more efficiently than other imaging sequences, but it is the grade of patients at admission that predicts the outcome best.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898104PMC
http://dx.doi.org/10.4103/ajns.AJNS_229_16DOI Listing

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