A promising method of enhancement for early detection of ischemic stroke

Computed Tomography (CT) scan without contrast is the modality of choice for diagnosis of stroke. However, routine brain CT scan, with linear processing has some limitations in early diagnosis of ischemic stroke. The aim of this study was to evaluate and compare the sensitivity and specificity of processed CT images with conventional ones in early diagnosis of cerebrovascular attack (CVA). This was a self-controlled study conducted in a university referal hospital from 2010 to 2011. Seventy CT scans underwent a process using Laplacian Pyramid transform. Thirty five of participants were diagnosed with CVA while others had only headache and no ischemic stroke diagnosis based on the first and follow-up CT scans. A neuroradiologist made diagnosis with and without the help of processed CT scans. The McNemar and Wilcoxon analysis were used to compare the sensitivity, specificity, positive and negative predictive values of two methods. The sensitivity (% 65.7 vs. %31.4, P value = 0.001), positive predictive value (% 85.2 vs. % 61, P value = 0.03) and negative predictive value (% 73.9% vs. %49, P value = 0.01) of the processed method were significantly higher than the routine one, while no difference was seen in specificity (% 88.6 vs. %77.1, P value = 0.15). Moreover, the accuracy of the processed method was significantly better than the linear one (P value < 0.001). It was concluded that nonlinear modified Laplacian Pyramid method can composed CT scans which can be more helpful in early detection of ischemic stroke.