Comparison of Different Post-Processing Algorithms for Dynamic Susceptibility Contrast Perfusion Imaging of Multiple Sclerosis Lesions: A Time to Peak Analysis

Objective: The purpose of the present study was to evaluate, in multiple sclerosis (MS) lesions, the diagnostic performance of two different commercial post-processing MR perfusion software. These two different algorithms for processing Dynamic susceptibility contrast (DSC) perfusion images have been used to differentiate perfusion values among white matter (WM) lesions, normal appearing white matter (NAWM), and grey matter (GM) in MS. The diagnostic performance for diff erentiating among lesions and normal tissue has been measured with respect to the Time to Peak (TTP). Methods and analysis: Analysing DSC perfusion imaging, a retrospective study has been performed on 74 MS patients and 15 normal subjects, by using 1.5 Tesla MRI scanner. TTP maps were generated by using 2 different commercially available algorithms (A;B). Analysis was conducted for the evaluation of diagnostic performance of different algorithms for differentiating between lesions and normal appearing WM and GM. Results: A statistically significant difference between the two algorithms was demonstrated by comparing TTP values among recent, stable lesions and NAWM. TTP values have been used to discriminate among recent, stable lesions and NAWM by using two different software packages. Conclusion: The optimal software should be that which increases the temporal resolution and be not operator dependent. TTP has been able to 1) examine the variability in the quantitative results of DSC MR perfusion imaging generated from identical source data of MS patients, 2) to identify the variables between two commercial post-processing algorithm and 3) to focus on the crucial role of post-processing inter-vendor differences.