Objective: MR-perfusion post-processing still lacks standardization. This study evaluates the results of perfusion analysis with two established software solutions in a large series of patients with different diseases when a highly standardized processing workflow is ensured.

Methods: Multicenter data of 260 patients (80 with brain tumors, 124 with cerebrovascular disease and 56 with dementia examined with the same MR protocol) were analyzed. Raw data sets were processed with two software suites: Olea sphere and NordicICE. Group differences were analyzed with paired -tests and one-way ANOVA.

Results: Perfusion metrics were significantly different for all examined diseases in the unaffected brain for both software suites [ratio cortex/white matter left hemisphere: mean transit time (MTT) 0.991 0.847, < 0.05; relative cerebral bloodflow (rBF) 3.23 4.418, < 0.001; relative cerebral bloodvolume (rBVc) 2.813 3.884, < 0.001; right hemisphere: MTT 1.079 0.854, < 0.05; rBF 3.262 4.378, < 0.001; rBVc 2.762 3.935, < 0.001)]. Perfusion results were also significantly different in patients with stroke (ratio cortex/white matter affected hemisphere: MTT 1.058 0.784; < 0.001), dementia (ratio cortex/white matter left hemisphere: rBVc 1.152 1.795, < 0.001; right hemisphere: rBVc 1.396 1.662, < 0.05) and brain tumors (ratio cortex/whole tumor rBVc: 0.778 0.919, < 0.001 and ratio cortex/tumor hotspot rBVc: 0.529 0.512, < 0.05).

Conclusion: Despite a highly standardized workflow, parametric perfusion maps are depended on the chosen software. Radiologists should consider software related variances when using dynamic susceptibility contrast perfusion for clinical imaging and research.

Advances In Knowledge: This multicenter study compared perfusion parameters calculated by two commercial dynamic susceptibility contrast perfusion post-processing software solutions in different central nervous system disorders with a large sample size and a highly standardized processing workflow. Despite, parametric perfusion maps are depended on the chosen software which impacts clinical imaging and research.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6948086PMC
http://dx.doi.org/10.1259/bjr.20190543DOI Listing

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