gms | German Medical Science

Objective: Data analysis and medical imaging are two essential requirements for diagnosis and treatment of neurologic diseases. Despite sustained progresses in the last decade, analysis of in vitro acquired data still remains challenging, especially in molecular imaging using positron emission tomography (PET). The present interdisciplinary study describes and tests a semi-automated data analysis tool, which should be able to analyze imaging data independently from the administrated radiotracer or imaging modality. As proof of principle, we evaluated the cerebral glucose metabolism by PET with [¹⁸F]flourodeoxyglucose (¹⁸FDG-PET) in a subarachnoid hemorrhage (SAH) rat model.

Methods: The uptake of [18F]fluordeoxyglucose was evaluated in different brain regions in 18 male Sprague-Dawley rats (weighing 250-300g) which were randomly assigned into one of two groups: (1) SAH induced by the endovascular filament model and (2) sham operated controls. Serial ¹⁸FDG-PETs were performed 3 hours following SAH/sham, as well as on day 1, day 4 and day 7 after SAH/sham operation. Data analysis was performed by uptake ratio using a self-developed data analysis tool, implemented in Matlab.

Results: In data analysis, multiple significant differences between sham and SAH experimental groups were determined in various brain regions using uptake ratio (UR), which could not be observed when analyzing the data using the standardized uptake value (SUV). The SAH group showed a significant higher tracer accumulation in the grey matter compared to the sham group (day 0 p<0.001, day 1 p<0.01, day 4 p<0.05, day 7 p<0.01), while the white matter region showed a significant reduced tracer accumulation in SAH animals (day 0 p<0.001, day 1 p<0.01, day 4 p<0.05). Significant URs in the neocortex could also be shown, but haven’t been as significant as the differences in the basal forebrain region or the olfactory system region.

Conclusion: Our interdisciplinary study on glucose metabolism in an experimental rat SAH-model could provide important insights into brain metabolism changes following SAH via ¹⁸FDG-PET in separation of different brain regions. Using a self-developed analysis instrument it could be shown that the extended evaluation methods allow a more flexible data evaluation, especially with regard to the preclinical evaluation of novel (PET) tracers.