Automatisierte quantitative MRT-Analyse zur Bestimmung der epileptogenen Läsion bei Patienten mit fokalen Epilepsien

Im Rahmen der vorliegenden Studie sollte eine Methode zur automatisierten Detektion epileptogener Läsionen bei Patienten mit fokaler Epilepsie bei bekannter FCD untersucht werden. Es wurden hierzu von allen Patienten hochauflösende 3T Schädel MRT T1 Volumendatensätze erhoben und mit Hilfe der spe...

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Bibliographische Detailangaben
1. Verfasser: Wehrmann, Enno
Beteiligte: Knake, Susanne (Prof. Dr.) (BetreuerIn (Doktorarbeit))
Format: Dissertation
Sprache:Deutsch
Veröffentlicht: Philipps-Universität Marburg 2014
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This study was designed to test a new method for automatic detection of epileptogenic lesions in patients with focal epilepsy and known FCD. For this all patients underwent high resolution 3T NMR of the brain. The NMR data was processed with the purpose-built software FreeSurfer. The processing pipeline included motion correction and normalization, the reconstruction by a VBM algorithm and the analysis and labeling of cortical and subcortical regions. A control group of 50 healthy adults was made up especially for this study. All members of the control group underwent the same imaging process on the identical 3T NMR scanner and the data was processed as described above. To guarantee a good comparability the control group was well-balanced regarding age, gender and education. Only right handed people were included in the study as patients as well as in the control group. The objective was to automatically detect focal cortical dysplasias who represent epileptogenic lesions by comparing the cortical thickness of one patient to a gender matches control group claiming that the thickness of the patient’s cortex is significantly increased. In addition to that blurring of the grey white boundary as indication for an epileptogenic lesion should automatically be detected. Statistical analysis was calculated with qdec and showed that only 60% of the patients had significantly increased cortical thickness within the assumed area of the epileptogenic lesion. In 50% of the patients significantly increased cortical thickness was detected that could not be related to the patients clinical symptoms (false positive). Blurring of the grey white boundary in the area of the assumed epileptogenic lesion could only be found in 60% of the patients. Only in the subgroup of patients with frontal lobe epilepsy the FCD was detected in 100% of the patients. A subgroup analysis regarding location or side of the lesion or having underwent an intracranial operation before did not show significant results. Anyway the group of patients was small and there for these subgroups have almost no statistical power. The main reason for the small number of detected lesions and the big number of false positive detections seems to be the reconstruction algorithm. All patients included in this 59 study have a FDC. In Type I FCDs only the cortex is affected by a disordered layering so even in high resolution NMR imaging often no correlate can be found. In addition type II FCDs include altered cell architecture such as dysmorphic neurons or balloon-cells (Blümcke, et al., 2012) which leads to a blurred grey white boundary. So they leave a trace within the white matter which can be detected by T1 NMR imaging (Colombo, Salamon, Raybaud, Ozkara, & Barkovich, 2009). For this study a volume based VBM algorithm was used that originally was designed to identify subcortical patterns. Cortical variations and those who are close to the cortex are frequently only detected if they leave a hint within the white matter. So in order to detect cortical lesions as tried in this study it might be better to use a surface based VBM algorithm for reconstruction (Thesen, et al., 2011). In addition the small group of patients decreases the power of the conclusions that can be made from this study. But negative impact on the results due to an unsuitable control group can be excluded.