Manganese-enhanced magnetic resonance imaging detects mossy fiber sprouting in the pilocarpine model of epilepsy

Purpose: Mossy fiber sprouting (MFS) is a frequent finding following status epilepticus (SE). The present study aimed to test the feasibility of using manganese-enhanced magnetic resonance imaging (MEMRI) to detect MFS in the chronic phase of the well-established pilocarpine (Pilo) rat model of temporal lobe epilepsy (TLE). Methods: To modulate MFS, cycloheximide (CHX), a protein synthesis inhibitor, was coadministered with Pilo in a subgroup of animals. In vivo MEMRI was performed 3 months after induction of SE and compared to the neo-Timm histologic labeling of zinc mossy fiber terminals in the dentate gyrus (DG). Key Findings: Chronically epileptic rats displaying MFS as detected by neo-Timm histology had a hyperintense MEMRI signal in the DG, whereas chronically epileptic animals that did not display MFS had minimal MEMRI signal enhancement compared to nonepileptic control animals. A strong correlation (r = 0.81, p < 0.001) was found between MEMRI signal enhancement and MFS. Significance: This study shows that MEMRI is an attractive noninvasive method for detection of mossy fiber sprouting in vivo and can be used as an evaluation tool in testing therapeutic approaches to manage chronic epilepsy.

Seeking tools for image fusion between computed tomography, structural and functional magnetic resonance methods for applications in neurosurgery

OBJECTIVE: To evaluate tools for the fusion of images generated by tomography and structural and functional magnetic resonance imaging. METHODS: Magnetic resonance and functional magnetic resonance imaging were performed while a volunteer who had previously undergone cranial tomography performed motor and somatosensory tasks in a 3-Tesla scanner. Image data were analyzed with different programs, and the results were compared. RESULTS: We constructed a flow chart of computational processes that allowed measurement of the spatial congruence between the methods. There was no single computational tool that contained the entire set of functions necessary to achieve the goal. CONCLUSION: The fusion of the images from the three methods proved to be feasible with the use of four free-access software programs (OsiriX, Register, MRIcro and FSL). Our results may serve as a basis for building software that will be useful as a virtual tool prior to neurosurgery.

Computerized brain tumor segmentation in magnetic resonance imaging

OBJECTIVE: To propose an automatic brain tumor segmentation system. METHODS: The system used texture characteristics as its main source of information for segmentation. RESULTS: The mean correct match was 94% of correspondence between the segmented areas and ground truth. CONCLUSION: Final results showed that the proposed system was able to find and delimit tumor areas without requiring any user interaction.