Diffusion tensor MRI of axonal plasticity in the rat hippocampus

Laitinen, Tomi; Sierra, Alejandra; Pitkänen, Asla; Gröhn, Olli

doi:10.1016/j.neuroimage.2010.02.077

Cited by 68 publications

(59 citation statements)

References 37 publications

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“…It was clearly highlighted in our analysis, serving as an excellent positive control for the TBSS approach since conventional ROI analysis together with histological analysis confirmed that axonal sprouting contributed to the FA changes. This was also shown in our previous work (Laitinen et al 2010). The other regions previously described to undergo degeneration after systemic kainic acid includes the entorhinal cortex, endopiriform cortex and thalamus (Schwob et al 1980;Hopkins et al 2000).…”

Section: Discussionsupporting

confidence: 84%

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Diffusion tensor MRI with tract-based spatial statistics and histology reveals undiscovered lesioned areas in kainate model of epilepsy in rat

et al. 2011

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In this study, we used tract-based spatial statistics (TBSS) to analyze diffusion tensor MR imaging (DTI) data acquired from the rat brain, ex vivo, for the first time. The aim was to highlight potential changes in the whole brain anatomy in the kainic acid model of epilepsy, and further characterize the changes with histology. Increased FA was observed in dorsal endopiriform nucleus, external capsule, corpus callosum, dentate gyrus, thalamus, and optic tract. A decrease in FA was seen in the horizontal limb of the diagonal band, stria medullaris, habenula, entorhinal cortex, and superior colliculus. Some of the areas have been described in kainic acid model before. However, we also found regions that to our knowledge have not been previously reported to undergo structural changes, in this model, including stria medullaris, nucleus of diagonal band, habenula, superior colliculus, external capsule, corpus callosum, and optic tract. Four of the areas highlighted in TBSS (dentate gyrus, entorhinal cortex, thalamus and stria medullaris) were analyzed in more detail with Nissl, Timm, and myelin-stained histological sections, and with polarized light microscopy. TBSS together with targeted histology confirmed that DTI changes were associated with altered myelination, neurodegeneration, and/or calcification of the tissue. Our data demonstrate that DTI in combination with TBSS has a great potential to facilitate the discovery of previously undetected anatomical changes in animal models of brain diseases.

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Section: Discussionsupporting

confidence: 84%

“…We previously reported this increase in FA together with a detailed histological analysis in kainate-and pilocarpinetreated rats (Laitinen et al 2010). Briefly, increased FA correlated with an increase in the density of myelinated fibers in the outer molecular layer of the dentate gyrus (black arrows in Fig.…”

Section: Histologymentioning

confidence: 77%

Diffusion tensor MRI with tract-based spatial statistics and histology reveals undiscovered lesioned areas in kainate model of epilepsy in rat

et al. 2011

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“…The parameters derived from the diffusion tensor [18], especially the mean diffusivity (MD) and fractional anisotropy (FA), have proved to be useful in the diagnosis and characterization of several human cerebral diseases, such as amyotrophic lateral sclerosis [19], epilepsy [20], ischemic lesions [21] and brain tumors [22,23]. DTI has found also wide application in preclinical research on animal models of neurological pathologies, many of which are developed on rats (for example [24][25][26][27][28]). …”

Section: Introductionmentioning

confidence: 99%

In vivo DTI tractography of the rat brain: an atlas of the main tracts in Paxinos space with histological comparison

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Aquino

Pennacchio

et al. 2015

Magnetic Resonance Imaging

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“…ADC increases may be related to vasogenic edema or increased metabolic activity [17,39,43,44], whereas the acute ADC decreases are associated with cytotoxic edema and neuronal loss [39,43,44]. Structural dependent changes in FA have also been identified at chronic epileptic stages after SE [45,46]. Although chronic FA changes that occur after the manifestation of spontaneous seizures hold little value as an early biomarker for epileptogenesis, FA may be an effective biomarker if validated at earlier stages.…”

Section: Diffusion-weighted Mrimentioning

confidence: 99%

Neuroimaging the Epileptogenic Process

et al. 2014

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Epilepsy is one of the most common chronic neurological conditions worldwide. Anti-epileptic drugs (AEDs) can suppress seizures, but do not affect the underlying epileptic state, and many epilepsy patients are unable to attain seizure control with AEDs. To cure or prevent epilepsy, disease-modifying interventions that inhibit or reverse the disease process of epileptogenesis must be developed. A major limitation in the development and implementation of such an intervention is the current poor understanding, and the lack of reliable biomarkers, of the epileptogenic process. Neuroimaging represents a non-invasive medical and research tool with the ability to identify early pathophysiological changes involved in epileptogenesis, monitor disease progression, and assess the effectiveness of possible therapies. Here we will provide an overview of studies conducted in animal models and in patients with epilepsy that have utilized various neuroimaging modalities to investigate epileptogenesis.

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Diffusion tensor MRI of axonal plasticity in the rat hippocampus

Cited by 68 publications

References 37 publications

Diffusion tensor MRI with tract-based spatial statistics and histology reveals undiscovered lesioned areas in kainate model of epilepsy in rat

Diffusion tensor MRI with tract-based spatial statistics and histology reveals undiscovered lesioned areas in kainate model of epilepsy in rat

In vivo DTI tractography of the rat brain: an atlas of the main tracts in Paxinos space with histological comparison

Neuroimaging the Epileptogenic Process

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