Background: The use of magnetic resonance (MR) tractography in neurosurgery is becoming an increasingly common practice for noninvasive imaging of white matter pathways. The most common method of tract reconstruction is the deterministic algorithm of diffusion tensor magnetic resonance imaging (MRI). However, this method of reconstructing pathways has a number of significant limitations. The most important of them are the lack of the possibility of visualizing the intersecting fibers, the complexity of building tracts in the area of perifocal edema and in the immediate vicinity of the tumor borders. The method of MR tractography, based on obtaining a diffusion image with a high angular resolution (High Angular Resolution Diffusion Imaging, HARDI), using the constrained spherical deconvolution (CSD) algorithm for post-processing of data, makes it possible to avoid these disadvantages. Relatively recently, a new algorithm, Single-Shell 3-Tissue CSD (SS3TCSD), has been proposed for processing HARDI data, which has the potential to improve the reconstructing of pathways in the area of perifocal edema or edema-infiltration.Aim: To evaluate the potential of the new SS3TCSD algorithm compared to ST-CSD (Single-Tissue CSD) in the imaging of the optic radiation and visual tracts in patients with gliomas.Materials and methods: Diffusion and routine brain MRI was performed in 10 patients with newly diagnosed cerebral gliomas, followed by reconstruction of the optic radiation and visual tracts. We compared new algorithms for postprocessing MR tractography (ST-CSD and SS3TCSD) in imaging of the optic tract and visual radiation in patients with brain gliomas affecting various parts of the visual system.Results: The SS3T-CSD method showed a lower mean percentage of false positive tracts compared to the ST-CSD method: 19.75% for the SS3T-CSD method and 80.32% for the ST-CSD method in cases of proximity of the tumor to the tracts, 5.27% for the SS3T-CSD method and 25.27% for the STCSD method in cases of reconstructing tracts in healthy white matter.Conclusion: The SS3T-CSD method has a number of advantages over ST-CSD and allows for successful imaging of the optic pathways that have a complex structure and repeatedly change direction along their course.
Aim:discover quantitative and qualitative variance of diffusion parameters in white and gray matter of healthyvolunteers brain. Discover correlation between diffusion and kurtosis parameters, find out if there is correlation between the parameters and aging microstructural changes.Materials and methods.14 healthy volunteers were investigated (9 men, 5 women; age from 21 to 55 years, mean 34). The volunteers were classified into two groups by age: 7 subjects who younger 35 (6 men and 1 woman, mean age 25) and 7 subjects who older 35 years (3 men and 4 women, mean age 44). We used 3.0 Tesla MRI (3.0T SignaHDxt, General Electric, USA) with 8 channel head coil, gradient strength 50 mT/m, slew rate 150 T/m/s. Diffusion imaging was based on echo planar “spin echo” sequence (SE EPI), TR = 10000 ms, TEmin = 102 ms, FOV = 240 mm, voxel size 3 × 3 × 3 mm3, 60 non-coplanar diffusion directions and three b-values: 0, 1000, 2500 s/mm2. Acquisition time of diffusion kurtosis imaging was 22 minutes. We excluded extracerebral areas on diffusion and kurtosis parametric maps using semi-automatic approach. After that, brain images were transformed to MNI152 space using affine method. Masks of 9 anatomical structures were applied to the transformed images. Diffusion and kurtosis values were measured in these structures.Results.Fractional anisotropy (FA) changed from 0.06 in lateral occipital cortex to 0.25 in cerebral white matter, kurtosis anisotropy (KA) changed from 0.03 to 0.14 in the same cerebral structures. Axial (AK), radial (RK) and mean kurtosis (MK) were minimal in superior frontal gyrus and maximal in cerebral white matter. AK changed from 0.55 to 0.72, RK changed from 0.62 to 1.05, MK from 0.59 to 0.88. Axial(AxEAD) and radial extra axonal water diffusion (RadEAD) were minimal in putamen and maximal in superior frontal gyrus. AxEAD was changing from 1.38 • 10–3 to 2.57 • 10–3, RadEAD from 1.03 • 10–3 to 2.34 • 10–3. Axonal water fraction (AWF) had minimal value 0,18 in superior frontal gyrus and maximal value 0.29 in cerebral white matter. Tortuosity (TORT) changed from 1.06 in lateral occipital cortex to 1.43 in cerebral white matter. There was significant difference between age groups in AWF, RK, RadEAD in putamen and in KA in superior temporal gyrus. Maximal correlation with age was in MK in superior temporal gyrus, anterior division. It was equal to 0.562.Conclusions:Diffusion kurtosis imaging is highly sensitive method of brain tissue microstructure assessment, which detects age-related changes.
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