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See detailDTI of the visual pathway - white matter tracts and cerebral lesions.
Hana, Ardian; Husch, Andreas UL; Gunness, Vimal Raj Nitish et al

in Journal of Visualized Experiments (2014), (90),

DTI is a technique that identifies white matter tracts (WMT) non-invasively in healthy and non-healthy patients using diffusion measurements. Similar to visual pathways (VP), WMT are not visible with ... [more ▼]

DTI is a technique that identifies white matter tracts (WMT) non-invasively in healthy and non-healthy patients using diffusion measurements. Similar to visual pathways (VP), WMT are not visible with classical MRI or intra-operatively with microscope. DIT will help neurosurgeons to prevent destruction of the VP while removing lesions adjacent to this WMT. We have performed DTI on fifty patients before and after surgery between March 2012 to January 2014. To navigate we used a 3DT1-weighted sequence. Additionally, we performed a T2-weighted and DTI-sequences. The parameters used were, FOV: 200 x 200 mm, slice thickness: 2 mm, and acquisition matrix: 96 x 96 yielding nearly isotropic voxels of 2 x 2 x 2 mm. Axial MRI was carried out using a 32 gradient direction and one b0-image. We used Echo-Planar-Imaging (EPI) and ASSET parallel imaging with an acceleration factor of 2 and b-value of 800 s/mm(2). The scanning time was less than 9 min. The DTI-data obtained were processed using a FDA approved surgical navigation system program which uses a straightforward fiber-tracking approach known as fiber assignment by continuous tracking (FACT). This is based on the propagation of lines between regions of interest (ROI) which is defined by a physician. A maximum angle of 50, FA start value of 0.10 and ADC stop value of 0.20 mm(2)/s were the parameters used for tractography. There are some limitations to this technique. The limited acquisition time frame enforces trade-offs in the image quality. Another important point not to be neglected is the brain shift during surgery. As for the latter intra-operative MRI might be helpful. Furthermore the risk of false positive or false negative tracts needs to be taken into account which might compromise the final results. [less ▲]

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See detailAn Extensible Development Environment for 3D Segmentations based on Active Shape Models
Bernard, Florian UL; Gemmar, Peter; Husch, Andreas UL et al

in Shape Symposium (2014)

Detailed reference viewed: 56 (6 UL)
See detailData Integration for Image Guided Deep Brain Stimulation
Husch, Andreas UL

Doctoral thesis (n.d.)

Detailed reference viewed: 182 (32 UL)