No abstract

This study compared tractography approaches for identifying cerebellar-thalamic fiber bundles relevant to planning target sites for deep brain stimulation (DBS). In particular, probabilistic and deterministic tracking of the dentate-rubro-thalamic tract (DRTT) and differences between the spatial courses of the DRTT and the cerebello-thalamo-cortical (CTC) tract were compared. Six patients with movement disorders were examined by magnetic resonance imaging (MRI), including two sets of diffusion-weighted images (12 and 64 directions). Probabilistic and deterministic tractography was applied on each diffusion-weighted dataset to delineate the DRTT. Results were compared with regard to their sensitivity in revealing the DRTT and additional fiber tracts and processing time. Two sets of regions-of-interests (ROIs) guided deterministic tractography of the DRTT or the CTC, respectively. Tract distances to an atlas-based reference target were compared. Probabilistic fiber tracking with 64 orientations detected the DRTT in all twelve hemispheres. Deterministic tracking detected the DRTT in nine (12 directions) and in only two (64 directions) hemispheres. Probabilistic tracking was more sensitive in detecting additional fibers (e.g. ansa lenticularis and medial forebrain bundle) than deterministic tracking. Probabilistic tracking lasted substantially longer than deterministic. Deterministic tracking was more sensitive in detecting the CTC than the DRTT. CTC tracts were located adjacent but consistently more posterior to DRTT tracts. These results suggest that probabilistic tracking is more sensitive and robust in detecting the DRTT but harder to implement than deterministic approaches. Although sensitivity of deterministic tracking is higher for the CTC than the DRTT, targets for DBS based on these tracts likely differ.

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Monitoring of local oxygen pressure in brain white matter (tip(O2)) and of local hemoglobin oxygen saturation (rS(O2)) with near-infrared spectroscopy (NIRS) are increasingly employed techniques in neurosurgical intensive care units. Using frequency-based mathematical methods, the authors sought to ascertain whether both techniques contained similar information. Twelve patients treated in the intensive care unit were included (subarachnoid hemorrhage, n = 3; traumatic brain injury, n = 9). A tip(O2) probe and an NIRS sensor were positioned over the frontal lobe with the most pathologic changes on initial computed tomography scan. The authors calculated coherence of tip(O2) and rS(O2) ts overall density distribution, its distribution per data set, and its time evolution. The authors identified a band of significantly correlated frequencies (from 0 to 1.3 x 10(3) Hz) in more than 90% of the data sets for coherence and overall density distribution. Time evolution showed slow but marked changes of significant coherence. By means of spectral analysis the authors show that tip(O2) and rS(O2)signals contain similar information, albeit using completely different registration methodologies.

In recent literature there are some reports describing cerebral blood flow measurements by a near infrared spectroscopy-based technique with indocyanine-green as an absorbant. To our knowledge there is no systematical study which evaluates this technique in comparison to absolute cerebral blood flow measurements. Ten patients suffering from head injury (n = 9) or subarachnoid hemorrhage (n = 1) were included. Twenty measurements of cerebral blood flow were performed, employing a Xenon133 clearance technique. Near-infrared spectroscopy measurements were performed with the Somanetics 4100 System. Indocyanine-green was given at a total dose of 0.2 mg kg-1 bodyweight intravenously. The indocyanine-green curve was compared to cerebral blood flow measurements according to rising time and area under the curve as suggested in the literature. No correlation between the indocyanine-green clearance curve and the Xenon133 cerebral blood flow measurements could be found. Neither the area under the curve (p = 0.93) nor the rising time (p = 0.75) showed a statistically significant correlation. The near-infrared spectroscopy based indocyanine-green clearance curve measurement method of cerebral blood flow seems not to give reliable results using simple mathematical models (area under the curve and rising time). In view of our findings, we have serious reservations in the potential of this technique.