gms | German Medical Science

Objective: There is an increasing interest in preoperative diffusion tensor imaging fiber tracking (DTI-FT) to preserve function during operations in motor eloquent brain regions. However, DTI tractography is challenged by inherent presumptions (e.g. fractional anisotropy, angulation, fiber length thresholds, etc.) and the missing ground-truth. Both widely used approaches to these problems (i.e. deterministic and probabilistic DTI) have advantages and disadvantages. In the present study, we suggest a novel and completely neurophysiology-driven approach to DTI-FT of the corticospinal tract (CST) integrating both imaging and neurophysiological information.

Methods: After preoperative navigated transcranial magnetic stimulation (nTMS) of both the healthy and the affected hemisphere, individual DTI-FT was performed from each nTMS stimulation point applying over 500 combinations of DTI parameters followed by a multidimensional mathematical modelling of this empirical data. Finally, optimal DTI parameters were determined by the relationship between DTI-FT (i.e. number of fibers, NoF) and nTMS (i.e. amplitudes of motor-evoked potentials, MEP) results. This neurophysiological DTI-FT was compared to anatomical imaging as well as to deterministic and probabilistic DTI in 14 patients with motor-eloquent lesions.

Results: Automated neurophysiological selection of optimized DTI parameters was possible in all patients. There was a high goodness-of-fit for the mathematical model for both healthy and affected hemisphere (r²=0.7756 ± 0.13 and r²=0.9194 ± 0.07, respectively). Automated parameter selection resulted in a good correlation between DTI-FT and nTMS results for both hemispheres (r=0.4607 ± 0.17 and r=0.6661 ± 0.17, respectively). Both, deterministic and probabilistic DTI showed less consistency to neurophysiology.

Conclusion: The present study evaluates a novel approach to extract objective DTI-FT-parameters completely based on neurophysiological data. The findings suggest that this method may improve specificity and sensitivity of DTI-FT and, thus, overcome disadvantages the current approaches.