OBJECT: The aim of this paper was to validate the diffusion tensor imaging (DTI) model for delineation of the corticospinal tract using cortical and subcortical white matter electrical stimulation for the location of functional motor pathways. METHODS: The authors compare probabilistic versus deterministic DTI fiber tracking by reconstructing the pyramidal fiber tracts on preoperatively acquired DTI in patients with brain tumors. They determined the accuracy and precision of these 2 methods using subcortical stimulation points and the sensitivity using cortical stimulation points. The authors further explored the reliability of these methods by estimation of the potential that the found connections were due to a random chance using a novel neighborhood permutation method. RESULTS: The probabilistic tracking method delineated tracts that were significantly closer to the stimulation points and was more sensitive than deterministic DTI fiber tracking to define the tracts directed to the motor sites. However, both techniques demonstrated poor sensitivity to finding lateral motor regions. CONCLUSIONS: This study highlights the importance of the validation and quantification of preoperative fiber tracking with the aid of electrophysiological data during the surgery. The poor sensitivity of DTI to delineate lateral motor pathways reported herein suggests that DTI fiber tracking must be used with caution and only as adjunctive data to established methods for motor mapping.
OBJECT: The aim of this paper was to validate the diffusion tensor imaging (DTI) model for delineation of the corticospinal tract using cortical and subcortical white matter electrical stimulation for the location of functional motor pathways. METHODS: The authors compare probabilistic versus deterministic DTI fiber tracking by reconstructing the pyramidal fiber tracts on preoperatively acquired DTI in patients with brain tumors. They determined the accuracy and precision of these 2 methods using subcortical stimulation points and the sensitivity using cortical stimulation points. The authors further explored the reliability of these methods by estimation of the potential that the found connections were due to a random chance using a novel neighborhood permutation method. RESULTS: The probabilistic tracking method delineated tracts that were significantly closer to the stimulation points and was more sensitive than deterministic DTI fiber tracking to define the tracts directed to the motor sites. However, both techniques demonstrated poor sensitivity to finding lateral motor regions. CONCLUSIONS: This study highlights the importance of the validation and quantification of preoperative fiber tracking with the aid of electrophysiological data during the surgery. The poor sensitivity of DTI to delineate lateral motor pathways reported herein suggests that DTI fiber tracking must be used with caution and only as adjunctive data to established methods for motor mapping.
Entities:
Keywords:
ANNull = architectural neighborhood null; DTI = diffusion tensor imaging; FA = fractional anisotropy; FSE = fast spin echo; IES = intraoperative electrical stimulation; PDF = probability density function; ROI = region of interest; SNR = signal-to-noise ratio; SPGR = spoiled gradient recalled; brain tumor; corticospinal tract; dMRI = diffusion MRI; diffusion tensor imaging; intraoperative stimulation; oncology; tractography
Authors: J Puig; G Blasco; M Terceño; P Daunis-I-Estadella; G Schlaug; M Hernandez-Perez; V Cuba; G Carbó; J Serena; M Essig; C R Figley; K Nael; C Leiva-Salinas; S Pedraza; Y Silva Journal: AJNR Am J Neuroradiol Date: 2019-04-18 Impact factor: 3.825
Authors: Carolin Weiss; Irada Tursunova; Volker Neuschmelting; Hannah Lockau; Charlotte Nettekoven; Ana-Maria Oros-Peusquens; Gabriele Stoffels; Anne K Rehme; Andrea Maria Faymonville; N Jon Shah; Karl Josef Langen; Roland Goldbrunner; Christian Grefkes Journal: Neuroimage Clin Date: 2015-01-20 Impact factor: 4.881