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Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

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Preoperative prediction of language function by diffusion tensor imaging.

C F Freyschlag¹, J Kerschbaumer², D Pinggera²

¹Department of Neurosurgery, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria. christian.freyschlag@i-med.ac.at.

Brain Informatics

|May 6, 2017

Summary

This summary is machine-generated.

Diffusion tensor imaging (DTI) combined with advanced processing shows promise in predicting functional brain areas near tumors. This may help surgeons estimate the extent of tumor resection during awake surgery.

Keywords:

Awake surgery Diffusion-tensor imaging Eloquent glioma surgery Functional MRI Prediction of function

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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

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Published on: September 12, 2011

Area of Science:

Neurosurgery
Neuroimaging
Brain Function Mapping

Background:

Direct cortical stimulation (DCS) is the gold standard for mapping eloquent brain areas during awake surgery.
Noninvasive methods for functional brain area detection are sought after.
The predictive value of diffusion tensor imaging (DTI) for functional areas in language-eloquent tumors remains unassessed.

Purpose of the Study:

To assess the potential of multimodal magnetic resonance imaging (MRI), specifically DTI and computational cortical parcellation, in predicting functional areas around language-eloquent tumors.
To evaluate the correlation between DTI-derived parameters and the extent of tumor resection and functional outcomes.

Main Methods:

A proof-of-concept study involving awake surgery for a temporodorsal tumor.
Preoperative DTI tractography initiated from the lesion volume, combined with whole-hemisphere tractography.
Elastic image fusion for correcting DTI data distortion.
Postoperative analysis correlating extent of resection and functional outcome with processed imaging data.

Main Results:

Postoperative imaging analysis identified and predicted the superior part of the lesion as functional cortex.
A strong correlation was found between the intraoperative tumor remnant and DTI connectivity parameters of the eloquent tissue.
Multimodal MRI, including complex DTI processing, demonstrated predictive value for functional areas.

Conclusions:

Complex DTI processing combined with multimodal MRI may predict functional brain areas in patients with eloquent brain tumors.
This approach could potentially aid surgeons in estimating the safe extent of tumor resection.
Further validation is needed to establish this technique as a reliable noninvasive alternative to DCS.