Connectomics meets neuro-oncology: mapping the brain for treatment planning

NIH RePORTER · NIH · R01 · $504,561 · view on reporter.nih.gov ↗

Abstract

 DESCRIPTION (provided by applicant): Surgical resection is one of the mainstay treatments for human gliomas and a growing number of studies have demonstrated the benefits of maximal safe resection for patient survival. The goal of modern treatment planning is to aid the surgeon in determining the optimal resection trajectory and margin that avoids eloquent (language, visual and motor) tracts, maximizing tumor removal while preserving eloquent function. Diffusion imaging provides critical insight into the WM fiber pathways of the brain. Identifying eloquent tracts in the vicinity of a tumor requires fiber tracking through regions affected by edema and mass effect. Current tractography tools frequently fail to reconstruct fiber pathways that have crossing fibers or are edematous, shifted and/or infiltrated by a surrounding tumor, limiting their clinical utility. Furthermore, these tools require manual placement of seed regions to segment tracts, which time consuming, and subject to inter-user and inter-software variability. Finally, there is no comprehensive validation undertaken in the presence of a tumor. This calls for the development of innovative technical solutions, translated to the clinic, that alleviate these issue with current surgical planning tools. In Aim 1, we will develop an edema invariant fiber tractography paradigm that incorporates a multi-compartment model into an anatomically and functionally constrained fiber tracking. The multi-compartment model will consist of a free water compartment that characterizes the edema and a high angular diffusion compartment to characterize underlying fibers. In Aim 2, we will develop an automated tract extraction paradigm, based on structural and functional connectivity information, robust to mass effect and edema. Finally, comprehensive validation will be undertaken in the form of voxel-wise validation of the tractography on a software phantom and replication dataset (Aim 1). The reconstructed fiber tracts (bundles) will be validated by comparing with manual drawings by experts. Additionally, in Aim 3, we propose a further validation of tracts (fiber bundles) using direct electrical stimulatio during awake surgery, task fMRI and comparison of tracts before and after surgery on the same patient, at two different stages of edema. These tracts will then be incorporated into a map of eloquent function comprising of automatically extracted fiber tracts along with tract proximity measures. This map will enable the surgeon to perform a sophisticated pre-surgical analysis when determining the surgical trajectory. These novel techniques will then be combined into a platform independent web-accessible tool, in Aim 4, that can be used by any clinician. The tool will be evaluated against current planning tools by surgeons and radiologists. Due to these methodologically advanced and clinically relevant features, we expect the tool to provide treatment planning capabilities beyond the currently availabl...

Key facts

NIH application ID
9894856
Project number
5R01NS096606-05
Recipient
UNIVERSITY OF PENNSYLVANIA
Principal Investigator
STEVEN BREM
Activity code
R01
Funding institute
NIH
Fiscal year
2020
Award amount
$504,561
Award type
5
Project period
2016-03-01 → 2022-06-30