Near real-time system for high-resolution computationaltms navigation

Active Project Grant Awarded Last action

Award ID
R01MH128421
Recipient
Awarding agency
Obligated
$7,602,178

Award facts

Assistance listing
93.242 Mental Health Research Grants
Completion date 98% complete
Place of performance
Charlestown, MA 02129, USA

Award details come from USAspending.gov.

Description

Abstract
Transcranial magnetic stimulation (TMS) is a widely used technology for non-invasive modulation of human brain activity. TMS induces electric fields (e-fields) in the intracranial tissue by means of time-varying magnetic fields (electromagnetic induction) that results in the possibility of obtaining suprathreshold stimulation intensities safely and with little discomfort to the subjects. Clinical applications of TMS include major depressive disorder (MDD) and treatment resistant depression (TRD) in which repetitive TMS (rtms) is administered to dorsolateral prefrontal cortex (dlpfc) with well-demonstrated efficacy. Both in clinical and basic neuroscience research applications, IT is important that the stimulation is accurately targeted to the desired region(s). The e-field distribution that is induced by the TMS pulse in the intracranial tissue is the key physical quantity that can be used to delineate which areas are stimulated and which are not. This is especially important for non-motor regions such as the dlpfc because a direct peripheral measure (e.g., electromyographic response) cannot be used to guide the stimulation. To date, computationally estimated e- field distributions have been used in "online" commercial neuronavigation systems to guide the TMS coil positioning, but the currently available systems offer only spherically symmetric head models that cannot properly take into account the individual differences in tissue geometries and may result in substantial targeting and dosing errors. On the other hand, the most accurate computational methods for e-field estimation are too slow to enable near real time operation. Therefore, no technique exists that has the computational efficiency to enable neuronavigation applications while at the same time incorporating high level of anatomical detail and numerical accuracy. To remove this efficiency VS. Accuracy dilemma that is currently posing a critical barrier for development of more quantitative TMS approaches, we propose to use our recently developed boundary element method (BEM) based computational strategy accelerated by the fast multipole method (FMM) that is suitable for both online and offline application scenarios. Our approach starts with developing an automatic segmentation and surface generation pipeline to obtain accurate representations of the tissue conductivity boundaries using individual MRI data. We will subsequently develop and experimental TMS neuronavigation system that utilizes the fast BEM-FMM method. The purpose of this system is to render the e-field distributions on top of the 3D brain anatomy and to guide the operator to position the TMS coil and associated e-field "hot spot" to the desired location. We will interface the computational engine with a commercial TMS navigator to demonstrate translational potential for clinical research and ultimately to therapeutic/clinical applications. Finally, we will validate the computational neuronavigation accuracy with an anthropomorphic head phantom and evaluate our system in healthy volunteers and in volunteer neurosurgical patients that are scheduled for invasive direct cortical mapping that will be used as a gold standard.

Transactions

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Amendment $783,657
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Original award $713,027
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Subawards

Subrecipient Amount Awarded
Neva Electromagnetics LLC NEVA Bioelectromagnetics, INC (NEVA, Yarmouth Port, MA) team will lead the development of fast numerical algorithms for the computational high-resolution… $538,741

Quick answers

Who received award R01MH128421?

R01MH128421 was awarded to The General Hospital Corporation by National Institute of Mental Health (National Institutes of Health) on February 1, 2022.

How much is award R01MH128421 worth?

$7,602,178 has been obligated on R01MH128421.

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