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Diffusion MRI Methods to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery

Primary Purpose

Focal Epilepsy

Status
Recruiting
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
Brain magnetic resonance imaging
Neuro-psychology testing
Sponsored by
Wayne State University
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Focal Epilepsy

Eligibility Criteria

3 Years - 19 Years (Child, Adult)All SexesAccepts Healthy Volunteers

Inclusion Criteria:

  1. Subjects with drug-resistant focal epilepsy

    1. Age 3-19 years. 2. Planned two-stage epilepsy surgery with subdural electrodes.

  2. Healthy control subjects 1. Age 5-19 years. 2. No cognitive, motor, and/or language impairment or clinical elevations on a measure of behavioral problems. 3. Brain MRI interpreted as normal.

Exclusion Criteria:

For all subjects:

1. History of prematurity or perinatal hypoxic-ischemic event. 2. Hemiplegia on preoperative neurological examination by pediatric neurologists. 3. Dysmorphic features suggestive of a clinical syndrome. 4. Diagnosis of any pervasive developmental or psychiatric condition which clearly predates the onset of seizures, including autism spectrum disorder, tic disorders, obsessive-compulsive disorder. 5. MRI abnormalities showing massive brain malformation and other extensive lesions that likely destroyed the contralateral tracts and severely affected i) spatial normalization accuracy in advanced normalization tools (ANTs), mutual information (MI) between native T1- MRI of Geodesic SyN transform and template T1-MRI < mean-3*standard deviation of MI in the healthy control group and ii) parcellation accuracy in surface-matching-based deformable registration, target registration error (TRE) of fine tetrahedra mesh between native T1- MRI brain surface and template T1-MRI brain surface > mean-3*standard deviation of TRE in the healthy control group. 6. History of claustrophobia. 7. Unsuccessful MRI showing head motion > 2 mm in DWMRI (i.e., voxel size of DWMRI) which is evaluated by NIH TORTOISE DWMRI motion artifact correction package. 8. Subject who cannot speak English.

Sites / Locations

  • Wayne State University/Children's Hospital of MichiganRecruiting

Arms of the Study

Arm 1

Arm Type

Experimental

Arm Label

Patients with drug-resistant epilepsy

Arm Description

All patients who undergo two-stage epilepsy surgery will receive two longitudinal evaluations of brain MRI and neuropsychology test: a month before surgery and 1.5 years after surgery.

Outcomes

Primary Outcome Measures

Accuracy of DCNN tract classification for detection of ESM-defined eloquent white matter pathways in healthy controls
Spatial overlap of DCNN tract classification (range: 0-100%, 0 indicating no overlap and 100% indicating complete overlap) will be evaluated between two different DWMRI scans of healthy controls: single-shell and generalized Q-sampling imaging (GQI) that are acquired on the same day. 14 ESM-defined eloquent pathways will be obtained using 14 DCNN tract classifications from the single-shell and GQI data, and the spatial overlap between single shell and GQI data (score: %) will be assessed per each pathway.
Accuracy of DCNN tract classification for detection of ESM-defined eloquent area that will be acquired a month after the DCNN tract classification in children with drug-resistant epilepsy
Spatial overlap (range: 0-100%, 0 indicating no overlap and 100% indicating complete overlap) will be measured between cortical terminals of DCNN-classified white matter pathways and their ground truth data: ESM-defined eloquent areas that will be acquired a month after the DCNN tract classification.
Accuracy of DCNN tract classification for prediction of eloquent white matter pathways providing no postoperative deficits that will be assessed at 1.5 years after surgery
Preservation (score: 1) vs. no preservation (score: 0) of preoperative DCNN-classified white matter pathways will be compared with presence (score: 1) vs. absence (score: 0) of postoperative deficits in primary motor, language, auditory, and visual functions that will be assessed at 1.5 years after surgery.
Accuracy of DCNN tract classification combined with Kalman analysis to predict optimal margin balancing maximal seizure freedom and minimal functional deficits that will be assessed at 1.5 years after surgery
Preservation (score: 1) vs. no preservation (score: 0) of preoperative DCNN-Kalman filter predicted surgical margin will be compared with presence (score: 1) vs. absence (score: 0) of postoperative deficits and seizure freedom that will be assessed at 1.5 years after surgery.
Strength of association between local efficiency of preoperative network and functional measure: full-scale IQ, verbal-IQ, non-verbal IQ, expressive language, receptive language, and motor function that will be assessed at 1.5 years after surgery
Local efficiency value (range: 0-1, 0 indicating no efficacy and 1 indicating the strongest efficacy) will be evaluated from full-scale IQ network, non-verbal IQ network, verbal IQ network, expressive language network, receptive language network, and motor network of preoperative DWMRI connectome data, respectively. Full-scale IQ (normal mean: 100, standard deviation: 15), verbal IQ (normal mean: 100, standard deviation: 15), non-verbal IQ (normal mean: 100, standard deviation: 15), expressive language score (normal mean: 50, standard deviation: 10), receptive language score (normal mean: 50, standard deviation: 10), and motor score (normal mean: 50, standard deviation: 10) will be also evaluated from neuro-psychology testing at 1.5 years after surgery. The correlation coefficient (range: 0-1, 0 indicating no correlation and 1 indicating complete correlation) will be evaluated between local efficiency and neuro-psychology score measured for each corresponding function.
Strength of association between local efficiency of preoperative full-scale IQ network and epilepsy duration that will be assessed at the time of preoperative MRI (Hypothesis 2.2)
Full-scale IQ (normal mean: 100, standard deviation: 15) will be assessed at the time of preoperative MRI scan. It will be associated with local efficiency (range: 0-1, 0 indicating no efficacy and 1 indicating the strongest efficacy) of preoperative full-scale IQ network and epilepsy duration (range: 0-19 years) that will be assessed within 1 day of preoperative MRI scan. The correlation coefficient (range: 0-1, 0 indicating no correlation and 1 indicating a perfect correlation) will be evaluated between full-scale IQ and local efficiency of preoperative full-scale IQ network.
Strength of association between local efficiency change of contralateral verbal-/non-verbal IQ network and verbal-/non-verbal IQ change that will be measured between 1 month before surgery and 1.5 years after surgery
Longitudinal change of local efficiency in contralateral verbal-/non-verbal IQ network (range: -1 - +1, -1 indicating a complete loss of local efficiency after surgery and +1 indicating a complete gain of local efficiency after surgery) will be measured from postoperative and preoperative DWMRI connectome data that will be measured between 1 month before surgery and 1.5 years after surgery, respectively. It will be then correlated with the longitudinal change of verbal/non-verbal IQ (range: -100 - +100, -100 indication a complete loss of verbal/non-verbal IQ after surgery and +100 indicating a complete improvement of verbal/non-verbal IQ after surgery) that will be measured between 1 month before surgery and 1.5 years after surgery. The correlation coefficient (range: 0-1, 0 indicating no correlation and 1 indicating a perfect correlation) will be calculated between two longitudinal changes.

Secondary Outcome Measures

Full Information

First Posted
July 22, 2021
Last Updated
April 24, 2023
Sponsor
Wayne State University
Collaborators
National Institutes of Health (NIH)
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1. Study Identification

Unique Protocol Identification Number
NCT04986683
Brief Title
Diffusion MRI Methods to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery
Official Title
Novel DWI Methods to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery
Study Type
Interventional

2. Study Status

Record Verification Date
April 2023
Overall Recruitment Status
Recruiting
Study Start Date
August 1, 2021 (Actual)
Primary Completion Date
June 30, 2026 (Anticipated)
Study Completion Date
June 30, 2026 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Wayne State University
Collaborators
National Institutes of Health (NIH)

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
Yes
Data Monitoring Committee
No

5. Study Description

Brief Summary
This project will test the accuracy of a novel diffusion-weighted magnetic resonance imaging (DWMRI) approach using a deep convolutional neural network (DCNN) to predict an optimal resection margin for pediatric epilepsy surgery objectively. Its primary goal is to minimize surgical risk probability (i.e., functional deficit) and maximize surgical benefit probability (i.e., seizure freedom) by precisely localizing eloquent white matter pathways in children and adolescents with drug-resistant focal epilepsy. This new imaging approach, which will acquire a DWMRI scan before pediatric epilepsy surgery in about 10 minutes without contrast administration (and also without sedation even in young children), can be readily applied to improve preoperative benefit-risk evaluation for pediatric epilepsy surgery in the future. The investigators will also study how the advanced DWMRI-DCNN connectome approach can detect complex signs of brain neuronal reorganization that help improve neurological and cognitive outcomes following pediatric epilepsy surgery. This new imaging approach could benefit targeted interventions in the future to minimize neurocognitive deficits in affected children. All enrolled subjects will undergo advanced brain MRI and neurocognitive evaluation to achieve these goals. The findings of this project will not guide any clinical decision-making or clinical intervention until the studied approach is thoroughly validated.
Detailed Description
This project will combine advanced brain MRI with detailed neuro-psychology evaluation, performed in children and adolescents affected by drug-resistant focal epilepsy, to address two main aims, each of them with the following research hypotheses: AIM 1. To determine the accuracy of deep learning tractography-based benefit-risk analysis compared to a standard electrical stimulation mapping (ESM) which is the current clinical standard for detecting eloquent cortical regions before epilepsy surgery. Hypothesis 1.1 In healthy controls, DCNN-based tract classification will localize eloquent cortices, which are significantly overlapped at both single shell DWI acquisition and generalized Q-sampling imaging, suggesting that the accuracy of this approach may not be significantly affected by the acquisition protocol. Hypothesis 1.2 DCNN-based tract classification will achieve at least 93% accuracy for prospective detection of ESM-defined eloquent cortices, including patients with a high likelihood of functional reorganization. Hypothesis 1.3 Preservation of DCNN-classified eloquent white matter pathways during surgery will predict the avoidance of postoperative deficits as accurately as the preservation of ESM-defined eloquent cortex. Hypothesis 1.4 Preservation of surgical margins optimized by Kalman filter on retrospective data will achieve seizure control and avoidance of postoperative deficits in a prospective surgical patient cohort. In this aim, the investigators will test the accuracy of a recently developed deep learning-based benefit-risk model, called deep convolutional neural network (DCNN) tract classification combined with Kalman filter analysis, for non-invasive detection of eloquent white matter pathways and optimization of surgical margin (i.e., the distance between epileptogenic area and eloquent area), resulting in seizure freedom and avoidance of functional deficits. Failure to identify eloquent areas in the proposed resection region can have potentially lifelong consequences, and overestimation or incorrect localization of the extent of the eloquent regions may lead to incomplete resection of the epileptogenic zone. Without optimizing the benefit-risk ratio, the minimum acceptable margin is highly variable across different settings, ranging from 0 to 2 cm across epilepsy surgery centers. The investigators will study whether the proposed benefit-risk model can standardize (or customize) epilepsy surgery of individual patients by accurately optimizing the margins of the eloquent white matter pathways to be preserved, which is ultimately essential to balance the benefit of seizure freedom with the risk of functional deficit. This proposed new imaging approach could change clinical practice for pediatric epilepsy surgery and is widely applicable for other types of neurosurgical procedures such as tumor resection. AIM 2. To determine the accuracy of deep learning-based connectome analysis for prediction of long-term neurocognitive improvement following epilepsy surgery. Hypothesis 2.1 Connectivity efficiencies preserved in specific modular networks of preoperative DCNN-based connectome, found to be associated with postoperative functional improvement on retrospective data, will accurately predict long-term functional improvement in a prospective patient cohort. Hypothesis 2.2 Longer epilepsy duration will be significantly associated with more decreased efficiency in full-scale IQ modular network of preoperative DCNN-based connectome, thus suggesting that earlier surgery will yield better long-term full-scale IQ improvement. Hypothesis 2.3 Patients with ipsilateral resections, who show signs of postoperative "crowding" (i.e., verbal IQ improvement at the expense of non-verbal function), will show decreased efficiency in non-verbal and increased efficiency in verbal IQ network of DCNN-based connectome in the contralateral hemisphere. In this aim, the investigators will test if an advanced DWMRI approach integrating DCNN and connectome helps decide timely surgery by providing 1) preoperative imaging markers underlying high likelihood of postoperative neurocognitive improvements and 2) mechanistic insight in structural brain reorganization associated with postoperative verbal IQ improvement. A series of preoperative imaging markers called "local efficiency" that quantifies how efficiently neural connection is shared by neighboring regions will be evaluated at the levels of specific modular networks. We expect that these markers can identify long-term and specific neurocognitive consequences (and potential predictors of these) associated with surgical intervention and their neural correlates for specific neurocognitive functions. In addition, neuronal remodeling associated with a functional crowding effect, studied with DWMRI connectome improved by the DCNN tract classification, will provide a new mechanistic insight in compensatory processes for verbal IQ function in children and adolescents who undergo resective surgery to treat drug-resistant focal epilepsy.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Focal Epilepsy

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
60 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
Patients with drug-resistant epilepsy
Arm Type
Experimental
Arm Description
All patients who undergo two-stage epilepsy surgery will receive two longitudinal evaluations of brain MRI and neuropsychology test: a month before surgery and 1.5 years after surgery.
Intervention Type
Diagnostic Test
Intervention Name(s)
Brain magnetic resonance imaging
Other Intervention Name(s)
MRI
Intervention Description
Brain magnetic resonance imaging (MRI) will be done using multiple sequences to evaluate the presence, type, and severity of brain abnormalities in enrolled subjects.
Intervention Type
Behavioral
Intervention Name(s)
Neuro-psychology testing
Other Intervention Name(s)
neuro-cognitive testing, neuro-psychology
Intervention Description
Participants will undergo age-appropriate neuro-psychology testing to assess motor, language, and other neurocognitive functions potentially affected by drug-resistant epilepsy.
Primary Outcome Measure Information:
Title
Accuracy of DCNN tract classification for detection of ESM-defined eloquent white matter pathways in healthy controls
Description
Spatial overlap of DCNN tract classification (range: 0-100%, 0 indicating no overlap and 100% indicating complete overlap) will be evaluated between two different DWMRI scans of healthy controls: single-shell and generalized Q-sampling imaging (GQI) that are acquired on the same day. 14 ESM-defined eloquent pathways will be obtained using 14 DCNN tract classifications from the single-shell and GQI data, and the spatial overlap between single shell and GQI data (score: %) will be assessed per each pathway.
Time Frame
During procedure
Title
Accuracy of DCNN tract classification for detection of ESM-defined eloquent area that will be acquired a month after the DCNN tract classification in children with drug-resistant epilepsy
Description
Spatial overlap (range: 0-100%, 0 indicating no overlap and 100% indicating complete overlap) will be measured between cortical terminals of DCNN-classified white matter pathways and their ground truth data: ESM-defined eloquent areas that will be acquired a month after the DCNN tract classification.
Time Frame
1 month
Title
Accuracy of DCNN tract classification for prediction of eloquent white matter pathways providing no postoperative deficits that will be assessed at 1.5 years after surgery
Description
Preservation (score: 1) vs. no preservation (score: 0) of preoperative DCNN-classified white matter pathways will be compared with presence (score: 1) vs. absence (score: 0) of postoperative deficits in primary motor, language, auditory, and visual functions that will be assessed at 1.5 years after surgery.
Time Frame
1.5 years
Title
Accuracy of DCNN tract classification combined with Kalman analysis to predict optimal margin balancing maximal seizure freedom and minimal functional deficits that will be assessed at 1.5 years after surgery
Description
Preservation (score: 1) vs. no preservation (score: 0) of preoperative DCNN-Kalman filter predicted surgical margin will be compared with presence (score: 1) vs. absence (score: 0) of postoperative deficits and seizure freedom that will be assessed at 1.5 years after surgery.
Time Frame
1.5 years
Title
Strength of association between local efficiency of preoperative network and functional measure: full-scale IQ, verbal-IQ, non-verbal IQ, expressive language, receptive language, and motor function that will be assessed at 1.5 years after surgery
Description
Local efficiency value (range: 0-1, 0 indicating no efficacy and 1 indicating the strongest efficacy) will be evaluated from full-scale IQ network, non-verbal IQ network, verbal IQ network, expressive language network, receptive language network, and motor network of preoperative DWMRI connectome data, respectively. Full-scale IQ (normal mean: 100, standard deviation: 15), verbal IQ (normal mean: 100, standard deviation: 15), non-verbal IQ (normal mean: 100, standard deviation: 15), expressive language score (normal mean: 50, standard deviation: 10), receptive language score (normal mean: 50, standard deviation: 10), and motor score (normal mean: 50, standard deviation: 10) will be also evaluated from neuro-psychology testing at 1.5 years after surgery. The correlation coefficient (range: 0-1, 0 indicating no correlation and 1 indicating complete correlation) will be evaluated between local efficiency and neuro-psychology score measured for each corresponding function.
Time Frame
1.5 years
Title
Strength of association between local efficiency of preoperative full-scale IQ network and epilepsy duration that will be assessed at the time of preoperative MRI (Hypothesis 2.2)
Description
Full-scale IQ (normal mean: 100, standard deviation: 15) will be assessed at the time of preoperative MRI scan. It will be associated with local efficiency (range: 0-1, 0 indicating no efficacy and 1 indicating the strongest efficacy) of preoperative full-scale IQ network and epilepsy duration (range: 0-19 years) that will be assessed within 1 day of preoperative MRI scan. The correlation coefficient (range: 0-1, 0 indicating no correlation and 1 indicating a perfect correlation) will be evaluated between full-scale IQ and local efficiency of preoperative full-scale IQ network.
Time Frame
Within 1 day
Title
Strength of association between local efficiency change of contralateral verbal-/non-verbal IQ network and verbal-/non-verbal IQ change that will be measured between 1 month before surgery and 1.5 years after surgery
Description
Longitudinal change of local efficiency in contralateral verbal-/non-verbal IQ network (range: -1 - +1, -1 indicating a complete loss of local efficiency after surgery and +1 indicating a complete gain of local efficiency after surgery) will be measured from postoperative and preoperative DWMRI connectome data that will be measured between 1 month before surgery and 1.5 years after surgery, respectively. It will be then correlated with the longitudinal change of verbal/non-verbal IQ (range: -100 - +100, -100 indication a complete loss of verbal/non-verbal IQ after surgery and +100 indicating a complete improvement of verbal/non-verbal IQ after surgery) that will be measured between 1 month before surgery and 1.5 years after surgery. The correlation coefficient (range: 0-1, 0 indicating no correlation and 1 indicating a perfect correlation) will be calculated between two longitudinal changes.
Time Frame
1.5 years

10. Eligibility

Sex
All
Minimum Age & Unit of Time
3 Years
Maximum Age & Unit of Time
19 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria: Subjects with drug-resistant focal epilepsy 1. Age 3-19 years. 2. Planned two-stage epilepsy surgery with subdural electrodes. Healthy control subjects 1. Age 5-19 years. 2. No cognitive, motor, and/or language impairment or clinical elevations on a measure of behavioral problems. 3. Brain MRI interpreted as normal. Exclusion Criteria: For all subjects: 1. History of prematurity or perinatal hypoxic-ischemic event. 2. Hemiplegia on preoperative neurological examination by pediatric neurologists. 3. Dysmorphic features suggestive of a clinical syndrome. 4. Diagnosis of any pervasive developmental or psychiatric condition which clearly predates the onset of seizures, including autism spectrum disorder, tic disorders, obsessive-compulsive disorder. 5. MRI abnormalities showing massive brain malformation and other extensive lesions that likely destroyed the contralateral tracts and severely affected i) spatial normalization accuracy in advanced normalization tools (ANTs), mutual information (MI) between native T1- MRI of Geodesic SyN transform and template T1-MRI < mean-3*standard deviation of MI in the healthy control group and ii) parcellation accuracy in surface-matching-based deformable registration, target registration error (TRE) of fine tetrahedra mesh between native T1- MRI brain surface and template T1-MRI brain surface > mean-3*standard deviation of TRE in the healthy control group. 6. History of claustrophobia. 7. Unsuccessful MRI showing head motion > 2 mm in DWMRI (i.e., voxel size of DWMRI) which is evaluated by NIH TORTOISE DWMRI motion artifact correction package. 8. Subject who cannot speak English.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Justin J Jeong, PhD
Phone
313-993-0258
Email
jjeong@med.wayne.edu
First Name & Middle Initial & Last Name or Official Title & Degree
Eishi Asano, MD, PhD
Phone
313-745-5547
Email
easano@med.wayne.edu
Facility Information:
Facility Name
Wayne State University/Children's Hospital of Michigan
City
Detroit
State/Province
Michigan
ZIP/Postal Code
48201
Country
United States
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Aimee Luat, MD
Phone
313-832-9620
Email
aluat@dmc.org
First Name & Middle Initial & Last Name & Degree
Eishi Asano, MD, PHD
Phone
313-745-5547
Email
easano@med.wayne.edu

12. IPD Sharing Statement

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Diffusion MRI Methods to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery

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