Novel DWI Methods to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 60
- 试验地点
- 1
- 主要终点
- Accuracy of DCNN tract classification for detection of ESM-defined eloquent white matter pathways in healthy controls
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 3 Years 至 19 Years（Child, Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Subjects with drug-resistant focal epilepsy
- •1. Age 3-19 years.
- •Planned two-stage epilepsy surgery with subdural electrodes.
- •Healthy control subjects
- •Age 5-19 years.
- •No cognitive, motor, and/or language impairment or clinical elevations on a measure of behavioral problems.
- •Brain MRI interpreted as normal.
排除标准
- •For all subjects:
- •1. History of prematurity or perinatal hypoxic-ischemic event.
- •Hemiplegia on preoperative neurological examination by pediatric neurologists.
- •Dysmorphic features suggestive of a clinical syndrome.
- •Diagnosis of any pervasive developmental or psychiatric condition which clearly predates the onset of seizures, including autism spectrum disorder, tic disorders, obsessive-compulsive disorder.
- •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.
- •History of claustrophobia.
- •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.
- •Subject who cannot speak English.
研究组 & 干预措施
Patients with drug-resistant epilepsy
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.
干预措施: Brain magnetic resonance imaging (Diagnostic Test)
Patients with drug-resistant epilepsy
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.
干预措施: Neuro-psychology testing (Behavioral)
结局指标
主要结局
Accuracy of DCNN tract classification for detection of ESM-defined eloquent white matter pathways in healthy controls
时间窗: During procedure
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.
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
时间窗: 1.5 years
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.
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
时间窗: 1 month
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
时间窗: 1.5 years
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
时间窗: 1.5 years
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 full-scale IQ network and epilepsy duration that will be assessed at the time of preoperative MRI (Hypothesis 2.2)
时间窗: Within 1 day
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
时间窗: 1.5 years
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.
次要结局
未报告次要终点
研究者
Justin Jeong-Won Jeong
Associate Professor
Wayne State University