Identifying Neuroimaging Biomarkers, Demographic, Personality and Sensory Factors for Predicting Extreme Pain Responses to Various Experimental Pain Stimulations in Healthy Subjects
试验速览
- 阶段
- 不适用
- 入组人数
- 48
- 试验地点
- 1
- 主要终点
- fMRI diffrences
研究概览
简要总结
The proneness to react to noxious stimuli varies widely between individuals and pain ratings of seemingly identical noxious stimuli may range from "no pain" to "excruciating pain" . Imaging studies in healthy subjects have provided useful information on the identification of the inter-individual variability in pain perception [2,3,4]. These studies have shown that subjective pain reports are closely related to the degree of neuronal activity in several brain regions known to be identified in pain processing. Furthermore, there has been a growing interest in understanding structural and functional mechanisms of inter-individual variability in responses to identical noxious stimuli [5,6,7]. Yet, the relationship between pain perception and various anatomical and functional connectivity within resting state brain networks is not completely understood. With regard to the anatomical correlate of pain sensitivity, differences in grey matter may reflect neural processes contributing to the construction and modulation of pain in healthy individuals. As such, studies are inconsistent regarding this issue, showing positive [7] or inverse connections [6] between pain sensitivity and brain morphology. The inconsistency regarding this issue warrant further investigation which may elucidate the relationship between differences in pain sensitivity and regional grey matter and may provide novel insights into brain mechanisms contributing to that topic. Understanding brain morphology and connectivity within specific regions associated with pain processing can provide reliable anchor for the individual differences in pain response.
A widely used approach to examine brain morphology from MRI images is voxel based morphometry (VBM). VBM tests for statistically significant differences in regional gray matter (GM) density between study groups, and its temporal changes. Diffusion tensor imaging (DTI) is a type of diffusion weighted imaging with the advantage of being able to resolve individual functional tracts within the white matter (WM) thus, DTI parameters serve as indirect measures of structural connectivity via the degree of integrity of WM tracts.
详细描述
Background The proneness to react to noxious stimuli varies widely between individuals and pain ratings of seemingly identical noxious stimuli may range from "no pain" to "excruciating pain" . Imaging studies in healthy subjects have provided useful information on the identification of the inter-individual variability in pain perception [2,3,4]. These studies have shown that subjective pain reports are closely related to the degree of neuronal activity in several brain regions known to be identified in pain processing. Furthermore, there has been a growing interest in understanding structural and functional mechanisms of inter-individual variability in responses to identical noxious stimuli [5,6,7]. Yet, the relationship between pain perception and various anatomical and functional connectivity within resting state brain networks is not completely understood. With regard to the anatomical correlate of pain sensitivity, differences in grey matter may reflect neural processes contributing to the construction and modulation of pain in healthy individuals. As such, studies are inconsistent regarding this issue, showing positive [7] or inverse connections [6] between pain sensitivity and brain morphology. The inconsistency regarding this issue warrant further investigation which may elucidate the relationship between differences in pain sensitivity and regional grey matter and may provide novel insights into brain mechanisms contributing to that topic. Understanding brain morphology and connectivity within specific regions associated with pain processing can provide reliable anchor for the individual differences in pain response.
A widely used approach to examine brain morphology from MRI images is voxel based morphometry (VBM). VBM tests for statistically significant differences in regional gray matter (GM) density between study groups, and its temporal changes. Diffusion tensor imaging (DTI) is a type of diffusion weighted imaging with the advantage of being able to resolve individual functional tracts within the white matter (WM) thus, DTI parameters serve as indirect measures of structural connectivity via the degree of integrity of WM tracts.
- Aim of the study To Identify neuroimaging biomarkers, demographic, personality and sensory factors for predicting extreme pain responses to various experimental pain stimulations in healthy subjects 3. Methods 3.1 Sample
The study population will consist of 196 healthy participants. Of these, 48 patients will undergo brain imaging after meeting the following inclusion and exclusion criteria:
Study design The proposed study has been conducted at the Pain Research Laboratory of University of Haifa (in which psychophysics tests will be conducted), and imaging tests will be performed at the Imaging department of Rambam Health Care Campus.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Healthy males and females, over the age of 18, free from chronic pain of any type.
- •No medication use (except for oral contraceptives).
- •Able to understand the purpose and instructions of the study and to sign an informed consent.
排除标准
- •Pregnant women
- •Inability to comply with study protocol.
- •A diagnosis of Raynaud's Syndrome
- •Subjects with metal implants of any kind (including pace maker) and Claustrophobia will be excluded from the study.
结局指标
主要结局
fMRI diffrences
时间窗: 2 years
a. Both subgroups will demonstrate differences in gray matter density and cortical thickness in key cortical regions that are responsible for the processing and modulation of sensory stimuli, such as primary somatosensory cortex (S1), cingulate cortex (ACC/MCC/PCC), prefrontal cortex (PFC including OFC) and insula.
次要结局
未报告次要终点
研究者
Eisenberg Elon MD
Elon Eisenberg MD Professor of Neurology and Pain Medicine Head, Pain Research Unit Institute of Pain Medicine Rambam Health Care Campus
Rambam Health Care Campus
