Identifying Neuroimaging Biomarkers, Demographic, Personality and Sensory Factors for Predicting Extreme Pain Responses to Various Experimental Pain Stimulations in Healthy Subjects
Identifying Neuroimaging Biomarkers, Demographic, Personality and Sensory Factors for Predicting Extreme Pain Responses to Various Experimental Pain Stimulations in Healthy Subjects
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.
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.
2. 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.
Subjects were recruited through advertisements distributed on campus bulletin board. Responders who met the inclusion criteria were invited to participate in the study. The trial will be held in two independent experimental sessions with an estimated duration of one hour and a half for the psychophysical tests and half an hour for the neuroimaging session.
This study is focused on extreme subgroups only. Therefore, in the first session (which took place in the pain lab) subjects (n=196) were either divided into two subgroups according to their tolerance results to the Cold Pressor Test (CPT) (high tolerance subgroup = 180 s vs. low tolerance subgroup ≤20 s). 24 subjects from each subgroup will be randomly selected and will receive an explanation about the option to participate in the brain imaging test. Subjects who will decide to participate in the imaging test will undergo it at the Imaging Department of Rambam Health Care Campus. Upon arrival, subjects will receive a full explanation of the course and time of the MRI scan of the brain and will be asked to sign an informed consent form. The duration time of the MRI procedure is around half an hour during which no material will be injected or pain tests will be performed.
During the test, several sequences will be performed; three-dimensional high-resolution anatomy, another structural test for the definition of connectivity (DTI), and resting state (RS) fMRI tests to examine the activity of brain networks. MRI will be performed using a 3-Tesla scanner (GE Discovery MR750). The protocol consists of (1) a T1-weighted 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence (176 slices; 220 × 220 matrix; TR = 2520 ms; TE = 1.74 ms; 1.0 × 1.0 × 1.0 mm voxels), (2) an echo-planar imaging (EPI) resting state sequence (34 slices; TR = 2010 ms; TE = 30 ms; 64 × 64 matrix; 3.5 × 3.5 × 5 mm voxels 200 volumes lag=4 RTs), (3) a diffusion-weighted imaging (DTI) sequence (70 slices; TR = 4600 ms; TE = 89 ms; 2 × 2 × 2 mm voxels) using non-collinear 64 directions and a single non-diffusion weighted (b = 0 s/mm2) image. At the end of the examination, analyzes of the data will be carried out for each individual and for each population of the study. After the MRI scan subjects will be asked to fill out the depression, anxiety and stress scales (DASS): The DASS assess depression, anxiety and stress with 7 Items each (Henry & Crawford, 2005). The DASS-Depression focuses on reports of low mood, motivation, and self-esteem, DASS-anxiety on physiological arousal, perceived panic, and fear, and DASS-stress on tension and irritability. The short-form version of the Depression Anxiety Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical sample. It was validated in a population of over 300 patients with chronic pain as well as healthy volunteers and found valid and reliable in both populations.
Inclusion Criteria:
Exclusion Criteria:
e_eisenberg@rambam.health.gov.il972502061091