duerden rotman 2009 07 29

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Impacts of pain on brain health explored using

neuroimaging techniques: implications for patient

treatment

Emma Duerden, M.Sc. PhD candidate (Neurological Sciences)

Département de physiologieUniversité de Montréal

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Outline Introduction

background Pain processing regions

Meta-analysisApplications

ROI analysis Cortical thickness Meditation Pain catastrophizing

Pain and memory fMRI study: Short-term memory of pain

Applications to patient treatment Brain-plasticity Amputation - phantom-limb pain Training

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Introduction

Pain: Unpleasant sensory and emotional experience

Actual or potential tissue damage

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Introduction

Pain: Statistics Canada 2001

1.5 million persons aged 15 to 64 3 in 4 personsWomen = 8.3%Men = 6.7%70% = affects daily life

National Population Health Survey (NPHS)1/4 seniors at home4/10 seniors in institutions

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Introduction

Pain = psychological experience

No objective measuresSensory and affective components of pain

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Peripheral mechanisms of pain

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Central mechanisms of pain

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Introduction

Neural processing of painful stimuli

Broad network of interconnected cortical regions

Sensory-discriminative Emotional-motivational

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Introduction

Discriminative processing of pain Lateral pain system

SI secondary somatosensory cortex (SII) Thalamus (ventroposterior lateral and medial

nuclei)

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Introduction

Affective (unpleasantness) processing of pain Medial pain system

ACCPFC

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Brain imaging methods

Laboratory of Neuro Imaging (LONI) at UCLA (http://www.loni.ucla.edu/)

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http://www.fmrib.ox.ac.uk

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Brain activity during pain

Positron emission tomography

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Brain activity during pain

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Brain activity during pain

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Brain activity during pain

Thalamus

S1S2Insula

ACC

Rainville et al., Médecine Science 16 (2000)

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Why do a meta-analysis?

Contiguous activation Particular task Cognitive function Particular function across different tasks

e.g. working memory Problems with single fMRI/PET studies:

Study confounds:Artifacts, head motion, few subjects, inter-individual

variability, low SNRType I errors (5% false positives)Greater rates of Type II errorContamination from irrelevant task features

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Probabilistic mapping

Activation Likelihood Estimate (ALE)BrainMap GingerALE

Convert coordinates = MNI and Talairach Meta-Analysis Group of coordinatesComparison ALE meta-analysis 2 groups

Method assessing statistical significanceTest peaks distributed at multiple sites Against H0 of random distribution

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ALE method

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Methods

Meta-analysis:ALE analytic method (Turkeltaub et al., 2002)Talairach spaceDate blurred (8mm)Distribution determined through permutation test

(N=5000)Thresholded (p = 0.003)

controlling the FDR q = 0.05ALE maps displayed on anatomical MRIPeak p values ABOVE threshold displayed

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Pain Meta-Analysis

Contrasts:Pain - baselinePain - control (warm, cool)High pain - low painCorrelation PI/PUExternally administered stimuliBetween groups (high vs low sensitivity;

PET studies)

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Pain Meta-AnalysisSummary

122 total original studiesfMRI: 79PET: 43

130 total2699 points!

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Thresholded 3D probability map

Duerden, Fu, Rainville, Duncan. IASP 2008

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Results: All pain

BILATERAL IC

BILATERAL thalamus

BILATERAL SII

R: 52, -26, 22 p = 0.18L: -52, -24, 22 p = 0.17

0.25

0.003

THAL (R): 10, -18, 6 p = 0.22THAL (L): -14, -16, 8 p = 0.25

IC (R): 34, 12, 8 p = 0.23IC (L): -36, 4, 6 p = 0.21

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Other ApplicationsALE Method

Comparison different types of painCold pain vs heat painLeft vs rightfMRI vs PETROI analysis:

Cortical thickness

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Pain sensitivity and cortical thickness in Zen meditators

Grant, Duerden, Courtemanche, Duncan, Rainville. Emotion 2009 submitted

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Pain and meditation

Hypnosis, attention, expectancy or placebo

Modulate experience of pain Mindfulness meditation

Effective in treating chronic pain Emotional and functional No long-term effects on pain sensation

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Pain and meditation

What the effects of meditation on pain perception?

Would differences be linked to morphological changes in the brain?

29Grant & Rainville. Psychosomatic Medicine 71:106–114 (2009)

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Pain mask

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Pain mask

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Pain Meta-AnalysisZen meditators have thicker cortex in pain

processing regions

Grant, Duerden, Courtemanche, Duncan, and Rainville, Emotion 2009 submitted

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Pain and meditation

Meditators required hotter temperatures Less pain while attending mindfullyCorrelation with increased thickness in pain

regionsGreater ability to modulate pain

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Other ApplicationsALE Method

Comparison different types of painCold pain vs heat painLeft vs rightfMRI vs PETROI analysis:

Cortical thickness

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Brain morphometric changes associated

with pain catastrophizingD. Laverdure-Dupont; E.G. Duerden; A.-A. Dubé; K.J. Worsley; G.H. Duncan; G. Lavigne; P. Rainville

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Pain catastrophizing

Personality traitCoping strategy

Pain Awful, horrible and unbearableAugments pain perception

enhanced attention to painful stimuli

heightened emotional responses to pain

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Pain catastrophizing

Personality traits are associated with cortical morphometric changes

PCACC PFC in chronic pain patients

CT analysis Identify potential persistent neural substrates underlying PC

20 young, healthy, subjects (RH; Age=23.2yrs; M=11).

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Pain catastrophizing

PCS is significantly correlated with CT in ACC

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Pain catastrophizing

PC is linked to morphometric differences

Limbic-paralimbic systemPronounced recruitment of affective processes in high catastrophizers

Enhanced development Emotional processing brain regions

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Outline Pain processing regions

Meta-analysisApplications

ROI analysis Cortical thickness Pain catastrophizing

Pain and memory fMRI study: Short-term memory of pain

Applications to patient treatment Brain-plasticity Amputation - phantom-limb pain Training

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Memory traces of pain in human cortex

Albanese, Duerden, Rainville, Duncan. J Neurosci, 2007

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IntroductionEvidence - sensory information is transiently stored

Sensory-specific cortical areas Involved in initial encoding SI - transient storage site for tactile informationNoxious sensory information?

Neural basis of encoding and retention Heat pain stimuli Right palm in 8 healthy volunteers

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Methods: Stimulation protocol

encoding

retention

retrieval

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Copyright ©2007 Society for Neuroscience

Albanese, M.-C. et al. J. Neurosci. 2007;27:4612-4620

Figure 2. Cortical regions significantly activated during the ISI between the pairs of stimuli in both the memory and control trials and memory-specific activation observed within

pain-related sites

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Copyright ©2007 Society for Neuroscience

Albanese, M.-C. et al. J. Neurosci. 2007;27:4612-4620

Figure 3. Mean time course of the memory-specific percentage BOLD signal from the group average observed during the course of experimental and control trials,

synchronized on the start of each trial

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Conclusions

Sustained pain-related activitySI associated with ISI in the MEMORY trials

Suggests a short-term retention of a 'pain trace’Sensory-specific cortex

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Long-term memory

Brain plasticityTraining-related changesLearning Chronic pain

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Copyright ©2008 Society for Neuroscience

Duerden, E. G. et al. J. Neurosci. 2008;28:8655-8657

Figure 1. Meta-analysis of voxel-based morphometric studies reporting increased gray matter density after learning in the cortex and cerebellum

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Habituation to painful stimuli

AVERAGE PAIN INTENSITY RATINGS FOR HABITUATORS ACROSS SESSIONS

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10

20

30

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50

60

70

80

90

100

VAS scale

Pain Intensity 66.17 64.94 53.00 48.61 74.44

session 1 session 2 session 3 session 4 session 5

AVERAGE PAIN UNPLEASANTNESS RATINGS FOR HABITUATORS ACROSS SESSIONS

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10

20

30

40

50

60

70

80

90

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VAS SCALE

PAINUNPLEASANTNESS

63.56 59.44 50.28 25.56 71.33

session 1

session 2

session 3

session 4

session 5

ratings tested for habituation sessions 1-4

ratings tested for habituation sessions 1-4

** *

*

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Pain Stimulus Session 1-4: H

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Copyright ©2004 Society for Neuroscience

Apkarian, A. V. et al. J. Neurosci. 2004;24:10410-10415

Figure 2. Regional gray matter density decreases in CBP subjects

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Copyright ©2007 Society for Neuroscience

Kuchinad, A. et al. J. Neurosci. 2007;27:4004-4007

Figure 2. Voxel-wise comparison of gray matter density between fibromyalgia patients and healthy control subjects

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DaSilva et al., Neurology. 2007 Nov 20;69(21):1990-5

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Chronic pain

Pain managementSensitive tests for measuring pain

Brain imaging?Pain treatment

MindfulnessHypnosisTraining

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Training: phantom limb pain Correlation - cortical remapping and pain in the phantom-limb Maladaptive mapping

Reversed Sensory training paradigms

Post-training = pain and cortical reorganization

(Flor et al. 2001)

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Acknowledgements Mentors:

Dr. Gary Duncan

Dr. Pierre Rainville

FundingCanadian Institutes of Health Research (CIHR)

Lab mates:Dr. Marie-Claire AlbaneseJen-I ChenMathieu RoyJoshua GrantAudrey-Anne DubéMarianne ArsenaultMathieu Piché

Collaborators:Dr. Bruce PikeDr. Stefan PosseDr. Keith Worsley

Tech Support:Mathieu DesrosiersLeo Tenbokum

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Thank you

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Introduction

These ‘maps’ are found in primary and secondary sensory areas and in thalamic nuclei

Many sensory systems are characterized by cortical representations of surface receptors, whereby the occurrence of neighbouring inputs is preserved in the cortex

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Topographic mapsThere is a similar somatotopic map in the primary somatosensory cortex (S1) that is the main sensory receptive area for the sense of touch

Primary somatosensory cortex

Areas of skin that are highly innervated and that have fine sensory discriminative properties have a larger cortical representation

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Phantom limbs

Studies have shown that cortical representations surrounding those that are inactive due to the loss of the limb will encroach on that region

Pain in the amputated body part occurs in 50–80% of all amputees

Cortical remapping as a result of an amputation often results in painful sensations in the amputated limb so called “phantom limb” pain

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Why do a meta-analysis?

Contiguous activation Particular task Cognitive function Particular function across different tasks

e.g. working memory Problems with single fMRI/PET studies:

Study confounds: Artifacts, head motion, few subjects, inter-individual variability, low

SNR Type I errors (5% false positives) Greater rates of Type II error Contamination from irrelevant task features Assumptions made based on Task A - B Each task isolates process?

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Introduction

What causes chronic pain?Plasticity = sites throughout pain pathway

Changes in peripheral receptorsreceptor

channel expression Distributionactivation threshold

Strengthening synapsesLTP = DHN