Transcript Document

PSYCHOSIS Neuro-Imaging
(Schizophrenia and Bipolar disorder)
What we know and what we could know
Stephen Lawrie
Edinburgh
Why brain scan in psychosis?
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Some current clinical utility
To improve understanding of pathophysiology
To refine (endo)phenotype definition
? (early) Diagnostic aids
? Predicting treatment response and/or prognosis
Lesion detection
– qualitative analyses of structural imaging
• Lawrie et al, Schizo Res, 1997:
– gross lesions (e.g. AVMs, cysts, tumours) in 0-5%
– ‘atrophy’ in 4-52% c.f. 2-19% controls
– HIS foci in 5-38% c.f. 3-19% controls
– Usually of little clinical importance
– i.e. CT/sMRI only indicated in atypical presentations
• Albon et al, HTA, 2008:
– In MRI studies, approximately 5% of patients had findings
that would influence clinical management, whereas in the CT
studies, approximately 0.5% of patients had these findings.
– The strategy of neuroimaging for all psychosis is either costincurring or cost-saving (dependent upon whether MRI or CT
is used) if the prevalence of organic causes is around 1%.
What did CT tell us?
- Ventriculomegaly (corr. hospitalisation) and
cerebral ‘atrophy’ (*Raz, Psychol Bull 1990, 108: 93-108)
– VBR not bimodally distributed
(Daniel, Biol Psych 1991, 30: 887-903)
– VBR related to duration & Dx criteria
(van Horn, Br J Psych 1992, 160: 687-97)
– VBR not related to treatment response
(Friedman, J Psychiatri Neurosci 1992, 17: 42-54)
i.e. not much more than pneumo-encephalography
Quantitative sMRI in schizophrenia
Original T1 image
Segment images (GM, WM & CSF)
& remove extra-cerebral voxels
Normalise GM seg. to template
to obtain norm. parameters
Voxel Based Morphometry
Smooth final images
Segment normalised images &
remove extra-cerebral voxels
unmodulated
modulated
Apply norm. parameters to
original images
sMRI systematic reviews in schizophrenia
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reduced whole brain volume (by ~3% Ward, Schiz Res 1996;197-213)
corpus callosum similarly (Woodruff, JNNP 1995; 58: 457-61)
reduced hippocampal and amygdala volume (by about 4% each: Nelson, Arch Gen Psych
1998; 55: 433-40)
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reduced pre-frontal & medial temporal lobe (MTL) volumes (Lawrie & Abukmeil, Br
J Psych 1998;172: 110-120)
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reduced superior temporal gyrus (STG) & increased globus pallidus volumes
(Wright, Am J Psych 2000; 157: 16-25)
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reduced thalamus (Konick & Friedman, Biol Psych 2001; 49: 28-38)
reduced anterior cingulate (Baiano, Schizo Res 2007)
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Similar changes also seen in first episode cases (Vita et al, 2005; Steen et al, 2006)
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Also, 15 VBM studies consistently find reduced grey matter (GM) in MTL
and STG (Honea et al, Am J Psych 2005; 162: 2233-45)
An ALE analysis of 27 articles found GM decreases in the thalamus, the left
uncus/amygdala region, the insula bilaterally, and the anterior cingulate both
first-episode schizophrenia (FES) and chronic schizophrenia. Comparing
patient groups, decreases in GM were detected in FES in the caudate head
bilaterally, while decreases were more widespread in cortical regions in
chronic schizophrenia (Ellison-Wright et al, Am J Psych 2008).
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Key unresolved questions
• When and how do the abnormalities arise?
• What is their neuropathology?
• How is the anatomical phenotype related to
the clinical and cognitive features?
• Does it progress after onset?
• Do antipsychotic drugs ameliorate or
exacerbate these abnormalities?
sMRI studies of relatives
• Relatives have smaller MTLs than
controls (Keshavan 1997 & 2002; Lawrie 1999 &
2001; Schreiber 1999; Seidman 1997 & 1999)
• Schizophrenics have smaller MTLs
than relatives (Lawrie 1999 & 2001;O'Driscoll
2001;Steel 2002 – but see Staal 2000)
• Best evidence for hippocampal
differences on ROI (Waldo 1994;Harris
2002;Seidman 2002;van Erp 2002 – but see Schulze 2003).
• Best evidence for pre-frontal
differences on VBM (Job 2003).
• Supported by twin studies (Suddath 1990;
Baare 2001; Cannon/Narr 2002; van Erp 2004)
• …and g-e risk factor studies (DeLisi 1988;
Stefanis 1999; McNeil 2000)
Boos et al meta-analysis (Archives 2007) of
relatives ROI finds hippocampal reductions in
relatives Vs controls (ES 0.3) and additional
difference in relatives Vs patients (ES 0.5)
Baseline prediction of conversion
- studies of relatives or ‘ultra-high risk’
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Hippocampus volume is a best a weak
and inconsistent predictor
(Lawrie, Archives 2007):
– No prediction
(Job, 2005; Johnstone, 2005;
Velakoulis, 2006)
– Small hippocampus predicts
(Pantelis 2003)
– Large hippocampus predicts (!)
(Phillips 2002; Bogwardt 2007)
Anterior cingulate and Superior
temporal gyrus volumes may however
predict (PACE studies)
Gyral folding may predict (EHRS:
Harris et al, 2007)
sMRI studies of pre-psychosis progression
from the PACE clinic & the EHRS
Pantelis et al (2003) reductions in grey
matter in the left parahippocampal,
fusiform, orbitofrontal and cerebellar
cortices, and the cingulate gyri.
Job et al (2005) reductions in grey
matter in the left (para)hippocampal
uncus and fusiform gyrus, and right
cerebellar cortex
Magnetic Resonance Spectroscopy
(MRS)
• Initial resolution problems solved
• Whole brain acquisitions still impractical
• Incredibly consistent literature – reductions in frontal and
temporal NAA which are not volume / medication artefacts
(see Steen et al 2005 Neuropsychopharmacology 30 1949-62)
• 3-4T systems give good enough resolution for reliable
estimation of Glu, Gln, GABA; and α-ATP, β-ATP and γATP moieties
• Interpretation difficulties - ? a structural or functional
index of integrity / viability
Diffusion Tensor Imaging (DTI)
• Can assess the structural
integrity of white matter tracts
• Inconsistency of the literature in
schizophrenia overplayed, but
inconsistency of methods
usefully highlighted, in a recent
review (Kanaan et al 2005, Biol
Psychiatry 58: 921-9)
• ROI and VBM analysis giving
way to TBSS and tractography
analyses
• Also, Magnetisation Transfer
Imaging (MTI)
The future of structural imaging in schizophrenia
• Increasingly sophisticated
automated analyses – DBM and
TBM
• The anatomical basis of
‘disconnectivity’ e.g. GI, DTI
• More high resolution studies e.g. 3T
of CA3, ?Cx layers
• The use of pattern classification
methods to use more information to
e.g. make diagnostic classifications
• Automated extraction of regional
volumes, to avoid brain averaging
• Multi-centre studies
• Integration with other techniques in
‘multi-modal imaging’
Functional imaging techniques
Electrophysiology
• EEG
• ERPs
• MEG
• NIRS
• LORETA
rCBF studies
• SPE(C)T
• PET
• fMRI
in conditions:
• Rest
• Active vs Rest
• Active Vs Active
• receptor ligands
• pharmacological
manipulation
Pouratian et al TINS May 2003, 26(5) Pages 277-282
Potential ‘confounders’ of
functional imaging abnormalities
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IQ
Reaction time
Distraction by positive symptoms
Motivation
Medication
Alcohol and other drugs
Structural brain abnormalities
Causative versus ‘effect modifying’ genes
EHRS
time-series
images
(n=200)
blocked
design
Design matrix
used in study
(first level)
realignment parameters entered into
design matrix (columns 6-11)
Numbers on y axis
represent images 1 200. Columns 1-5
represent the four active
conditions plus rest, 611 represent the
realignment parameters
SMOOTHING
REALIGNMENT
to first volume in
series
with 6x6x6mm3
FWHM Gaussian
kernal
NORMALISATION
GENERAL LINEAR MODEL
STATISTICAL INFERENCE
to SPM EPI template,
linear affine and nonlinear deformations
SPM EPI
template
Individual subject activation map
Statistical maps of regional cerebral blood flow
(a) Conjunction analysis showing voxels with significantly (p <
0.01, voxel level) higher rCBF during the task than the control
task.
(b) Wisconsin Card Sorting Test stimuli.
(c) Voxels showing significantly (p < 0.05) higher rCBF in the taskminus-control contrast in the frontal lobes of controls as
compared to patients.
Functional imaging (‘brain mapping’) systematic reviews
Delayed and reduced P300
• Increased P300 peak latency (Ebmeier, Biol Psych 1991; 29: 1156-60)
• Reduced P300 amplitude too (Jeon & Polich Psych Res 2001; 104: 61-74 & Psychophysiol 2003; 40: 684701; also Bramon et al 2004 Sch Res 70: 315-29 PSES~0.6 & 0.8)
‘Hypo-’ and ‘Hyper-’ frontality
• 21 resting PET studies ES –0.64 (95%CI –0.91 to –0.38) & 9 activated studies
overall ES –1.13 (–1.53 to –0.73) (Zakzanis & Heinrichs, JINS 1999; 5: 556-66; see also Davidson &
Heinrichs Psych Res 2003 122: 69-87 and Hill et al Acta Psychiatr Scand. 2004 110:243-56.)
• Glahn et al (*Hum Brain Mapp 2005 25: 60-9) reviewed 12 N-back studies to find DLPFC
‘hypofrontality’ and ‘hyper-frontality’ in Ant. Cing. & (L) frontal pole
‘Hyper-’ and ‘Hypo-’ temporality
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13 SPECT studies show effect sizes from 0.25 (superior) to 2.0 (inferior); 6 PET studies show
effect sizes from 0.14 (right) to 1.3 (superior) (Zakzanis, Psychol Med 2000; 30: 491-504)
• Achim & Lepage (*Br J Psych 2005 187: 500-9) examined 18 episodic memory studies
and found consistent (L) IPFC and (Bi) MTL reductions in activation
Prefrontal cortex dysfunction during working memory
performance in schizophrenia: reconciling discrepant findings
(Manoach Schizo Res,2003; 60: 285-298)
(A) Schizophrenics show increased DLPFC activation in high load condition (five targets).
(B) When task performance is matched by comparing schizophrenics in low load condition
(two targets) to controls in high load condition (five targets), DLPFC activation does not
differ.
(C) If WM load was increased, one would expect relative hypofrontality in schizophrenia.
(D) If the WM capacity of controls were exceeded, they might show reduced activation.
SPECT & PET dopamine - ligand studies
Dopamine D2 receptor numbers are increased
• effect size 1.47 in 17 PM & PET studies (Zakzanis, Schizo Res
1998; 32: 201-6)
• by 12% in 13 imaging studies… (Laruelle, QJ Nucl Med 1998; 42:
211-21)
• with moderate increases in both DA D2 density (Bmax)
and affinity (Kd) (Kestler et al Behav Pharmacol 2001; 12: 355-71)
Presynaptic dopaminergic function increased in striatum
• …with greater amphet. DA release and DOPA decarb.
activity (Laruelle, QJ Nucl Med 1998; 42: 211-21)
• Striatal F-DOPA uptake and DOPA decarb. activity is
increased in schizophrenia (e.g. Meyer-Lindenberg et al.
2002, replicates four previous reports)
Trends in functional imaging of schizophrenia
• Testing the dis-connectivity hypothesis
• Examining relatives and genetic / symptomatic high risk
subjects
• Genetic imaging
• Computational modelling
• Testing more specific hypotheses in activation studies
e.g. fearful face processing, associative learning
• ‘Default mode’ resting studies
• ‘Biomarkers’ and other ‘Translational studies’
PET and/or fMRI replicated
pre-frontal… functional disconnectivity
• Less DLPFC reduction of (left) STG metabolism during
verbal fluency on PET (Frith, 1995, Br J Psychiatry) and fMRI
(Yurgulun-Todd et al, 1996)
• Abnormal anterior cingulate dopaminergic modulation of
STG activity on PET (*Dolan, Nature 1996 378:180-2; Fletcher,
1996 1998 & 1999)
• Reduced (left) DLPFC-STG functional connectivity
correlates with auditory hallucinations on fMRI
(Lawrie, Biol Psychiatry 2002; Shergill, 2003)
• Widespread disconectivities at rest and on activation
including reduced fronto-temporal and fronto-parietal
connectivities with both PET and fMRI (Meyer-Lindenburg,
2001 & 2005; Kim et al 2003; Foucher, 2005)
Other replicated disconnectivities
1. Reduced EEG coherence
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Including reduced fronto-temporal coherence and hallucinations (Norman 1997; Ford
2002)
2. Effective connectivity on PET/fMRI:
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Different AC-fronto-temporal interactions on PET (Jennings 1998)
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Disease and medication related changes in Fronto-fronto/-parietal/-thalamo-cerebellar
networks on fMRI (Schlosser, 2003 Schizo Res)
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PET D2 binding path connections reduced in AC to frontal, parietal and thalamus
regions with no Papez connectviity (Yasuno, 2005 PR:NI)
3. Increased ‘weirdness’ on fMRI (Welchew 2002) and signal variability on EEG (Winterer
2000) and MEG (Ioannides 2004)
4. Reduced (shortened) EEG ‘microstates’ (spontaneous concatenations) at rest (Koenig
1999; Lehmann 2005)
5. Abnormal gamma-band oscillation and synchronisation (Spencer 2003&4; Symond 2005)
Overall, several EEG, PET and fMRI studies find disturbances in functional and
effective connectivity within and from pre-frontal lobes (Stephan et al Biol Psych 2006)
Functional imaging in relatives
‘Hypo-’ & compensatory ‘Hyper-’ frontality
• Berman (1992) – Sch twins hypofrontal on WCST
• Blackwood (1999) – reduced L-IPFC & AC at rest
• O’Driscoll (1999) – NS diffs in 17 relatives
• Spence (2000) – NS diffs in 10 ‘obligates’
• Keshavan (2002) – reduced BOLD in DLPFC &
IPC on MGS task
• Callicott (2003) – (R)DLPFC increased BOLD on
matched N-back task
• Thermenos (2004) – increased BOLD in (L)
DLPFC, AC, thalamus & PHG on CPT
• Whalley (2004) – increased parietal & reduced
front-thalamo-cerebellar BOLD on HSCT (etc)
• Seidman (2005) - exaggerated fMRI response in
DLPFC on auditory WM
Disconnectivity
Replicated reduced fronto-frontal connectivity on
SPET (Spence, 2000) and fMRI (Whalley, 2005)
Electrophysiology
Bramon (2005) pooled 472 relatives & 513 controls:
- P300 amplitude reduced (PSES 0.61, 0.30 to 0.91)
- P300 latency delayed (PSES -0.50; -0.88 to -0.13)
In a series of studies Winterer et al (2001, 2003, 2004)
have internally replicated reduced EEG coherence
and increased variance / reduced STN in relatives
fMRI in the Edinburgh High Risk Study
- results with the Hayling sentence completion test
• Reduced fronto-thalamo-cerebellar activation in all at genetic high
risk & Increased parietal activation in those with psychotic
symptoms (Whalley, Brain 2004)
• Increased fronto-thalamo-cerebellar functional connectivity but no
alteration in fronto-temporal connectivity (Whalley, Brain 2005)
• Increased parietal, reduced lingual and reduced MTL/STG
activation predicts onset of schizophrenia 1-15 months later
(Whalley, Biol Psychiatry 2005)
• Individuals homozygous for the risk allele (T/T) of the Neuregulin
1 (SNP8NRG243177) all developed psychotic symptoms, had
reduced NART scores and decreased activation of right medial
PFC and right posterior MTG (Hall et al Nature Neuroscience, 2006)
COMT Val > Met differences for parametric contrast
19 MM
29 MV
9 VV
High Risk subjects with the
COMT Val allele also had
reduced grey matter density in
anterior cingulate cortex and a
greater risk of becoming ill
(McIntosh et al, Biological
Psychiatry 2007; 61:1127-34).
Bipolar Disorder
Cyclical
Depression
Mania
Disinhibition
Elevated mood
Schizophrenia
Mood disturbance
Delusions
Delusions
Disorganisation
Hallucinations
Negative symptoms
No biological parameter defines either illness
Bipolar Disorder
Schizophrenia
Structure
↓ ventral PFC
↑ amygdala
Structure
↓ thalamus
↓ HPC
↓ medial PFC
Structure
↓ dorsal > ventral PFC
↓ amygdala / MTL
Function
↑↓ ventral PFC
↑↓ ventral striatum
↑ amygdala
Function
↓↑ Cingulate
Function
↓↑ dorsal PFC
↓↑ striatum
↓↑ amygdala
Overall Conclusions
• The gross structural neuroanatomy of schizophrenia…is evident to
some extent in those at high risk and further MTL reductions are
likely around onset…but it is at least partly non-specific and of
largely unknown cause(s)
WE NEED:
#1 More longitudinal sMRI studies within 5 years of onset
#2 Urgent harmonisation of multi-centre sMRI and approaches to DTI acquisition and
analysis
• The functional neuroanatomy of schizophrenia involves
hypofrontality, and dopamine modulated striatal abnormalities and
(symptom related) fronto-temporal disconnectivity
WE NEED:
#1 Functional imaging studies which examine performance at multiple points across the loadresponse curve, with and without pharmacological challenge
#2 Harmonisation of approaches to functional and effective connectivity analyses, for EEG,
MEG & fMRI, with a view to integration with DTI (and sMRI)