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Imaging Cognitive States and Traits with BOLD and Perfusion fMRI

Imaging Cognitive States and Traits with BOLD and Perfusion fMRI

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Imaging Cognitive States and Traits with BOLD and Perfusion fMRI

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  1. Imaging Cognitive States and Traits with BOLD and Perfusion fMRI John A. Detre, M.D. Director, Center for Functional Neuroimaging University of Pennsylvania

  2. Neuroimaging • Allows noninvasive assessment of brain structure and function • Is the primary means of assessing regional brain function in humans • Provides a critical link between animal models and human brain • Complements lesion-based inferences on brain-behavior correlations

  3. Imaging is Critical for Human Brain Research ? Some Guy

  4. Physiology of Functional Activation ??? Magistretti, Brain Res. 2000

  5. PET CBF, CMRGlu, and CMRO2 during ActivationFox and Raichle, PNAS 1986 • Increase in CBF and CMRGlu with minimal change in CMRO2 • Suggests uncoupling of oxidative metabolism during activation

  6. Magnetic Resonance (1H) + + = + structure fiber tracts blood flow task activation metabolites

  7. Brain Mapping with fMRI • Noninvasive; Ideal for serial studies • Comparatively inexpensive, widely available • Time-series data provides improved sensitivity within individual subjects (vs. PET pseudosubject) • Group sensitivity (Random Effects Model) similar to PET • Fundamentally correlative (does not prove necessity or sufficiency) • Hemodynamic/metabolic response used as surrogate marker for neural activity (same as PET)

  8. Contrast Mechanisms for fMRI • Blood Oxygenation Level Dependent (BOLD) fMRI • represents a complex interaction between CBF, CBV, CMRO2 • CBF >> CMRO2 less deoxyhemoglobin with activation • Qualitative: only differences between conditions can be measured • Arterial spin labeling (ASL) provides an endogenous flow tracer for perfusion MRI • Directly analogous to 15O-H2O in PET • Allow both resting CBF and CBF changes to be measured • Quantitative: provides CBF in ml/100g/min • CBF obtained by modeling image intensity with and without ASL • CBF changes may be better localized than BOLD • CBF changes may be more linearly coupled with neural activity than BOLD • ASL/Control scheme yields “white” noise, provides temporal stability and other benefits

  9. T2*-weighted Snapshot Image Average Difference Image Statistical Significance Image Thresholded Statistical Image Overlay on T1 Anatomic Image Brain Activation Analysis TIME SERIES ON TASK OFF fMRI SIGNAL

  10. FMRI with BOLD Contrasttask activation Photic Stimulation Verbal Fluency Task calcarine cortex Broca’s area Wernicke’s area

  11. Perfusion MRI with Arterial Spin Labeling (ASL) • Uses magnetically labeled arterial blood water as an endogenous flow tracer • Provides quantifiable CBF in classical units (ml/g/min) • Effects of ASL are measured by interleaved subtractive comparison with control labeling • ASL effects can be measured with any imaging sequence • CBF calculated using model (diffusible tracer)

  12. Perfusion in the Steady Statefrom J.H. Wood (ed.) Cerebral Blood Flow dCt/dt = F.Ca - F.Cv - Ct dCt/dt = F.Ca - F.Ct/ - Ct = 0 f= /(Ca/Ct - 1/) • Requires tracer with decay  (such as 15-O for PET)

  13. Quantification of regional CBF with ASL • Requires a model for determining CBF from measured signals • Other key parameters are T1blood, T1brain, arterial transit time, • Some models also require  (blood:brain partition coefficient) • Single compartment model (Detre 1992) • Assumes ASL in well-mixed equilibrium with brain (Kety-Schmidt) • Two compartment model (Alsop 1996) • Includes arterial blood water compartment with arterial transit time • Modified two compartment model (Chalela 2000) • *Assumes labeled spins remain in vasculature (relax with T1blood) • Three compartment model (Parkes 2002) • Includes limited diffusion and venous component • Identical results with kinetic model (Buxton 1998) • Microsphere analogy (Buxton 2005) • Emphasizes rapid tracer decay

  14. ASL in Human Brain: 2 Comparment Model Flow is exponentially dependent on transit time Transit times in human brain are comparable to T1 Postlabeling delay allows labeled water to reach tissue Rat Brain Wiliams et al., PNAS 1992 Human Brain Roberts et al., PNAS 1994 Alsop and Detre, JCBFM 1996

  15. Control - Label Single Slice Perfusion Image about 1% effect Perfusion MRI with Arterial Spin LabelingDetre et al., Magn. Reson. Med. 1992 and ff Control Inversion Plane B Field Gradient Imaging Slice Arterial Tagging Plane Continuous Adiabatic Inversion Geometry CBF in “classical” units of ml/100g/min

  16. 15O-PET Validation of CASL (2 compartment)Ye et al., Magn Reson Med 2000 CASL PET

  17. Key Technical Advances in ASL Initial demonstration of ASL (pseudocontinuous saturation in rat) Detre et al., MRM 1992 Continuous inversion ASL (velocity driven adiabatic inversion=CASL) Williams et al., PNAS 1992 Human ASL (single slice CASL) Roberts et al., PNAS 1994 Transit time correction (postlabeling delay) Alsop and Detre, JBCFM 1998 Multislice (amplitude modulated control inversion) Alsop and Detre, Radiology 1998 Background suppression (nulling static signal) Ye et al., MRM 2000 High Field Benefits - T1 and SNR (1.5T vs. 4T) Wang et al., MRM 2002 Wang et. Al., Radiology 2004 Multicoil/Parallel Imaging (hybrid coil) Wang et al, MRM 2005 Snapshot 3D Imaging (FSE and GRASE) Duhamel and Alsop, ISMRM abstracts 2004 Fernandez-Seara et al., MRM 2005 Improved Labeling (Pseudocontinuous ASL) Garcia et al., ISMRM abstracts 2005 Total ~10X SNR Gains over the past decade

  18. neural function disease biophysics*** blood volume Physiological Basis of fMRI behavior metabolism BOLD fMRI ASL MRI blood flow ***site/scan effects

  19. ASL vs. BOLDLocalization of Functional Contrast Perfusion Perfusion Activation BOLD Activation BOLD

  20. BOLD CBF 1 BOLD-CBF BOLD-Mn++ CBF-Mn++ 2 OVERLAP 12 Cortical Localization; Rat Forepaw StimulationDuong et al., Magn. Reson. Med., 2000 Mn++

  21. Temporal Characteristics of Perfusion fMRI • Control/Label pair typically every 4-8 sec • “Turbo” ASL (Wong) can increase resolution by ~50% • Qualitative CBF (no control) in ~2 sec • S:N much lower than BOLD for event-related fMRI • Control/Label pair eliminates drift effects • White noise (instead of 1/f) • Stable over long durations (learning, behavioral state changes, pharmacological challenge etc.) • Sinc subtraction eliminates BOLD derivative

  22. Event-Related ASL • Event-related ASL possible • e.g. Yang NeuroImage 2000 and ff • Nominally less sensitive than BOLD • However, CBF>> BOLD signal • BS-ASL provides improved sensitivity • Temporal resolution lower than BOLD • Can use label-only for CBF • Can use “turbo” ASL (Wong) for limited slice coverage • Activation peaks faster than BOLD • Demonstrated with jittered acquisition • Consistent with capillary/tissue sensitivity from Huppert et al., NeuroImage 2006

  23. Statistical power as a function of frequency of experimental design Observed power spectra 12 10 8 6 4 2 0 perfusion fMRI is superior to BOLD for detecting neural activity that evolves over 60 seconds or greater 0.15 0.1 0.05 0 BOLD perfusion perfusion fMRI observations are independent in time BOLD perfusion normalized power delta value 0 0.025 0.05 0.075 0.1 0.125 0 0.025 0.05 0.075 0.1 0.125 freq (Hz) freq (Hz) BOLD vs. ASL: Noise SpectraAguirre, NeuroImage 2002

  24. Concurrent ASL and BOLDWong et al., NMR Biomed 1997 and ff ASL with GE EPI Control-tag=CBF Control+tag=BOLD

  25. ASL 24 hr Perfusion vs. BOLD: Very Low Task FrequencyWang et al., MRM 2002

  26. ASL Perfusion fMRI vs. BOLDImproved Intersubject Variability vs. BOLD Group (Random Effects) Single Subject Aguirre et al., NeuroImage 2002

  27. ASL fMRI of Motor Learning Olson et al., Brain and Cognition 2005 sequence learning transfer fixation1 fixation2 2.5min 15min 5min 2.5min Right premotor Right superior temporal Right inferior parietal • Motor sequence learning (SRT) • N=10, 3 X 25 min runs/subject

  28. Developmental Changes in CBFWang et al., JMRI 2003 and ff • Mean CBF images for: • child group (age 5-10, n=31) • adolescent group (age 11-16, n=33) • young adult group (age 18-30, n=26) Age-related regional CBF changes in cingulate, angular, hippocampus, and frontal cortex. A multicenter, longitudinal and cross-sectional study of ages 7-16 was recently funded

  29. ASL Perfusion of Psychological Stress Wang et al., PNAS 2005 • 25 Subjects • 4 x 8min CASL perfusion scans: • Rest • Low stress (Counting backward) • High stress (Serial subtraction by 13) • Rest • Self rating of stress, anxiety and salivary cortisol with each scan • Heart rate continuously recorded

  30. Wang et al., Soc Cog Affect Neurosci 2007 Correlation of CBF and Perceived Stress: RPFC

  31. Imaging Genotype: 5-HTTLPRHariri et al., Science 2002 Allelic variations in serotonin transporter genes are associated with anxiety-related traits and risk of depression (short allele carries greater risk) BOLD fMRI demonstrates that carriers of s allele (vs. l/l) show greater amygdala activation in response to fearful faces

  32. Resting Brain Function vs.5-HTTLPR Genotype Rao et al., Biol Psychiatry 2007 • N=26 healthy volunteers • rCBF vs. 5-HTTLRP Genotype

  33. fMRI Studies of the Neural Substrate for Risk Risk is a ubiquitous phenomenon Risk may be assumed or environmental Some amount of risk-taking is likely beneficial to advancement Excessive risk-taking may underlie impulse-control disorders such as drug abuse and gambling Behavioral economics is a “hot” area in social neurobiology that considers human decision-making according to principles of risk and reward.

  34. Balloon Analog Risk Task (BART) Lejuez et al., J Exp Psychol Appl 2002 • Developed as a behavioral index to predict risky behaviors • - Correlates with real-world risky behavior e.g. smoking, seat belt use etc. • Participants are told to press the “pump” button to inflate the balloon. • The balloon will explode at some point (between 1st – fill the screen, e.g., 128th). • Typically 30 balloons • Participants earn 5¢ per pump placed to a temporary bank. • If balloon explode, participants lose all money in temporary bank • Participants hit collect button to earn the money in temporary bank • Participants were paid an amount proportional to what they earn A screen shot of BART.

  35. fMRI BART Pump End with explosion -- lose End without explosion -- win Pump End with explosion -- lose End without explosion -- win Wager: XXX Total: XXX • Modified for fMRI with improved graphics, reduced trials, increasing risk/reward • Active and passive modes • Can segregate trial effects from risk/reward covariate

  36. Neural Correlates on Voluntary and Involuntary Risk Rao et al;., Neuroimage 2008

  37. Neural Correlates of Individual Differences in Risk Tolerance R L

  38. Resting CBF Predicts Risk Tolerance N=12 healthy controls (of 14 studied for fMRI) pCASL acquired prior to fMRI task

  39. 20 m PVT 4m 4m rest1 rest2 • 15 young, healthy right-handed adults (23 ± 4 years, 8 male) • Pseudo-continuous ASL with TR = 4 s, labeling time = 1.8 s, post-labeling delay = 1 s • 20 min PVT flanked by 5 min rest • Visual analog ratings of subjective fatigue prior to and immediately after the PVT scan ASL fMRI: Pyschomotor Vigilance TaskRao et al., ISMRM 2008 Example of quantitative CBF image from one subject

  40. Behavioral Results • Significant TOT effects were observed during the PVT: • Mental fatigue (MF) scores increased from 3.7 before the task to 5.1 after the task (36% change; p < 0.001) • Reaction times increased from 284ms for the first 10min to 302 ms for the second 10 min (6.3%; p = 0.002)

  41. MRI Results: Regional CBF Changes PVT vs. Rest A right parietal-cingulate-frontal network, the left sensorimotor cortex, and bilateral basal ganglia were activated by the PVT task. PVT vs. Rest (FDR p < 0.05)

  42. Regional CBF: Predictors of RT Change r = 0.67, p = 0.009 r = 0.56, p = 0.04 During PVT, regional CBF changes (CBF%) in thalamus and ACC correlated with the performance decline (RT%)

  43. r = -0.74, p = 0.002 MRI Results: Post-task rest vs. Pre-task rest r = -0.66, p = 0.01 r = -0.59, p = 0.03 The parietal-cingulate-frontal network was deactivated after prolonged PVT task, and the deactivations correlated with RT%.

  44. Regional CBF at Baseline: Predictors of RT(Brain State/Phenotype) r = 0.68, p = 0.008 r = -0.59, p = 0.03 Before the PVT task, regional CBF activity (normalized to global CBF) in thalamus and right MFC predicted the subsequent performance decline (RT%).

  45. ASL CBF as a Biomarker of Brain Function • Can measure “function” during rest, state, or task • Can measure cognitive, affective, or pharmacological state • Also shows correlations with genotype/phenotype (traits) • Complementary to BOLD fMRI studies of “events” • Quantifies a biological parameter (CBF) • CBF coupled to neural activity (both magnitude and location) • CBF is better localized than BOLD (so far only for animal studies) • Theoretically insensitive to scanning parameters, scanner platform, and field strength - should be ideal for multisite or longitudinal studies • Future Directions • Optimization of the “resting” state • Ultra-high field ASL to improve sensitivity

  46. Functional Imaging TimescalesComplementary Utility of BOLD and ASL ASL fMRI BOLD fMRI • BOLD fMRI optimal for events and short blocks (< few min) • Unable to characterize states except as manifested in event/block activation • ASL fMRI optimal for behavioral ‘states’ or stable ‘traits’ • Independent of biophysical effects - should be stable across time, platform • Less well suited to characterizing events due to lower SNR EVENT BLOCK BEHAVIORAL STATE TRAIT 100 msec 10 sec 1 hr 1 day log time FDG-PET 15O-PET

  47. “Brainomics” • Richness of neuroimaging data allow brain-behavior correlations to be detected through statistical analysis without a hypothesis • Can examine structure and/or function • ASL provides ideal functional modality for this – not constrained by task • Analogous to approach used in molecular biology to find gene/function or gene/disorder correlations • For brain imaging data, added benefit of meaningful spatial organization Gene Chip Array A Priori Knowledge of Local and Distributed Networks