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Motivation

Arterial Spin Labeling Qualifying Exam Oral Presentation Ajna Borogovac Department of Biomedical Engineering Columbia University. Motivation. Perfusion: Delivery of nutrients and oxygen to brain Patho-physiological correlate Viability of ischemic tissue Applications:

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Motivation

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  1. Arterial Spin LabelingQualifying Exam Oral PresentationAjna BorogovacDepartment of Biomedical EngineeringColumbia University

  2. Motivation • Perfusion: • Delivery of nutrients and oxygen to brain • Patho-physiological correlate • Viability of ischemic tissue • Applications: • Quantify damage due to vascular diseases (e.g. cancer, stroke) • Longitudinal perfusion studies • Disease progression • Drug/treatment efficacy • Brain function – activation studies

  3. Overview • Arterial Spin Labeling (ASL) • Technique overview • Quantification of CBF • ASL Applications • Clinical studies of pathology • Functional Imaging

  4. CASL DM CONTROL LABEL

  5. PASL DM CONTROL LABEL

  6. ASL Technique Overview • Inverted blood flows through vasculature and exchanges with tissue. • Inflow reduces total tissue magnetization in slice (~1%) compared to control. • “Control” – “Labeled”  CBF

  7. CASL vs. PASL • Absolute quantification of CBF more straight forward • SNR higher • Whole brain coverage • But, more affected by Magnetization Transfer (MT) effects We focus on CASL!

  8. Tracer Kinetics Theory – Kety Schmidt Method Buxton’s Model: Tissue signal = Arterial signalTissue response M = control-label tissue magnetization f = CBF Ma,0= arterial equilibrium magnetization c(t)=exp(-a/T1a) =Inflow function r(t-t’)=exp(-f(t-t’)/) =Residual function m(t-t’)= exp(-(t-t’)/T1t) = T1 decay function T1a =Longitudinal relaxation of blood T1t = Longitudinal relaxation of tissue a = Arterial transit time  = Blood-tissue partition coefficient Buxton et al., MRM, 40:383(1998)

  9. Buxton’s Model (Cont.) • Assuming plug flow and a single vascular compartment: M(t)=0 t<a =2MaoT1appfe-a/T1a(1-e -(t- a)/T1app) a<t<a+ =2MaoT1appfe-a/T1a e-(t--a)/T1app(1- e -/T1app) t>a+ T1app=1/T1t+f/l Buxton et al., MRM, 40:383(1998)

  10. Advanced Models • Optimize model for inflow, residual and T1 decay functions • Acquire images after a PLD to decrease sensitivity to da • Account for off-resonance effects

  11. Advanced Models • Optimize model for inflow, residual and T1 decay functions • Smoother inflow function due to range of transit times • Finite blood tissue exchange rate, Incomplete extraction of water • Account for different T1 in vascular and tissue compartments

  12. Advanced Models • Decrease sensitivity to arterial transit time: Insert Post Labeling Delay (PLD)>da before imaging Alsop et al. J. CBF & Met. 16 (1996)

  13. Advanced Models +

  14. Advanced Models • Account for off-resonance effects. Long off-resonance tagging saturates macromolecule bound protons. Saturated protons exchange with free water: Magnetization Transfer (MT) Solution: Acquire Control in presence of a long RF pulse Correct CBF estimation: T1app = T1s during tagging T1app = T1ns otherwise. Place labeling plane farther from imaging volume

  15. CASL CBF Calculation • Solve previously derived equations for f: • Obtain direct measurement of CBF in mL/100g*min

  16. Applications • Study baseline effects of a disease/drug on CBF • Alzheimer’s Disease • Functional MRI (fMRI) • Quantify vascular response to stimulus • Activation due to motor task • Activation due to olfactory stimulus • Longitudinal activation study • Sleep Deprivation

  17. Alzheimer’s Disease • Nerve degeneration, hypometabolism • Alsop et al. and our CASL study showed marked, widespread hypoperfusion present in AD group • Voxelwise (Healthy – AD) perfusion maps • ROI analysis Alsop et al

  18. Alzheimer’s Disease • Alsop Study • Used Gradient Echo (GE) sequence • Mini-mental state examination (MMSE) score = 20.8 ± 7 • Studied only several global ROIs • ROIs were hand-drawn on a single subject • Incomplete brain coverage • Our Study: • Used spin echo (SE) sequence • Higher MMSE score = 38.6 ± 7 • More ROIs, many small gray matter structures • Used publicly available atlas • More brain coverage • Included multivariate analysis

  19. Image Processing

  20. Voxelwise difference in CBF between AD and Healthy Controls Our Study Alsop et al Study Yellow: p<0.001 uncorrected Red: p<0.01 uncorrected Yellow: p<0.01 uncorrected Red: p<0.05 corrected

  21. Our Study: ROI Analysis

  22. Covariance Analysis of AD Study CASL data CASL cov. pattern applied to PET data

  23. CASL advantages over BOLD fMRI • Provides absolute quantification of CBF BOLD signal = coupled effect of CBF, CMRO2, CBV CASL has better localization • Quantifies resting and activated CBF BOLD can only measure activated states • Flat power spectra allows low-frequency fMRI BOLD negatively affected by 1/f noise • Insensitive to magnetic susceptibility effects BOLD signal based on susceptibility effects • Lower inter-subject variability than BOLD

  24. 3. CASL flat power spectra allows low-frequency fMRI Avg. across-subject, voxel average power spectra for BOLD and perfusion data. Aguirre et al., Neuroimage (2002)

  25. 3. CASL flat power spectra allows low-frequency fMRI Finger Tapping High frequency (1min) Task Activation Low Frequency (24hr) Task Activation Wang et al. Our experiment

  26. 3. CASL flat power spectra allows low-frequency fMRI Effect of 48hrs Sleep Deprivation on CASL CBF Good Agreement with PET:

  27. 4. CASL insensitivity to susceptibility effects • BOLD relies on susceptibility changes -> Requires Gradient Echo sequence (T2* weighted) • CASL signal is not based on susceptibility. -> Can use Spin Echo sequence (T2 weighted)

  28. Olfaction Study 4. CASL insensitivity to susceptibility effects • CASL (our experiment) BOLD (Poellinger et al.)

  29. 5. Reduced inter-subject variability • Group data more signicicant with perfusion than BOLD • ROI in visual cortex, T-values across subjects Aguirre, G.K. et al. Neuroimage

  30. Future Directions • Imaging at 3T • Benefits: Longer T1 relaxation  Higher Signal • Downside: Shorter coil • PASL at 3T • Regional Perfusion Imaging Techniques • Optimization of acquisition parameters to increase SNR • Separate Coils and/or SENSE coil

  31. Acknowledgements • Iris Asllani, PhD • Eric Zarahn, PhD • John Krakauer, MD • Christian Habeck, PhD • Truman Brown, PhD

  32. Normalization/Coregistration Issues

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