Declaration of Conflict of Interest or Relationship

1. Declaration of Conflict of Interest or Relationship Speaker Name: Thomas Liu I have no conflicts of interest to disclose with regard to the subject matter of this presentation.

2. Thomas LiuUniversity of California, San DiegoMay 4, 2008 Functional MRISignal Interpretation and Calibration

3. Topics • BOLD signal model • Sources of Variability and Confounds • Normalization Methods • Calibration Methods

4. BOLD Contrast Source: Ogawa et al., 1992

5. Baseline Signal Activation Signal TE BOLD Signal Change

6. Field Maps B0 More dHB Less dHB Hemoglobin and Field Inhomogeneities Oxygen binds to the iron atoms to form oxyhemoglobin HbO2 Release of O2 to tissue results in deoxyhemoglobin dHBO2 http://www.people.virginia.edu/~rjh9u/hemoglob.html

7. Some dHB, Some dephasing 0 TE time More dHB, More dephasing, Decrease in MR signal Signal Decay

8. Cerebral Blood Volume Large vessels Linear =1 Diffusion around small vessels Quadratic =2 Ogawa et al, 1993 BOLD Signal Equation Simulations suggest  1.5 is a reasonable value Ogawa et al, 1993; Boxerman et al 1995, Hoge et al. 1999

9. CBF [O2]arterial Oxygen extraction fraction (E) CMRO2= E CBF [O2]arterial Blood Flow and Oxygen Metabolism Cerebral Blood Flow (CBF) measures delivery of blood to brain tissue (units of ml/(g-min)) Cerebral Metabolic Rate of (CMRO2)is the rate of oxygen consumption(units of mol/(g-min)) CMRO2

10. O2 [dHB]venous E [O2]arterial / 4 CMRO2 [dHB]venous [dHB]venous CBF Deoxyhemoglobin = CMRO2 / 4CBF

11. CBF dHb CMRO2 CBV CBF CBF dHb CMRO2 dHb CMRO2 CBV CBV fMRI: Spatial Temporal Dynamics capillary bed arteriole venule CBF oxyHb deoxyHb Neural activity CMRO2 Positive BOLD Post-stimulus Response Initial dip

12. Grubb’s Relation;  0.38 Maximal BOLD signal BOLD Signal Equation (Davis Model)

13. Davis Model Hoge et al. 1999

14. Cerebral Blood Volume Cerebral Blood Flow BOLD Signal Metabolism (CMRO2) deoxyHb BOLD Signal Path Neural Activity

15. Interpreting BOLD • Most fMRI studies assume that the BOLD signal is is proportional to brain activity. • This is a reasonable assumption for basic studies of healthy young unmedicated subjects. • However, the assumption is less valid for studies where disease, medication, and age may be a factor. Boynton et al, 1996

16. Variability in BOLD amplitude Data courtesy of J. Liau

17. BOLD Signal Chain Ianetti and Wise, MRI, 2007

18. Effect of Age D’Esposito et al 2003

19. Effects of Vascular Disease D’Esposito et al 2003 Iadecola et al 2003

20. Lower CBF Higher CBF Carbon Dioxide Cohen et al 2002

21. Lower CBF Caffeine Liu et al 2004

22. Interpreting BOLD Ianetti and Wise, MRI, 2007

23. ASL measures of regional baseline CBF Response to Breathhold or CO2; Resting-state Fluctuations Cerebral Blood Volume Cerebral Blood Flow BOLD Signal Metabolism (CMRO2) deoxyHb Trust MRI Measures of whole brain venous oxygenation Neural Activity

24. Yv [dHB]venous BOLD BOLD and Venous Oxygenation Inter-subject Differences in M can lead to inter-subject differences in BOLD TRUST MRI (Lu et al 2007): Measures of whole brain venous oxygenation saturation.

25. Venous Oxygenation (TRUST MRI) Lu, ISMRM 2007

26. TRUST MRI Lu et al, Abstract 855, ISMRM 2008

27. CBF0 M BOLD BOLD dHb BOLD CBF BOLD and Baseline CBF ?

28. BOLD variability and Baseline CBF • M appears to be independent of CBF -- effects of increased CBF and decreased [dHb] appear to cancel out • Variability in the BOLD response across subjects appears to be driven by inter-subject differences in the CBF response. Liau et al, Abstract 854, ISMRM 2008

29. 1 Breathold/Hypercapnic Normalization

30. Breathhold Calibration Breathhold Signal Thomason et al, 2007

31. Breathhold Calibration Thomason et al, 2007

32. Hypercapnic Calibration Cohen et al, 2004

33. Scaling with Resting-State Fluctuations Wise et al 2004;

34. Scaling with Resting-State Fluctuations Birn et al 2006;

35. Scaling with Resting-State Fluctuations Kannapurti and Biswal 2008; also Abstract 750

36. Summary of Normalization Approaches • Additional measures can account for BOLD variability due to variations in baseline blood flow, volume, oxygenation, field strength, etc. • Measures of venous oxygenation, cerebral blood flow, and resting fluctuations have the advantage of not requiring the subject to perform additional tasks. • These approaches offer some insight into the factors that can affect the BOLD response between subjects, groups, and conditions.

37. ASL Signal Cerebral Blood Volume Cerebral Blood Flow BOLD Signal Metabolism (CMRO2) deoxyHb Neural Activity

38. 1 Calibrated fMRI (Davis et al 1998)

39. 2x Block design visual stimulus 2x 5% CO2 Scans 20s 60s 2min air 3min CO2 2min air %∆CBF %∆BOLD M %∆CMRO2 Experimental Protocol

40. Calibrated fMRI Ances et al, NIMG 2007

41. Calibrated fMRI of HIV Ances et al, in preparation

42. %CMRO2 Normalized CMRO2 Young Old Young Old Effect of age on CBF and BOLD Restom et al, NIMG 2007

43. Calibrated fMRI • Can provide insights that BOLD measures alone cannot provide. • Can be difficult to apply to cognitive tasks and special populations, due to low sensitivity of ASL. • The need for breathhold or hypercapnia can also be an issue. Hyperoxia-based method may be an alternative.

44. Conclusions • The BOLD signal is a complex function of the baseline state and changes in blood flow, volume, and metabolism. • Differences in the BOLD signal do NOT always reflect differences in neural activity. • Instead they may reflect differences in the baseline vascular or metabolic state. • Normalization methods can help to reduce inter-subject variability. • Calibrated fMRI can provide additional insights into differences in brain activity, especially in the presence of disease, medication, and age.

45. Acknowledgements Beau Ances Yashar Behzadi Rick Buxton David Dubowitz Joy Liau Oleg Leontiev Joanna Perthen Khaled Restom Eric Wong