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BOLD fMRI John VanMeter, Ph.D. Center for Functional and Molecular Imaging

BOLD fMRI John VanMeter, Ph.D. Center for Functional and Molecular Imaging Georgetown University Medical Center. Outline. BOLD contrast fMRI conceptually Relationship between BOLD contrast and hemodynamics History of BOLD contrast

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BOLD fMRI John VanMeter, Ph.D. Center for Functional and Molecular Imaging

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  1. BOLD fMRI • John VanMeter, Ph.D. • Center for Functional and Molecular Imaging • Georgetown University Medical Center

  2. Outline • BOLD contrast fMRI conceptually • Relationship between BOLD contrast and hemodynamics • History of BOLD contrast • Relationship between neuronal glucose metabolism and blood flow • Theories and properties of BOLD contrast mechanisms

  3. Neuronal Activity and Blood Flow Changes: Initial Hypothesis • Roy and Sherrington hypothesized that local neuronal activity is related to regional changes in both cerebral blood flow and metabolism (1890). • “There are, then, two more or less distinct mechanisms for controlling the cerebral circulation, viz. - firstly, an intrinsic one by which the blood supply of the various parts of the brain can be varied locally in accordance with local requirements, and secondly, an extrinsic, viz. - the vasomotor nervous system…”

  4. Roy and Sherrington’s Experiments “… the increase in the volume of the brain which results from stimulation of the sensory nerves is mainly if not entirely due to passive or elastic distension of its vessels as a result of the blood-pressure in the systemic arteries.”

  5. History of BOLD fMRI • Initial discovery of magnetic properties of blood by Linus Pauling and graduate student Charles Coryell (1936): • Magnetic properties of a blood cell (hemoglobin) depends on whether it has an oxygen molecule • With oxygen  zero magnetic moment • Without oxygen  sizeable magnetic moment

  6. Initial In Vivo Measurement of Neuronal Activity • Initial techniques used PET (positron emission tomography) • PET uses injection of a radiotracers which are variants of physiological molecules that include a radio isotope • FDG (2-fluoro-2deoxy-D-glucose) for glucose metabolism • H2015 for blood flow

  7. Functional Imaging - PET • Sokoloff demonstrated that rCBF (blood flow) increases in visual cortex in proportion to photic stimulation using PET (1961). • Demonstrated “coupling” between blood flow and metabolism (1981).

  8. Relationship Between Glucose Metabolism and Blood Flow • Sokoloff (1981) used autoradiography • Measured both glucose metabolism and blood flow • 39 brain regions in rat brain • Correlation r=0.95 • Slope m=2.6

  9. First MRI-based Measurement of Neuronal Activity • Belliveau (1990) used MRI contrast agent Gadolinium as an exogenous tracer • Gadolinium locally disrupts MRI signal • Perfusion weighted imaging (PWI)

  10. Oxy- vs. Deoxy- Hemoglobin • Oxygenated hemoglobin (Hb) isdiamagnetic (zero magnetic moment) • Deoxygenated hemoglobin (dHb) isparamagnetic (magnetic moment) • Magnetic susceptibility of dHb is about 20% greater than Hb • Magnetic susceptibility affects rate of dephasing - T2 and T2* contrast!

  11. T1 & T2 Contrast Versus Oxygenated Hemoglobin

  12. Demonstration of BOLD Contrast • Seiji Ogawa (1990) manipulates oxygen content of air breathed by rats • Results in variation of oxygenated state of blood • Demonstrates effect on T2* contrast to make images of blood vessels

  13. Ogawa’s Images of Blood Vessels Based on Oxygen Content Pure oxygen Normal Air

  14. Magnetic Susceptibility Greater on T2* than T2 Images Spin Gradient Echo (T2) Echo (T2*) Oxygenated Hemoglobin Deoxygenated Hemoglobin

  15. Oxygenation vs Local Field Changes Bandettini and Wong. Int. J. Imaging Systems and Technology. 6:133 (1995)

  16. First fMRI BOLD in Human • Kwong (1992) demonstrated first BOLD-contrast fMRI in human visual cortex

  17. Blood Flow vs BOLD Changes • Kwong also showed how changes in BOLD corresponded to changes in blood flow • Important to show that BOLD and blood are related

  18. Build Up to BOLD Contrast • Hypothesis of relationship between blood flow and activity (Roy & Sherrington, 1890) • Discovery of differential magnetic properties of oxygenated and deoxygenated hemoglobin (Pauling, 1936) • Blood flow increases with activity (Sokoloff, 1961) • Blood flow correlated with glucose metabolism (Sokoloff, 1981) • Demonstration of blood flow measured using MRI with an exogenous tracer (Belliveau, 1990) • Demonstration of effect of dHb on T2* contrast (Ogawa, 1990) use of blood as an endogenous tracer • Generation of first BOLD images (Ogawa, 1990) • First BOLD images in humans (Kwong, 1992)

  19. WHY DOES MRI SIGNAL INCREASE? Basic Model of Relationship Between BOLD fMRI & Neuronal Activity

  20. Disparity Between Blood Flow & Oxygen Consumption • Fox & Raichle conducted PET experiments to measure glucose metabolism (CMRglu), blood flow (CBF), and rate of oxygen metabolism (CMRO2) • Measured percent change between visual stimulation and rest • Increase in CBF=50%, CMRglu=51% • But increase in CMRO2 is only 5%!! • Implies anaerobic metabolism of glucose

  21. Disparity & MRI Signal Increase • Upshot of Fox & Raichle: much more oxygen (CBF) is supplied than is used (CMRO2) • While neuronal activity results in more deoxygenated hemoglobin much more oxygenated hemoglobin flows in flushing out deoxygenated hemoglobin • Result is a decrease in dHB and thus an increase in MRI signal • But there’s uncoupling of glucose metabolism and oxygen metabolism - WHY?

  22. Uncoupling Problematic • Fox & Raichle data nicely explains why MRI signal increases with neuronal activity • But a new problem is presented: uncoupling of glucose and oxygen metabolism • We expect a 6:1 ratio of oxygen-to-glucose (OGI) for aerobic glycolysis but F&R saw about 1:10 • Implication is anaerobic glycolysis is used

  23. Theories to Explain Uncoupling Found by Fox & Raichle • Watering the Garden for the Sake of One Thirsty Flower • Astrocyte-Neuron Lactate Shuttle Model • Transit Time and Oxygen Extraction

  24. Separate Measurement of Oxy & Deoxy Hemoglobin • Malonek & Grinvald used optical imaging to measure Hb and dHb separately during visual stimulation • dHb spatially focal and co-located to neuronal activity • Hb more widely distributed

  25. Implications of Differences in Concentration of Hb & dHb • Rapid increase in dHb implies oxidative metabolism initially • High spatial correspondence between initial dHb increase and neuronal activity • Coarse spatial correspondence and greater extent of delivery of Hb

  26. Theories to Explain Uncoupling Found by Fox & Raichle • Watering the Garden for the Sake of One Thirsty Flower • Astrocyte-Neuron Lactate Shuttle Model • Transit Time and Oxygen Extraction (extended to Balloon Model) • Aerobic glycolysis already near max at rest thus activity requires quick increase in energy via anaerobic glycolysis (Prichard, 1991)

  27. Watering the Garden • According to this model uncoupling observed by Fox & Raichle does not imply anaerobic glycolysis • Instead Malonek & Grinvald’s data shows hugeexcess of freshly oxygenated hemoglobin spread over a wide area displacing deoxygenated hemoglobin • But CMRglu wasn’t measured; still haven’t explained why Fox & Raichle gets a 1:10 versus expected 6:1 OGI

  28. Astrocyte-Neuron Lactate Shuttle Model • Initially anaerobic glycolysis occurs producing excess glutamate (consistent with Fox & Raichle) • Glutamate taken up by astrocyte to prevent toxicity and converted to glutamine which neuron can reuse • Delicate balance is achieved by astrocyte through intake of Na+ produced by sodium-potassium pump of neuron • Astrocyte uses 2 ATP molecules • Great because that’s all the ATP available! • But where’s the ATP for the neuron?

  29. ANLS Model (cont’d) • Astrocyte dumps resulting lactate, which diffuses into neuron that turns into pyruvate and into TCA cycle to give neuron 36 ATP molecules for neuron’s energy • Thus, we’re back to aerobic glycolysis, which requires 6 molecules of oxygen • Model hypothesizes early anaerobic followed by aerobic glycolysis • Support for this comes from Mintun (2002) who showed uncoupling only occurs with initial onset of stimulus then coupling is reestablished with continued stimulation

  30. Astrocyte-Neuron Lactate Shuttle Model

  31. Transit Time and Oxygen Extraction • Disputes that uncoupling implies anaerobic glycolysis as does Watering the Garden • Model is based on limited time for extraction of oxygen due to increase in velocity of blood flow with neuronal activity

  32. Transit Time and Oxygen Extraction • Model proposed by Buxton (1998) rests on four assumptions: • Increased blood flow accomplished by increase in velocity as opposed pumping more blood through more capillaries • Virtually all oxygen is metabolized • But not all of the glucose is metabolized • Extraction of oxygen from blood by neurons is limited and proportional to transit time Transit time - how long it takes for blood to pass through a given area

  33. Transit Time and Oxygen Extraction • Wouldn’t limited time for extraction of oxygen due to increase in velocity of blood also limit glucose availability? • Buxton - well actually glucose availability is even more limited than oxygen but less than half that is extracted is actually used… • Data from Gjedde (2002) supports glucose part

  34. Balloon Model • No uncoupling of CBF and CMRO2; difference between CBF and CMRO2 lowers oxygen extraction fraction (E) [Fick Principle] • Initial increase in blood flow increases blood volume (ballooning of venous capillary to accommodate) • Predicts an initial dip in BOLD signal Buxton et al. Neuroimage 2004

  35. Uncoupling Problem • Debate continues to this day • Uncoupling problem important to understanding the fundamental basis of fMRI signal • fMRI is an indirect measure of blood flow and is not directly tied to glucose metabolism or even oxygen metabolism • Relationship between mechanisms of metabolism and blood flow is important to understanding how closely related BOLD and blood flow are to neuronal activity

  36. Implications of Theories for Uncoupling • “Watering the Garden” model posits widespread distribution of CBF increase  poor fMRI spatial resolution • “Transit Time” model implies excess oxygen rich blood passing over area of activity getting into venous system  poor fMRI spatial resolution • Both imply a “Draining Vein” problem with dHb flowing downstream of area of activity • Frahm (1994) asked “Brain or Vein?” • Uncoupling issue remains unresolved

  37. Physiological Mechanisms for Regulation of Blood Flow • How is blood flow controlled? • Arterioles well upstream need to respond to produce local changes in blood flow • Mechanism for accomplishing this is largely unknown • Possible candidates include nitrous oxide synthesis, potassium accumulation, generation of lactate, or acetylcholine activity

  38. Initial Dip • Studies used very short TR (100ms) and visual stimulus for 10s at 4T or higher • Menon (1995) found Initial Dip in fMRI signal before expected increase • There’s also a post stimulus undershoot

  39. Spatial Extent of Initial Dip • Voxels with initial dip were more spatially restricted and localized to gray matter around calcarine sulcus

  40. Implications of Initial Dip • Menon suggested dip is directly related to oxygen extraction and thus more closely related to neuronal activity • But dip could also result from temporary decrease in blood flow or increase in blood volume • Initial dip if it occurs is contradictory with anaerobic glycolysis - Why? • Balloon model predicts increase in blood volume and thus consistent with initial dip but for a different reason than Menon posits

  41. HDR (Hemodynamic Response)HRF (Hemodynamic Response Function) • Change in MR signal related to neuronal activity (HRF) • Has multiple components • Changes delayed by 1-2 sec (lags activity) • Initial dip (not always seen) • Influx of Hb greater than needed for activity • 5-6 sec time to peak • Undershoot follows ~6s after peak

  42. Typical HDR for Long Stimulus (Block) • Peak is sustained with prolonged stimulation • Block is also referred to as an epoch • Brief stimulus is referred to as an event

  43. Undershoot • Arises from rapid return to baseline of CBF but delayed return of CBV • Delay in CBV return to baseline results in an accumulation of dHb

  44. BOLD vs Neuronal Activity • Logothetis, et al., 2001 recorded LFP, MUA, SUA, and BOLD simultaneously • BOLD response best explained by changes in LFP • Suggests BOLD reflects “incoming input and local processing rather than spiking activity” • ”The BOLD contrast mechanism directly directly reflects the neural responses elicited by a stimulus.”

  45. Open Questions about Basis of BOLD fMRI • Uncoupling problem - Why does it occur? To what extent? • Is there an Initial Dip? What causes the dip? Is it more localized than the expected signal increase? • What about “Draining Veins”? • How does the arterial system upstream know when and by how much to increase blood flow?

  46. Factors Affecting BOLD Signal • Physiology • Cerebral blood flow (baseline and change) • Metabolic oxygen consumption • Cerebral blood volume • Equipment • Static field strength • Field homogeneity (e.g. shim dependent T2*) • Pulse sequence • Gradient vs spin echo • Echo time, repeat time, flip angle • Resolution

  47. Physiological Baseline • Baseline CBF changes (up for hypercapnia, down for hypocapnia) • But CBF CMRO2 unchanged (probably)(Brown et al JCBFM 2003) • BOLD response  (probably) Cohen et al JCBFM 2002

  48. Spatial & Temporal Properties of BOLD • Spatial resolution - ability to distinguish unique changes in activity from one location to the next • Temporal resolution - ability to distinguish changes across time • Linearity vs Nonlinearity - does combined response to 2 or more events with short ISI (inter-stimulus interval) lead to sum in BOLD response?

  49. Problems With Increasing Spatial Resolution • Increased spatial resolution results in smaller voxels • Fewer protons so less MRI signal • Less dHb thus more noise in BOLD fMRI signal • Degree of activation varies by brain region with greater activation in sensorimotor areas and less in frontal and association cortices • Smaller voxels ultimately make detecting changes harder

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