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Functional neuro-imaging methods -blood CO 215 , CO 15 , O-O 15 -blood volume Functional neuro-imaging methods -blood CO 215 , CO 15 , O-O 15 -blood volume FDG PET H 2 O 15 flow -metabolism Specific neuro-transmitters -blood flow Optical Signal Imaging -blood volume f. MRI Perfusion with contrast agents Perfusion without contrast agents Blood Oxygenated Level dependence (BOLD) Connectivity EEG MEG

PET Optical Imaging Spatial resolution 4 mm ~50 m Temporal resolution 1 min few PET Optical Imaging Spatial resolution 4 mm ~50 m Temporal resolution 1 min few ms Field of view The whole brain ~2 cm, cortex only f. MRI <1 mm <100 ms The whole brain

MRI Timeline 1946 MR phenomenon – Bloch & Purcell 1952 Nobel Prize – Bloch MRI Timeline 1946 MR phenomenon – Bloch & Purcell 1952 Nobel Prize – Bloch & Purcell 1960 NMR development as an analytical tool 1972 Computerized Tomography 1973 Backprojectionj MRI – Lautembur 1975 Fourier Imaging – Ernst 1980 MRI demonstration – Edelstein 1986 Gradient Echo Imaging MRI Microscopy Functional MRI demonstration 1988 Angiography – Dumoulin 1989 Echo-Planar Imaging – Mensfield Perfusion imaging 1991 Nobel Price – Ernst 1994 Xe Imaginng Hyperpolarized (Xe-129) 2004 Nobel Price – Lautembur & Mensfield

Necessary Equipment 4 T magnet RF Coil gradient coil (inside) Magnet Gradient Coil RF Necessary Equipment 4 T magnet RF Coil gradient coil (inside) Magnet Gradient Coil RF Coil Source: Joe Gati, photos

The Big Magnet Very strong 1 Tesla (T) = 10, 000 Gauss Earth’s magnetic The Big Magnet Very strong 1 Tesla (T) = 10, 000 Gauss Earth’s magnetic field = 0. 5 Gauss 4 Tesla = 4 x 10, 000 0. 5 = 80, 000 X Earth’s magnetic field Continuously on Main field = B 0 Robarts Research Institute 4 T x 80, 000 = Source: www. spacedaily. com B 0

Microscopic Property Responsible for MRI The human body contains ~63% hydrogen atoms Single voxel Microscopic Property Responsible for MRI The human body contains ~63% hydrogen atoms Single voxel cells Water molecules Each hydrogen molecules can be thought of as a small magnetic field, and will cause the nucleus to produce an NMR signal

Spins Spin is a fundamental property of nature like electrical charge or mass. Spin Spins Spin is a fundamental property of nature like electrical charge or mass. Spin comes in multiples of 1/2 and can be + or -. Protons, electrons, and neutrons possess spin. Individual unpaired electrons, and neutrons each possesses a spin of 1/2. When placed in a magnetic field of strength H, a particle with a net spin can absorb a photon, of frequency wo. The frequency wo depends on the gyromagnetic ratio, g of the particle. wo =- g. Ho The Larmor frequency For hydrogen g= 42. 58 MHz/T

Energy transitions E=-1/2 hwo Low energy state E=+1/2 hwo High energy state wo =- Energy transitions E=-1/2 hwo Low energy state E=+1/2 hwo High energy state wo =- g. Ho The Larmor frequency E=hwo=gh. Ho Energy for transition

The magnetization vector N-/N+ = exp(-E/k. T) – Boltzmann distribution The magnetization vector N-/N+ = exp(-E/k. T) – Boltzmann distribution

Two magnetic moments – procession The Bloch eq. (without relaxation) Ho Mo Two magnetic moments – procession The Bloch eq. (without relaxation) Ho Mo

DT- MRI Fiber Tract Visualization Coronal Sagittal Diffusion ellipsoids in coronal slice of human DT- MRI Fiber Tract Visualization Coronal Sagittal Diffusion ellipsoids in coronal slice of human brain Axial

Diffusion ellipsoids in coronal slice of human brain Diffusion ellipsoids in coronal slice of human brain

In 1890, Roy and Sherrington concluded that “…the chemical products of cerebral metabolism contained In 1890, Roy and Sherrington concluded that “…the chemical products of cerebral metabolism contained in the lymph which bathes the walls of the arterioles of the brain cause variations of the caliber of the cerebral vessels: that in this re-action the brain possesses an intrinsic mechanism by which its vascular supply can be varied locally in correspondence with the local variations of functional activity. ” This “neurovascular coupling” is the base of functional neuroimaging.

The First “Brain Imaging Experiment” … and probably the cheapest one too! Angelo Mosso The First “Brain Imaging Experiment” … and probably the cheapest one too! Angelo Mosso Italian physiologist (1846 -1910) E = mc 2 ? ? ? “[In Mosso’s experiments] the subject to be observed lay on a delicately balanced table which could tip downward either at the head or at the foot if the weight of either end were increased. The moment emotional or intellectual activity began in the subject, down went the balance at the head-end, in consequence of the redistribution of blood in his system. ” -- William James, Principles of Psychology (1890)

Blood Oxygenation Level Dependent (BOLD) f. MRI contrast Based on modulation of blood susceptibility Blood Oxygenation Level Dependent (BOLD) f. MRI contrast Based on modulation of blood susceptibility with activation. Measures: Amount of deoxy-hemoglobin in the tissue. This indirectly is proportional to the ratio of oxygenated/deoxygenated hemoglobin (diamagnetic and paramagnetic) • changes in T 2* • changes in T 2 Gradient echo - GEFI, GE-EPI Spin Echo - FSE, SE-EPI

vs. T 2 • T 2* changes caused by signal dephasing • Extravascular (~33%) vs. T 2 • T 2* changes caused by signal dephasing • Extravascular (~33%) contribution in T 2* (none in T 2 ) B 0 inhomogeneity T 2* Distance from blood vessel • T 2 changes caused by either: i) diffusion through the gradients surrounding the erythrocytes or by ii) exchange of water between regions of different susceptibility (erythrocyte-plasma) cout cin diffusion

Activation Statistics Functional images ROI Time Course f. MRI Signal (% change) ~2 s Activation Statistics Functional images ROI Time Course f. MRI Signal (% change) ~2 s Time Condition Co nd itio n Statistical Map 1 Time superimposed on anatomical MRI image Co nd itio n 2 Region of interest (ROI) . . . ~ 5 min

The BOLD signal 1 2 3 neuronal activity energy demand need for oxygen/glucose hemodynamic The BOLD signal 1 2 3 neuronal activity energy demand need for oxygen/glucose hemodynamic response • Coupling between oxygen/glucose utilization and hemodynamic response • Control mechanism • Blood flow vs. blood volume ?

The BOLD signal - 2 Phase 1: Diamagnetic oxy-hemoglobin minus oxygen > paramagnetic deoxy The BOLD signal - 2 Phase 1: Diamagnetic oxy-hemoglobin minus oxygen > paramagnetic deoxy Effective T 2* relaxation ; smaller T 2* signal decreased Localized to the activation neurons. Over flow of arterial blood – uncoupling between flow and oxygen Phase 2: Less paramagnetic material > inefficient relaxation > T 2* increase Signal increases Phase 3: 1. 2. Flow returns to rest, still high rate of oxygen utilization Flow returns to rest, blood volume return slower Increase dexoy > efficient relaxation > short T 2* >> signal decrease

The f. MRI BOLD signal • Aid in neurosurgery planning f. MRI mapping of The f. MRI BOLD signal • Aid in neurosurgery planning f. MRI mapping of the brain’s language areas replaces invasive presurgery electrocortical stimulation mapping which requires a patient to be awake. • Used for brain mapping Medical imaging can now display changes in brain activity caused by normal thought processes, disease, or therapeutic drugs

 • The basis of cognitive research: e. g. , relation between perception cognition • The basis of cognitive research: e. g. , relation between perception cognition behavior mood and health Human brain circuitry for imagining one's hand in the posture of another's hand. • Used in neuropathology research Brain Iron Distribution as a Potential Biomarker for Neurodegenerative Diseases (NDD) (By short T 2 mapping) Dementia Patient Volunteer

 • Allow research on brain function, architecture and organization Neural architecture of emotion • Allow research on brain function, architecture and organization Neural architecture of emotion perception and affects-related cognition Generation of cortical transient clusters during activation • Used to understand brain network

Flow vs. volume Increase in blood flow > less deoxy Hb > signal increases Flow vs. volume Increase in blood flow > less deoxy Hb > signal increases Increase in blood volume > more deoxy Hb > signal decreases CBV=0. 5 CBF 0. 5 • Increase/decrease in blood flow FASTER than blood volume • In normal conditions, in the cortex - flow is dominant (~70%)

Temporal resolution f. MRI speed: • GEFI produces an image in few sec (1 Temporal resolution f. MRI speed: • GEFI produces an image in few sec (1 -2 sec). • EPI produces an image in few tens of ms (100 -1000 ms) Brief Stimuli • The shortest stimuli that gives f. MRI signal is ~35 ms • The shortest distinguished time-difference between two stimuli is 200 ms

Temporal resolution – 2 Hemodynamic Delays • A delay of ~1 -2 sec for Temporal resolution – 2 Hemodynamic Delays • A delay of ~1 -2 sec for the initial deep • A delay of ~5 -8 sec for the positive main BOLD signal • The coupling between neuronal activity and blood flow is not direct it includes a cascade of events of chemical signaling of several messengers. • Some delay due to “plumbing” is expected Neither of these effects seems to add up to the delay observed

Temporal resolution -3 • • The brain venous network is not uniform. Particularly, deep Temporal resolution -3 • • The brain venous network is not uniform. Particularly, deep brain nuclei do not have the cortical venous structure. The yet unknown main mechanism of the BOLD delay Limits the possibility to follow neuronal information processing relates to the serial order of events in different brain areas.

Spatial resolution What is the size element of neural data processing ? Cortical Columns Spatial resolution What is the size element of neural data processing ? Cortical Columns are radially oriented clusters of neurons processing similar task • Functional connectivity within the columns is rich, between columns is much weaker • Size of cortical column is 100 -300 m in diameter and ~3 mm in length Are cortical columns the brain elementary processing units?

Spatial resolution -2 Relationship of microvasculature to cortical elements: Cortical columns seems to be Spatial resolution -2 Relationship of microvasculature to cortical elements: Cortical columns seems to be arranged about a single common artery and vein that presumably perfussed the column. Using optical imaging it was shown that activity in single column affects vascular signal for several mm around Typical f. MRI voxel is 2 -4 mm, covering tens of columns Practical needed resolution – ~2 mm for definition of area of activity and ~300 m for detailed structure

Linearity of BOLD response Dale & Buckner, 1997 Linearity: “Do things add up? ” Linearity of BOLD response Dale & Buckner, 1997 Linearity: “Do things add up? ” red = 2 - 1 green = 3 - 2 Sync each trial response to start of trial Not quite linear but good enough

Data Analysis • Single voxel time course Vs. Cluster analysis • Model driven Vs. Data Analysis • Single voxel time course Vs. Cluster analysis • Model driven Vs. Model free statistics • Strength of activation Vs. Volume of activation • Choice of threshold Signal and effect -to-noise ratio

Model based analysis Knowledge of the neuronal response is assumed – • linear or Model based analysis Knowledge of the neuronal response is assumed – • linear or non-linear with the stimulus • impulse response • hemodynamics delay • assuming no spatial dependence Neuronal response, even strong, that do not mach the model will be invisible !!!

Model based analysis - problems • In pathological conditions the basis assumption for the Model based analysis - problems • In pathological conditions the basis assumption for the BOLD signal might change. (i. e. , the fraction of flow and volume) • the model have to be modified – • spatial dependent model is needed but the dependency is unknown (i. e. , tumor) • For long stimulus or short rest intervals between stimulus – adaptation have to be included – how ?

Model-free statistics When it is necessary: • Pharmaceutical MRI - in most cases model Model-free statistics When it is necessary: • Pharmaceutical MRI - in most cases model is unknown • In pathological conditions - BOLD basic assumption might change • Non cortical areas Possible approaches Cluster analysis PCA ICA

f. MRI Signal Threshold level Area of activation How sure we are that this f. MRI Signal Threshold level Area of activation How sure we are that this is the area of activation ?