Week 1. Basics of multimodal imaging and image processing. Functional magnetic resonance imaging.

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Week 1. Basics of multimodal imaging and image processing. Functional magnetic resonance imaging.

  1. 1. 2012.10.30. Multimodal Imaging in Neurosciences Course Diagnostic neuroimaging modalities CT – Computed Tomography Structural MRI Brain anatomy Fine brain anatomy Stereotactic reference frame Vascular structure Multi-modal imaging Intra-operative imaging Diffusion, perfusion MRI field spectrum for modalities, open MRI, low- Fine pathological information 1.Diagnostic imaging Positron Emission MR Spectroscopy Introduction to Multi-modal 2.Research Tomography PET Brain metabolism Brain function Brain metabolism Biochemical mapping neuroimaging 3.Neurosurgery Electro encephalography, Dr. Ervin Berenyi, MD, PhD Functional MR imaging fMRI LORETTA, Brain function Dr. András Jakab, MD, PhD Magnetoencephalography Dr. Peter Katona, MD What is multimodality? PET-CT HYBRID Combining images and information from multiple imaging tools, devices Anatomical alignment of images Fusion display, co-analysis of multiple information sources What is needed for multimodality? CT, PET, MRI, SPECT, EEG, … Hybrid devices – PET-CT, PET-MRI Image processing skills to create image fusions, etc. CT: anatomy + attenuation correction PET: metabolism, functionPET-MRI HYBRID SCANNER Measuring tissue properties with MRI T1 relaxation T2 relaxation Structural MRI Proton density Diffusion- Tissue diff i Ti diffusion weighted imaging Diffusion direction Diffusion tensor imaging Acquire PET and MRI Diffusion anisotropy together Diffusion spectral Great technological challenge Diffusion maps imaging, HARDI $$$ Metabolites MR spectroscopy 1
  2. 2. 2012.10.30. removed temporal lobe parts OPTIC RADIATION CORTICOSPINAL TRACTVISUALIZATION OF STRUCTURERecidive tumor, 2 foci, purple and magentaMarkers on the skin VISUALIZATION OF FIBERS Part I. Basics of fMRI and functional pp g mapping Multimodal Imaging in Neurosciences Course Functional MR Imaging Dr. Ervin Berenyi, MD, PhD Dr. András Jakab, MD, PhD Dr. Peter Katona, MD Brain functions – how to interpret COGNITIVE PROCESSING IN THE BRAIN The synchronous activity of neuronal groups Primary sensory areas (somato-, auditory, etc.) Cerebral cortex Secondary, tertiary, etc. sensory areas (i.e. visual: 5-9 Examples of brain functions levels) + Parallel processing (not Visual processing Association areas purely hierarchical!) Auditory processing Memory functions, recall „Association areas for higher cognitive functions” Wernicke area Motor response behavior response, Broca area Movement of limbs Somatosensory cortex (SI) Emotional response: e.g. human face Somatosensory cortex (SII) Parietal association area „not processing anything” - default mode networks and „DLPFC – higher cognitive processing” resting state networks Drive, behavioral processing etc. Speech motor center 2
  3. 3. 2012.10.30. The brain never rests! Default network Mapping neuronal function Default mode network Default state network Task-negative network Electric activity of neurons Electro encephalography EEG Action potential, propagation of signal Magnetoencephalography MEG „Wandering and Wondering” Electric current – magnetic field variations Posterior cingulate cortex Precuneus Metabolic activity of neurons emission tomography Positron Prefrontal cortex Glucose metabolism (18F-FDG) PET Daydreaming Blood supply of neurons Synchronised areas fMRI Vasodilatation, perfusion change Age dependency Diseases affecting it Rapid changes of cell compartments Not dreaming! Cell swelling? fDTIFair DA, Cohen AL, Power JD et al. (2009). "Functional brainnetworks develop from a local to distributed organization". PLoSComput Biol 5 (5): e1000381 History “[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) Angelo Mosso (1846-1910) (1846 1910) E = mc2 Zago et al. (2009) The Mosso ??? method for recording brain pulsation: The forerunner of functional neuroimaging. Neuroimage History The first evidence for the coupling between energy metabolism and brain blood perfusion (animals) The blood volumen elevated during brain activity Sir C. S. Sherrington, 1890 Seymour Kety & Carl Schmidt, 1948 Increased oxigen take-up Sir Charles Dilatation of blood vessels Scott Sherrington Near infrared spectroscopy ea a e spec oscopy (1857 1952) (1857-1952) PET fMRI (90’s): Seji Ogawa, Ken Wong Cerebral Cortex. 12:225-233; 2002. 3
  4. 4. 2012.10.30. Activity Increases Flow Blood pressure • sensory stimulation leads to increased blood flow • sciatic nerve, electronic stimulation (0,2 V 5-10 Hz), rats, automated video dimension analyzer Arteriole diameter Blood velocity Data Source: Ngai et al., 1988, Am J Physiol Figure Source, Huettel, Song & McCarthy, Functional Magnetic Resonance I iSummary of in vivo imaging methods Structural imaging fMRI CT MRI T1 – 3DT1 – „anatomical” T2 FLAIR, DWI, etc. Functional imaging PET fMRI ….. Structural MRI Functional MRI OK. Now show me the trick.Good spatial resolution = 0.6 – 1 mm Bad spatial resolution = 2 – 4 mm Short scan time (a few minutes) Long scan time (10-30 minutes) One time point is imaged Multiple time points, multiple scans Good tissue contrast Bad tissue contrastNo image post-processing is required Post-processing is required The result is robust The result depends on the patient, the protocol and paradigm 4
  5. 5. 2012.10.30. The hemoglobine -Four globin chains -Each chain contains a haem molecule -Each haem has an iron atom in the center (Fe) -Each haem can absorb one oxygen molecule (O2) -oxy-Hgb (four O2) has DIAMAGNETIC effect →it does not affect the magnetic field ΔB -deoxy-Hgb is PARAMAGNETIC → if [deoxy-Hgb] ↓ → then local ΔB ↓ 25 Source: http://wsrv.clas.virginia.edu/~rjh9u/hemoglob.html, Jorge Jovici & Huettel, Song, McCarthy, Functional Magnetic Resonance Imaging Measuring deoxy-hemoglobineDiamagnetism and paramagnetism • During fMRI acquisitions, we get information of the brain’s deoxy- hemoglobine contentDiamagnetism(oxy- & carbonmonoxyhemoglobine) • The relative oxygenation changes with the deoxygenated hemoglobine No magnetic momentum content Has paired electronsParamagnetism (deoxyhemoglobine) Magnetic momentum – atoms behave as small magnets Has unpaired electrons Seiji OgawaHow does this work? The BOLD effect! HEMODYNAMIC RESPONSEBlood Oxygen Level DependentThe funcitonal activity is coded in the BOLD effect. OxyHb and DeoxyHb- their MR relaxation properties are different! deoxyHb: paramagnetic!!! Mxy Signal Mo sinθ T2* task T2* control Stask Scontrol ΔS TEoptimum time Source:, Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging Source: Jorge Jovicich 5
  6. 6. 2012.10.30. Part II. How to perform an fMRI? pEnd of Part I. – any questions?The MRI recipe 1. Patient (water + fat = lot of spins) MRI sequences 2. Excite (Shout at the patient with a Image coded as waves, Fourier transformation is used to „decode” the raw Repeat this! This is called SEQUENCE radiofrequency coil) signal and get an image 3. Wait until the excited spins „relax” 4. During relaxation, the spins (water + You can „excite” the spin system in numerous ways to have image signals, fat =patient) shout back at you, they i.e. SPIN ECHO or GRADIENT ECHO sequences. send an ECHO 5. You listen to the echo and record it GRADIENT ECHO SEQUENCES ARE SENSITIVE FOR (this is the k-space acquisition) DEOXYHEMOGLOBINE CHANGES! , Human, made of 6. Decode the i l t image! 6 D d th signal, get i ! excitable spins (H ECHO proton spins) How does echo planar imaging works? Echo-planar imaging (SE-EPI, GRE-EPI) T2 contrast After one excitation, an entire slice is read out. It is a fast MR imaging sequence Has many artifacts, i.e. susceptibility IMAOIS – www.imaios.com 6
  7. 7. 2012.10.30. fMRI and all the toolsHow to perform an fMRI scan? Checklist! Can our MRI device perform fast EPI, what is the field strength? 1.5T vs. 3T? What are we interested in? fMRI experiments are task-specific It is necessary to construct a PARADIGM which „observes” one specific brain function Do D we h have i image processing skills? i kill ? $$$ Patient cooperative? IQ, attention? Do we have enough time? Sedation, drugs, etc. The first step: imaging the anatomy Anatomical acquisitionT1 weighted anatomical images as references • High resolution images (1x1x2.5 mm) • 3D acquisition VOXEL • pl. 64 anatomical images ~ 5 perc (Volumetric Pixel) Slice Thickness e.g., 6 mm In-plane resolution e.g., 192 mm / 64 = 3 mm 3 mm 6 SAGITTAL SLICE IN-PLANE IN PLANE SLICE mm 3 mm Number of Slices e.g., 10 Matrix Size e.g., 64 x 64 Field of View (FOV) e.g., 19.2 cm Paradigm and block designSecond step: the actual fMRI acquisition Functional imagesT2*-weighted images fMRI ROI • Image contrast relates to neuronal activity ~2 sec signal Time • Low spatial resolution (3x3x5 mm) Course • One volume of the brain is acquired in 2 seconds! (% change • We acquire many volumes in time (4D), ie. 150 • Repeated scanning Time Tasks Statistical … activation map on T1 image first volume (2 sec to acquire) Time Region of interest ~ 5 minutes kijelölés (ROI) 7
  8. 8. 2012.10.30.Interpreting fMRI results: TALAIRACH ATLAS - 1988LOCALIZATION - 1 SZEMÉLYVariability of sulci - problematic Fathers of Localization (brain atlases) Jean Talairach Gabor Szikla (January 15, 1911, Perpignan – March 15, 2007, Paris) Source: Szikla et al., 1977 in Tamraz & Comair, 2000 Anatomical localization of activity: gyri and sulci How to display fMRI results? gray matter (dendrites & synapses) white matter (axons) ANK BA Brain extraction Inflation FISSURE FUNDUSSource: Ludwig & Klingler, 1956 in Tamraz & Comair, 2000 Creating 3D visualizations of the individual brain: Skull-stripping, inflating the cortex 8
  9. 9. 2012.10.30. Standardization of fMRI images to brain Segmentation, filtering, masking atlasesFuzzy thresholding Anisotropic filtering Only brainDisplaying fMRI fMRI display Part III. Examples and research applications p pp End of Part II. – any questions? 9
  10. 10. 2012.10.30.What functions can we image using The logic of a „simple” fMRI experimentfMRI? Rest = empty screen Paradigm-dependent! Vision („vibrating checkboard”) Audition (variable frequency stimuli) Limb movement – active Passive limb movement - infants Task1 Time Task 2 Memory (hometown walking test) Speech … and many others (but not everything!) The subject views an object, i.e. apple „Scrambled” – image Results: object recognition First images of visual activity Flickering Checkerboard OFF (60 s) - ON (60 s) -OFF (60 s) - ON (60 s) - OFF (60 s) Source: Kwong et al., 1992Kalanit Grill-Spector et al. Motor paradigm of the left hand CO-ACTIVATION OF V1 -> V2.. AFTER VISUAL STIMULUS 10
  11. 11. 2012.10.30. Lesion in the left precentral gyrus (malformation) – REDFinger tapping test of the Hand movement activation: Yellow, CS tract: yellowright hand Source: Katona P., DEOEC Jakab, Katona et al.HOMUNCULUS Left hand Source: Berenyi, Emri, Jakab et alLeft foot Auditory activation Task: Listening to ordersForrás: Berényi E,Emri M. DEOEC Forrás: Berényi E, Emri M. DEOEC 11
  12. 12. 2012.10.30. Late speech development – pathologicalFREQUENCY PROGRESSION OF localization of speech centers?HUMAN AUDITORY CORTEX J Neurophysiol. 91:1282-1296, 2004. Radiology. 2003;229:651-658.Speech paradigm: say a word beginning Localizing swallowing movementwith a,b,c, etc. Jakab A, Katona P et al. AJNR. 20:1520-0526. 1999. 12
  13. 13. 2012.10.30. 13
  14. 14. 2012.10.30. Patient history A case of drug resistant epilepsy 8 yrs old right handed boy Born on term from uneventful pregnancy Szentágothai TK - Semmelweis Egyetem MR Kutatóközpont fMRI in a Case of Childhood Epilepsy First seizures at 3.5 yrs About the time of falling asleep starting with left hand twithcing then generalizing Later atypical absence seizures EEG results Normal EEG on the onset Lajos R Kozak Later slow spike and wave activity developed with clinical abscence MR Research Center, Semmelweis University, Budapest, Hungary Finally, electric status epilepticus during sleep (ESES), irregular high amplitude spike and wave activity, during the whole night Physical examination Paresis on the left limbs Patient history Imaging Smaller right hemisphere On T1 weighted images (A-B) widespread irregularities of the cortical surface suggestive of multiple small folds with abnormally thick cortex, irregular appearance of the gray matter-white matter junction tt hit tt j ti suggestive of polymicrogyria On FLAIR images (C) numerous high intensity foci predominantly in the subcortical white matter Question: is the malformed cortex functional?Kozák et al., Clin Neurosci2009;62(3–4):130–135. fMRI #1 #1 fMRI #1 no result The reason for unsuccesful fMRI? Imaging at 3T Philips Achieva scanner Bad acquisition ? TR=3000ms, TE=30ms, 500-700μV FA=75°, 3x3x3mm2 voxels (80x80 matrix, 240x240 Bad stimulation ? FOV), axial slices, no gap, Overanesthetized ? SENSE factor of 2 Block design paradigm, WHAT WAS THE 24s movement, 24s rest PROBLEM WITH THE • flexion/extension of fingers ~0.5-1Hz fMRI? Electric status • left and right limb moved in separate blocks epilepticus during sleep (ESES) ? movement rest Clonazepam was the solution Kozák et al., Clin Neurosci 2009;62(3–4):130–135. 14
  15. 15. 2012.10.30. fMRI #2 #2 fMRI #2 #2 right hand movement pre- and postoperatively left hand movement pre- and postoperatively Preop. Preop. Postop Postop Functional reorganization to the healthy hemisphere Conclusions Passive range-of-movement paradigms are range-of- considered useful for the mapping of sensory- motor cortex in pediatric epilepsy patients patients. If fMRI fails in this patient population we have to check if there is ongoing epileptic activity during anesthesia These paradigms are able to describe cortical reorganization thus they have clear reorganization, prognostic value in a pre-operative setting pre- setting. Research with fMRISummary of facts so far fMRI is based on the BOLD = Blood Oxygen Level Dependent contrast Neurovascular coupling "...the single most critical piece of equipment A stringent paradigm is required is still the researchers own brain. All the equipment in the world will not help us if we (protocol) ( l) do not know how to use it properly, which requires more than just knowing how to Mapping brain activity can be operate it. Aristotle would not necessarily have been more profound had he owned a achieved in living humans laptop and known how to program. What is badly needed now, with all these scanners Many factors can influence the whirring away, is an understanding of exactly what we are observing, and seeing, and results measuring, and wondering about." fMRI = localization -- Endel Tulving, interview in Cognitive Neuroscience (2002, Gazzaniga , Ivry & Mangun, Eds., NY: Norton, p. 323) 15
  16. 16. 2012.10.30. A new localizationism? Example for a BAD fMRI experiment The accepted application ~2 sec Surgical planning For cognitive neuroscience, localization itself has INFERIOR significance Popularity, factoid literature Task 2: Subject observes a 3: 1: noise + a screen car on(control) CAR Elmo Muppet Time The brain before the fMRI eraBAD INTERPRETATION OF FMRI RESULTS CANSTILL MAKE A JOURNAL PUBLICATION? - =CAR against noise Elmo + CAR Elmo (negative elmo)Visual areas for „car Visual areas for „car + elmo Elmo Brain Area ??? Polyak, in Savoy, 2001, Acta Psychologica observation” observation” THE BRAIN AFTER FMRI (INCOMPLETE) Basic types of fMRI research reaching and pointing Testing models, theories Localize the activations after stimuli motor control touch retinotopic visual maps eye Activating networks after stimuli movements executive grasping Spatial encoding of the brain: control motion near head Retinotopy, somatotopy, frequency memory orientation selectivity coding motion perception Behavior and cognition Diseases, i.e. psychiatry scenes moving bodies static social cognition bodies faces objects Inter-species comparisons 16
  17. 17. 2012.10.30. ULTRA-LOW-FIELD IMAGING The future of functional brain imaging Earth magnetic field SQUID MAGNETOMETRY 3T, 4T, 7T, … ? Los Alamos, USA Ultra-low-field imaging Arterial spin labeling Functional diffusion tensor imaging (Le Bihan) The small electric currents of neuronal activity induce changes in the magnetic field, which interferes with the Earth’s and imaging can be performedArterial Spin Labeling - ASL Arterial Spin Labeling - ASL z (=B0) inversion slab excitation blood y x inversion imaging i i plane • Perfusion: delivery of metabolites (via local blood flow) (BOLD - hemoglobin) • Represents an interesting physiological parameter • Arterial Spin Labeling (ASL): invert of in-flowing • Quantitative: fit kinetic curve for perfusion in blood ml/100g/min • IMAGEperfusion = IMAGEuninverted - IMAGEinverted 99 • Lower SNR than BOLD 100 • Limited coverage (~5 slices)Arterial Spin Labeling - ASL Arterial Spin Labeling - ASL Magn Reson Med, 48:242-254 (2002) Magn Reson Med, 48:242-254 (2002) 17
  18. 18. 2012.10.30. Stroke. 2000;31:680-687. Part IV. The functional brain connectomeEnd of Part III. – any questions? Resting state fMRI Spontaneous synchronity in the brain = low frequency oscillations <0.1 Hz neuronal activity is present during „rest” Background for continuous sensory processing? Don’t do anything. What regions are „synced” ? 18
  19. 19. 2012.10.30. THE SHORT HISTORY OF Correlated time courses = networks CONNECTOMICS 1. Regional slow neuronal activity Theodor Meynert Jules Dejerine Tracing studies „In vivo methods”: 3. Their correlation (temporal) Diffusion tensor imaging Functional MR imaging Functional Connectivity 2. Regional slow neuronal activityHypothesis: if two neuronal time courses are This is called FUNCTIONAL CONNECTIVITYcorrelated, the regions are interconnected. 19
  20. 20. 2012.10.30.Modeling the brain’s connections Modeling the brain’s connectionsBrain regions: network nodes Brain regions: network nodesStructural OR functional brain connection strength: network edges Structural OR functional brain connection strength: network edges Graph-theoretical analysis, a purely mathematical approach Graph-theoretical analysis, a purely mathematical approach Node (region) Edge (connection) Short path-length, Low degree Long path-length, Low degreeHow can information be exchanged among brain regions? How can information be exchanged among brain regions?Modeling the brain’s connections Modeling the brain’s connectionsBrain regions: network nodes Brain regions: network nodesStructural OR functional brain connection strength: network edges Structural OR functional brain connection strength: network edges Graph-theoretical analysis, a purely mathematical approach Graph-theoretical analysis, a purely mathematical approach Hub Short path-length, High degree Example of a highly (low efficiency) efficient networkHow can information be exchanged among brain regions? How can information be exchanged among brain regions? 20
  21. 21. 2012.10.30.Modeling the brain’s connections What is the cortico-cortical brain network like? cortico- like?Brain regions: network nodes CORTEX The internet FacebookStructural OR functional brain connection strength: network edges Graph-theoretical analysis, a purely mathematical approach Source: Paul Weinstein’s blog Example of an inefficient network (almost random) Modha & Singh. Network architecture of the long-distance pathways in the macaque How can information be exchanged among brain regions? brain. PNAS, 2010 Small World Networks Network properties of the brain: brain: Network properties of the brain: brain: normal development normal and pathological Network cost Network efficiency cost=sum(wij)Gong et al. Age- and Gender-Related Differences in the Cortical Anatomical Network. The Journal of Gong et al. Age- and Gender-Related Differences in the Cortical Anatomical Network. The Journal ofNeuroscience 2009; 29: 15684-15693. Neuroscience 2009; 29: 15684-15693. Network properties of the brain: brain: Network properties of the brain: brain: gender differences correlation with intelligence Network cost Network efficiency Path length negatively correlates with IQ, especially in the left frontal medial cortex cost=sum(wij)Gong et al. Age- and Gender-Related Differences in the Cortical Anatomical Network. The Journal of Van Heuvel et al. Efficiency of Functional Brain Networks and Intellectual PerformanceNeuroscience 2009; 29: 15684-15693. The Journal of Neuroscience, 2009, 29(23): 7619-7624. 21
  22. 22. 2012.10.30. Network properties of the brain: brain: Detecting areas with similar connectivity profiles schizophrenia -Exekutív skill +Exekutív LOSS OF HIERARCHICAL skill ORGANIZATION IN FRONTAL REGIONSJakab A et al. Mapping changes of in vivo connectivity patterns in the human mediodorsal Bassett, D. S. et al. 2008thalamus: correlations with higher cognitive and executive functions. Brain Imaging and Van Heuvel. et al. 2010Behavior 2012; DOI: 10.1007/s11682-012-9172-5 Network properties of the brain: brain: high functioning autistic adults Thank you for your attention! n=9 (HLFA) Presentation credits: vs. n=40 (controls) Suggests the impairment of long-range Dr. András Jakab, M.D. Ph.D. association fibers, Dr. Ervin Berényi, M.D. Ph.D. especially in the left fronto-temporo- Dr. Péter Katona, M.D. ocipital connectivities Dr. Miklós Emri, Ph.D. Tamás Spisák, M.sc.Jakab A, Spisak T, Szeman-Nagy A, Beres M, Molnar P, Emri M, Berenyi E. Pathological patterns offunctional connectivity and white matter anisotropy in high functioning autistic adults. Under review @PLoS One 22

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