RF Excitation. RF Excitation. Bioengineering 280A Principles of Biomedical Imaging. Fall Quarter 2013 MRI Lecture 4

Similar documents
[ ]e TE /T 2(x,y ) Saturation Recovery Sequence. T1-Weighted Scans. T1-Weighted Scans. I(x, y) ρ(x, y) 1 e TR /T 1

RF Excitation. RF Excitation. Bioengineering 280A Principles of Biomedical Imaging

RF Excitation. Rotating Frame of Reference. RF Excitation. Bioengineering 280A Principles of Biomedical Imaging. Fall Quarter 2012 MRI Lecture 6

Relaxation. T1 Values. Longitudinal Relaxation. dm z dt. = " M z T 1. (1" e "t /T 1 ) M z. (t) = M 0

RF Excitation. Bioengineering 280A Principles of Biomedical Imaging. Fall Quarter 2006 MRI Lecture 4. Thomas Liu, BE280A, UCSD, Fall 2006

Refocusing t. Small Tip Angle Example. Small Tip Angle Example. Bioengineering 280A Principles of Biomedical Imaging. Fall Quarter 2010 MRI Lecture 5

HW6: MRI Imaging Pulse Sequences (7 Problems for 100 pts)

Spin. Nuclear Spin Rules

Spin. Nuclear Spin Rules

Topics. The concept of spin Precession of magnetic spin Relaxation Bloch Equation. Bioengineering 280A Principles of Biomedical Imaging

SE Sequence: 90º, 180º RF Pulses, Readout Gradient e.g., 256 voxels in a row

The NMR Inverse Imaging Problem

k B 2 Radiofrequency pulses and hardware

Topics. Spin. The concept of spin Precession of magnetic spin Relaxation Bloch Equation

Sampling in k-space. Aliasing. Aliasing. Bioengineering 280A Principles of Biomedical Imaging. Fall Quarter 2010 MRI Lecture 3. Slower B z (x)=g x x

Exam 8NC20-8NC29 - Introduction to NMR and MRI

K-space. Spin-Warp Pulse Sequence. At each point in time, the received signal is the Fourier transform of the object s(t) = M( k x

Bioengineering 278" Magnetic Resonance Imaging" Winter 2010" Lecture 1! Topics:! Review of NMR basics! Hardware Overview! Quadrature Detection!

Topics. The History of Spin. Spin. The concept of spin Precession of magnetic spin Relaxation

NMR Spectroscopy: Principles and Applications. Nagarajan Murali 1D - Methods Lecture 5

Apodization. Gibbs Artifact. Bioengineering 280A Principles of Biomedical Imaging. Fall Quarter 2013 MRI Lecture 5. rect(k x )

Principles of MRI EE225E / BIO265. Lecture 14. Instructor: Miki Lustig UC Berkeley, EECS. M. Lustig, EECS UC Berkeley

Chemistry 431. Lecture 23

Biomedical Imaging Magnetic Resonance Imaging

M. Lustig, EECS UC Berkeley. Principles of MRI EE225E / BIO265

Week 1 Lecture 2 Problems 2, 5. What if something oscillates with no obvious spring? What is ω? (problem set problem)

Exam 8N080 - Introduction to MRI

Basic MR image encoding

Magnetic Resonance Imaging. Pål Erik Goa Associate Professor in Medical Imaging Dept. of Physics

Biomedical Imaging. Nuclear Magnetic Resonance. Patrícia Figueiredo IST,

Physical fundamentals of magnetic resonance imaging

The Basics of Magnetic Resonance Imaging

Nuclear Magnetic Resonance Imaging

EE225E/BIOE265 Spring 2016 Principles of MRI. Assignment 4. Due Friday Feb 19st, 2016, Self Grading Due Monday Feb 22nd, 2016

e 2t u(t) e 2t u(t) =?

Introduction to Magnetic Resonance Imaging (MRI) Pietro Gori

Part II: Magnetic Resonance Imaging (MRI)

EXPLICIT TIME INTEGRATORS FOR NONLINEAR DYNAMICS DERIVED FROM THE MIDPOINT RULE

MRI Physics I: Spins, Excitation, Relaxation

' ' ' t. Moving Spins. Phase of Moving Spin. Phase of a Moving Spin. Bioengineering 280A Principles of Biomedical Imaging

Physics of MR Image Acquisition

We have seen that the total magnetic moment or magnetization, M, of a sample of nuclear spins is the sum of the nuclear moments and is given by:

Spin echo. ½πI x -t -πi y -t

Program: RFEM 5, RSTAB 8, RF-DYNAM Pro, DYNAM Pro. Category: Isotropic Linear Elasticity, Dynamics, Member

Introduction to MRI. Spin & Magnetic Moments. Relaxation (T1, T2) Spin Echoes. 2DFT Imaging. K-space & Spatial Resolution.

3, so θ = arccos

A Lecture on Selective RF-pulses in MRI

ψ(t) = V x (0)V x (t)

Get: Nuclear (equilibrium) magnetization M 0. (Magnitude dictated by Boltzmann distribution)

MR Fundamentals. 26 October Mitglied der Helmholtz-Gemeinschaft

RF Pulse Design. Multi-dimensional Excitation I. M229 Advanced Topics in MRI Kyung Sung, Ph.D Class Business

Principles of Magnetic Resonance Imaging

Sketch of the MRI Device

Physikalische Chemie IV (Magnetische Resonanz) HS Solution Set 2. Hand out: Hand in:

Introduction to AC Power, RMS RMS. ECE 2210 AC Power p1. Use RMS in power calculations. AC Power P =? DC Power P =. V I = R =. I 2 R. V p.

Spectral Broadening Mechanisms

Kinematics and kinematic functions

Spectral Broadening Mechanisms. Broadening mechanisms. Lineshape functions. Spectral lifetime broadening

Pulse Sequences: RARE and Simulations

Answers to 1 Homework

!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)

2 int T. is the Fourier transform of f(t) which is the inverse Fourier transform of f. i t e

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 9: Advanced DFT concepts: The Exchange-correlation functional and time-dependent DFT

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence

EECS 2602 Winter Laboratory 3 Fourier series, Fourier transform and Bode Plots in MATLAB

Nuclear Magnetic Resonance Imaging

Introduction to Biomedical Imaging

R.#W.#Erickson# Department#of#Electrical,#Computer,#and#Energy#Engineering# University#of#Colorado,#Boulder#

Classical Description of NMR Parameters: The Bloch Equations

MRI Physics II: Gradients, Imaging. Douglas C. Noll, Ph.D. Dept. of Biomedical Engineering University of Michigan, Ann Arbor

Product Operators. Fundamentals of MR Alec Ricciuti 3 March 2011

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

EE 224 Signals and Systems I Complex numbers sinusodal signals Complex exponentials e jωt phasor addition

System of Linear Differential Equations

Field trip: Tuesday, Feb 5th

Classical Description of NMR Parameters: The Bloch Equations

Structural Dynamics and Earthquake Engineering

Part III: Sequences and Contrast

( ) = b n ( t) n " (2.111) or a system with many states to be considered, solving these equations isn t. = k U I ( t,t 0 )! ( t 0 ) (2.

Lecture #8 Redfield theory of NMR relaxation

Fundamental MRI Principles Module 2 N. Nuclear Magnetic Resonance. X-ray. MRI Hydrogen Protons. Page 1. Electrons

Topics. 2D Image. a b. c d. 1. Representing Images 2. 2D Fourier Transform 3. MRI Basics 4. MRI Applications 5. fmri

NMR, the vector model and the relaxation

Principles of MRI. Practical Issues in MRI T2 decay. Tissue is a combination of. Results are complex. Started talking about off-resonance

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

Introduction to Probability and Statistics Slides 4 Chapter 4

Lab 2: Magnetic Resonance Imaging

DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 2008

INSTANTANEOUS VELOCITY

Classical behavior of magnetic dipole vector. P. J. Grandinetti

Bloch Equations & Relaxation UCLA. Radiology

Extended Phase Graphs (EPG)

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum

Voltage/current relationship Stored Energy. RL / RC circuits Steady State / Transient response Natural / Step response

BMB 601 MRI. Ari Borthakur, PhD. Assistant Professor, Department of Radiology Associate Director, Center for Magnetic Resonance & Optical Imaging

1 1 + x 2 dx. tan 1 (2) = ] ] x 3. Solution: Recall that the given integral is improper because. x 3. 1 x 3. dx = lim dx.

Two Coupled Oscillators / Normal Modes

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws

' ' ' t. Moving Spins. Phase of a Moving Spin. Phase of Moving Spin. Bioengineering 280A Principles of Biomedical Imaging

Transcription:

Bioengineering 80A Principles of Biomedical Imaging Fall Quarer 013 MRI Lecure 4 TT. Liu, BE80A, UCSD Fall 01 Simplified Drawing of Basic Insrumenaion. Body lies on able encompassed by coils for saic field B o, gradien fields (wo of hree shown), and radiofrequency field B 1. Image, capion: copyrigh Nishimura, Fig. 3.15 RF Exciaion RF Exciaion From Levi, Spin Dynamics, 001 hp://www.drcmr.dk/main/conen/view/13/74/ 1

RF Exciaion A equilibrium, ne magneizaion is parallel o he main magneic field. How do we ip he magneizaion away from equilibrium? On-Resonance Exciaion Image & capion: Nishimura, Fig. 3. B 1 radiofrequency field uned o Larmor frequency and applied in ransverse (xy) plane induces nuaion (a Larmor frequency) of magneizaion vecor as i ips away from he z-axis. - lab frame of reference hp://www.eecs.umich.edu/%7ednolłbme516/ Hanson 009 hp://www.drcmr.dk/javacompass/ RF Exciaion Roaing Frame of Reference Reference everyhing o he magneic field a isocener. hp://www.eecs.umich.edu/%7ednolłbme516/

a) Laboraory frame behavior of M b) Roaing frame behavior of M Images & capion: Nishimura, Fig. 3.3 B 1 () = B 1 ()cos( ω)i () cos( ω)i sin( ω)j ( ) + B 1 ()( cos( ω)i + sin( ω)j) hp://www.eecs.umich.edu/%7ednolłbme516/ Nishimura 1996 hp://www.mrinsrumens.com/ hp://www.berlin.pb.de/en/org/8/81/811/researchtopics/coildevelopmen.hml 3

Precession Roaing Frame Bloch Equaion dµ d = µ x γb B dµ µ Analogous o moion of a gyroscope Precesses a an angular frequency of ω = γ Β This is known as he Larmor frequency. dm ro = M d ro γb eff & B eff = B ro + ω 0 ) ro γ ; ω ( + ro = ( 0 + '( ω * + Noe: we use he RF frequency o define he roaing frame. If his RF frequency is on-resonance, hen he main B0 field doesn cause any precession in he roaing frame. However, if he RF frequency is off-resonance, hen here will be a ne precession in he roaing frame ha is give by he difference beween he RF frequency and he local Larmor frequency. hp://www.asrophysik.uni-kiel.de/~hhaerełmpg_e/gyros_free.mpg Le B ro ()i + B 0 k B eff = B ro + ω ro γ % ()i + B 0 ω ( ' * k & γ ) Flip angle = ω 1 (s)ds 0 where ω 1 () = () If ω = ω 0 = γb 0 Then B eff ()i Nishimura 1996 4

Example = 400 µ sec; =π / B 1 = γ = π / (457Hz / G)(400e 6) = 0.1468 G Nishimura 1996 Le B ro ()i + ( B 0 + γg z z)k B eff = B ro + ω ro γ % ()i + B 0 + γg z z ω ( ' * k & γ ) If ω = ω 0 B eff ()i + ( γg z z)k Nishimura 1996 5

slice Slice Selecion z Δz f rec(f/w) W=γG z Δz/() sinc(w) Nishimura 1996 Small Tip Angle Approximaion Exciaion k-space For small M z M 0 M z = M 0 cos M 0 = M 0 sin M 0 1 D random 3 walk G z () k(,) k(,) = γ G z ( s)ds 100 seps M 0 exp( jk z ( 1,)z) 400 seps M 0 exp( jk z (,)z) M 0 6

Exciaion k-space A each ime incremen of widh Δ, he exciaion B 1 ( ) produces an incremen in magneizaion of he form Δ jm 0 ( )Δ 100 seps D random walk (small ip angle approximaion) In he presence of a gradien, his will accumulae phase of he form ϕ=-γ Δ zg z ( s)ds, such ha he incremenal magneizaion a ime is ( ) Δ (,z ; ) = jm 0 ( )exp jγ zg z ( s)ds N random seps of lengh d Inegraing over all ime incremens, we obain ( ) d (,z) = jm 0 ( )exp jγ zg z ( s)ds = jm 0 ( )exp( jk(,)z)d where k(,) = γ G z ( s)ds 400 seps Exciaion k-space (,z) = jm 0 ( )exp( jk(,)z)d This has he D form random of a Fourier walk ransform, where we are inegraing he conribuions of he field B 1 100 seps ( ) a he k-space poin k, RF N random seps of lengh d 400 seps 1 3 Slice selec gradien G z () k(,) = γ G z ( s)ds 3 1 ( ). k z RF N random seps of lengh d Refocusing (,z) = jm 0 ( )exp( jk(,)z)d This has he D form random of a Fourier walk ransform, where we are inegraing he conribuions of he field B 1 G z () k(,) 1 3 4 Slice selec gradien Slice refocusing gradien k(,) = γ G z ( s)ds 3 100 seps ( ) a he k-space poin k, 400 seps 4 ( ). 1 k z RF G z () G x () G y () Slice Selecion Slice selec gradien Slice refocusing gradien 7

Gradien Echo slice Slice Selecion z RF G z () G x () G y () ADC Slice selec gradien Slice refocusing gradien Spins all in phase a k x=0 f rec(f) Δf = 1 = γg zδz Δz sinc(/) Example (x) = M 0 cos(4π x) ( ) = M 0 ( ) F (x) δ(k )+δ(k + ) x x g max = 4 G / cm γ g max T = 4 cm 1 ; T = 35 µ sec wih small ip angle approximaion --> = 1 " Compare wih sin π % $ ' = 1 # 6 & = π 6 = 0.536 Quesion : Should we use = π 4 insead? 1 D random walk G x () T k(,) - Nishimura 1996 Exercise: Skech he quiver diagrams corresponding o he conribuions of he wo RF pulses and show ha hey produce he desired paern. 8

Muli-dimensional Exciaion kspace D random walk ( (,r) = jm 0 ω1 ( ) exp jγ 100 seps G(s) rds)d Exciaion k-space 100 seps D random walk = jm 0 ω1 ( ) exp( jk( ) r ) d 400 seps γ where ) = d N random seps ofk( lengh G( &)d& 400 seps N random seps of lengh d Pauly e al 1989 Pauly e al 1989 Exciaion k-space D random walk Cardiac Tagging 100 seps 400 seps N random seps of lengh d Panych MRM 1999 9