FMRI – Week 4 – Contrast Scott Huettel, Duke University

MR Contrast

FMRI Graduate Course (NBIO 381, PSY 362)

Dr. Scott Huettel, Course Director

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Review: Image Formation

• Every image can be constructed from spatial frequency information– i.e., sinusoidal gratings of particular

frequency, orientation, and phase

• Images vary in the contributions from different spatial frequencies

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Spatial Image = Combination of Spatial

Frequencies

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Review: Image Formation

• Every image can be constructed from spatial frequency information– i.e., sinusoidal gratings of particular

frequency, orientation, and phase• Images vary in the contributions from

different spatial frequencies• By using magnetic gradients, we

change the relative precession phase of protons across space, according to spatial freq.

FMRI – Week 4 – Contrast Scott Huettel, Duke University

k space = spatial frequency

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Contrast

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Types of Contrast

• Static Contrast– Proton Density – T1

– T2

– T2*

• Motion Contrast– Flow– Perfusion– Diffusion

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Defining “Contrast”

• The intensity difference between different quantities being measured by an imaging system.

• The physical quantity measured in an image.

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Quick Self-Assessment

• Define the following– TR– TE

– T1 relaxation

– T2 relaxation

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Creating Proton-Density-Weighted Images

Proton density contrast measures, quite simply, how many protons are present in a

voxel.

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Proton-Density-Weighted Imaging

Gradient-Echo Imaging (GRE)

Flip Angle

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Overview of Imaging Parameters

• Proton-Density-Weighted– Long TR, short TE

• T1

– ??

• T2 or T2*– ??

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Generating T1-weighted Images

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T1-weighted Imaging

Spin-Echo Imaging (SE)

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Overview of Imaging Parameters

• Proton-Density-Weighted– Long TR, short TE

• T1

– Intermediate TR, short TE

• T2 or T2*– ??

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Inversion Recovery (IR-prep)

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IR-Prepped T1-Weighted Images

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Generating T2- (and T2*-)weighted Images

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Thought problem: What can cause nearby protons to lose phase

coherence?(They must precess at different rates… what could cause

that to happen?)

Indianapolis = 2.5mi

Darlington = 1.4mi

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T2Cars on the same track

Indianapolis = 2.5mi

Darlington = 1.4mi

T2 : spin-spin relaxation T2* : spin-spin interactions + local field

inhomogeneities

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How can we compensate for the fact that local field inhomogeneities cause

some spins to precess faster than others?

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Phase Compensation via Spin-Echo

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Creating T2-weighted Images

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Overview of Imaging Parameters

• Proton-Density-Weighted– Long TR, short TE

• T1

– Intermediate TR, short TE

• T2 or T2*– Long TR, intermediate TE

FMRI – Week 4 – Contrast Scott Huettel, Duke University

PD ImagesPD Images

T2* ImagesT2* Images

T2* = Sensitivity to Field Inhomogeneity

Susceptibility Artifacts

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Types of Contrast

• Static Contrast– Proton Density – T1

– T2

– T2*

• Motion Contrast– Flow (e.g., Time of Flight)– Perfusion– Diffusion

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Time of Flight (ToF) Flow Imaging

Angiogram

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Perfusion Imaging

Perfusion: The irrigation of tissue through blood delivery (typically through capillaries).

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Perfusion Contrast

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PerfusionPerfusionDiffusionDiffusion

Reduced Perfusion following Stroke

By adding diffusion weighting (to eliminate the effects of flow), perfusion imaging can be made

specific to capillaries.

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Diffusion (in homogeneous medium)

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Core Approach of Diffusion Tensor Imaging (DTI)

Gx

Apply alternating, opposite gradients along one direction.

Measure signal.

Apply alternating, opposite gradients along a different

direction. Measure signal.

Repeat for a total of 6+ directions. The amplitude of the

signal across these directions constitutes the diffusion tensor.

Gy

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Pulse Sequences for DTI

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Diffusion Tensors

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ADC FA

Measures Provided by Diffusion Imaging

Tracts

Apparent Diffusion

Coefficient (ADC): Information

about the relative mobility of protons.

Fractional Anisotropy (FA):

Information about the

constraints on proton mobility.

Tractography: Information about the

directionality of proton mobility

across the brain.

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Isotropic and Anisotropic Diffusion

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Reduced Anisotropic Diffusion in Older Adults

OlderYounger

Data from Madden et al. (2007)

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Madden et al. (in press)

Older (60-85y) and younger (18-27y) adults

made categorical judgments.

We modeled information accumulation (i.e., drift rate) using a model for each subject’s response

time.

Age-related variance in information accumulation was reduced dramatically, when integrity of two fiber tracts was included in the

model.

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Fiber Tracking (Tractography)

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AB

C

D

Integrating DTI and fMRI

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Common Fast Imaging Sequences

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Echo-Planar Imaging (EPI)

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Gradient Artifacts in EPI Images

None

X

Y

Z

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Spiral Imaging

Shown is a spiral-out sequence.

We could also use spiral-in or spiral-in-and-out

sequences.

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Interpolation of Spiral Images

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Gradient Artifacts in Spiral Images

None

X

Y

Z

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EPI vs. Spiral Imaging

• Both can acquire 64*64 resolution T2*-weighted images within about 40ms (~20slices/s) on BIAC scanners

• EPI Properties– Generally fast, simple, efficient– Covers k-space in Cartesian coordinates– Subject to flow effects (gradient at k=0)

• Spiral Properties– Very fast, uses both gradients simultaneously– Shorter time between images (spiral-in)– Easier on gradients– Requires interpolation in k-space– Minimizes flow effects (no gradient at k=0)– Can easily add preparatory gradients (spiral-out)

FMRI – Week 4 – Contrast Scott Huettel, Duke University

FMRI – Week 4 – Contrast Scott Huettel, Duke University

Gradient Problems

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Magnetic Field Inhomogeneity