HHighlighlYY Constrained Back Constrained Back PRPRojection (ojection (HYPRHYPR))

Thank you to Oliver Wieben!!

K-space

time

1 3 5 7 9

‘Composite’

HHighlighlYY Constrained Back Constrained Back PRPRojection (ojection (HYPRHYPR))

HHighlighlYY Constrained Back Constrained Back PRPRojection (ojection (HYPRHYPR))

• An approximate acquisition and reconstruction method

• Images should be sparse (few pixels w/signal)

• No movement allowed!

• Fairly high spatio-temporal correlations

• Radial under-sampling at each time frame• Decrease total scan time• Improve temporal resolution

• Composite image • Combines data from many time frames • Allows higher SNR for each time frame• Constrains the backprojection reconstruction for each time frame which reduces streak artifacts

Mistretta, et al., MRM 55:30-40;2006

Interleaving – Dynamic ImagingInterleaving – Dynamic Imaging1. Acquire data in interleaves

Highly undersample each time frame

1 2 3 4 5 6 7 8 9 ….

K-space

CE-MRA time

artery vein

signal

All Inclusive CompositeAll Inclusive Composite2. Calculate composite images

Sum of ALL projections through time

1 2 3 4 5 6 7 8 9 ….

K-space

All inclusive composite

Sliding CompositeSliding Composite2. Calculate composite images

Sum of “some” projections through time

1 2 3 4 5 6 7 8 9 ….

K-space

2. Calculate composite imagesSum of “some” projections through time

1 2 3 4 5 6 7 8 9 ….

K-space

Sliding CompositeSliding Composite

2. Calculate composite imagesSum of “some” projections through time

1 2 3 4 5 6 7 8 9 ….

K-space

Sliding CompositeSliding Composite

All-inclusive versus Sliding CompositeAll-inclusive versus Sliding Composite

All-inclusive Composite+ High SNR

+ Few streak artifacts

Good for nearly homogeneous temporal behaviour

– In CE-MRA: contains early and late filling vessels

The SNR of the composite dictates the SNR in thetime-resolved images

Sliding Composite– Lower SNR– More streak artifacts

+ Better separates early and late filling vessels

k-space projections

Image-space projections

N21

1D FT 1D FT 1D FT 1D FT

N21

Time frames withinterleaved angular projections

time

Filtered backproject.

Composite image

or sum,regrid, and FT

Multiply

HYPR time frame N

Radon + Unfiltered backprojection

P/Pc

PPc

Sum over all projections

H C . ppci

Unfiltered backproject.

BackprojectionBackprojection

k-space projections

Image-space projections

N21

1D FT 1D FT 1D FT 1D FT

N21

Time frames withinterleaved angular projections

time

Filtered backproject.

Composite image

or sum,regrid, and FT

Multiply

HYPR time frame N

Radon + Unfiltered backprojection

P/Pc

PPc

Sum over all projections

Unfiltered backproject.

H C . ppci

Input (Truth)

Composite Weighting HYPR

× =

Schematic

Two Vessels – Horizontal – All-inclusiveTwo Vessels – Horizontal – All-inclusive

F. Korosec & Y. Wu

Input (Truth)

Composite Weighting HYPR

× =

Schematic

Wro

ng!

Two Vessels – Vertical – All-inclusiveTwo Vessels – Vertical – All-inclusive

F. Korosec & Y. Wu

More Projections per HYPR Time FrameMore Projections per HYPR Time Frame

HYPR

HYPR

HYPR

HYPR

Weighting

Weighting

Weighting

Weighting

1 Projection 4 Projections

2 Projections 8 Projections

F. Korosec & Y. Wu

Input Curves and Vessel LocationsInput Curves and Vessel Locations

Input Curves Vessel Locations

F. Korosec & Y. Wu

Composite Image #5Composite Image #5Composite

100 projections5 frames x 20proj/frame

Time Frame #5

Input Curves

Time frame #5

F. Korosec & Y. Wu

Composite Image #5Composite Image #5Composite

100 projections5 frames x 20proj/frame

Time Frame #11

Input Curves

Time frame #11

F. Korosec & Y. Wu

Time Curves – Input and HYPRTime Curves – Input and HYPR

Input HYPR

F. Korosec & Y. Wu

HYPR SimulationHYPR Simulation

Parameters– Gd-doped water injected in tube

– 2D Fourier acquisition @ 1 frame / s

– Generate k-space projections from images (Matlab)

– Simulate HYPR acquisition

– 32 projections per interleave

– 8 unique sets of interleaves• -> 256 angles sampled

– Composite image: moving window [-4 .. +3]

Simulation – Time Frame 5Simulation – Time Frame 5Original Undersampled

Composite HYPR

Simulation – Time Frame 9Simulation – Time Frame 9Original Undersampled

Composite HYPR

Comparison Videos: FootComparison Videos: Foot

Undersampled16 projections per time frame

T = 2.0 s

HYPR

T = 2.0 s

Comparison Videos: CalfsComparison Videos: Calfs

Undersampled16 projections per time frame

T = 2.1 s

HYPR

T = 2.1 s FOV = 48 cm, BW = 62.5 kHz, flip = 25 deg.

TR/TE = 5.2 / 1.1 msHYPR frame rate = 2.1 sComposite: sliding window (duration: 16*2 = 32s)

ApplicationsApplications

HYPR Applications– Dynamic Contrast-enhanced

MR Angiography– Quantitative Flow Imaging– Diffusion Tensor Imaging– MR and CT Perfusion Imaging– Cardiac Function

HYPR SummaryHYPR Summary

– Improves temporal resolution (also reduces total imaging time)

– Improves SNR by incorporation of a time averaged composite image

– Small number of projections are used to produce weighting images that are multiplied by high SNR composite image

– Composite image constrains backprojection to reduce streak artifacts

– Degree of achievable undersampling depends on

• sparsity

• spatio-temporal correlation

• acceptable error