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1 Carnegie Mellon Reconstruction of 3-D Dense Cardiac Motion from Tagged MRI Sequences Hsun - Hsien Chang and José M.F. Moura Dept. of Electrical and Computer Engineering Yijen Wu, Kazuya Sato, and Chien Ho Pittsburgh NMR Center for Biomedical Research Carnegie Mellon University, Pittsburgh, PA, USA Work supported by NIH grants (R01EB/AI-00318 and P4EB001977)

Reconstruction of 3-D Dense Cardiac Motion from Tagged …moura/seminars/ISBI Presentation-04... · Reconstruction of 3-D Dense Cardiac Motion from Tagged MRI Sequences ... – Continuum

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Page 1: Reconstruction of 3-D Dense Cardiac Motion from Tagged …moura/seminars/ISBI Presentation-04... · Reconstruction of 3-D Dense Cardiac Motion from Tagged MRI Sequences ... – Continuum

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Carnegie Mellon

Reconstruction of 3-D Dense Cardiac Motion from Tagged MRI Sequences

Hsun- Hsien Chang and José M.F. MouraDept. of Electrical and Computer Engineering

Yijen Wu, Kazuya Sato, and Chien HoPittsburgh NMR Center for Biomedical Research

Carnegie Mellon University, Pittsburgh, PA, USA

Work supported by NIH grants (R01EB/AI-00318 and P4EB001977)

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Carnegie Mellon

Outline

• Introduction• Methodology: Prior knowledge + MRI data

– Myocardial Fiber Based Structure

– Continuum Mechanics

– Constrained Energy Minimization

• Results and Conclusions

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Carnegie Mellon

Nslices

M frames per slice

Y. Sun, Y.L. Wu, K. Sato, C. Ho, and J.M.F. Moura, Proc. Annual Meeting ISMRM 2003

sparse displacements

2-D Cardiac MRI Images

dense displacements

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3-D Reconstruction: myocardial fiber model

Use a fiber based model to find the correspondence between transversal slices.

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3-D Reconstruction: fiber deformation model

Use continuum mechanics to describe the motion of fibers.

Fit the model to MRI data by constrained energy minimization

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Carnegie Mellon

Outline

• Introduction

• Methodology: Prior knowledge + MRI data– Myocardial Fiber Based Structure

– Continuum Mechanics

– Constrained Energy Minimization

• Results and Conclusions

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Carnegie Mellon

Endocardium

-60º

+60º

Mid-wall

Epicardium

Prior Knowledge: myocardial anatomy

Streeter, in Handbook of Physiology Volume 1: the Cardiovascular System, American Physiological Society, 1979

Multiple-layer view:

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Carnegie Mellon

a(t) da(t)a(t)+da(t)

a(0)+da(0)a(0)

da(0)

Displacement:u(t)=a(t)-a(0)

)0()0(

)()( a

aa

a dt

td∂∂=

Motion of a small segment

=

)(

)(

)(

)(

3

2

1

ta

ta

ta

ta

Notations are column vectors, ex:

Prior Knowledge: fiber dynamics

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Deformation Gradient Matrix

=∂∂=

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂

)0(

)(

)0(

)(

)0(

)()0(

)(

)0(

)(

)0(

)()0(

)(

)0(

)(

)0(

)(

3

3

2

3

1

3

3

2

2

2

1

2

3

1

2

1

1

1

)0(

)()(

a

ta

a

ta

a

taa

ta

a

ta

a

taa

ta

a

ta

a

ta

tt

aa

F

+=∂∂+=+=

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂

)0(

)(

)0(

)(

)0(

)()0(

)(

)0(

)(

)0(

)()0(

)(

)0(

)(

)0(

)(

3

3

2

3

1

3

3

2

2

2

1

2

3

1

2

1

1

1

)0(

)()(

a

tu

a

tu

a

tua

tu

a

tu

a

tua

tu

a

tu

a

tu

ttd I

au

IFI

Deformation gradient F(t) is a function of displacement u(t).

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Strain

)(2

1IFFS −= T

[ ] IFFIIFIFS −+=−+++≈ )(2

1

2

1 TT dd

• When strain is small, it is approximated as

• Strain is the displacement per unit length, and is written mathematically as

Ref: Y.C. Fung, A First Course in Continuum Mechanics, 3rd ed., Prentice-Hall, New Jersey, 1994

(Note: S is symmetric)

[ ] [ ]FFFFIFIFIS dddddd TTT ++=−++=2

1)()(

2

1

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Linear Strain Energy Model

• S is symmetric, so we vectorize the entries at upper triangle.

=

33

2322

131211

S

SS

SSS

S

)(uCss ee T ==

[ ]TSSSSSS 231312332211 ,,,,,=s

• Let C describe the material properties. It can be shown the linear strain energy is

• The entire energy of the heart:

∑ ∑∑ ∑∀ ∀∀ ∀

==fibers segmentsfibers segments

)()( CssuU TeE

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Constrained Energy Minimization

• Internal energy: continuum mechanics governs the fibers to move as smooth as possible.

∑ ∑∀ ∀

=fibers segments

T)( CssUintE

)()()(),( 21 UUUU conextint EEEE λγγλ ++=

2)1()()( +−= ttEext IIU

• External energy: pixel intensities of fibers should be kept similar across time.

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2-D Displacement Constraints

)()()(),( 21 UUUU conextint EEEE λγγλ ++=

D: 2-D displacements of the taglines

ӨU: picks the entries of U corresponding to D

2-D displacement constraints: ӨU=D

λ: Lagrange multiplier

2

21 )()(),( DΘUUUU −++= λγγλ extint EEE

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Outline

• Introduction

• Methodology: Prior knowledge + MRI data– Myocardial Fiber Based Structure

– Continuum Mechanics

– Constrained Energy Minimization

• Results and Conclusions

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4slices

10 frames per sliceData Set

256×256 pixels per image

Y. Sun, Y.L. Wu, K. Sato, C. Ho, and J.M.F. Moura, Proc. Annual Meeting ISMRM 2003

Transplanted rats with heterotropic working hearts.

MRI scans performed on a Bruker AVANCE DRX 4.7-T system

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Whole left ventricle

endocardium mid-wall epicardium

Fiber Based Model

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3-D Reconstruction of the Epicardium

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Conclusions

• Take into account the myocardial fiber based structure.

• Adopt the continuum mechanics framework.

• Implement constrained energy minimizationalgorithms.