Physics:Extended phase graph

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Short description: MRI sequence simulation technique
The extended phase graph formalism represents the spin vectors along a voxel as a sum of helices with integer numbers of twists.[1]

In magnetic resonance imaging and nuclear magnetic resonance the extended phase graph (EPG) is a mathematical framework used to track how magnetization evolves in a voxel through a series of radiofrequency (RF) pulses and gradients. While traditional Bloch simulations track individual spins in the spatial domain, EPG operates in the Fourier domain.[2] The magnetization vectors along one dimension of a voxel are stored as Fourier coefficients. Each Fourier coefficient represents the weighting of a helix that twists along one dimension of the voxel with an integer number of twists. Performing a weighted sum of all the helices gives the magnetization vectors in the spatial domain. In this representation, a gradient along one dimension of the voxel that causes an integer number of twists simply shifts the index of each Fourier coefficient by that integer, making EPG very computationally efficient at modeling sequences with many RF pulses and gradients. EPG was first proposed by Jürgen Hennig to model multiecho sequences[2] and is now used to model magnetic resonance fingerprinting,[3] turbo spin echos,[4] and other sequences.[5]

Definition

In the Bloch equations, within a voxel each spin along the dimension z can be described by a magnetization vector [Mx(z),My(z),Mz(z)]T where every element is real valued.[6] But Mx(z) and My(z) can also be described by the complex number M+(z)=Mx(z)+iMy(z).[7] Using a similarity matrix S we can convert between the real valued basis and the complex transverse magnetization basis:

S=[1i01i0001],𝐦(z)=[M+(z)M(z)Mz(z)]=S[Mx(z)My(z)Mz(z)]

where M is the complex conjugate of M+. To perform a rotation on the complex magnetization vector 𝐦 due to an RF pulse with angle α and phase ϕ, we first apply a change of basis with S1, then apply standard cartesian rotation matrices Rz(ϕ), Rx(α),[8] then another change of basis with S:[9]

Rz(ϕ)=[cosϕsinϕ0sinϕcosϕ0001],Rx(α)=[1000cosαsinα0sinαcosα]Tϕ(α)=SRz(ϕ)Rx(α)Rz(ϕ)S1Tϕ(α)=[cos2α2e2iϕsin2α2eiϕsinαe2iϕsin2α2cos2α2ieiϕsinαi2eiϕsinαi2eiϕsinαcosα]𝐦+(z)=Tϕ(α)𝐦(z)

Where 𝐦+ denotes the magnetization vector after the rotation. In the EPG representation we perform a Fourier decomposition of each element of the complex magnetization vector:[2]

M+(z)=k=F+(k)ei2πkzF+(k)=0.50.5M+(z)ei2πkzdzM(z)=k=F(k)ei2πkzF(k)=0.50.5M(z)ei2πkzdzMz(z)=k=Z(k)ei2πkzZ(k)=0.50.5Mz(z)ei2πkzdz

If F+(k)=0, F(k)=0, and Z(k)=0 when k>n or k<n. We can write the summations as being from k=n to n. We can also write the Fourier coefficients as a vector valued function:

𝐟(k)=[F+(k)F(k)Z(k)],𝐦(z)=k=nn𝐟(k)ei2πkz

RF pulses

When performing a rotation, because Tϕ(α) is constant across k it can enter the sum:

𝐦+(z)=Tϕ(α)𝐦(z)=kTϕ(α)𝐟(k)ei2πkz𝐟+(k)=Tϕ(α)𝐟(k)

It can be seen in the equation above that the rotation matrix can be applied directly to the Fourier coefficients to produce updated Fourier coefficients.[1]

Gradients

A gradient in the z dimension that creates one twist from z=0.5 to z=0.5 can be applied with the matrix:

T(z)=SRz(2πz)S1=[ei2πz000ei2πz0001]

This matrix is independent of k so it can enter the Fourier sum:[10]

𝐦+(z)=T(z)𝐦(z)=T(z)k𝐟(k)ei2πkz=kT(z)𝐟(k)ei2πkz

Looking at each element of 𝐦+:

M++(z)=kei2πzF+(k)ei2πkz=kF+(k)ei2π(k+1)zM+(z)=kei2πzF(k)ei2πkz=kF(k)ei2π(k1)zMz+(z)=Mz(z)

Performing a substitution with k^=k+1 for the first element we get:

M++(z)=k^=n+1n+1F+(k^1)ei2πk^z

If F+(n)=0 and F+(n1)=0 the above summation is equal to:[11]

M++(z)=k^=nnF+(k^1)ei2πk^z

and it can be seen that F++(k)=F+(k1). By the same logic F+(k)=F(k+1). So gradients in the EPG formalism simply shift the indices of the Fourier coefficients.[12][1]

Relaxation

The relaxation and recovery matrices given by the Bloch equations for a real valued magnetization vector 𝐯 are:[7] E=[et/T2000et/T2000et/T1],𝐫=[00M0(1et/T1)]𝐯+=E𝐯+𝐫

Substituting with 𝐯=S1𝐦:

S1𝐦+=ES1𝐦+𝐫𝐦+=SES1𝐦+S𝐫

S and E are commutative so SES1=ESS1=E. Also S𝐫=𝐫, so:

𝐦+(z)=E𝐦(z)+𝐫=Ek𝐟(k)ei2πkz+𝐫=kE𝐟(k)ei2πkz+𝐫

𝐫 is a constant vector but we can still Fourier decompose it to 𝐫(z)=k𝐠(k)ei2πkz where 𝐠(k)=𝐫 if 𝐤=0 else 𝐠(k)=𝟎, so:[13]

𝐦+(z)=kE𝐟(k)ei2πkz+k𝐠(k)ei2πkz=k(E𝐟(k)+𝐠(k))ei2πkz

So it can be seen that to apply a relaxation, you can multiply every Fourier coefficient with the relaxation matrix E and then add the recovery vector 𝐫 to the 0th coefficient.[14]

Total signal in voxel

The total transverse signal in the voxel is obtained by integrating over M+(z):

M+total=0.50.5k=nnF+(k)ei2πkzdz=k=nn(F+(k)0.50.5ei2πkzdz)=k=nnF+(k)1i2πk(eiπkeiπk)

so when k is nonzero, F+(k) is multiplied by zero and doesn't end up in the sum. If k=0 the inner integral is 1. So the total transverse signal in the voxel is just F+(0). By the same logic the total longitudinal signal is Z(0).[11]

Coefficient redundancy

It can be proven that F+(k)=F(k)*:[13][15]

F(k)=M+(z)*ei2πkzdzF(k)=M+(z)*ei2πkzdz=(M+(z)ei2πkz)*dz=F+(k)*

and so in practice only coefficients with k0 are stored and if a gradient occurs that would shift a coefficient to having a negative index, instead that coefficient is conjugated and stored at a non-negative index.

Computation

In practice a discrete number of Fourier coefficients are tracked. A matrix can be set up with n+1 frequencies tracked like so:[14]

[F+(0)F+(1)...F+(n)F(0)F(1)...F(n)Z(0)Z(1)...Z(n)]

This matrix can be multiplied by the RF pulse rotation matrix Tϕ(α), or multiplied by the relaxation matrix E and then have r added to the first column, to update the coefficients. A gradient that adds one twist along the z dimension will result in the first row being shifted right by one, and the second row being shifted left. Then F+(0) can be set to F(0)*.[16]

References

  1. 1.0 1.1 1.2 Matthias Weigel (2015). "Extended phase graphs: dephasing, RF pulses, and echoes - pure and simple". J Magn Reson Imaging. doi:10.1002/jmri.24619. 
  2. 2.0 2.1 2.2 Jürgen K. Hennig (1988). "Multiecho Imaging Sequences with Low Refocusing Flip Angles". Journal of Magnetic Resonance 78: 397–407. doi:10.1016/0022-2364(88)90128-X. 
  3. Jiang, Yun; Ma, Dan; Seiberlich, Nicole; Gulani, Vikas; Griswold, Mark A. (2015). "MR fingerprinting using fast imaging with steady state precession (FISP) with spiral readout: MR Fingerprinting with FISP". Magnetic Resonance in Medicine 74 (6): 1621–1631. doi:10.1002/mrm.25559. PMID 25491018. PMC 4461545. https://onlinelibrary.wiley.com/doi/10.1002/mrm.25559. Retrieved 2026-01-21. 
  4. Weigel, Matthias; Hennig, Juergen (2006). "Contrast behavior and relaxation effects of conventional and hyperecho‐turbo spin echo sequences at 1.5 and 3 T". Magnetic Resonance in Medicine 55 (4): 826–835. doi:10.1002/mrm.20816. ISSN 0740-3194. https://onlinelibrary.wiley.com/doi/10.1002/mrm.20816. Retrieved 2026-01-21. 
  5. Sobol, Wlad T.; Gauntt, David M. (1996). "On the stationary states in gradient echo imaging". Journal of Magnetic Resonance Imaging 6 (2): 384–398. doi:10.1002/jmri.1880060220. ISSN 1053-1807. https://onlinelibrary.wiley.com/doi/10.1002/jmri.1880060220. Retrieved 2026-01-21. 
  6. Bloch, F. (1946). "Nuclear Induction". Physical Review 70: 4604–73. doi:10.1103/PhysRev.70.460. ISSN 0031-899X. 
  7. 7.0 7.1 Jaynes, E. T. (1955-05-15). "Matrix Treatment of Nuclear Induction". Physical Review 98 (4): 1099–1105. doi:10.1103/PhysRev.98.1099. ISSN 0031-899X. https://link.aps.org/doi/10.1103/PhysRev.98.1099. Retrieved 2026-01-25. 
  8. Hahn, E. L. (1950-11-15). "Spin Echoes". Physical Review 80 (4): 580–594. doi:10.1103/PhysRev.80.580. ISSN 0031-899X. https://link.aps.org/doi/10.1103/PhysRev.80.580. Retrieved 2026-01-25. 
  9. Woessner, D. E. (1961-06-01). "Effects of Diffusion in Nuclear Magnetic Resonance Spin-Echo Experiments". The Journal of Chemical Physics 34 (6): 2057–2061. doi:10.1063/1.1731821. ISSN 0021-9606. https://pubs.aip.org/jcp/article/34/6/2057/80177/Effects-of-Diffusion-in-Nuclear-Magnetic-Resonance. Retrieved 2026-01-25. 
  10. Lukzen, N.N.; Savelov, A.A. (2007). "Analytical derivation of multiple spin echo amplitudes with arbitrary refocusing angle". Journal of Magnetic Resonance 185 (1): 71–76. doi:10.1016/j.jmr.2006.11.010. https://linkinghub.elsevier.com/retrieve/pii/S1090780706003922. Retrieved 2026-01-25. 
  11. 11.0 11.1 Hennig, Jürgen (1991). "Echoes—how to generate, recognize, use or avoid them in MR‐imaging sequences. Part I: Fundamental and not so fundamental properties of spin echoes". Concepts in Magnetic Resonance 3 (3): 125–143. doi:10.1002/cmr.1820030302. ISSN 1043-7347. https://onlinelibrary.wiley.com/doi/10.1002/cmr.1820030302. Retrieved 2026-01-25. 
  12. Zur, Yuval (2004). "An algorithm to calculate the NMR signal of a multi spin-echo sequence with relaxation and spin-diffusion". Journal of Magnetic Resonance 171 (1): 97–106. doi:10.1016/j.jmr.2004.07.018. https://linkinghub.elsevier.com/retrieve/pii/S1090780704002265. Retrieved 2026-01-25. 
  13. 13.0 13.1 Scheffler, Klaus (1999). "A pictorial description of steady-states in rapid magnetic resonance imaging". Concepts in Magnetic Resonance 11 (5): 291–304. doi:10.1002/(SICI)1099-0534(1999)11:5<291::AID-CMR2>3.0.CO;2-J. ISSN 1043-7347. https://onlinelibrary.wiley.com/doi/10.1002/(SICI)1099-0534(1999)11:53.0.CO;2-J. Retrieved 2026-01-25. 
  14. 14.0 14.1 Weigel, M.; Schwenk, S.; Kiselev, V.G.; Scheffler, K.; Hennig, J. (2010). "Extended phase graphs with anisotropic diffusion". Journal of Magnetic Resonance 205 (2): 276–285. doi:10.1016/j.jmr.2010.05.011. https://linkinghub.elsevier.com/retrieve/pii/S1090780710001540. Retrieved 2026-01-25. 
  15. Sodickson, A (1998-08-31). "A generalized k-space formalism for treating the spatial aspects of a variety of NMR experiments". Progress in Nuclear Magnetic Resonance Spectroscopy 33 (2): 77–108. doi:10.1016/S0079-6565(98)00021-1. https://linkinghub.elsevier.com/retrieve/pii/S0079656598000211. Retrieved 2026-01-25. 
  16. Hargreaves, Brian; Miller, Karla (2013). "Using extended phase graphs: review and examples.". Proceedings of the 21st Annual Meeting of ISMRM. Salt Lake City. https://archive.ismrm.org/2013/3718.html.