Recent advances in quantitative MR spectroscopy · Recent advances in quantitative MR spectroscopy...

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July 2009

Recent advances in quantitative MR spectroscopy

Anke Henning, PhDInstitute for Biomedical Engineering, University and ETH Zurich, Switzerland

AAPM 2009 – Quantitative MRI and MRS Symposium

Cho tCr

Ins

tCr

GlxGlx

NAA

Gln

NAA

3T

Courtesy: Dept. of Radiology, University of Bonn, GermanyCourtesy: Dept. of Radiology, University of Bonn, Germany

MOTIVATION: non-invasive metabolite quantification

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NAA

CreCho

MOTIVATION: Spectroscopic Imaging

NAA

Cho


B0

f0 = γ* x B0

γ: property of nucleus

γ*H = 42.58 Mhz/T

γ*P = 17.24 Mhz/T

γ*C = 10.71 Mhz/T

)2πγ

*(γ =

51.7 MHz25.85 MHz31P

127.73 MHz63.86 MHz1H

3 T1.5 T

Lamor frequency

13C 32.12 MHz16.06 MHz

BASIC PRINCIPLE: Larmor frequency

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+H

-e

B0

BASIC PRINCIPLE: Chemical Shift


H HC

H

ion bondinghydrogen deprived from electron

weak shielding

covalent bondingshared electrons

strong shielding

Water Water FatFat


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Cho

Cre

NAA

t

FID

Spectrum

f

Cho CreNAA

FTTime domain Frequency domain



BASIC PRINCIPLE: J-coupling

O H

C-C-CH3

O OHrest CH CH3

OH

1:1

1:3:3:1

1H SPECTRUM OF LACTATE

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BASIC PRINCIPLE: metabolite concentrations


QUANTIFICATION

area under peak / amplitue of FID

estimation of fitting reliability

additional influence factors

reference standard

concentrations in mM

relat

iveab

solu

te

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QUANTIFICATION

Estimation of area under peak / amplitue of FID: - time domain vs. frequency domain- peak integration- line fitting (JMRUI/AMARES; scanner packages)

- fitting of basis spectra (LC Model; JMRUI/QUEST; TDFD Fit )

- considering phase evolution & distortion- considering RF pulses- spatial statistics for MRSI fitting- 2D prior knowledge fitting (ProFit)


QUANTIFICATION: time vs. frequency domain

jMRUIVAPRO

SVD

TDFDfitLCmodel

ProFit

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QUANTIFICATION: time vs. frequency domaintime domain fitting frequency domain fitting

TDFDfit: Slotboom et al; Magn Reson Med. 1998 Jun;39(6):899-911.

signal truncationcan be considered

frequency range can not berestricted residual waterand lipid signals have to bemodeled or suppressed byadditional filters

fitting of multi-frequencybasis spectra is not straight forward

user-dependent prior knowledgerequired to initialise fit: frequencies, linewidth, phase

signal truncationcan not be considered directly

frequency range can berestricted residual waterand lipid might be consideredas baseline

fitting of linear combination of multi-frequency basis spectrastraight forward

no user-dependent priorknowledge required to initialisefit

discrete time domain model and frequency domain fitting


Problemsoverlapping peaksbaselinephasing

-> magnitude spectra-> complex integration

depends on shimming

QUANTIFICATION: peak integration

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QUANTIFICATION: peak fitting

Problemsoverlapping peaks baselinephasing

-> magnitude spectra-> complex integration

depends on shimming

JMRUI/AMARES; scanner packages


QUANTIFICATION: Fitting basis spectraFitting a linear combination of basis spectra

LCmodel; TDFDfit; ProFit; jMRUI/QUEST

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QUANTIFICATION: macro-molecular baseline

De Graaf; In vivo NMR spectroscopy; WILEY 2007 (2nd Edition)

Hofmann L et al, Magn Reson Med.2002 Sep;48(3):440-53.


QUANTIFICATION: “spline fit” (LCModel)

insufficient water suppression

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RF

GR

90°5.5 ms

Cre

Cho

Glx

NAA

MM

strong linear phaseacquisition delay

= truncation of first

few points of the FID

FID(LOVS) MRSI

Henning et al, NMR in Biomedicine (Epub ahead of print), 2009.

QUANTIFICATION: truncation of FID


OVSOVSOVS

RF

GM

GP

GS

VAPOR - WS MRSI

90° * 90° 160° 90° 140° 90° 160° 160°

150 ms 100 ms 122 ms 105 ms 102 ms 61 ms 67 ms **

FID acquisition Localized by Outer Volume Supression

Tkac et al, Magn Reson Med, 41:649-659, 1999. Henning et al, Magn Reson Med 59:40-51, 2008.



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NAA

a ba

b

c

NAA

Cre

Cho

modulationsidebands

two pulse WS prior OVS VAPOR



Non-apodized spectra from individual voxels

white matter

Voxel size: 1 ml; TR = 4500 ms; Acquisition time: 26 min

AspGln

NAAG

Glu

Cho

Tau

mI

GlxCre

scylloI

CreGM

Cre

NAA

NAAG

GSHCho

GABA

NAA

Cre Glx mI

NAA

WM

grey matter


How reliable is the quantification of FIDLOVS MRSI data?


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NAA

Cre

Cho

mI

GSH

GABA

Glu

Gln



truncationincorporated

in the time domainof model spectra

AAPM 2009 – Quantitative MRI and MRS SymposiumHenning et al, NMR in Biomedicine (Epub ahead of print), 2009.


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voxel size: 1 ml

(1 cm3)

no phase correction prior fitting

phase correction prior fitting



90° 180°t2

Tacq=TE=t1(1)

QUANTIFICATION: 2D J-resolved MRS

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90° 180°t2

Tacq=TE=t1(2)



90° 180°t2

Tacq=TE=t1(3)


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90° 180°

CSsame evolution

FT along t1

Jdifferent evolution



QUANTIFICATION: 2D JPRESS & ProFIT

Schulte et al, NMR Biomed 19(2), 255-263 & 264-270, 2006.

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QUANTIFICATION: 2D JPRESS & ProFIT

Schulte et al, NMR Biomed 19(2), 255-263 & 264-270, 2006.

time efficient

model-free regularization

fit of linear combination of model spectra(discrete, simulated time domain model:

max echo sampling pattern considered)

global fit parameters: zeroth-order phaseGaussian line broadening in f2shift in f1biexponential phase decay due

to eddy currents

individual fit parameters: concentrationsame exponential line-broadening

for f1 and f2shift in f2

robust convergence

ProFit = VAPRO & LCModel


fitting a linear combinationof 2-dimensional COSY basis metabolite sets

Alexander Fuchs, IBT

QUANTIFICATION: COSY & ProFIT

Extension of ProFitto other 1D or 2D sequences possible!

courte

sy of IBT, Unive

rsity a

nd ETH Zurich

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QUANTIFICATION

Estimation of fitting reliability:- Residue- Cramer-Rao lower bounds (CRLB) - Covariance matrix- CRLB maps for MRSI


QUANTIFICATION: residue

Tkac I et al; ISMRM (2008) 16:1624 Govindaraju et al; ………………..

mouse brain, 9.4 T

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QUANTIFICATION: Fisher information matrix


)(1

2 DPDPF HT

Nσ=

Fisher information matrix

standard deviation of noise

transposition

Hermitianconjugation

j

iij p

xD

∂∂

=

model function matrix element:

model function

parameter n

mmn p

pP

∂∂

=

prior knowledge matrix element:

parameter n

parameter m

model function: exponentially damped, gaussian filtered sinusoidsparameters: metabolite prior knowledge (frequencies, coupling constants)


QUANTIFICATION: CRLB1−=≥ iipp FCRLB

iiσ inverted Fisher

information matrix

Cramer-Rao Lower bounds

standard deviationof fitting result for

parameter i

Tkac I et al; ISMRM (2008) 16:1624.

diagonal elements

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Ala

Asc

Asp Glc

LacCre

GA

BA

Gln

Glu

tCh

o

GS

H mI

MM

/ L

ip

NA

A

NA

AG

PE

scyl

loI

Tau


1H FIDLOVS MRSI @ 7T

statistical analysis considers SNR

QUANTIFICATION: CRLB


QUANTIFICATION: covariance matrix

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1

−−

−

=nnmm

mnmn

FF

Fρ

unambiguous and simultaneous quantification of GABA, Gln, Glu and NAA

JPRESS @ 3T

Walter/Henning/Grimm et al, Archives of General Psychiatry 2009; 66(5):478-486

covariance coefficientfor parameters m and n inverted Fisher

information matrices

off-diagonal elements

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QUANTIFICATION: covariance matrix

JPRESSCOSY

1D

Fuchs et al, ISMRM (2009) 17: 2406.

3T

courtesy of IBT, University and ETH Zurich


GM WM

GM WM Cortex voxel

GM

WM Cor

voxel size: 0.2 ml (6 mm3)

QUANTIFICATION: covariance matrix & CRLB maps1H FIDLOVS MRSI @ 7T


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no phase correction prior fittingTau

scylloIPE

PChNAAGNAA

MM/LipmI

LacGSHGPCGluGlnGlc

GABACreAspAscAla

Ala

Asc

Asp Cre

GA

BA

Glc

Gln

Glu

GP

CG

SH

Lac m

IM

M/ L

ipN

AA

NA

AG

PC

hP

Esc

yllo

IT

au Ala

Asc

Asp Cre

GA

BA

Glc

Gln

Glu

GP

CG

SH

Lac m

IM

M/ L

ipN

AA

NA

AG

PC

hP

Esc

yllo

IT

au


correlation analysis considers spectral overlap at original shim quality


QUANTIFICATION: covariance matrix1H FIDLOVS MRSI @ 7T


no phase correction prior fitting

QUANTIFICATION: CRLB maps


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QUANTIFICATION: CRLB maps



QUANTIFICATIONAdditional influence factors:

Smet = Cmet x NS x RG x V x ω0 x fsequence x fcoil x fadd

# averages receive gain

volume

volume

metaboliteconcentration

metabolitesignal

intensity

fsequence:

fcoil:

fadd:

TE (T2); TR (T1); partial volume effectsRF pulses (phase evolution, NOE);gradients (diffusion)

transmit and receive B1 distribution, power optimizationcoil load (load dependent resistance of coil)contributing nuclei per moleculeB0 , temperature, pH, conductivity artifacts (f.i. eddy currents; lipid and water)

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Relaxation

Tkac et al; Magn Reson Med 46:451, 2001

T2 relaxation

invivoE

phantomET TT

TTf

)/exp(

)/exp(

2

2

2 −−

=

invivoR

phantomRT TT

TTf

)/exp(1

)/exp(1

1

1

1 −−−−

=

1T2T

metcorr,met f*f

cc =

Or: TR > 5 T1, max

TE ultra-short (also for diffusion)


QUANTIFICATION: IDAP

IDAP: Kreis et al, Magn Reson Med 54, 761-768, 2005; .TDFDfit:

multi-dimensional fitting

Slotboom et al; Magn Reson Med. 1998 Jun;39(6):899-911.

Basis spectra can be subdived intoparts with different T2 relaxation behavior:T2 determination from lineshape analysis.

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0.5 kHz

0.9 kHz

1.6 kHz90°

180°

180°

1.6 kHz

3.6 kHz

28.3 kHz9.1 kHz4.65 kHz

90°

180°

30°90°150°

RF pulses


LacGlxH2O NAACre

0 -1000-200 -400 -600 -800

90° 180°90° 180°

excitation & refocusing

RF pulses

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RF pulses

90° 180°

90°

180°

PRESS7T

brain phantomTE = 66 ms

pulses andgradients need

to be consideredin simulations

of basis spectra


Contributing nuclei per molecule

CH3

HO-CH2-CH2-N-CH3

CH3

CholineO O

C-CH2-CH-C

O NH O

C=O

CH3

N-Acetylaspartate

H3C-N-CH2-COO-

C=NH2+

NH2

Creatine

2 mM 6 mM

12 mM

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B1 and B0 inhomogeneity


Transmit B1

B0

line broadephase encod


Conductivity, pH and temperature

0))()(3

21()( BTTTwater σχγω −−=

Buchli R.; SMRM (1990) 9:504


bulk susceptibility electronicshielding

)log(δδ

δδ−

−+=A

HAApKpH

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QUANTIFICATION

Reference standards:-Internal reference standards (water, creatine)

-External reference calibration (simultaneous phantom calibration)

-Symmetric phantom calibration-Phantom replacement method (simulation phantom calibration)

-ERETIC (Electric reference to assess in vivo concentrations)


QUANTIFICATION: metabolite ratios

tCr (PCr + Cr): 1. Energy Buffer:H + PCr + ADP ⇔ ATP + Cr

2. Energy shuttle: “Energy transport” from production (mitochondria) to energy utilizing sites

The CRE peak is stable during activation/exercise and therefore may serve as an internal reference for 1H MRS.

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QUANTIFICATION: metabolite ratios

relative quantification: ambigious

or ?

healthy pathology


QUANTIFICATION: internal water reference

assumes stable and known water concentration

additional unsuppressed water spectrum needs to be measured from same voxel

be sure the same preparation settings are used (e.g. receiver gain & power optimizations, shimming)

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QUANTIFICATION: internal referencesAdvantages Disadvantages

coil loadreceive gain settingsvolumetemperaturpHconductivity

are considered

B1 inhomogeneities power optimization

are considered forthe same type of nucleus (f.i. internalwater reference for 1H MRS)

internal water or referencemetabolite concentrations as well as all relaxation times depend on:

agevoxel composition (f.i. CSF content)

and change in pathologies

B1 inhomogeneities PO

are not considered fordifferent types of nuclei(f.i. internal water referencefor 31P and 13C MRS)


QUANTIFICATION: external reference calibration

External reference calibrationphantom with known concentrationB1 variations should be taken into account especiallyfor surface coilsbe sure the same preparation settings are used

(f.i. receiver gain & power optimizations, shimming)

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QUANTIFICATION: external reference calibrationAdvantages Disadvantages

additional reference spectrumneeded each timereceive gain settingsvolumetemperaturpHconductivityB1 inhomogeneitiespower optimizationrelaxation times of in vivo metabolites

need to be consideredby adjustments or correctionfactors determined byadditional measurements

known & stableconcentration forreference standard

known relaxation timesfor reference standard

coil load is directlyconsidered


QUANTIFICATION: symmetrical phantom calibration

Symmetric phantom calibrationphantom with known concentrationbe sure the same preparation settings are used for localized version(f.i. receiver gain & power optimizations, shimming)

Buchli et al, MRM (1993) 30: 552-558.

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QUANTIFICATION: symmetrical phantom calibrationAdvantages Disadvantages

additional reference spectrumneeded each timereceive gainvolumetemperaturpHconductivityrelaxation times of in vivo metabolites


known & stableconcentration forreference standard

known relaxation timesfor reference standard

coil load is directlyconsideredB1 inhomogeneities aredirectly considered ifconductivity of phantom isadjusted to in vivo valuesand PO is not repeated forphantom measurement


QUANTIFICATION: phantom replacement method

make sure to adjust coil load to in-vivo condition by moving the saline tube in or out each time

correction for receiver gain is necessary

power optimization & shim differences are not considered

saline

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QUANTIFICATION: phantom calibration methodsAdvantages Disadvantages

coil load (additional reference spectrumneeded each time)receive gain settingsvolumetemperaturpHconductivityB1 inhomogeneities PO relaxation times of in vivo metabolites


known & stableconcentration forreference standardknown relaxation timesfor reference standard


ERETIC: Electric REference To access In vivo Concentrations

Heinzer-Schweizer et al, ISMRM 2009: 232


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ERETIC: Fitting with LC Model & TDFD fit




ERETIC: Electric REference To access In vivo Concentrations

Why ERETIC?

1H MRS @ 1.5T and 3T: reliable reference standard in lesions where waterconcentration is unknown

clinical application

13C & 31P MRS @ 3T & 7T: reliable reference standard

no internal reference availablewater reference is unreliable sincetransmit and receive fields of waterand heavy nucleus are very different at 3T & 7T

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ERETIC: optical signal transmission




ERETIC: optical vs. electrical signal transmission



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ERETIC: scaling with coil load




ERETIC: stability over time



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ERETIC: phantom calibration




ERETIC: cross validation with internal water reference



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31P MRS: simultaneous 1H decoupling and ERETIC

Schweizer et al, ISMRM 2008: 193.

ATP ATP



JPRESS & ERETIC

ERETIC NAA Cho Cr Cr

in vivo, 3T, GM rich voxel

H2OMM

Fuchs et al, ISMRM 2009: 2405.


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QUANTIFICATION: ERETICAdvantages Disadvantages

volumetemperaturpHconductivityB1 inhomogeneities PO relaxation times of in vivo metabolites

need to be considereddue to adjustments orcorrection factorsdetermined byadditional measurements

known & stablereference standardknown relaxation timesfor calibration metabolitesreceive gain settingsconsideredcoil load directlyconsideredphantom calibration needsto be performed only once


IBT spectroscopy group

Mateo PavanNicola de Zanches Rolf F. SchulteKlaas Pruessmann

Recent advances in quantitative MR spectroscopy · Recent advances in quantitative MR spectroscopy...

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