Recent advances in quantitative MR spectroscopy

Transcription

1 Recent advances in quantitative MR spectroscopy Anke Henning, PhD Institute for Biomedical Engineering, University and ETH Zurich, Switzerland July 2009 MOTIVATION: non-invasive metabolite quantification 3T NAA tcr Cho tcr Glx Ins NAA Glx Gln Courtesy: Dept. of Radiology, University of Bonn, Germany 1

2 MOTIVATION: Spectroscopic Imaging NAA NAA Cho Cre Cho BASIC PRINCIPLE: Larmor frequency B 0 f 0 = γ* x B 0 (γ * = γ ) 2π γ: property of nucleus γ* H = Mhz/T γ* P = Mhz/T γ* C = Mhz/T 1 H 31 P 1.5 T MHz MHz Lamor frequency 3 T MHz 51.7 MHz 13 C MHz MHz 2

3 BASIC PRINCIPLE: Chemical Shift H + e - B 0 BASIC PRINCIPLE: Chemical Shift Water Fat H C H H ion bonding hydrogen deprived from electron weak shielding covalent bonding shared electrons strong shielding 3

4 BASIC PRINCIPLE: Chemical Shift NAA Spectrum FID t Cre Cho Cre NAA f Cho Time domain FT Frequency domain BASIC PRINCIPLE: J-coupling 1 H SPECTRUM OF LACTATE OH rest CH CH 3 O H C-C-CH 3 O OH 1:1 1:3:3:1 4

5 BASIC PRINCIPLE: metabolite concentrations QUANTIFICATION relative area under peak / amplitue of FID estimation of fitting reliability additional influence factors absolute reference standard concentrations in mm 5

6 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 jmrui VAPRO SVD TDFDfit LCmodel ProFit 6

7 QUANTIFICATION: time vs. frequency domain time domain fitting signal truncation can be considered frequency range can not be restricted residual water and lipid signals have to be modeled or suppressed by additional filters fitting of multi-frequency basis spectra is not straight forward user-dependent prior knowledge required to initialise fit: frequencies, linewidth, phase frequency domain fitting signal truncation can not be considered directly frequency range can be restricted residual water and lipid might be considered as baseline fitting of linear combination of multi-frequency basis spectra straight forward no user-dependent prior knowledge required to initialise fit discrete time domain model and frequency domain fitting TDFDfit: Slotboom et al; Magn Reson Med Jun;39(6): QUANTIFICATION: peak integration Problems overlapping peaks baseline phasing -> magnitude spectra -> complex integration depends on shimming 7

8 QUANTIFICATION: peak fitting Problems overlapping peaks baseline phasing -> magnitude spectra -> complex integration depends on shimming JMRUI/AMARES; scanner packages QUANTIFICATION: Fitting basis spectra Fitting a linear combination of basis spectra LCmodel; TDFDfit; ProFit; jmrui/quest 8

9 QUANTIFICATION: macro-molecular baseline De Graaf; In vivo NMR spectroscopy; WILEY 2007 (2 nd Edition) Hofmann L et al, Magn Reson Med Sep;48(3): QUANTIFICATION: spline fit (LCModel) insufficient water suppression 9

10 QUANTIFICATION: truncation of FID FID(LOVS) MRSI NAA ms Cho MM RF GR Cre Glx acquisition delay = truncation of first few points of the FID strong linear phase Henning et al, NMR in Biomedicine (Epub ahead of print), QUANTIFICATION: truncation of FID VAPOR - WS OVS OVS OVS MRSI RF 90 * ms 100 ms 122 ms 105 ms 102 ms 61 ms 67 ms ** G M G P G S FID acquisition Localized by Outer Volume Supression Henning et al, NMR in Biomedicine (Epub ahead of print), Tkac et al, Magn Reson Med, 41: , Henning et al, Magn Reson Med 59:40-51,

11 QUANTIFICATION: truncation of FID a b a c Cho modulation sidebands b Cre NAA NAA two pulse WS prior OVS VAPOR QUANTIFICATION: truncation of FID Non-apodized spectra from individual voxels Voxel size: 1 ml; T R = 4500 ms; Acquisition time: 26 min white matter WM NAA grey matter GM Cre NAAG NAA How reliable is the quantification of FIDLOVS MRSI data? Cre NAAG scylloi GSH Cho NAA Cre Glx mi GABA Cre Glx mi Cho Asp Gln Glu Tau Henning et al, NMR in Biomedicine (Epub ahead of print),

12 QUANTIFICATION: truncation of FID GSH GABA Gln Glu mi Cho Cre truncation incorporated in the time domain of model spectra NAA Henning et al, NMR in Biomedicine (Epub ahead of print), QUANTIFICATION: truncation of FID Henning et al, NMR in Biomedicine (Epub ahead of print),

13 QUANTIFICATION: truncation of FID no phase correction prior fitting voxel size: 1 ml (1 cm 3 ) phase correction prior fitting QUANTIFICATION: 2D J-resolved MRS T acq =T E =t 1 (1) t 2 13

14 QUANTIFICATION: 2D J-resolved MRS T acq =T E =t 1 (2) t 2 QUANTIFICATION: 2D J-resolved MRS T acq =T E =t 1 (3) t 2 14

15 QUANTIFICATION: 2D J-resolved MRS FT along t same different CS evolution J evolution QUANTIFICATION: 2D JPRESS & ProFIT Schulte et al, NMR Biomed 19(2), & ,

16 time efficient QUANTIFICATION: 2D JPRESS & ProFIT ProFit = VAPRO & LCModel global fit parameters: zeroth-order phase Gaussian line broadening in f 2 shift in f 1 biexponential phase decay due to eddy currents individual fit parameters: concentration same exponential line-broadening for f 1 and f 2 shift in f 2 robust convergence model-free regularization fit of linear combination of model spectra (discrete, simulated time domain model: max echo sampling pattern considered) Schulte et al, NMR Biomed 19(2), & , QUANTIFICATION: COSY & ProFIT fitting a linear combination of 2-dimensional COSY basis metabolite sets Extension of ProFit to other 1D or 2D sequences possible! courtesy of IBT, University and ETH Zurich Alexander Fuchs, IBT 16

17 QUANTIFICATION Estimation of fitting reliability: -Residue - Cramer-Rao lower bounds (CRLB) - Covariance matrix - CRLB maps for MRSI QUANTIFICATION: residue mouse brain, 9.4 T Tkac I et al; ISMRM (2008) 16:1624 Govindaraju et al;.. 17

18 QUANTIFICATION: Fisher information matrix Fisher information matrix F = σ N standard deviation of noise transposition 1 T H ( P D DP) 2 Hermitian conjugation model function matrix element: D ij xi = p j model function parameter prior knowledge matrix element: P mn p = p m n parameter m parameter n model function: exponentially damped, gaussian filtered sinusoids parameters: metabolite prior knowledge (frequencies, coupling constants) De Graaf; In vivo NMR spectroscopy; WILEY 2007 (2 nd Edition) QUANTIFICATION: CRLB standard deviation of fitting result for parameter i σ p i CRLB p i = Cramer-Rao Lower bounds F 1 ii inverted Fisher information matrix diagonal elements Tkac I et al; ISMRM (2008) 16:

19 QUANTIFICATION: CRLB 1 H FIDLOVS 7T Cre GABA Gln Glu tcho GSH mi MM / Lip NAA NAAG PE scylloi Tau Ala Asc Asp Glc Lac statistical analysis considers SNR Henning et al, NMR in Biomedicine (Epub ahead of print), QUANTIFICATION: covariance matrix covariance coefficient for parameters m and n ρ mn = F F 1 mn 1 mm F 1 nn off-diagonal elements inverted Fisher information matrices 3T unambiguous and simultaneous quantification of GABA, Gln, Glu and NAA Walter/Henning/Grimm et al, Archives of General Psychiatry 2009; 66(5):

20 QUANTIFICATION: covariance matrix COSY JPRESS courtesy of IBT, University and ETH Zurich 1D 3T Fuchs et al, ISMRM (2009) 17: QUANTIFICATION: covariance matrix & CRLB maps 1 H FIDLOVS 7T voxel size: 0.2 ml (6 mm 3 ) GM WM GM WM Cor GM WM Cortex voxel Henning et al, NMR in Biomedicine (Epub ahead of print),

21 QUANTIFICATION: covariance matrix 1 H FIDLOVS 7T no phase correction prior fitting Tau scylloi PE PCh NAAG NAA MM/Lip mi Lac GSH GPC Glu Gln Glc GABA Cre Asp Asc Ala phase correction prior fitting Ala Asc Asp Cre GABA Glc Gln Glu GPC GSH Lac mi MM/ Lip NAA NAAG PCh PE scylloi Tau Ala Asc Asp Cre GABA Glc Gln Glu GPC GSH Lac mi MM/ Lip NAA NAAG PCh PE scylloi Tau correlation analysis considers spectral overlap at original shim quality Henning et al, NMR in Biomedicine (Epub ahead of print), QUANTIFICATION: CRLB maps no phase correction prior fitting Henning et al, NMR in Biomedicine (Epub ahead of print),

22 QUANTIFICATION: CRLB maps phase correction prior fitting Henning et al, NMR in Biomedicine (Epub ahead of print), Additional influence factors: QUANTIFICATION metabolite signal intensity metabolite concentration volume S met = C met x NS x RG x V x ω 0 x f sequence x f coil x f add # averages receive gain volume f sequence : f coil : f add : T E (T 2 ); T R (T 1 ); partial volume effects RF pulses (phase evolution, NOE); gradients (diffusion) transmit and receive B 1 distribution, power optimization coil load (load dependent resistance of coil) contributing nuclei per molecule B 0, temperature, ph, conductivity artifacts (f.i. eddy currents; lipid and water) 22

23 Relaxation T 2 relaxation cmet c met,corr = f * f T2 T1 f f T T 1 exp( TR = 1 exp( T 1 exp( TE / T2 ) = exp( T / T ) 2 E Or: T R > 5 T 1, max / T ) R / T ) phantom invivo phantom invivo Tkac et al; Magn Reson Med 46:451, 2001 T E ultra-short (also for diffusion) QUANTIFICATION: IDAP multi-dimensional fitting Basis spectra can be subdived into parts with different T 2 relaxation behavior: T 2 determination from lineshape analysis. IDAP: Kreis et al, Magn Reson Med 54, , 2005;.TDFDfit: Slotboom et al; Magn Reson Med Jun;39(6):

24 RF pulses khz 1.6 khz khz 0.5 khz khz khz 0.9 khz khz RF pulses excitation & refocusing H 2 O Glx Cre NAA Lac

25 RF pulses pulses and gradients need to be considered in simulations of basis spectra PRESS 7T brain phantom T E = 66 ms Contributing nuclei per molecule Choline CH 3 HO-CH 2 -CH 2 -N-CH 3 CH 3 Creatine H 3 C-N-CH 2 -COO - C=NH + 2 NH 2 N-Acetylaspartate O O C-CH 2 -CH-C O NH O C=O 2 mm 6 mm 12 mm CH 3 25

26 B 1 and B 0 inhomogeneity Transmit B 1 B 0 line broade phase encod De Graaf; In vivo NMR spectroscopy; WILEY 2007 (2 nd Edition) Conductivity, ph and temperature Buchli R.; SMRM (1990) 9:504 δ δ HA ph = pk A + log( ) δ δ A ω water 2 ( T ) = γ (1 χ( T ) σ ( T )) B 3 0 bulk susceptibility electronic shielding De Graaf; In vivo NMR spectroscopy; WILEY 2007 (2 nd Edition) 26

27 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 1 H MRS. 27

28 QUANTIFICATION: metabolite ratios healthy pathology or? relative quantification: ambigious 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) 28

29 QUANTIFICATION: internal references Advantages coil load receive gain settings volume temperatur ph conductivity are considered B 1 inhomogeneities power optimization are considered for thesametypeof nucleus (f.i. internal water reference for 1 H MRS) Disadvantages internal water or reference metabolite concentrations as well as all relaxation times depend on: age voxel composition (f.i. CSF content) and change in pathologies B 1 inhomogeneities PO are not considered for different types of nuclei (f.i. internal water reference for 31 P and 13 C MRS) QUANTIFICATION: external reference calibration External reference calibration phantom with known concentration B 1 variations should be taken into account especially for surface coils be sure the same preparation settings are used (f.i. receiver gain & power optimizations, shimming) 29

30 QUANTIFICATION: external reference calibration Advantages known & stable concentration for reference standard known relaxation times for reference standard coil load is directly considered Disadvantages additional reference spectrum needed each time receive gain settings volume temperatur ph conductivity B 1 inhomogeneities power optimization relaxation times of in vivo metabolites need to be considered by adjustments or correction factors determined by additional measurements QUANTIFICATION: symmetrical phantom calibration Symmetric phantom calibration phantom with known concentration be sure the same preparation settings are used for localized version (f.i. receiver gain & power optimizations, shimming) Buchli et al, MRM (1993) 30:

31 QUANTIFICATION: symmetrical phantom calibration Advantages known & stable concentration for reference standard known relaxation times for reference standard coil load is directly considered B 1 inhomogeneities are directly considered if conductivity of phantom is adjusted to in vivo values and PO is not repeated for phantom measurement Disadvantages additional reference spectrum needed each time receive gain volume temperatur ph conductivity relaxation times of in vivo metabolites need to be considered by adjustments or correction factors determined by additional measurements QUANTIFICATION: phantom replacement method saline 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 31

32 QUANTIFICATION: phantom calibration methods Advantages known & stable concentration for reference standard known relaxation times for reference standard Disadvantages coil load (additional reference spectrum needed each time) receive gain settings volume temperatur ph conductivity B 1 inhomogeneities PO relaxation times of in vivo metabolites need to be considered by adjustments or correction factors determined by additional measurements ERETIC: Electric REference To access In vivo Concentrations courtesy of IBT, University and ETH Zurich Heinzer-Schweizer et al, ISMRM 2009:

33 ERETIC: Fitting with LC Model & TDFD fit courtesy of IBT, University and ETH Zurich Heinzer-Schweizer et al, ISMRM 2009: 232 ERETIC: Electric REference To access In vivo Concentrations Why ERETIC? 1 H 1.5T and 3T: reliable reference standard in lesions where water concentration is unknown clinical application 13 C & 31 P 3T & 7T: reliable reference standard no internal reference available water reference is unreliable since transmit and receive fields of water and heavy nucleus are very different at 3T & 7T 33

34 ERETIC: optical signal transmission courtesy of IBT, University and ETH Zurich Heinzer-Schweizer et al, ISMRM 2009: 232 ERETIC: optical vs. electrical signal transmission courtesy of IBT, University and ETH Zurich Heinzer-Schweizer et al, ISMRM 2009:

35 ERETIC: scaling with coil load courtesy of IBT, University and ETH Zurich Heinzer-Schweizer et al, ISMRM 2009: 232 ERETIC: stability over time courtesy of IBT, University and ETH Zurich Heinzer-Schweizer et al, ISMRM 2009:

36 ERETIC: phantom calibration courtesy of IBT, University and ETH Zurich Heinzer-Schweizer et al, ISMRM 2009: 232 ERETIC: cross validation with internal water reference courtesy of IBT, University and ETH Zurich Heinzer-Schweizer et al, ISMRM 2009:

37 31 P MRS: simultaneous 1 H decoupling and ERETIC courtesy of IBT, University and ETH Zurich ATP ATP Schweizer et al, ISMRM 2008: 193. JPRESS & ERETIC ERETIC MM NAA Cho Cr Cr H 2 O courtesy of IBT, University and ETH Zurich Fuchs et al, ISMRM 2009: in vivo, 3T, GM rich voxel 37

38 QUANTIFICATION: ERETIC Advantages known & stable reference standard known relaxation times for calibration metabolites receive gain settings considered coil load directly considered phantom calibration needs to be performed only once Disadvantages volume temperatur ph conductivity B 1 inhomogeneities PO relaxation times of in vivo metabolites need to be considered due to adjustments or correction factors determined by additional measurements IBT spectroscopy group Mateo Pavan Nicola de Zanches Klaas Pruessmann Rolf F. Schulte 38