Fit plots

Standard

Stackplot

-CrCH2

Ala

Asp

Cr

GABA

Glc

Gln

GSH

Glu

GPC

Ins

Lac

Lip09

Lip13a

Lip13b

Lip20

MM09

MM12

MM14

MM17

MM20

NAA

NAAG

PCh

PCr

sIns

Tau

PEth

Gly

Results table

Name Amp. (mmol/kg) 95% CI (mmol/kg) Amp. (/tCr) 95% CI (/tCr) SD %
X.CrCH2 0.0000 [0.000, 0.902] 0.00000 [0.0000, 0.0840] 999%
Ala 0.0517 [0.000, 2.995] 0.00481 [0.0000, 0.2788] 999%
Asp 6.9456 [5.649, 8.242] 0.64661 [0.5259, 0.7673] 10%
Cr 7.3008 [5.565, 9.036] 0.67967 [0.5181, 0.8412] 12%
GABA 3.8616 [2.366, 5.357] 0.35950 [0.2203, 0.4987] 20%
Glc 1.3950 [0.499, 2.291] 0.12986 [0.0464, 0.2133] 33%
Gln 1.1490 [0.195, 2.103] 0.10697 [0.0182, 0.1957] 42%
GSH 2.7075 [2.126, 3.289] 0.25205 [0.1979, 0.3062] 11%
Glu 13.3170 [11.939, 14.695] 1.23977 [1.1115, 1.3680] 5%
GPC 1.9802 [1.300, 2.660] 0.18435 [0.1210, 0.2477] 18%
Ins 5.3293 [3.579, 7.080] 0.49614 [0.3332, 0.6591] 17%
Lac 0.7387 [0.000, 3.873] 0.06877 [0.0000, 0.3605] 216%
Lip09 6.4496 [0.000, 26.067] 0.60044 [0.0000, 2.4267] 155%
Lip13a 1.9410 [0.000, 11.192] 0.18070 [0.0000, 1.0420] 243%
Lip13b 0.0000 [0.000, 7.308] 0.00000 [0.0000, 0.6804] 999%
Lip20 0.0000 [0.000, 1.877] 0.00000 [0.0000, 0.1747] 999%
MM09 0.0000 [0.000, 19.213] 0.00000 [0.0000, 1.7886] 999%
MM12 1.6167 [0.000, 16.614] 0.15051 [0.0000, 1.5467] 473%
MM14 7.6268 [0.000, 31.866] 0.71003 [0.0000, 2.9666] 162%
MM17 2.3814 [0.000, 6.644] 0.22170 [0.0000, 0.6186] 91%
MM20 12.2743 [8.235, 16.313] 1.14269 [0.7667, 1.5187] 17%
NAA 14.7358 [13.261, 16.210] 1.37184 [1.2346, 1.5091] 5%
NAAG 1.9547 [0.699, 3.210] 0.18197 [0.0651, 0.2989] 33%
PCh 0.0000 [0.000, 0.741] 0.00000 [0.0000, 0.0690] 999%
PCr 3.4408 [1.931, 4.950] 0.32033 [0.1798, 0.4608] 22%
sIns 0.2516 [0.000, 0.555] 0.02342 [0.0000, 0.0517] 62%
Tau 0.2474 [0.000, 1.637] 0.02304 [0.0000, 0.1524] 287%
PEth 1.4726 [0.227, 2.718] 0.13710 [0.0212, 0.2530] 43%
Gly 2.0020 [0.000, 4.541] 0.18637 [0.0000, 0.4227] 65%
tNAA 16.6904 [16.284, 17.097] 1.55382 [1.5160, 1.5916] 1%
tCr 10.7416 [10.513, 10.970] 1.00000 [0.9787, 1.0213] 1%
tCho 1.9802 [1.827, 2.133] 0.18435 [0.1701, 0.1986] 4%
Glx 14.4661 [14.034, 14.898] 1.34674 [1.3065, 1.3869] 2%
tLM09 6.4496 [6.096, 6.803] 0.60044 [0.5675, 0.6334] 3%
tLM13 11.1845 [9.674, 12.695] 1.04123 [0.9006, 1.1818] 7%
tLM20 12.2743 [11.111, 13.437] 1.14269 [1.0344, 1.2509] 5%

See the spant User Guide for details on water scaling.

Dynamic plots

Spectrogram with dynamic correction

Spectrogram without dynamic correction

Spectral plots

Processed cropped

Processed full

Water reference resonance

Diagnostics table

Name Value
Spectral SNR 374.92
tNAA linewidth (ppm) 0.0467
tCho linewidth (ppm) 0.0575
tCr linewidth (ppm) 0.0523
Water amplitude 930967.4
Water suppression efficiency (%) 0.206
Fit quality number (FQN) 4.24
Baseline effective d.f. per ppm 4.12
Lineshape asymmetry 0.17
Spectral signal to residual ratio 181.99

Provenance

packageVersion("spant")
## [1] '3.2.9000'
Sys.time()
## [1] "2024-12-19 11:07:41 GMT"
print(params$fit_res$data, full = TRUE)
## MRS Data Parameters
## ----------------------------------
## Trans. freq (MHz)       : 123.2492
## FID data points         : 2048
## X,Y,Z dimensions        : 1x1x1
## Dynamics                : 1
## Coils                   : 1
## Voxel resolution (mm)   : 30x20x20
## Sampling frequency (Hz) : 6002.4008682235
## Repetition time (s)     : 2 
## Reference freq. (ppm)   : 4.65
## Nucleus                 : 1H
## Spectral domain         : FALSE
## Number of transients    : 64 
## Echo time (s)           : 0.028 
## Manufacturer            : Siemens 
## Pulse sequence type     : slaser 
## Sequence name           : %CustomerSeq%\dkd_svs_slaser_MoCoNav2 
## TE1, TE2, TE3 (s)       : 0.008, 0.011, 0.009
## 
## Meta data
## 
## $EchoTime
## [1] 0.028
## 
## $FlipAngle
## [1] 90
## 
## $SequenceName
## [1] "%CustomerSeq%\\dkd_svs_slaser_MoCoNav2"
## 
## $ChemicalShiftReference
## [1] 2.7
## 
## $NumberOfTransients
## [1] 64
## 
## $Manufacturer
## [1] "Siemens"
## 
## $PulseSequenceType
## [1] "slaser"
## 
## $TE1
## [1] 0.008
## 
## $TE2
## [1] 0.011
## 
## $TE3
## [1] 0.009
## 
## $fid_filt_dist
## [1] TRUE
## 
## $dim_5
## [1] "DIM_COIL"
## 
## $dim_6
## [1] "DIM_DYN"
## 
## Affine matrix
##             [,1]        [,2]         [,3]       [,4]
## [1,] 29.99848366  -0.2004098   0.01623864  -1.282188
## [2,] -0.29153696 -18.8548050   6.66772652 -64.227051
## [3,] -0.07725763  -6.6675472 -18.85579872 -49.050060
## [4,]  0.00000000   0.0000000   0.00000000   1.000000
print(params$w_ref, full = TRUE)
## MRS Data Parameters
## ----------------------------------
## Trans. freq (MHz)       : 123.2492
## FID data points         : 2048
## X,Y,Z dimensions        : 1x1x1
## Dynamics                : 1
## Coils                   : 1
## Voxel resolution (mm)   : 30x20x20
## Sampling frequency (Hz) : 6002.4008682235
## Repetition time (s)     : 2 
## Reference freq. (ppm)   : 4.65
## Nucleus                 : 1H
## Spectral domain         : FALSE
## Number of transients    : 4 
## Echo time (s)           : 0.028 
## Manufacturer            : Siemens 
## Pulse sequence type     : slaser 
## Sequence name           : %CustomerSeq%\dkd_svs_slaser_MoCoNav2 
## TE1, TE2, TE3 (s)       : 0.008, 0.011, 0.009
## 
## Meta data
## 
## $EchoTime
## [1] 0.028
## 
## $FlipAngle
## [1] 90
## 
## $SequenceName
## [1] "%CustomerSeq%\\dkd_svs_slaser_MoCoNav2"
## 
## $ChemicalShiftReference
## [1] 4.7
## 
## $NumberOfTransients
## [1] 4
## 
## $Manufacturer
## [1] "Siemens"
## 
## $PulseSequenceType
## [1] "slaser"
## 
## $TE1
## [1] 0.008
## 
## $TE2
## [1] 0.011
## 
## $TE3
## [1] 0.009
## 
## $fid_filt_dist
## [1] TRUE
## 
## $dim_5
## [1] "DIM_COIL"
## 
## $dim_6
## [1] "DIM_DYN"
## 
## Affine matrix
##             [,1]        [,2]         [,3]       [,4]
## [1,] 29.99848366  -0.2004098   0.01623864  -1.282188
## [2,] -0.29153696 -18.8548050   6.66772652 -64.227051
## [3,] -0.07725763  -6.6675472 -18.85579872 -49.050060
## [4,]  0.00000000   0.0000000   0.00000000   1.000000
print(argg)
## $metab
## [1] "svs_slaser_example/sub-01_svs.nii.gz"
## 
## $w_ref
## [1] "svs_slaser_example/sub-01_ref.nii.gz"
## 
## $output_dir
## [1] "sub-01"
## 
## $external_basis
## NULL
## 
## $p_vols
##  WM  GM CSF 
##   0 100   0 
## 
## $format
## NULL
## 
## $pul_seq
## NULL
## 
## $TE
## NULL
## 
## $TR
## NULL
## 
## $TE1
## NULL
## 
## $TE2
## NULL
## 
## $TE3
## NULL
## 
## $TM
## NULL
## 
## $append_basis
## [1] "peth" "gly" 
## 
## $remove_basis
## NULL
## 
## $pre_align
## [1] TRUE
## 
## $dfp_corr
## [1] TRUE
## 
## $output_ratio
## [1] "tCr"
## 
## $ecc
## [1] FALSE
## 
## $hsvd_width
## NULL
## 
## $fit_opts
## NULL
## 
## $fit_subset
## NULL
## 
## $legacy_ws
## [1] FALSE
## 
## $w_att
## [1] 0.7
## 
## $w_conc
## [1] 35880
## 
## $use_basis_cache
## [1] "auto"
## 
## $summary_measures
## NULL
## 
## $dyn_av_block_size
## NULL
## 
## $dyn_av_scheme
## NULL
## 
## $verbose
## [1] FALSE

Please cite the following if you found ABfit and spant useful in your research:

Wilson M. Adaptive baseline fitting for 1H MR spectroscopy analysis. Magn Reson Med. 2021 Jan;85(1):13-29. https://doi.org/10.1002/mrm.28385

Wilson, M. spant: An R package for magnetic resonance spectroscopy analysis. Journal of Open Source Software. 2021 6(67), 3646. https://doi.org/10.21105/joss.03646

Wilson M. Robust retrospective frequency and phase correction for single-voxel MR spectroscopy. Magn Reson Med. 2019 May;81(5):2878-2886. https://doi.org/10.1002/mrm.27605