INSPECTOR: free software for magnetic resonance spectroscopy data inspection, processing, simulation and analysis

Gajdošík, Martin; Landheer, Karl; Swanberg, Kelley M.; Juchem, Christoph

doi:10.1038/s41598-021-81193-9

Cited by 31 publications

(33 citation statements)

References 42 publications

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“…One of the main findings in this work is that, largely, CRLBs only robustly approximate standard deviations when the model perfectly characterizes the data. It is important to put this in the context that although fitting packages [2][3][4]6 typically obtain excellent fits this does not, on its own, validate a model. 51 Additionally, many packages use a spline to model the baseline, which implicitly assumes that the employed model does not adequately characterize the data.…”

Section: Discussionmentioning

confidence: 99%

“…The parameters were estimated using a linear combination modelling approach in INSPECTOR. 4 For each individual spectrum the parameters (amplitude, frequency shift, Lorentzian linewidth, Gaussian linewidth and phase) were estimated via the interior trust region approach 41 with least squares as implemented in MATLAB 2013b (MathWorks, Natick, MA) in INSPECTOR. The metric minimized was the sum of the residuals between the spectrum and the model in the frequency domain.…”

Section: Calculation Of Standard Deviation and Crlbsmentioning

confidence: 99%

“…problem and it has been incorporated into packages such as LCModel, 2 TARQUIN, 3 INSPECTOR, 4,5 and jMRUI. 6 The CRLB is highly appealing as it can be calculated directly from a simple analytical expression via the Fisher information matrix and circumvents the issue of multiple repetitions.…”

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confidence: 99%

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Are Cramér‐Rao lower bounds an accurate estimate for standard deviations in in vivo magnetic resonance spectroscopy?

Landheer

Juchem

2021

NMR in Biomedicine

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Due to inherent time constraints for in vivo experiments, it is infeasible to repeat multiple MRS scans to estimate standard deviations on the desired measured parameters. As such, the Cramér-Rao lower bounds (CRLBs) have become the routine method to approximate standard deviations for in vivo experiments. Cramér-Rao lower bounds, however, as the name suggests, are theoretically a lower bound on the standard deviation and it is not clear if and under what circumstances this approximation is valid. Realistic synthetic 3 T spectra were used to investigate the relationship between estimated CRLBs, true CRLBs and standard deviations. Here we demonstrate that, although the CRLBs are theoretically truly a lower bound on the standard deviation (not an equality) for the problem typically encountered in quantification, they are still an adequate approximation to standard deviation as long as the model perfectly characterizes the data. In the case when the macromolecule basis deviates from the measured macromolecules it was shown that the CRLBs can deviate from standard deviations by approximately 50% for N-acetylaspartic acid, creatine and glutamate and of the order of 100% or more for myo-inositol and γ-aminobutyric acid.In the case when the model perfectly reflects the data the CRLBs are within approximately 10% of standard deviations for all metabolites. The result of the CRLB being within 10% of standard deviations means that, for an accurate model, novel quantification methods such as machine learning or deep learning will not be able to obtain substantially more precise estimates for the desired parameters than traditional maximum-likelihood estimation.

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Section: Discussionmentioning

confidence: 99%

Section: Calculation Of Standard Deviation and Crlbsmentioning

confidence: 99%

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Are Cramér‐Rao lower bounds an accurate estimate for standard deviations in in vivo magnetic resonance spectroscopy?

Landheer

Juchem

2021

NMR in Biomedicine

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“…Further spectral processing and analysis was performed with the freeware MRS software package INSPECTOR. 37,38 The complex data were truncated up to 1024 points and zero-filled to 4096 points. No line-broadening was performed.…”

Section: Data Processing and Quantificationmentioning

confidence: 99%

Hippocampal single‐voxel MR spectroscopy with a long echo time at 3 T using semi‐LASER sequence

et al. 2021

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The hippocampus is one of the most challenging brain regions for proton MR spectroscopy (MRS) applications. Moreover, quantification of J‐coupled species such as myo‐inositol (m‐Ins) and glutamate + glutamine (Glx) is affected by the presence of macromolecular background. While long echo time (TE) MRS eliminates the macromolecules, it also decreases the m‐Ins and Glx signal and, as a result, these metabolites are studied mainly with short TE. Here, we investigate the feasibility of reproducibly measuring their concentrations at a long TE of 120 ms, using a semi‐adiabatic localization by adiabatic selective refocusing (sLASER) sequence, as this sequence was recently recommended as a standard for clinical MRS. Gradient offset‐independent adiabatic refocusing pulses were implemented, and an optimal long TE for the detection of m‐Ins and Glx was determined using the T2 relaxation times of macromolecules. Metabolite concentrations and their coefficients of variation (CVs) were obtained for a 3.4‐mL voxel centered on the left hippocampus on 3‐T MR systems at two different sites with three healthy subjects (aged 32.5 ± 10.2 years [mean ± standard deviation]) per site, with each subject scanned over two sessions, and with each session comprising three scans. Concentrations of m‐Ins, choline, creatine, Glx and N‐acetyl‐aspartate were 5.4 ± 1.5, 1.7 ± 0.2, 5.8 ± 0.3, 11.6 ± 1.2 and 5.9 ± 0.4 mM (mean ± standard deviation), respectively. Their respective mean within‐session CVs were 14.5% ± 5.9%, 6.5% ± 5.3%, 6.0% ± 3.4%, 10.6% ± 6.2% and 3.5% ± 1.4%, and their mean within‐subject CVs were 17.8% ± 18.2%, 7.5% ± 6.3%, 7.4% ± 6.4%, 12.4% ± 5.3% and 4.8% ± 3.0%. The between‐subject CVs were 25.0%, 12.3%, 5.3%, 10.7% and 6.4%, respectively. Hippocampal long‐TE sLASER single voxel spectroscopy can provide macromolecule‐independent assessment of all major metabolites including Glx and m‐Ins.

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“…The improvements of the MR system have led to the reduction of MRS scan time, and the possibility of data acquisition and analysis remote controlled by skilled specialists improves its feasibility in a clinical setting. Additionally, efforts have been made towards automate- or semi-automate data analysis from both the commercially and freely available software mentioned in this review that enable accurate and consistent liver fat MRS measurement [ 145 , 146 , 147 ]. These improvements, while providing accurate liver fat quantification, therefore propose liver MRS as a time and cost-effective addition to the routine scan.…”

Section: Possible Confounders and Limitation Of Liver Mrsmentioning

confidence: 99%

Magnetic Resonance Spectroscopy of Hepatic Fat from Fundamental to Clinical Applications

et al. 2021

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The number of individuals suffering from fatty liver is increasing worldwide, leading to interest in the noninvasive study of liver fat. Magnetic resonance spectroscopy (MRS) is a powerful tool that allows direct quantification of metabolites in tissue or areas of interest. MRS has been applied in both research and clinical studies to assess liver fat noninvasively in vivo. MRS has also demonstrated excellent performance in liver fat assessment with high sensitivity and specificity compared to biopsy and other imaging modalities. Because of these qualities, MRS has been generally accepted as the reference standard for the noninvasive measurement of liver steatosis. MRS is an evolving technique with high potential as a diagnostic tool in the clinical setting. This review aims to provide a brief overview of the MRS principle for liver fat assessment and its application, and to summarize the current state of MRS study in comparison to other techniques.

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INSPECTOR: free software for magnetic resonance spectroscopy data inspection, processing, simulation and analysis

Cited by 31 publications

References 42 publications

Are Cramér‐Rao lower bounds an accurate estimate for standard deviations in in vivo magnetic resonance spectroscopy?

Are Cramér‐Rao lower bounds an accurate estimate for standard deviations in in vivo magnetic resonance spectroscopy?

Hippocampal single‐voxel MR spectroscopy with a long echo time at 3 T using semi‐LASER sequence

Magnetic Resonance Spectroscopy of Hepatic Fat from Fundamental to Clinical Applications

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