Reproducibility and the future of MRI research

Stikov, Nikola; Trzasko, Joshua D.

doi:10.1002/mrm.27939

Cited by 29 publications

(27 citation statements)

References 15 publications

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“…Independent from field strength, our numerical evaluation also showed that there is a crucial need for standardization, and one potential asset is the growing availability of open‐source programs to encourage reproducible research . Fitting algorithms can significantly impact parameter estimation errors.…”

Section: Discussionmentioning

confidence: 92%

Intravoxel Incoherent Motion at 7 Tesla to quantify human spinal cord perfusion: limitations and promises

Levy

Rapacchi

Massire

et al. 2020

Magnetic Resonance in Med

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Purpose:To develop a noninvasive technique to map human spinal cord (SC) perfusion in vivo. More specifically, to implement an intravoxel incoherent motion (IVIM) protocol at ultrahigh field for the human SC and assess parameters estimation errors. Methods: Monte-Carlo simulations were conducted to assess estimation errors of 2 standard IVIM fitting approaches (two-step versus one-step fit) over the range of IVIM values reported for the human brain and for typical SC diffusivities. Required signal-to-noise ratio (SNR) was inferred for estimation of the parameters product, f IVIM D* (microvascular fraction times pseudo-diffusion coefficient), within 10% error margins. In-vivo IVIM imaging of the SC was performed at 7T in 6 volunteers.An image processing pipeline is proposed to generate IVIM maps and register them for an atlas-based region-wise analysis. Results: Required b = 0 SNRs for 10% error estimation on f IVIM D* with the one-step fit were 159 and 185 for diffusion-encoding perpendicular and parallel to the SC axis, respectively. Average in vivo b = 0 SNR within cord was 141 ± 79, corresponding to estimation errors of 12.7% and 14.7% according to numerical simulations.Slice-and group-averaging reduced noise in IVIM maps, highlighting the difference in perfusion between gray and white matter. Mean ± standard deviation f IVIM and D* values across subjects within gray (respectively white) matter were 16.0 ± 1.7 (15.0 ± 1.6)% and 11.4 ± 2.9 (11.5 ± 2.4) × 10 −3 mm 2 /s. Conclusion: Single-subject data SNR at 7T was insufficient for reliable perfusion estimation. However, atlas-averaged IVIM maps highlighted the higher microvascular fraction of gray matter compared to white matter, providing first results of healthy human SC perfusion mapping with MRI. K E Y W O R D S7T MRI, intravoxel incoherent motion, IVIM, perfusion, spinal cord, ultrahigh field MRI | 1199 LÉVY et aL.

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Section: Discussionmentioning

confidence: 92%

Intravoxel Incoherent Motion at 7 Tesla to quantify human spinal cord perfusion: limitations and promises

Levy

Rapacchi

Massire

et al. 2020

Magnetic Resonance in Med

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“…In conclusion, new MRS analysis method with adaptive baseline modeling is presented and validated on simulated and experimentally acquired data. The approach is fully‐automated and integrated into a free and open‐source software package—providing a transparent and reproducible platform for future MRS studies 43 …”

Section: Discussionmentioning

confidence: 99%

“…The approach is fullyautomated and integrated into a free and open-source software package-providing a transparent and reproducible platform for future MRS studies. 43…”

Section: Discussionmentioning

confidence: 99%

Adaptive baseline fitting for MR spectroscopy analysis

Wilson

2020

Magnetic Resonance in Med

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“…In conclusion, new MRS analysis method with adaptive baseline modeling is presented and validated on simulated and experimentally acquired data. The approach is fully-automated and integrated into a free and open-source software package -providing a transparent and reproducible platform for future MRS studies [42].…”

Section: Discussionmentioning

confidence: 99%

Adaptive Baseline Fitting for¹H MR Spectroscopy Analysis

Wilson

2020

Preprint

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Purpose: Accurate baseline modeling is essential for reliable MRS analysis and interpretation -particularly at short echo-times, where enhanced metabolite information coincides with elevated baseline interference. The degree of baseline smoothness is a key analysis parameter for metabolite estimation, and in this study a new method is presented to estimate its optimal value. Methods: An adaptive baseline fitting algorithm (ABfit) is described, incorporating a spline basis into a frequency-domain analysis model, with a penalty parameter to enforce baseline smoothness. A series of candidate analyses are performed over a range of smoothness penalties, as part of a four stage algorithm, and the Akaike information criterion is used to estimate the appropriate penalty. ABfit is applied to a set of simulated spectra with differing baseline features and an experimentally acquired 2D MRSI dataset.Results: Simulated analyses demonstrate metabolite errors result from two main sources: bias from an inflexible baseline (underfitting) and increased variance from an overly flexible baseline (overfitting). In the case of an ideal flat baseline ABfit is shown to correctly estimate a highly rigid baseline, and for more realistic spectra a reasonable compromise between bias and variance is found. Analysis of experimentally acquired data demonstrates good agreement with known correlations between metabolite ratios and the contributing volumes of gray and white matter tissue. Conclusion:ABfit has been shown to perform accurate baseline estimation and is suitable for fully-automated routine MRS analysis. KEYWORDS ABfit; MRSI; spectral analysis; automated; open-source; spline Word count : 5535 1 2 Wilson | INTRODUCTIONA number of key metabolites may be detected using 1 H Magnetic Resonance Spectroscopy (MRS), providing a noninvasive measure of healthy and diseased brain tissue metabolism. Clinical applications include the assessment of brain tumors, metabolic disorders and neonatal encephalopathy [1,2] where the concentration of certain metabolites may inform disease diagnosis or predict patient outcome. Further applications are present in the neuroscience and psychiatry domains, with particular interest in the direct detection of neurotransmitter levels such as GABA and glutamate -which have been shown to be abnormal in Schizophrenia [3] and modulate in response to tasks [4,5].MRS scans are typically performed at short (30 ms) or long (144 ms) TE's, with short-TE scans being preferred due to reduced T2 relaxation and dephasing of multiplets resulting in improved metabolite detection sensitivity [6].However, short-TE scans are typically more susceptible to artefacts originating from insufficient water and scalp lipid suppression, in addition, broad signals from macromolecules also become enhanced [7]. Residual water signals, lipid signals and macromolecules all have the potential to bias metabolite measurements due to spectral overlap and interference. Therefore, appropriate analysis methodology is particularly important to achieve the...

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Reproducibility and the future of MRI research

Cited by 29 publications

References 15 publications

Intravoxel Incoherent Motion at 7 Tesla to quantify human spinal cord perfusion: limitations and promises

Intravoxel Incoherent Motion at 7 Tesla to quantify human spinal cord perfusion: limitations and promises

Adaptive baseline fitting for MR spectroscopy analysis

Adaptive Baseline Fitting for¹H MR Spectroscopy Analysis

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Reproducibility and the future of MRI research

Cited by 29 publications

References 15 publications

Intravoxel Incoherent Motion at 7 Tesla to quantify human spinal cord perfusion: limitations and promises

Intravoxel Incoherent Motion at 7 Tesla to quantify human spinal cord perfusion: limitations and promises

Adaptive baseline fitting for MR spectroscopy analysis

Adaptive Baseline Fitting for1H MR Spectroscopy Analysis

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Adaptive Baseline Fitting for¹H MR Spectroscopy Analysis