ArticleMagnetic resonance in medicine2026
A Digital Phantom for MR Spectroscopy Data Simulation.
Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- A Digital Phantom for MR Spectroscopy Data Simulation.Magnetic resonance in medicine · 2026Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
purposeSimulated data is increasingly valued by researchers for validating MRS processing and analysis algorithms. However, there is no consensus on the optimal approaches for simulation models and parameters. This study introduces a novel MRS digital brain phantom framework, providing a comprehensive and modular foundation for MRS data simulation.
methodsThe framework generates a digital brain phantom by combining anatomical and tissue label information with metabolite data from the literature. This phantom contains all necessary information for simulating spectral data. The MRS phantom is combined with a signal-based model to demonstrate its functionality and usability in generating various spectral datasets. Outputs can be saved in the NIfTI-MRS format, enabling their use in downstream applications. To evaluate the realism of the simulated spectra, a comparison was performed against in vivo MRS data acquired under similar conditions.
resultsThe phantom was implemented using two anatomical templates at different resolutions and tested across a range of user-defined simulation parameters. Simulated spectra exhibited realistic signal characteristics and structural variability. When compared to in vivo data, the simulated spectra closely matched in terms of spectral shape, signal-to-noise ratio, and metabolite quantification. The simulations also captured key variability features and provided additional diversity not present in the in vivo dataset, supporting use in robustness testing and data augmentation.
conclusionThis novel digital phantom provides a flexible and extensible platform for MRS data simulation. Its modular architecture, user-friendly GUI, and open-source implementation support reproducible research, algorithm development, and validation in the MRS community.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.