Vespa: Integrated applications for RF pulse design, spectral simulation and MRS data analysis

Abstract

Purpose The Vespa package (Versatile Simulation, Pulses, and Analysis) is described and demonstrated. It provides workflows for developing and optimizing linear combination modeling (LCM) fitting for 1H MRS data using intuitive graphical user interface interfaces for RF pulse design, spectral simulation, and MRS data analysis. Command line interfaces for embedding workflows in MR manufacturer platforms and utilities for synthetic dataset creation are included. Complete provenance is maintained for all steps in workflows. Theory and Methods Vespa is written in Python for compatibility across operating systems. It embeds the PyGAMMA spectral simulation library for spectral simulation. Multiprocessing methods accelerate processing and visualization. Applications use the Vespa database for results storage and cross‐application access. Three projects demonstrate pulse, sequence, simulation, and data analysis workflows: (1) short TE semi‐LASER single‐voxel spectroscopy (SVS) LCM fitting, (2) optimizing MEGA‐PRESS (MEscher–GArwood Point RESolved Spectroscopy) flip angle and LCM fitting, and (3) creating a synthetic short TE dataset. Results The LCM workflows for in vivo basis set creation and spectral analysis showed reasonable results for both the short TE semi‐LASER and MEGA‐PRESS. Examples of pulses, simulations, and data fitting are shown in Vespa application interfaces for various steps to demonstrate the interactive workflow. Conclusion Vespa provides an efficient and extensible platform for characterizing RF pulses, pulse design, spectral simulation optimization, and automated LCM fitting via an interactive platform. Modular design and command line interface make it easy to embed in other platforms. As open source, it is free to the MRS community for use and extension. Vespa source code and documentation are available through GitHub.

Dissecting the chain of information processing and its interplay with neurochemicals and fluid intelligence across development

“…MRS neurotransmitters were quantified with LCModel ( Provencher, 2001 ) using a basis set of simulated spectra generated based on previously reported chemical shifts and of coupling constants generated based on a VeSPA (versatile simulation, pulses, and analysis) simulation library ( Soher et al, 2011 ). Simulations were performed using the same RF pulses and sequence timings as in the 3T system described above.…”

Linewidth-related bias in modelled concentration estimates from GABA-edited1H-MRS

“…While many of the key findings in this study present across several of the algorithms examined, they do not necessarily generalise further. A number of other algorithms and implementations are available to the MRS community [62][63][64][65][66][67][68][69][70][71] , each potentially differing in modelling strategy, baseline handling and constraint models and therefore likely to present unique characteristics. Most implementations are also highly configurable, with even subtle differences in modelling parameters or prior knowledge having potentially substantial impact on the behaviour, as observed in previous work 23,44 and also here in the supplementary analyses (supplementary sections E, F, G).…”

Exploratory Multisite MR Spectroscopic Imaging Shows White Matter Neuroaxonal Loss Associated with Complications of Type 1 Diabetes in Children

“…28,29 This design choice was made for the following reasons: 1) to simplify both the present and future studies across multiple sites where MRSI pulse sequences and envelope parameters may not be readily available or reliably queried from scanners (as was the case for sites B and C presently); 2) because custom basis sets leveraging techniques like density operator simulation or the Versatile Simulation, Pulses, and Analysis (VeSPA; https://www. opensourceimaging.org/project/vespa-versatile-simulation-pulsesanalysis/) toolkit primarily impact multiplet signals, whereas NAA and Cr are largely singlet; [28][29][30] and 3) because initial attempts using these custom sets did not dramatically affect results.…”