1. Vespa – Versatile Simulation, Pulses and Analysis
Created via an NIH software support/maintenance grant
Derived from three existing applications on the ‘sneakernet’
MatPulse – MatLab
GAMMA – C++
SITools/FITT – IDL/C/Fortran
URL:

2. Vespa – Versatile Simulation, Pulses and Analysis
Interconnected, Python-based, applications for MRS spectral analysis
Pulse designs, spectral simulations and metabolite fits all shareable via database/XML
Full provenance/versioning for all design, processing and analysis steps
Open source, runs on Windows, OS X and Linux
Vespa Package
Simulation
Application
Pulse
Analysis
Optimized RF pulse waveforms
Spectral simulation metabolite basis set
PRESS TE=30ms 1.5T

3. Vespa – Pulse Application
Pulse allows users to create, compare and analyze RF pulses for MR applications.
The Python language allows for easy prototyping and cross platform compatibility.
The GUI interface displays the RF waveform at all creation/modification steps.
The integrated design/test GUI lets users contribute their own algorithms.
Side by side display of two pulse designs … an SLR 90 and a BASSI hyperbolic inversion pulse

4. Vespa – Pulse Application
Standard Results Display
Interactive Algorithm Test Windows
Create new pulses from a list of user defined algorithms
Store/re-load pulse designs and their design parameters into a database
Display results for each design step and compare side-by-side results from one or more designs
Output results graphically or in MR manufacturer platform formats
Import pulse designs to/from other users – or from manufacturer formats

5. Vespa – Simulation Application
Simulation allows users to create and analyze spectral simulations.
Pulse sequence simulations can use ‘real’ RF pulses from Vespa-Pulse results.
The GUI interface displays the simulated spectral results and 1D and 2D analyses.
Provides a user friendly front end to the GAMMA/PyGAMMA NMR library.
Side by side display of two Experiments … Ideal PRESS for multiple metabolites for one TE value, and Ideal PRESS for multiple TE1 and TE2 values showing integral variations through time

6. Vespa – Simulation Application
Metabolite Controls
Interactive Pulse Sequence Test Windows
Run simulated Experiment from lists of metabolites and pulse sequences
Store Experiment results in a database
Display the results in a plotting/graphing tool
Compare side-by-side results from Experiments
Export/Import results from other users
Design and test your own PyGAMMA pulse sequences for addition to the list of pulse sequences available for use in Experiments

7. Vespa – Simulation Example Code Ideal PRESS import pygamma as pg
def run(sim_desc):
# This is an example PyGAMMA pulse sequence
spin_system = sim_desc.spin_system
obs_iso = sim_desc.observe_isotope
te1 = sim_desc.dims[1] /
te2 = sim_desc.dims[2] /
H = pg.Hcs(spin_system) + pg.HJ(spin_system)
D = pg.Fm(spin_system, obs_iso)
ac = pg.acquire1D(pg.gen_op(D), H, )
ACQ = ac
sigma0 = pg.sigma_eq(spin_system)
# excite, propagate, refocus and acquire the data
sigma1 = pg.Iypuls(spin_system, sigma0, obs_iso, 90.0)
Udelay = pg.prop(H, te1*0.5)
sigma0 = pg.evolve(sigma1, Udelay)
sigma1 = pg.Iypuls(spin_system, sigma0, obs_iso, 180.0)
Udelay = pg.prop(H, (te1+te2)*0.5)
Udelay = pg.prop(H, te2*0.5)
sim_desc.mx = pg.TTable1D(ACQ.table(sigma0))

8. Vespa-Analysis: MRS Data Processing and Quantitation
Can be run interactively in GUI mode or as batch job from command line
Highlights
Multiple data sets can be loaded and compared
Native read for Siemens, Bruker, GE, Philips and Varian MRS data
User extensible via Python scripts
HTML and CSV output
Individual FID B0 and Phase 0 correction.
(future) Inline processing of Siemens MRS data via embedded Python/Analysis within the ICE pipeline
Example: Siemens Trio SVS-EDIT, raw file (twix) read/process, fitted data for both Sum and Difference spectra

9. Vespa-Analysis: MRS Data Processing and Quantitation

10. The Future and my Wish List
Inline processing of Siemens MRS data via embedded Python/Analysis within the ICE pipeline
Output to bitmap image of results
Standardized semi-LASER sequence and processing on Siemens and Philips
Want to wrap results into DICOM Structured Report
More centralized processing location – Syngo Via.Frontier server?
Also able to embed Python code
NiPype – Neuroimaging in Python workflow package

11. Thank you!