magnetic resonance spectroscopy (mrs): overview of mrs ......magnetic resonance spectroscopy (mrs):...
TRANSCRIPT
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Magnetic Resonance Spectroscopy (MRS):
Overview of MRS software
SINAPSE MRS workshop
John McLean, Clinical Scientist
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Content of presentation
• Overview of MRS software
• LCmodel
• JMRUI
• Proprietary
• Interpret Decision support system
• Spectral Classifier (SC)
• Others : 3Dcsi
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LCModel aim / overview
• The Linear Combination Model
• Website: http://s-provencher.com/pages/lcmodel.shtml
• Current version: 6.2
• LCmodel analyses in-vivo spectra as a linear combination of Modelled In-vitro spectra from individual metabolite solutions
• Automatic quantification of in-vivo proton MRS data
• GUI
• Phasing, referencing, quantitation done automatically
• A constrained non-linear least-squares analysis estimates metabolite concentrations and their uncertainties
• Absolute quantification via calibration phantom or water scalingbut check LCmodel manual and your hardware
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LCModel Pros & Cons
• Pros
• Quick analysis of SV and MV* MRS data
• Fully automatic, wide range of basis sets available
• Operator independent
• Published info on methods in literature
• Extensive manual
• Good support
• Used widely
• One-page output
• Accepts most manufacturer data
• Cons
• Linux based
• Commercial ~ 6-10k £
• Limited customisation
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LCModel Interface
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LC model overview
• Residuals
• Metabolite concentration
and ratios
• Confidence levels (< 20%)
• Data vs. model plot
• FWHM (<0.1ppm)
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LCModel Comments
• Try before you buy
• Read manual
• Consider purpose
• Contact S Provencher
• Check quantification options in manual for your scanner manufacturer & Hardware
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JMRUI aim / overview• Java Magnetic resonance user interface• Web address:
http://www.mrui.uab.es/mrui/mrui_Overview.shtml
• Current version is: v4.0
• MRUI is a Graphical User Interface that allows MR spectroscopists to easily perform time-domain analysis of in vivo MR data: 1D spectra, time-series and 3D-MRSI datasets.
• Various algorithms included
• frequency selective filtering of signals
• correction of eddy-currents artefacts
• Cadzow enhancement of the FID
• Linear Prediction
• non-linear fitting in the time-domain (AMARES, QUEST)
• quantum-mechanics simulation of spectra (NMR-SCOPE)
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JMRUI Pros & Cons
• Pros• Free
• Customisable
• Interface is simple and easy to use
• Various options for pre-processing / quantification
• Analysis of SV and MV MRS data
• Published info on methods in literature
• Extensive manual
• Used widely
• Accepts most manufacturer data
• Other useful MRS modules: e.g. simulation
• Cons• Inputting data may require some customisation
• Potential for user variability
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JMRUI Interaface
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JMRUI Interaface
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JMRUI Comments
• It’s free so a good place to start
• Licence/ approval necessary
• Go on the JMRUI course
• Pre-processing with JMRUI can lead to use of SC / Interpret
• Algorithms are published
• Potential to incorporate additional modules to aid quantification
• What about T1 or T2 correction?
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INTERPRET aim / overview
• INTERPRET Decision support system
• http://gabrmn.uab.es/dss
• Current version: v.3.0.2
• Aim to facilitate the use of MRS for improved diagnosis and therapy of patients with brain tumours
• Standard acquisition/ processing
• A database of cases
• Implementation of classifiers
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INTERPRET Pros & Cons
• Pros• Free
• Built in data
• GUI can present a lot of info at once
• Use of multi-variate spectra classifier
• Reads JMRUI data
• Customisable with use of sister SC program
• Methods published in literature
• Multi-platform
• Incorporate imaging data/ clinical report Info
• Cons• Be aware of deviations in practice
• GUI presentation of cases not immediately intuitive
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INTERPRET
Patient Information
Mean Spectra
All data in database
Image
Spectra for comparison
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INTERPRET Examples
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Spectral Classifier overview
• SC
• http://gabrmn.uab.es/sc
• Current version: v.2.0
• Java based tool for implementing MRS spectra classifiers
• Only minimal knowledge of statistics necessary
• Modular based program
• Interactive GUI
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SC Pros & Cons
• Pros• Free
• Customisable
• GUI
• Can integrate with JMRUI/ INTERPRET
• Good manual
• Published methods
• Simple implementation of advanced statistics
• Training data can be used
• Cons• Requires cases / time / consistency
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SC Examples
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SC Examples
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Closing comments
• Various frameworks already exist
• No need to re-invent the wheel
• Understand processes, appreciate limitations
• Customise to your needs
• Decide on quantification method before you
start and test it out on pilot data/ normal volunteer
• Consistency of practice is key!
• As far as possible, check your assumptions