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Vespa – Analysis User Manual and Reference - VeSPA

1. Parameters Results l Results Results l i Results Display i Display I Display l l l l l l settings SaL 7 IE The following chapters run through the operation of the Vespa Analysis program both in general and widget by widget In this manual command line instructions will appear in a fixed width font on individual lines for example Vespa Analysis ls Specific file and directory names will appear in a fixed width font within the main text References Examples of spectral analysis using simulated spectral priors Young K Govindaraju V Soher BJ and Maudsley AA Automated Spectral Analysis Formation of a Priori Information by Spectral Analysis Magnetic Resonance in Medicine 40 812 815 1998 Young K Soher BJ and Maudsley AA Automated Spectral Analysis II Application of Wavelet Shrinkage for Characterization of Non Parameterized Signals Magnetic Resonance in Medicine 40 816 821 1998 Soher BJ Young K Govindaraju V and Maudsley AA Automated Spectral Analysis Ill Application to in Vivo Proton MR Spectroscopy and Spectroscopic Imaging Magnetic Resonance in Medicine 40 822 831 1998 Soher BJ Vermathen P Schuff N Wiedermann D Meyerhoff DJ Weiner MW Maudsley AA Short TE in vivo 1 H MR spectroscopic imaging at 1 5 T acquisition and automated spectral analysis Magn Reson Imaging 18 9 1159 65 2000 Online Resources The Vespa project and each of its application
2. Parametric Model of Metabolite Signal Contributions For complete characterization of each metabolite in the data to be analyzed only two additional parameters were required beyond the metabolite database an amplitude multiplier and frequency shift value The complete parametric model used for the metabolite portion of the signal is shown here a priori relative amplitude frequency and phase of all resonances for each metabolite Met N n j oto Jeg p SS J FFI gt gt A Ave m n l t L t model signal model model zero YUH i concentration frequency and first Ta Ty of each metabolite shift order phase Lit e z The metabolite portion of the spectrum was modeled as the sum of decaying sinusoids over time t Fourier transformed into the frequency domain Terms indexed over m comprise the actual metabolites being analyzed in the spectrum with each metabolite modified by amplitude scal e Am and frequency shift wm This latter term was used to account for minor frequency shifts only since a preprocessing stage was used to initially align the whole spectrum with respect to the theoretical frequency offsets defined in the database Terms indexed over Nm comprise the a priori information describing the resonances structures for each metabolite with amplitude An Wn and phase that do not change in the course of the analysis Four additional parameters were applied over the whole spectrum the zero and fir
3. RESUS OUP T chs ele Sacer tae ea are hei lee 32 8 1 Plot results to image file formats cccccecccceee eee eeeeeeeeeeeeeeeeeeeeessseeeeneeneeeeneees 32 8 2 Plot results to vector graphics formats wis ecco he A assedeieceeeg elie erences 32 Append A TUON AS ia austebeastaa a teuetecuaseon 33 A 1 Importing a data file into a dataset c cece eeeceeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeees 33 A 2 Importing multiple files into a datastack ccccceeeeeeeeeeeeeeeeenneeeeeeeeeeeeeees 34 A 3 Opening and comparing multiple datasets cceeeeeeeeeeeeeeeteeeeeeeeeeeeeees 35 A 4 Applying ECC correction using an associated dataset Overview of the Vespa Package The Vespa package enhances and extends three previously developed magnetic resonance spectroscopy MRS software tools by migrating them into an integrated open source open development platform Vespa stands for Versatile Analysis Pulses and Analysis The original tools that have been migrated into this package include e GAVA Gamma software for spectral simulation e MatPulse software for RF pulse design e IDL_Vespa a package for spectral data processing and analysis The new Vespa project addresses current software limitations including non standard data access closed source multiple language software that complicates algorithm extension and comparison lack of integration between programs for sharing prior information and incompl
4. Dataset2 x Flip X axis V FFT 7 chop Eddy Current Correction Filter None Water Filter HLSVD Zz V Apply Threshold Threshold from On resonance Hz 11 Zero Fil Multiplier 1 Apodize Gaussian v Width Hz 1 000 lock Bo BO Shift Hz 0 500 Area Multiplier 1 000 P lock Pho1 Phase0 deg 237 000 SetPhitoZero Phasei deg 80 000 Pivot ppm 2 010 DC Offset 0 000 Correct Phase1 Left Shift pts 0 Do Automatic Phasing m Raw Basic SVD Spectral Fitting i PPM 4 556 Hz 1962 311 Value 0 139235700185 Area 521 32 RMS 2 01904 jj A new dataset tab is typically created by importing an MRS data file and then processing it tab by tab to create the desired results Dataset are only saved to file when specifically requested 10 by the user On selecting File Save the current state of the dataset ie all data settings and results in all tabs is saved into a file in the Vespa Interchange File Format or VIFF This file can be updated when desired by the user by again hitting Save or a new filename can be used to save different states in different files When a VIFF file is opened in Analysis all tabs and results are restored to the state they were in upon save Each processing sub tab display the filename of the displayed data the x voxel index and the y scale of the plot in the sub tab As discussed in more detail in the
5. first order phase pivot DC offset left shift and other convenience settings for interactive display of the results from changing these processing steps Most results from changing setting in the Spectral tab are displayed in the plot windows as they are made As shown in this figure the eddy current correction and water filter controls can be set to None and have no sub panel of controls showing Or a filtering method can be selected from the drop menu and a sub panel of controls displayed for that particular algorithm Due to the complexity of user interactions with the eddy current correction and water filter panels these controls are described in more detail in subsequent sections nl File Processing View Help The top line of controls includes as in all sub tabs the filename of the displayed data the x voxel index and the y scale of the plot in the sub tab You can step through each spectrum in the dataset by increasing or decreasing the index in the x voxel widget Dataset6 X File zode yepository_svn vespa docs tutorial_analysis tutorial_02_multiple files press_cp0 rsd Location X 1 Scale 11 55743 PlotB None nA Flip X axis V FFT Chop Eddy Current Correction Filter None z Threshold from On resonance Hz 11 F Apply Threshold J Water Filter HLsvo Zero Fill Multiplier Diese Apodize Gaussian Width Hz 1 000 Para
6. 0 85000 Calculate for V Area PPM Linewidth E Phase Cramer Rao Bounds V Do Cramer Rao Bounds Noise measure range ppm Start 8 000 End 6 000 Update Initial Values Fit the Spectrum Raw Basic SVD Spectral Fitting check flag Select whether to calculate confidence interval values spin control float The threshold about the parameter across which the variation is measured 0 85 shown above means a 15 variation about the fitted value You can select to calculate limits for specific parameters in order to save on calculation time check flag Select whether to calculate Cramer Rao bounds spin controls Allows you to specify a region of the data from PPM start to end that an RMS noise calculation can be made from 7 3 6 On the Results Panel On this control panel can see a text based report on the results of fitting the data 30 gt Analysis Voigt Results Filename C Users bsoher code repository_svn vespa docs tutorial_analysis tutorial_02_mltiple fi Vozel 1 1 1 Area Results Area CrRao CnfInt choline truncated 18 894 0 768 3 443 creatine 17 372 0 712 3 128 glutamate 22 855 1 375 6 617 myo inositol 23 459 0 720 3 763 n acetylaspartate 31 917 0 657 2 034 PPM Results PPM CrRao CnfInt ppm choline truncated 19 2791 0 0016 0 0083 creatine 19 1787 0 0015 0 0077 glutamate 18 8616 0 0061 0 0397 myo
7. Damping Phase Area 7 1 0 64 258 9 18 829 113 1 L E 2 087 2438 229 105 6 95 2 J 3 143 208 4 10 6 101 7 137 6 7 4 2 02 1709 102 4 115 8 1315 7 5 214 163 2 791 0 133 4 45 7 6 2 24 156 5 109 123 0 283 1 4 W Allon I All Off 7 Use cursor span to pick lines nan aaneen anaa a a a Raw Basic SVD Spectral Fitting PPM 8 818 Hz 1690 758 Value 0 123281045634 Area 542 28 RMS 0 32004 spectrum The top line of controls includes as in all sub tabs the filename of the displayed data the Location X index and the y scale of the plot in the sub tab You can step through each spectrum in the dataset by increasing or decreasing the index in the Location X widget Parameter values specific to each spectrum are automatically updated in the widgets of each sub tab The y scale on the plot can be adjusted by clicking on the arrows in the Scale control typing in a value or using the roller ball on the mouse while in the plot Once the SVD tab is open the algorithm is run for the active voxel Each time you click on the Location X widget the algorithm is run for that voxel If the voxel has already been run once and the input parameters have not changed then the algorithm is not run rather the current results are displayed in the plot Each voxel can have different settings for the HLSVD algorithm These default to typical values but can be set by navigating to the desired voxel via the
8. Location X widget and setting the widgets in the left panel Most results from changing HLSVD parameters or results widgets are reflected in the widgets and plots within a few seconds Occasionally the HLSVD algorithm fails for a particular set of input parameters and data This is seen in the plot by all the model FID values being set to zero Typically we just bump the Hankel Matrix Points up down by one click and the algorithm successfully completes 6 2 On the SVD Sub tab Reset All Voxels button Sets algorithm input values back to default values for all voxels of Data Pts slider number of data points of the FID to use in the calculation May not be less than spectral points in the raw data or more than 2048 Exponentials in Model slider Integer between 1 and 50 Hankel Matrix Points slider Integer Size of the Hankel matrix Max Iterations slider An internal threshold in the HLSVD algorithm to time out if taking too much time Results Model Signals check matrix This matrix acts similarly to a spreadsheet Column widths can be adjusted Rows can be sorted by a particular column by clicking on the column label The HLSVD algorithm returns a frequency phase area and damping term for each exponential line in the model We provide a conversion of frequency to ppm for convenience You can add lines to be plotted and used by manual setting in the HLSVD water filter by checking the box at the left of each row You can use the
9. Locaton x 1 Seale 48 27824 the list on the right side of the sub er scee ___ p ea s Etor s n vespa docs tuto nalysis tutorial_02_multiple files press_cp0 rsd FILE INFORMATION a H H sitory_svn vespa docs tutorial_analysis tutorial_02_multiple files press_cp4 rsd i_header_ 2 08 tab When you click on a filename zey snvese doc utors_snayesiutoraoo miltple Respresso7isd dau beoc data_format xdr the corresponding header data tpe cone ot total_data_bytes 32768 information for that file is displayed tds 1 in the text box on the right side of patent pame oN the sub tab patent bree OD MM YY acon ee Plot Information There is NO plot inane IDENTIFICATION INFORMATION in this tab because there are no fe movednteo iane EO processing steps Note The raw omen data can typically be viewed in the measure ate 01 01 1998 POMM K measure_time 00 00 00 h mm ss Spectral tab by turning off all parameter fierame processing and scaling the plot to seus pecsi h display the FID data m r T AE Raw Basic Spectral Sse se Hz 2175 351 Value 1 11598804393 Pasei kaii WU it On the Standard Raw Data Sub tab Filenames list select list of filenames for the one or more SVS data files loaded into this dataset Header information text box header data for the filename selected in the Filenames list 3 1 2 Summed FID Raw Data Sub tab When SVS data is saved as individual FIDs it needs
10. Variable Knot options Polynomial power value of the splines used in the model Notes on Baseline Algorithms Use of the wavelet filter baseline estimate requires that you have installed the pywavelet module Details on this can be found in the Analysis wiki here http scion duhs duke edu vespa analysis wiki PyWavelets 27 Wavelets are a great way to dial in a baseline estimate that has a fixed amount of smoothness relative to a reasonable range of metabolite linewidths That is the baseline rate of change is fixed by the minimum dyad scale being used which in turn is determined by some multiple of the calculated FWHM linewidth for a metabolite singlet peak In some cases typically when there are a few areas with very narrow linewidths the minimum dyad scale can jump up and down leading to small but noticeable regional differences in peak areas The Wavelet Dyad Min Scale control can be used to mitigate this effect Both fixed and variable spline baseline methods use the scipy interpolate splrep method which is based on the FORTRAN routine curfit from FITPACK It finds the b spline representation of a 1 D curve given the set of data points x i y i it determine a smooth spline approximation of degree k on the interval xb lt x lt xe The fixed spline representation places knots based on the user set spacing The farther apart the knots generally the smoother the spline baseline estimate The variable knot represent
11. inositol 19 4518 0 0023 0 0122 n acetylaspartate 18 6799 0 0010 0 0056 Global Results Value CrRao delta CnfInt Ta 0 30788 0 01495 0 00000 Tb 0 16668 0 00226 0 00000 PhaseO 237 73167 0 00002 0 00000 Phasei 422 43278 5 90677 0 00000 Calculation Results Value Max LW Min LW Linewidth 1 78273 0 00000 0 00000 ChiSquare 0 00276 E Weighted ChiSquare 0 00090 Math Finite Error False Output to HTML button Creates an HTML file to display the text shown above with the plots currently selected in the plot window left User must select a filename 31 8 Results Output 8 1 Plot results to image file formats The plots displayed in all sub tabs which contain View panels can all be saved to file in PNG portable network graphic PDF portable document file or EPS encapsulated postscript formats to save the results as an image The Vespa Analysis View menu lists commands that only apply to the active Dataset tab and selected processing sub tab Select the View Output option and further select either Plot to PNG Plot to PDF or Plot to EPS item The user will be prompted to pick an output filename to which will be appended the appropriate suffix 8 2 Plot results to vector graphics formats The plots displayed in all sub tabs which contain View panels can all be saved to file in SVG scalable vector graphics or EPS encapsulated postscript formats to save the results as a vector graphics file that can be
12. right displays the spectrum you are designing The top plot shows each individual line you add The bottom plot shows the sum of all lines You can zoom in out of this plot the same as described in Section 2 3 You will likely need to zoom in to clearly see the lines you are creating 4 2 On the Basic AutoPrior Sub tab Model Lines Use the Add and Delete buttons to create however many lines you want in your AutoPrior spectrum As you change values in the PPM Area Phase and Linewidth controls this will be reflected in the plotted spectra Restore Defaults button Resets the Model lines to a set of default 1H values ie NAA Cr Cho singlets Algorithm Parameters Auto BO Range spin controls This is the range over which the BO shift is optimized Auto Phase 0 Range spin controls This is the range over which the zero order phase is optimized Auto Phase 1 Range spin controls This is the range over which the first order phase is optimized Phase 1 Pivot spin control float ppm This is the pivot point used in the phase 1 calculation 15 5 Processing Sub tab Spectral 5 1 General When a dataset tab is added to the Notebook it automatically has three sub tabs added to it called Raw Basic and Spectral The Spectral tab provides controls for most of the typical processing steps involved in spectral processing including eddy current correction water filtering zero fill signal apodization BO shift zero and first order phase
13. roll on FID prior to FFT effectively shifts frequency data either left or right by any amount Value can vary for each voxel spin control Control to scale FID FFT by some floating point amount Same value for all voxels spin control Control to set phase 0 for the displayed data plot Value can vary for each voxel spin control Control to set phase 1 for the displayed data plot Value can vary for each voxel spin control Control to set phase 1 pivot value This value must be the same in all voxels in all datasets thus changing it in one dataset tab will change it in all dataset tabs spin control Control to set phase 1 pivot value Same value for all voxels spin control Control the number of points dropped from the front of the FID data before FFT To maintain the same number of points the last data point is repeated Same value for all voxels check When the number of left shift points are known a time varying phase roll can be applied to the data to correct for the phase 1 added by dropping points button Performs automatic set of Phase01 values The Lock BO and Lock Ph01 check boxes allow these parameters to be changed simultaneously of all data that has been loaded into the screen in the main dataset in Plot A With Lock off the BO Shift and Phase0 1 changes in widgets or by mouse are applied only to the active voxel shown in the plot With Lock on all parameter values are changed by whatever de
14. roller bar can be used to increment decrement the Y axis scale value A maximum value for the Y axis scale is determined the first time a dataset is loaded and displayed That max value is the value displayed in the scale widget top right in the dataset and used when you zoom all the way out As you roll the ball up down or you click on the SpinCtrl widget next to the scale field the scale value changes and the plot is updated Note It may be necessary to actually click in the plot window to move the focus of the roller ball into the plot before the roller ball events will be applied to the Scale value Roller balls can typically be used also as a middle button but pushing down on it without rolling it up or down You can click and drag the middle button in a plot to change the values of the zero and first order phase Phase0 1 of the data plotted in the window Note that the PhaseO 1 value that is set in any sub tab is also updated in all other sub tabs and store internally in just one location Thus there is effectively only one PhaseO 1 regardless of however many plots and sub tabs there are in a dataset Click and release the left mouse button in place and the plot will zoom out to its max setting Click and release the right mouse button in place and the cursor span will be turned off 3 Processing Sub tab Raw 3 1 General When a dataset tab is added to the Notebook it automatically has three sub tabs added to it called Ra
15. to be added together to form the summed single FID that is the actual raw data for the dataset In some cases the quality of the data can be improved by adjusting the frequency shift and or phase each FID prior to summing In this case the data is opened into the Raw sub tab shown right For summed FID data files only one SVS voxel can be loaded into a dataset This is because you usually have to select multiple files each of which contains one FID to be summed Thus it would be unclear which files were FIDs to be summed and which files were to be loaded into the screen fam Analysis BISDEV_JULZ8 TESTEP MR DUKE DEVELOPMENT SOHER 3 1 2009 07 28 14 09 19 281250 252144851MA The panel on the left of the Raw sub tab contains controls that set the parameters for routines that sort the data and apply frequency shift and phase corrections to each FID prior to summing You can navigate through the FIDs using the FID index widget The action for other controls are listed below DatasetS X File C Users bsoher code yepository_svn sample_data siemens_dicom_export_fids BJSDEV_ Location X 1 Scale 21306 44172 FiDindex 7 Data Processing and Manual Corrections Gauss apodize Hz 2 00 Peakshift Hz 0 00 FID left shift pts 0 Phase 0 deg 271 00 Automated Data Corrections V Apply Peak Shift Reset Peak Shifts mme a E A e Vapi bry Peak search width ppm 0 200 fApoly Phased Res
16. 237 733 Phase 1 0 000 Update Initial Values Fit the Spectrum Raw Basic SVD Spectral Fitting 25 Data Pre processing BO Shift Baseline Estimate Peak Ignore Width Filter Window Size Area and PPM Area from abs Real Cho Cr 0 2 PPM Separ Small peaks Area Small peaks PPM Linewidth Initial width multiplier Phase 0 1 These steps are performed prior to metabolite value estimation drop list spin control This control sets the method for BO shift evaluation Methods are Manual and Auto Correlate This is the same value that is shown on the Spectral tab Changes to this spin control will also be reflected on the Spectral tab The Auto Correlate algorithm compares the data spectrum to the AutoPrior spectrum in the range listed on the AutoPrior panel The offset with the highest correlation is selected as the BO value drop list This control selects the algorithm used to estimate initial baseline signals using either a Lowess or Savitzky Golay filtering technique Prior to the application of the filter regions known to have metabolite peaks from the ppm list in AutoPrior are modified by estimating a straight line across the bottom of the metabolite peak region spin control Sets the width in Hz of the metabolite region that is modified prior to the filter application The region s are centered on the ppm values in the AutoPrior basis set spin control Sets the filter windo
17. All On and All Off buttons to set reset all check boxes at once All On button Checks all boxes in all rows in the results matrix All Off button Unchecks all boxes in all rows in the results matrix Use Cursor Span check When this box is checked and the you draw a cursor span right mouse click and drag the tab calculates all model lines that are within the PPM range of the span and check their boxes in the results list Checks are additive in that the next cursor span you draw does not turn off any check boxes it just checks any additional lines in the new span Use the All Off button to start over 6 3 Mouse Events in the Plot The SVD sub tab always has three axes drawn We will typically refer to these as top middle and bottom plots The top plot displays the dataset without any water filtering The middle plot displays an overlay plot of green lines of all the model results that are checked The bottom plot displays the middle results plot subtracted from the top data plot 20 Most mouse events in the plot are as described above in Section 2 3 7 Processing Sub tab Fitting 7 1 Fitting Method Voigt This sub tab allows you to estimate metabolite signal contributions within your data while accounting for nuisance signals such as unsuppressed water lipids and macromolecular resonances The Fitting sub tab makes use of algorithm we call the Voigt method 7 1 1 Background and General Algorithm The Vo
18. Mwy Reece domain frequency domain metabolite to to wees oe ees fitting The View menu items set the plotting options for whichever sub tab is active The Help menu provides links to useful resources kay Currently there are no datasets loaded You can use the File menu to load data files The status bar provides information about where the cursor is located within the various plots and images in the interface throughout the program During plot zooms or region selections it also provides useful information about the cursor start and end points and the distance between Finally it also reports short messages that reflect current processing while events are running On the Menu Bar File Open Opens an existing VIFF dataset XML file into a new dataset tab in the dataset Notebook The state of the dataset as it was saved including all sub tabs and results are restored as the dataset is opened into its tab File lmport lt various gt This will allow the user to select one or more MRS data file from a variety of data formats that can be imported into the Analysis program and concatenated into a new dataset Tab More information about importable data formats is given below File Save Saves the state of the dataset as it currently exists including all sub tabs and results into a VIFF Vespa Interchange File Format XML file File Close Closes the active dataset tab File Exit Closes the applic
19. Values Baseline Optimize Quality Results Customize the Baseline Estimation Baseline Method B spline fixed knot Smoothing Parameters iE Smoothing OFF for last iteration Smooth whole metabolite region V Smoothing OFF for last iteration Metab region Lowess window size Hz 20 000 z Metab region Lowess window size Hz 20 000 First pass underestimation 0 000 P B spline Parameters i Variable smoothing factor 20 Fixed knot spacing pts of 13 000 Order of B splines 3 gives Hz spacing of 12 39776611 Update Initial Values Fit the Spectrum Update Initial Values Fit the Spectrum Raw Basic SVD Spectral Baseline Method Smoothing Parameters Smooth whole region OFF for last iteration Lowess window size First pass underest Fitting or Raw Basic SVO Spectral Fitting drop list Options include None Wavelet filter basic B spline fixed knot and B spline variable knot The panel below the Smoothing Parameters panel will reconfigure depending on the method selected Note that the variable knot option can take considerably more processing time than the other two methods check flag turns smoothing off on in the metabolite region during iterations for the baseline estimation check flag turn on to NOT apply filtering to baseline on the final iteration of baseline and metabolite signals fitting spin control float in Hz Window
20. Vespa Analysis User Manual and Reference Version 0 4 0 Release date May 24 2012 Developed by Brian J Soher Ph D Philip Semanchuk Duke University Medical Center Department of Radiology Durham NC Karl Young Ph D David Todd Ph D University of California San Francisco Department of Radiology San Francisco CA Developed with support from NIH grant EB008387 01A1 Table of Contents Overview of the Vespa Package ccccccccccecececeeeceeeeeeeeeeeeeeeeeeeess 4 Introduction to Vespa AnalySIS cccccccccccceeseceeeeeeeeeeeeeeeeeeaeaeees 5 Using Analysis A User Manual ccscccseseeeeeeeseneneseneneenees 7 1 Overview How to launch Vespa AnalySis 2 ecceeeeeeeeeeeeeeeeeeeeeeeeeeeeeees 7 2 The Analysis Main Window ccccceeeeeeeseeeceeeeeeeeeeeesenaaaaeeeeeeeeeeeneesaaaees 9 2 1 The Dataset Notebook x wieicppecissatdncceteccesanenicnsnettelsageseeeasstnaladaoerdeneedoe deepens 10 Zee B I fe ET TAS a E A E A Motattasatteans 10 2 3 M use Events in Plots csacceevecie dns nteeeasansssauente inp laste vey seeande eesti eaeeaiae 11 3 Processing Sub tab SIhaW ca AL adi A eae aa eae 12 e SSIS ac eas tee a tN Fee Nea a O uae aan 12 4 Processing Sub tab Basic ccccceeeeeeeeesseeeeeeeeeeeeeeeenseseeeeeeeeeeeeeeenenas 15 ck GCG al EE E EEA E estas ETET sev jane A ES 15 4 2 On the Basic AutoPrior Sub tab
21. ab when an ECC filter panel is opened All of the following filters except where noted require a lineshape FID to use as a reference to correct the main dataset This reference must already be loaded into a dataset in the notebook When a filter is selected a button is displayed that allows you to select the dataset to use as a reference in the algorithm The following ECC filters are provided as part of the Analysis application Klose based on the paper by Klose MRM 14 p 26 30 1990 This method simply subtracts the phase of the reference from the phase of the data However this correction only partially restores the Lorentzian lineshape since only BO t distortions are corrected Quality based on the paper by deGraaf et al MRM 13 p 343 357 1990 Performs a simple division of the main data by reference dataset This method can cause artifacts where the denominator in the complex division is too close to zero Strong apodization can reduce these artifacts but broaden the effective lineshape QUECC based on the paper by Bartha et al MRM 44 p 641 645 2000 A combination of both the Quality and Klose s ECC algorithms this method preserves the strengths of each while overcoming their respective limitations The main limitation in this filter is that a crossover point between the two methods must be selected At the moment this is hard coded Simple variation on the Quality method This algorithm takes the refere
22. alues for all FID data sets to 0 This action is reflected immediately in the other controls and plots Ref peak center ppm spin control Controls the value of the reference peak around which the peak shift algorithm searches for a maximum value in the magnitude data Pk search width ppm spin control Controls the width of the search region around the reference peak in which the peak shift algorithm searches for a maximum value in the magnitude data Apply phase 0 check Sets a flag off on to indicate if the Phase 0 correction algorithm should be applied Changing this control does not trigger the calculation for this correction Reset PhaseO Values button Sets all phase Ot values for all FID data sets to 0 This action is reflected immediately in the other controls and plots Calculate Corrections button runs the algorithms to calculate peak shift and phase 0 corrections for each FID data set in the tab Only runs the respective algorithms if the Apply check boxes are checked 14 4 Processing Sub tab Basic 4 1 General When a dataset tab is added to the Notebook it automatically has three sub tabs added to it called Raw Basic and Spectral The Basic tab is a bit of a catch all for certain information and data that is typically user derived or at least user editable but that needs to be available for use in later processing sub tabs As of this release the Basic tab contains only the AutoPrior control panel This is show
23. aset If you choose to save both datasets to the 33 original file name this will overwrite the data in that file and only the last tab saved will be available in the future Use File SaveAs to save a dataset tab to a new name Note For convenience each time you import data of a particular type VASF Siemens DICOM etc the program will by default start in the last directory you used to get a file of that type A 2 Importing multiple files into a datastack Tutorial Data tutorial_analysis tutorial_02_import stack Goal In this tutorial we will learn how to import data from multiple data files to create a datastack in an Analysis dataset We will learn to navigate and process individual voxels Run Vespa Analysis you will see the Welcome screen stating that no datasets are loaded Select File Import VASF and navigate to the directory above select all three files shown press _cp0 rsd press _cp4 rsd and press_cp7 rsd A dataset tab will appear populated with Raw Basic and Spectral sub tabs The Spectral sub tab should be active The press_cp0 data set should be displayed Select the Raw sub tab You should see three filenames listed in the left panel Click on each filename and carefully examine the small differences in the header information Select the Spectral sub tab Click on the Location X widget to scroll through the three spectra Use the mouse to set different Phase 0 1 values for each spectrum Zoom in on the 1 4 5
24. ation uses the s smoothing condition that splrep can take to determine the tradeoff between closeness of knots and smoothness of the fit Larger s means more smoothing while smaller values of s indicate less smoothing See scipy docs for scipy interpolate splrep for more details Note In Analysis baseline smoothing factor widget value for variable knot is directly related to the s value Generally the allowed range of 1 100 unit less is mapped internally to a semi linear increasing value of s that was determined empirically for a variety of MRS single voxel data In general we only recommend the use of the variable spline baseline if the wavelet filter and fixed spline baseline routines have failed due to the non linear performance of this routine 7 3 4 _On the Optimize Panel On this control panel you select the general parameters for the optimization algorithm set up the constraints on the Metabolite model and create a Weighting schema to use in the least squares calculation Metabolites Initial Values Baseline f Opti e Quality Results Select the Optimization Algorithm Algorithm Constrained Levenburg Marquardt x Parameter scaling Globaliterations 6 Stop tolerance 0 005 MaxMatrixIter 100 Constraints for Metabolite Model Parameters Area 50 000 pho Deg 45 000 Freq Hz 5 000 Phi Deg 2000 00 Ta Tb s Min of 0 040 gt Max LW H
25. ation window Processing Add HLSVD Tab Adds an HLSVD analysis sub tab to the active dataset tab Processing Add Voigt Fitting Tab Adds a Voigt model fitting sub tab to the active dataset tab View lt various gt Changes plot options in the plots on each sub tab of the active dataset tab including display a zero line turn x axis on off or choose units select the data type real imag magn displayed and various output options for all plot windows Help User Manual Launches the user manual from vespa docs into a PDF file reader Help Analysis Vespa Online Help Online wiki for the Analysis application and Vespa project Help About Giving credit where credit is due 2 1 The Dataset Notebook The dataset notebook is an advanced user interface widget AUINotebook What that means to you and me is a lot of flexibility Multiple tabs can be opened up inside the window They can be moved around arranged and docked as the user desires by left click and dragging the desired tab to a new location inside the notebook boundaries In this manner the tabs can be positioned side by side top to bottom or stacked as shown in Section 1 They can also be arranged in any mixture of these positions There is only the one Notebook in the Analysis application but it can display multiple MRS data sets by loading them into Dataset tabs 2 2 Dataset Tabs The dataset notebook can be populated with one or more dataset tabs eac
26. auto correlation of the spectral region listed in the Calculation range widgets with itself Again the FWHM of the max peak sets the linewidth value spin control Used to modify the linewidth value from Deconvolution and Auto Correlate methods drop list spin controls These controls set the method for zero and first order phase values These are the same values shown on the Spectral tab Changes to these spin controls will also be reflected on the Spectral tab Methods include Manual Correlation and Integration Both automated methods can be applied to phase 0 only or both phase 0 and 1 Automated phasing method parameters are set in the AutoPrior tab on the Basic sub tab 7 3 3 On the Baseline Panel On this control panel you select the algorithm to non parametrically estimate baseline signal contributions Selections include wavelets splines or none You can also specify whether smoothing filters should be applied to the data as part of the estimation Note The typical Voigt model uses wavelets for baseline estimation but spline options are included for convenience 26 Customize the Baseline Estimation Baseline Method Wa Smoothing Parameters Wavelet Filter Parameters Smooth whole metabolite region First pass underestimation 0 000 Wavelet scale multiplier x Linewidth X Wavelet dyad min scale Hz 6 000 Metabolites Initial Values Baseline Optimize Quality Results Metabolites Initial
27. be either None A B or B A If None is selected plot C is not displayed on the canvas gt Output View lt various gt writes the entire plot to file as either PNG SVG EPS or PDF format gt Output PlotA lt various gt Spectral sub tab only writes the values of the complex64 array displayed in PlotA top plot into either an ASCII or binary file using the numpy tofile method User is prompted for a filename The entire vector in the plot is saved not just the zoomed in portion if zoom is applied Note this functionality is provided as a convenience to users only This output format is not cross platform compatible and can not be read back into Analysis 2 3 Mouse Events in Plots Most processing sub tabs have plots in their left hand panels These plots may contain one or more axes which may change dynamically For example the SVD pane always has three axes displayed but the Spectral tab may have one two or three axes drawn We will typically refer to these as top middle and bottom plots OR as Plot A Plot B and Plot C respectively You can control a number of functions by using your mouse interactively within the plot area of most sub tabs Vespa Analysis is best used with a two button mouse that has a roller ball but can also work fine with a two button mouse as most mouse driven features for the roller ball also have a corresponding widget that can be clicked on or typed in to cause the same effect Th
28. ch contains the data and processing for an entire Dataset Multiple Datasets can be loaded into the tabs of the Analysis application but all the data loaded must have the same spatial and spectral dimensions This is necessary to allow proper comparison between tabs Analysis Main Window Dataset 1 Dataset 2 Dataset 3 Raw data Raw data Processing sub tabs Processing sub tabs Graphical displays of results Graphical displays of results Processing step provenance Processing step provenance Datasets are processed through a progression of pipeline steps which are shown as sub tabs of the Dataset tab These sub tabs currently include Raw Data SVD Spectral and Fitting steps although only the raw data and spectral tabs are required Each processing tab contains a series of processing steps known as its functor chain and also maintains the current state for all processing parameters within its widgets Upon output a full provenance for parameters and functor algorithms applied to the data is created as part of the Analysis XML output data format A variety of graphical and text based methods are available for saving results as well Dataset 1 Raw data General l optional l optional Spectral I Time Freq e Access Information l Spatial l HLSVD signal processing l Domain Fitting Header e Automatic l processing l removal Parameters l Parameters display phase BO Parameters basis set Pulse sequence
29. d in more detail below but first let s look at an outline of the procedure itself Iterative Algorithm for Fitting 1 Initial spectral parameter estimation from raw data and formation of a model spectrum Subtraction of the spectral model from a copy of the raw data Baseline characterization using the wavelet filtering procedure Subtraction of the baseline characterization from a copy of the raw data Spectral parameter optimization of the metabolite model create spectral model for next iteration 6 Repeat 2 5 for N iterations Voigt Model Starting Values The best fitting results occur when voxels are already corrected for BO shifts and zero and first order phase in the Spectral sub tab A priori metabolite knowledge is very useful for determining the initial starting values for frequency BO shift zero and first order phase and line width 21 however at the moment all of these value are set manually within the parameter panels of the Fitting sub tab Voigt Model a Priori Information The Voigt model uses a priori information selected from Experiments stored in the Vespa data base to create a metabolite basis set It is very important that the Experiment used to build the basis set be matched to the actual pulse sequence used to acquire the data Metabolite resonance patterns in an Experiment are described as collections of individual resonances with relative amplitude frequency and phase values for each line in the pattern
30. decomposed into various parts This is particularly desirable when creating graphics in PowerPoint or other drawing programs At the time of writing this only the EPS files were readable into PowerPoint The Vespa Analysis View menu lists commands that only apply to the active Dataset tab and selected processing sub tab Select the View Output option and further select either Plot to SVG or Plot to EPS item The user will be prompted to pick an output filename to which will be appended the appropriate suffix 32 Appendix A Tutorials Data sets referred to in these tutorials need to be downloaded from the Vespa Analysis wiki at http scion duhs duke edu vespa analysis wiki Tutorials Data is in a zipped file called analysis_tutorial_data zip The zipped data file contains a parent directory called tutorial_analysis The sub directories are numbered to correspond to the sections below For the most part the data that we will import will be in the VASF VA San Francisco data format because it is a simple format to understand and that is what we have our de identified data stored in A 1 Importing a data file into a dataset Tutorial Data tutorial_analysis tutorial_0l_import file Goal In this tutorial we will learn how to import data from a single data file into Analysis We will examine the basic functionality of the Raw and Spectral tabs We will save and open the processed data into an Analysis VIFF Vespa Interchange File Fo
31. e following describes the typical actions that can be effected using the mouse in a plot window Any variations from this will be noted in the following sub tab sections 11 The mouse can be used to set the X axis and Cursor values in sub tab plots Where there are two or more plots the same X axis or Cursors are set on all three The left mouse button sets the X axis zoom range Click and hold the left mouse button in the window and a vertical cursor will appear Drag the mouse either left or right and a second vertical cursor will appear PPM value changes will be reflected in the status bar Release the mouse and the plot will be redisplayed for the axis span selected This zoom span will display its range in a pale yellow that disappears when the left mouse is released Click in place with the left button and the plot will zoom out to its max x and y axis settings In a similar fashion two vertical cursors can be set inside the plot window Click and drag then release to set the two cursors anywhere in the window This cursor xpan will display as a light gray span Click in place with the right mouse button and the xursor span will be turned off The cursor values are used to determine the area under the peak values that are displayed in the status bar While performing a right click and drag to create a cursor span the status bar will also display the start end location of the span and the delta Hz and delta PPM size of the span The
32. eaks other than NAA Cr and Cho can have this additional scale multiplier added to the weights in their local regions This causes the fits to these smaller peaks to have more emphasis in the least squares calculation Recommend 1 5 7 3 5 On the Quality Panel On this control panel you set up the calculation of Confidence Limits and Cramer Rao bounds for the current data set Both are used as measures of goodness of fit Cramer Rao bounds are calculated using only the metabolite model and a measure of the noise in the data They provide a measure of the range of uncertainty if the absolute best fit has been achieved Cramer Rao bounds do NOT tell you if this fit has been achieved The Confidence Intervals method makes use of both the data and the metabolite model to measure the variation about the given fit for a given threshold of goodness le the Confidence Intervals measure the variation around a parameter s value for which the least squares measurement changes only by a given percentage More details to this method can be found in Young K Khetselius D Soher BJ and Maudsley AA Confidence images for spectroscopic imaging Magnetic Resonance in Medicine 44 537 545 2000 29 Do Confidence Alpha Calculate for Do Cramer Rao Noise Measure Range Metabolites Initial Values Baseline Optimize Select Which Goodness Criterion to Calculate Results Confidence Intervals V Do Confidence Intervals Alpha
33. eee eeeecceeeeeeeeeeeeeeeaeeeeeeesaaaeeeeessaaeeeeneaas 15 5 Processing Sub tab Spectral c cccceceesesssseeecceeeeeeeeeeseseeeeeseeeeeeeeeeseseeeees 16 hs PERSIST EA EE EE E ee aay SS T NS AE 16 5 2 On the Spectral SU AAD sy aaie ie cenceeyiecensnenscbededas ct htexsblomenwneagenteealaaaeeuieanss Aeeunaaety 16 5 3 Mouse Events in the Plot wccicteiesisssSe scl ea ee Siaes SA reseed asec teeetan oan eed 18 5 4 Eddy Current Correction Control cccccceeeeseceeeeeeeceeeeeeecaeeeeeeceeeeeseeneeeeteeeeees 18 5 5 Water Filter Control recess cia sel eeetce sadisenc thes l ub a a lad teeta edeaeioadty 18 6 Processing Sub tab SVD ccccccceceeeeeeeeeeeeeceeeeeeeeeeeeesaaeeeeeeeeeeeeeeenenaeeees 19 ed SIN A coche oc ates ap acattna etanercept da se haene tenons E EEE 19 62 Onithie SVD SUBstAD sc se naa ta nie tstecc a das enh aa 20 6 3 Mouse Events in the Ploti ermesine arsenite ea sian ecm 20 7 Processing Sub tab Fitting aiceeistttstaohesies atiintaeietal el inie attic tarsi igteis etal ee 21 AA Fitting Method VOIGtscccnctessidteccnctees dna eas eo Nokimicet iene 21 1 2 Voigt Fitting Sub Tab ecvess ocd ren tinctoieeicisavetanconenebewader wedeawakaeeasiedhasevennaltabereeaceeenaneet 22 5 3 Mouse Events in the Ploticc 2 diverges ccd oid es nattecehudeasngeecoeeenaenehcre hora taaatass 22 7 3 Voigt Algorithm Parameter Control Panels ccccccceeeeeeneeeeeeeeeeeeeeetneeeeeneaes 24 Be
34. en If it is not then when you select this filter it will automatically be opened To apply HLSVD results you check the Apply box and must select the cutoff frequency in Hz beyond the on resonance frequency for which model signal should be included Alternatively you may uncheck the Apply box switch into the SVD sub tab and manually select which lines to apply see the SVD section below When you switch back to the Spectral tab you will see that the filtering has been applied with the manually selected lines 6 Processing Sub tab SVD 6 1 General The SVD sub tab can be added to a dataset using the Processing Add HLSVD Tab menu item It will also be added automatically when the HLSVD water filter is selected on the Spectral tab if it is not already open This sub tab allows you to Lite tse set the input parameters for the HLSVD algorithm based on the paper by Pijnappel JMR 97 p 122 134 1992 the code for this method was kindly contributed by the jMRUI project http sermn02 uab es mrui and visualize the results and compare them to the original Dataset6 x File code yepository_svn vespa docs tutorial_analysis tutorial_02_multiple files press_cp0 rsd Location X 1 Scale 8 95767 Hankel Lanczos Singular Value Decomposition Reset All Voxels Data Points 64 1024 1024 g Exponentials 1 20 50 g Matrix Size 1 390 g Max Iterations 1 1000 Results Model signals Line PPM Freq
35. et Phased Values Calculate Corrections Plot_ Information This Raw sub tab contains a plot because pre processing PPM 3 877 Hz 1101 483 Value 177974793936 Area 110208 60 RMS 1258 4982 13 Raw Basic Spectral occurs to sum the FIDs into the SVS data to be processed in the dataset The top plot if for data from a single FID as selected by the FID index control Peak shift and phase 0 values are updated in their controls as you change this index The bottom plot is the sum of all FIDs with the peak shift and phase 0 corrections applied as they are currently stored Mouse controls in the plot act as described in the previous section except that the only phase 0 can be applied to the FIDs and this phase 0 value is only applied in this sub tab The phase O value used in all other processing sub tabs is not changed by mouse or widget events in this sub tab Peak shift and phase 0 values can be edited manually in the control panel Phase 0 can also be edited using the mouse If you start your phase 0 mouse event in the top plot single FID then the phase 0 value for only that FID is changed If you start your phase 0 mouse event in the bottom plot Summed FIDs then all FID phase 0 values are changed by a delta phase 0 amount caused by the mouse motion In both cases the summed FID plot is updated after each mouse or control widget event On the Summed FID Raw Data Sub tab FID index spin c
36. ete or missing documentation and educational content Introduction to Vespa Analysis Vespa Analysis is application written in the Python programming language that allows users to interactively read process and analyze MR spectroscopic data Vespa Analysis allows users to Read one or more single voxel data files from various standard formats Perform typical spatial and or spectral Fourier processing steps Apply HLSVD methods to remove unwanted signal components Apply iterative time domain frequency domain metabolite and baseline models to fit MRS data and estimate metabolite signal areas Observe graphically the results of processing steps on the fly Store processed results and processing settings into a human readable XML format Do side by side comparison of results from two or more data sets Output results in text or graphical format 9 Exchange data and processing settings between users What is a Dataset A Dataset consists of one or more raw single voxel data sets Single voxel data can be stacked into the screen by selecting multiple files or from a single file with multiple 1D data sets stored in a 2D format All Datasets can be traversed using a simple voxel widget selectors The Dataset also contains information about all processing steps that have been performed on the data What is the Dataset Notebook This is the main window of the Analysis application It contains one or more tabs each of whi
37. files stored in the VIFF file 36
38. following section one or more MRS files can be loaded into a single dataset tab When multiple files are selected the dataset organizes them by stacking the data into the screen You can step through each spectrum in the dataset by increasing or decreasing the index in the x voxel widget Parameter values specific to each spectrum are automatically updated in the widgets of each sub tab The View menu on the main menu bar can be used to modify the display of the plots in the active sub tab The state of plot options in each sub tab is maintained in each sub tab as the user switches between them The following lists the functions on the View menu item On the Menu Bar View this menu affects the plots in the currently active Dataset tab ZeroLine Show toggle zero line off on ZeroLine Top Middle Bottom display the zero line in the top 10 region middle or bottom 10 region of the canvas as it is drawn on the screen Xaxis Show display the x axis or not Xaxis PPM Hz x axis value in PPM or Hz Data Type select Real Imaginary or Magnitude spectral data to display Area Calc Plot A B C when the right mouse button is used to define a region along the x axis the status bar displays the area in the plot between the start end of this region This option selects whether the area is calculated from plot A B or C Plot C Function the plot in the bottom canvas aka plot C of the spectral sub tab can
39. h range would be when both have the same min and max range Optimization Wight Calculation Weight Scheme drop list Select the weight array creation from Equal Weighting and Local Weighting methods Equal method sets all weights to be equal to 1 at all points in the optimization Local method uses the controls below to set up regions that are weighted more or less in the least squares calculation Local scale factor spin control The local region is defined as the region near to any spectral lines in the prior information used to create the metabolite basis set All points within line width times a multiplier see below are included These points are weighted according to the value in this Local Scale Factor widget Line Width Multiplier spin control Multiplier to determine width of the region around spectral lines that in included in the local region This value is multiplied by the estimated line width Min in Water region check spin controls Modifies the weight array A region affected by water suppression pulses can be selected using the start end values and weighted to a minimum value to minimize its effects on the least squares calculation Min in Lipid region check spin controls Modifies the weight array A region affected by lipid signals can be selected using the start end values and weighted to a minimum value to minimize its effects on the least squares calculation Small peaks scale spin control Metabolite p
40. h of which contains the data setting and results of one dataset Tabs for datasets are arranged along the top of the notebook and can be grabbed left click and drag and moved to different locations inside the notebook as you like Tabs can be closed using the X box on the tab or with a middle click on the tab itself When a tab is closed the dataset is removed from memory but can be restored to its current state at a future time assuming it was saved to Analysis VIFF format Each dataset tab has one or more imre err sub tabs that represent blocks of processing Dataset tabs are automatically populated with a Raw sub tab which reflects the import and organization of one or more MRS file s into the Analysis program and a Spectral tab in which a variety of time and frequency domain spectral processing steps can be applied Other types of tabs which can be added interactively by the user include those for SVD analysis and Fitting a spectral model to metabolites in the data Each processing sub tab is described in more detail in the following section The figure above shows an Analysis application with two datasets open in the notebook The active dataset tab has four processing sub tabs open Raw SVD Spectral and Fitting and the Spectral sub tab is active File Processing View Help Dataseti X Dataset2 File tutorial_analysis tutorial_03_multiple datasets press_cp0 rsd Location X 1 Scale 14 12268 Sync Plot8
41. hift pts 0 DC Offset Correct Phase1 Left Shift pts 0 z pr Raw Basic SVD Spectral Raw Basic Spectral PPM 4 331 Value 0 240521158262 Area 521 32 RMS 2 01904 2 The Analysis Main Window This is a view of the main Vespa Analysis user interface window It is the first window that appears when you run the program It contains the dataset Notebook a menu bar and status bar The dataset Notebook can be populated with one or more dataset tabs each of which contains input data and results from one dataset As described above a Dataset is a comprised of raw data plus a number of blocks of processing Each processing block has its own sub tab in the respective dataset tab Sub tabs are organized along the bottom edge while dataset tabs are organized along the top edge The dataset Notebook is initially fee tooi view Help populated with a welcome text wetcomeinfo x Welcome to Vespa Analysis window but no datasets are loaded From the File menu bar you can 1 open a dataset that has previously been processed by Analysis and then saved into the Analysis VIFF XML format or 2 import data from a variety of MRS formats into a new dataset In either case a tab will appear for each dataset that is opened or imported The Processing menu allows users to add certain processing sub tabs to each dataset that is opened such as for SVD analysis or for time Jo ow 7
42. ignal is subtracted from the original to remove the water The FIR kernel is calculated by the scipy signal firwin algorithm based on the filter length half width and ripple controls Because the kernel performs poorly at the beginning of the FID you can choose to extrapolate these values using a linear model using the Extrapolation drop menu At the moment the AR Model method does not work Hamming the raw FID data is convolved by a Hamming filter to remove high frequency signals ie Non water signals This low pass signal is subtracted from the original to remove the water The FIR kernel is calculated by the numpy hamming algorithm based on the filter length control Because the kernel performs poorly at the beginning of the FID you can choose to extrapolate these values using a linear model using the Extrapolation drop menu At the moment the AR Model method does not work HLSVD based on the paper by Pijnappel JMR 97 p 122 134 1992 the code for this method was kindly contributed by the jMRUI project http sermn02 uab es mrui This method is a black box estimation of the time domain FID using a model composed of summed orenizian lines A Hankel Lanczos singular value decomposition of the FID signal onto this model is performed Subsequently the subset of model signals that correspond to the water signals to be removed are summed and subtracted from the original signal Note that this filter requires that the SVD sub tab be op
43. igt method and is based on the papers by Young Soher et al e Young K Soher BJ and Maudsley AA Automated Spectral Analysis Il Application of Wavelet Shrinkage for Characterization of Non Parameterized Signals Magnetic Resonance in Medicine 40 816 821 1998 e Soher BJ Young K Govindaraju V and Maudsley AA Automated Spectral Analysis lll Application to in Vivo Proton MR Spectroscopy and Spectroscopic Imaging Magnetic Resonance in Medicine 40 822 831 1998 The Voigt method is an automated spectral analysis procedure that combines a parametric model of signals of interest with a non parametric characterization of the unknown signal components A least squares fit using a priori Knowledge of the MR observable compounds from Vespa Simulation results is first used to create a parametric model that is optimized to the known spectral contributions spectrum minus baseline signal estimate in the MR signal This is then followed by a wavelet filtering of the residual data signal spectrum minus metabolite signal estimate to characterize the so called baseline contributions Use of wavelets allows us to dial in the scale of features in the baseline estimate to be more slowly changing than the more narrow signals in metabolite model The repeated application of these operations rapidly converges to obtain an optimum fit of both signal components These features are used in the iterative procedure described below Each step above is explaine
44. l be copied into memory for use in the current dataset text box Read only Displays the name of the prior information source spin controls The start and end PPM values for spectral lines to be included in the metabolite model Note All spectral information from the prior source is read into Analysis 24 Dynamic Metabolite List Lineshape Model Update Initial Values Fit the Spectrum but can be limited to a specific range as it is used in the fitting algorithm using these widgets list All metabolites in the prior source are displayed in a list that resizes itself for each prior source you load Check the box in front of each metabolite you want to include in your model Scale the starting peak amplitude using the Area Scale Factor widget for each metabolite Peak PPM Location is initially set by finding the ppm of the max value of an ideal plot of each metabolite in the basis set The program uses this value to search for a peak on which to set the starting peak area in the initial values routine You can change the region it searches for a particular metabolite peak by changing this widget Use the Peak Search Width to limit how far from the peak center the algorithm searches drop list You can choose to use a Voigt Lorentzian or Gaussian line shape in your metabolite model Note The Voigt line shape uses two internal parameters in the model called Ta and Tp to simulate T2 and T2 effects on the ideal FID model The Lore
45. lta is applied to the active voxel Checking Sync synchronizes values between Plot A and Plot B Only Frequency Shift Phase 0 and Phase 1 are synchronized using the Sync option Parameters in the comparison dataset are changed by the delta of the value being changed in the main dataset 17 5 3 Mouse Events in the Plot The Spectral sub tab may have one two or three axes drawn We will typically refer to these as top middle and bottom plots OR as Plot A Plot B and Plot C respectively Most mouse events in the plot are as described above in Section 2 3 However one difference is that when an interactive phase 0 1 event middle mouse click and drag starts within Plot B then the phase of the dataset shown in Plot B is changed not that for the main dataset Plot A To change the phase of the main dataset start the interactive phase event within Plot A If the Sync box is checked both plots will be phased If an interactive phase event starts within Plot C no phase changes will be made 5 4 Eddy Current Correction Control The eddy current correction drop menu can be set to None and have no sub panel of controls showing Or a filtering method can be selected from the drop menu and a sub panel of controls displayed for that particular algorithm The main Spectral panel automatically reconfigures itself to accommodate any additional controls Note Widgets near the bottom of the main panel may be pushed below the visible edge of the t
46. meter values LockBO BO Shift Hz 0 500 specific to each Area Multiplier 1 000 spectrum are LockPhO1 PhaseO deg 242 000 automatically updated in the widgets of each sub tab The y scale on the plot can be adjusted by clicking on the arrows in the Scale control typing in a value or using the roller ball on the mouse while in the plot 5 2 On the Spectral Sub tab SetPhito Zero Phasei deg 0 000 Pivot ppm 2 010 DC Offset 0 000 Correct Phase1 Left Shift pts 0 EEr 5 4 3 2 1 Do Automatic Phasing rrejieney Thnk Raw Basic SVD Spectral Fitting Hz 1903 473 Value 0 0592850601809 PPM 5 479 Area 542 28 RMS 0 32004 J Sync check Flag for whether to sync changes made to the main data to whatever data is selected in the PlotB drop menu Not all controls are bound by Sync see wiki for more details PlotB drop menu You can select a comparison dataset to plot in the middle plot Plot B from all the open datasets in the notebook If None is selected then the plot automatically reconfigures to not show Plot B The Sync flag has no effect if None is selected Plot B can be used to visualize simple comparisons in plot C such as A B or B A as set in View Plot C Function 16 Flip X axis FFT Chop Eddy Current Filter Water Filter Zero Fill Multiplier Apodize Width Hz BO Shift Hz Area Multiplier Phase deg Phase deg Pivot ppm DC Offset Lef
47. n in the figure below and described in more detail in the following paragraph The AutoPrior control panel allows you to manually create prior information about the structure of the data to be analyzed that will enable automated BO shift Li ebet ecsctem a and Phase 0 1 routines to better i estimate these values The File code yepository_svn vespa docs tutorial_analysis tutorial_02_multiple fles press_cp0 rsd Location x 1 scale 0 10532 methods used in the automate phase and BO shift routines User defined prior spectrum for auto phase B0 algorithms Bee need a model spectrum to ee SS Se i compare to the corrected 52 So so 6 Model lines check box to delete phased data It is often not 725 t8 a h 3 22 0 400 0 0 5 00 desirable to have a full blown Crum ose seca Restore etait review model such as would be j i Algorithm parameters provided by the metabolite prior Auto B0 Range ppm Start 1 700 E erd 3 400 information ie We may not f oPhseoRaoempml sin 1850 ed 2250 want multiplet resonance rroeSet m lt me a structures Often a simpler mu model is more effective such as one that only contains singlets or other prominent metabolite features Raw Basic SVD Spectral Fitting PPM 4 716 Hz 1952 106 Value 2 46113458386e 10 Area 646 56 RMS 0 77347 4 3 2 1 Freauencv foom The plot to the
48. nce dataset and optimizes a frequency shift to best position the reference signal on resonance This simplifies the signal decay to look more like a Gaussian shape with fewer zero crossings and thus less chance for an artifact to occur BO shifts in the main dataset are not corrected for by the method Strong apodization can reduce any remaining artifacts but broaden the effective lineshape Traff developed by Jerry Matson and Lana Kaiser Similar to the QUECC method however it determines the cross over point automatically based on an estimate of signal T2 decay Also a Traff filter is applied to the data after the reference signal has been deconvolved in order to restore a Gaussian lineshape Typically no additional apodization is necessary 5 5 Water Filter Control The water filter drop menu can be set to None and have no sub panel of controls showing Or a filtering method can be selected from the drop menu and a sub panel of controls displayed for 18 that particular algorithm The main Spectral panel automatically reconfigures itself to accommodate any additional controls Note Widgets near the bottom of the main panel may be pushed below the visible edge of the tab when a water filter panel is opened The following water filters are provided as part of the Analysis application FIR the raw FID data is convolved by a finite impulse response filter to remove high frequency signals ie Non water signals This low pass s
49. ntzian and Gaussian line shapes are enforced by setting either Tp or Ta respectively to very large values that contribute insignificantly to the lines shape model However they may have some minimal effect on the eventual line shape modeled button Most initial value parameter changes are automatically reflected on the plot This button allows you to force a recalculation of these values button Triggers a fit of the data using the current set of parameters Progress messages about the various steps of the fitting process are displayed in the status bar Plots and the Results tab are updated automatically at the end of each fit 7 3 2 On the Initial Values Panel On this control panel you select the methods for calculating starting values for the Voigt model optimization Values for each starting value are displayed in the respective section Baseline Optimize Quality Results Initial Values Methods Data Pre processing BO Shift aligns data with model Method Manual BO Value Hz 9 500 Baseline Estimate improves peak estimation Method None Z Area and PPM by peak search Area from abs Real data Small peaks Area from V Cho Cr 0 2 PPM separation Small peaks PPM from Refpeak Linewidth Method Deconvolution Linewidth Value Hz 3 433 Calculation range ppm Start 4 100 End 1 900 Initial width multiplier 0 600 Phase 0 1 Method Manual z Initial Value Phase 0
50. onality is determined not by the number of files if you are loading a stack but by the actual dimensions of the final dataset datastack created just prior to it being loaded into a dataset tab in the notebook A 3 Opening and comparing multiple datasets Tutorial Data tutorial_analysis tutorial_03_open multiple datasets Goal In this tutorial we will learn how to open multiple datasets into tabs in the notebook Run Vespa Analysis you will see the Welcome screen stating that no datasets are loaded Select File Open and navigate to the directory above select press_cp0 xml After this dataset tab opens click on File Open and select the press_cp4 xml file This will open into a second dataset tab Note that both of these files are VIFF format and contain phased data in their Spectral tabs At this point you should have Dataset1 and Dataset2 tabs in the notebook In Dataset1 click on the PlotB drop menu you should see that there are three values None Dataset and Dataset2 Select Dataset2 and the plot will reconfigure to show three axes The top is the data for Datase1 middle is Dataset2 data and bottom is the subtraction of top middle Position the mouse in the top spectrum Middle click and drag and the top spectrum will be phased The Phase 0 1 widgets to the left will show the interactive change of these values The bottom subtraction plot will reflect the phase changes interactively as well Position the mouse in the middle
51. ontrol Selects the index of the FID data to display in the top plot This is also the index of the data whose peaks shift and phase 0 values are displayed in the respective widgets below Gauss oreniz Hz spin control Controls the width of the Gaussian apodization function that is applied to the data shown in the plots This apodization value is also used in the peak search routine The apodization applied in this tab is NOT applied to the final summed FID that is used by subsequent processing tabs It is only applied in the Raw sub tab to improve data visualization by the user FID left shift pts spin control Controls number of points dropped from the beginning of the FID data To maintain the total number of points the last data point is repeated Peak shift Hz spin control Each FID data set has a separate value for peak shift This control lets you set the shift value in Hz for the FID index data set displayed It is updated as you click through the different FID data Phase 0 deg spin control Each FID data set has a separate value for phase 0 This control lets you set the phse 0 value in degrees for the FID index data set displayed It is updated as you click through the different FID data Apply peak shift check Sets a flag off on to indicate if the Peak Shift correction algorithm should be applied Changing this control does not trigger the calculation for this correction Reset Peak Shifts button Sets all peak shift v
52. ppm range Set a reference span from 1 5 to 2 01 ppm Click through the three spectra and note how far the NAA peak is frequency shifted from its proper location at 2 01 ppm Use the BO widget in each voxel to line up the NAA peaks Select File Save and give this dataset a name You can use the default which is press cp0 xml because it is the first of the three files selected or choose your own Use your file browser to check the tutorial directory and note that the data from all three data files have now been stored into one Analysis VIFF file Select File Open and select the file you just saved This should open into a different dataset tab but contain the same data as in your original tab This file has the same data dimensions as the first dataset that you opened so the program allowed it to be loaded into a new dataset tab Select File Import VASF and select only the press_cp 7 rsd file You should see a warning dialog open that looks like this 34 T p Ci The dimensions and or sweep width of the currently open datasets differ from those of the file s you asked to open You can open these files but first you have to close all currently open datasets Go ahead and select File Import VASF and select all three rsd files again These should open up into a new dataset tab with no error message The dimensionality of the data you want to load has to match that in any datasets already open However the dimensi
53. rmat file Run Vespa Analysis you will see the Welcome screen stating that no datasets are loaded Select File Import VASF and navigate to the directory above select the press_cp0 rsd file A dataset tab will appear populated with Raw Basic and Spectral sub tabs The Spectral sub tab should be active Select the Raw sub tab note that the header information on the right is for the filename listed on the left Select the Spectral sub tab Click once in the plot to make that active Click and drag the left mouse button to zoom in on the plot Left click in place to zoom back out Click and drag the middle mouse button or scroll ball moving the mouse up down to set the phase 0 and left right to set the phase 1 values Note that the PhaseO and Phase1 widget values on the left change interactively as the mouse moves Right click and drag to set a reference span in the data plot Note that the area value and cursor location values in the status bar change interactively Roll the scroll button up down to change the y scale value for all plots Select File Save enter a file name or use the default press_cp0 xml Select File Open and navigate to the tutorial directory select the xml file you just saved This should open up in a separate dataset tab While this data comes from the same file into which the original dataset was saved the data in this tab is a unique copy and will not affect or be affected by changes made to the other dat
54. s have Trac Wiki sites with extensive information about how to use and develop new functionality for each application These can be accessed through the main portal site at http scion duhs duke edu vespa Using Analysis A User Manual This section assumes Vespa Analysis has been downloaded and installed See the Vespa Installation guide on the Vespa main project wiki for details on how to install the software and package dependencies http scion duhs duke edu vespa In the following screenshots are based on running Analysis on the Windows OS but aside from starting the program the basic commands are the same on all platforms 1 Overview How to launch Vespa Analysis Double click on the Simulation icon that the installer created on your Desktop Shown below is the Vespa Analysis main window as it appears on first opening No actual Dataset windows are open only the Welcome banner is displayed File Tools View Help welkome Info x Welcome to Vespa Analysis L A mera Ih M i Al J E MM A Currently there are no datasets loaded You can use the File menu to load data files Ready Use the File Open menu to open existing Datasets into tabs or the File Import menu to load third party MR scanner data files into a Dataset Shown below is a screen shot of a Vespa Analysis session with two Dataset tabs opened side by side for compari
55. set1 and select the Spectral tab From the Eddy Current Correction Filter drop menu select Traf The widgets will reconfigure to show a Ecc Data Browse button with no file name in the field to the right Click on the Browse button and in the dialog that appears select the press_cp4_wref rsd file from the list of open datasets you may need to resize the dialog to see the entire filenames The algorithm is applied directly after you select the water file You can switch back and forth between None and Traf in the drop menu to see the change in the data due to the ECC filter Note In this example data the change is not very significant if you want to send us poor data with a better improvement please feel free Click on File Save and give the output file a name Check in the tutorial directory and you will see that only one xml VIFF file has been created Since the water file is used in the ECC processing of the metabolite data it is assumed to be associated with that dataset When we saved it both sets of data were written to the VIFF file Note In the tutorial directory have already saved a file called press_cp4_with_ecc xml recommend that you annotate the default filename to indicate that a VIFF file contains associated data as well as the main dataset Close both dataset tabs Click File Open and select the VIFF file that you just created This will open up two dataset tabs showing both the metabolite and water data
56. son Note that the data from Dataset2 has also been selected to be displayed in PlotB of Dataset1 The difference between the top and middle plots of Dataset1 is shown in the bottom plot Also note that while Dataset1 tab has a SVD sub tab the Dataset2 tab does not and similarly for the Fitting sub tab in Dataset2 The functionality of all processing tabs will be described further in the following sections Ly Analysis press_cpO xmi File Processing View Help Dataseti x Dataset2 x File tutorial_analysis tutorial_03_multiple datasets press_cp0 rsd Location X 1 File gt rial_analysis tutorial_03_multiple datasets press_cp4 rsd Location X 1 _ sync plot Dataset2 v Sync PlotB None lFlip X axis V FFT V Chop Flip X axis FFT Chop Eddy Current Correction Filter None v Eddy Current Correction Filter Water Filter HSV Water Filter Threshold from On resonance Hz 11 e Zero Fil Multipier 1 x a we pee 10o E Zero Fal Multiplier dam ElokBo BOShift Hz 1 000 Apodize Width Hz 1 000 amidin E EllokB0 BO Shift Hz 0 500 LockPho1 Phase0 deg 173 000 E Area Multiplier 1 000 F setPhitoZero Phasei deg 0 000 ElLokPho1 Phaseo deg 237 000 Pivot ppm 2 010 Set Phi to Zero Phasei deg 80 000 DC Offset 0 000 Pivot ppm 2 010 E Correct Phase1 Left S
57. spectrum Middle click and drag and the middle spectrum will be phased regardless of where the mouse travels so long as you don t release the middle button The Phase 0 1 widgets to the left will not show any changes because we are changing 35 the Dataset2 phase values If you switch to Dataset2 tab you will see that it has the same phase as that shown in the middle plot for Dataset1 Conversely if you change the phase in Datase2 this will be reflected in the middle plot of Dataset1 The bottom subtraction plot will reflect the phase changes interactively as well Close Dataset2 by clicking on the X in its tab Note that the Dataset1 tab reconfigures itself to set PlotB to None and have only one Plot A 4 Applying ECC correction using an associated dataset Tutorial Data tutorial_analysis tutorial_04_eddy current correction Goal In this tutorial we will learn how to open multiple datasets into tabs and then associate them so that the eddy current correction ECC algorithm will have the water data needed to correct the water suppressed data Run Vespa Analysis you will see the Welcome screen stating that no datasets are loaded Select File Import VASF and navigate to the directory above select press_cp4 rsd Select File Import VASF and select press_cp4_wref rsd At this point you should have two dataset tabs open Dataset1 with the metabolite water suppressed data and Dataset2 with the water data Click on Data
58. splayed There are 14 different plot types that can be displayed For example in the figure below Plot A shows Raw and InitialModel Plot B shows Raw and Base Plot C shows Raw and Fit Base and Plot D shows Raw Fit Base or the residual spectrum j Analysis press_cpO cm ys leo File Processing View PlotA PlotB PlotC PlotD Help Dataset6 X File code yepository_svn vespa docs tutorial_analysis tutorial_02_multiple files press_cp0 rsd Location X 1 Scale 8 12129 Metabolites Initial Values Baseline Optimize Quality Fitting Results Analysis Voigt Results Filename C Users bscher code repository_svn vespa decs tutorial_analysis tuterial_02 sultiple fi Voxel 1 1 1 Area Results Area CrRao CnfInt choline truncated 18 894 768 aes creatine 17 372 712 128 glutamate 22 855 379 617 myo inositol 459 720 763 n acetylaspartate 917 657 034 PPM Results PPM CrRao ppm CnfInt ppm choline truncated 19 2791 0016 0 0083 creatine 19 1787 0015 0 0077 glutamate 18 8616 0061 0 0397 myo inositol 19 4518 0023 0 0122 n acetylaspartate 18 6799 0010 0 0056 Global Results Value CrRao delta CnfInt Ta 0 30788 0 01495 0 00000 Tb 0 16668 0 00226 0 00000 PhaseO 237 73167 0 00002 0 00000 Phase1 422 43278 5 90677 0 00000 Calculation Results Value Max LW Min LW ChiSquare 0 00276 Weighted ChiSquare 0 00090 Math Finite Error False 4 w Outp
59. st order phase terms o and and two decay constants in L t Ta and T used to describe a Voigt Lorentz Gauss lines shape By making use of all available spectral information for each metabolite the procedure is better able to separate contributions from overlapping multiplets while also using maximum available signal energy In addition by defining a fixed relationship between all resonances for each compound the model above is greatly simplified and the number of parameters is minimized 7 2 Voigt Fitting Sub Tab 5 3 Mouse Events in the Plot The Voigt Fitting sub tab has a top line of controls that includes as in all sub tabs the filename of the displayed data the Location X voxel index and the y scale of the plot in the sub tab You can step through each spectrum in the dataset by increasing or decreasing the index in the x 22 voxel widget The y scale on the plot can be adjusted by clicking on the arrows in the Scale control typing in a value or using the roller ball on the mouse while in the plot An example of a fitted short TE PRESS spectrum is shown in the figure below with the results tab displayed The Fitting sub tab can display between one and four axes drawn in the plot panel to the right These are typically referred to as Plots A through D The plot number is set in the View menu Each of the four plots has its own control menu in the menu bar This allows you to individually set the plot type and data type di
60. t Shift pts Correct Phase 1 Do Automatic Phasing check Flag for whether to flip the spectral plot along the X axis This value must be the same in all voxels in all datasets thus changing it in one dataset tab will change it in all dataset tabs check Flag for whether to perform FFT on spectral data May have to resize x y axes after turning this off on This value must be the same in all voxels in all datasets thus changing it in one dataset tab will change it in all dataset tabs check Flag for whether to apply a chop filter to the FID data prior to FFT This will shift the data halfway along the X axis This value must be the same in all voxels in all datasets thus changing it in one dataset tab will change it in all dataset tabs drop menu Selects the filter used to correct for eddy currents See section below for more details Same method for all voxels drop menu Selects the filter used to correct for unwanted water signals See section below for more details Same method for all voxels drop menu You can select to zero fill up to 32 times the raw data size This value must be the same in all voxels in all datasets thus changing it in one dataset tab will change it in all dataset tabs drop menu Selects apodization filter to apply None Gaussian Lorentzian Same value for all voxels spin control Width of the selected apodization filter Same value for all voxels spin control Control to perform phase
61. ude in model f Metabolites Area Scale Peak PPM Peak Search Factor Location Width ppm NAAG truncated 1 00000 2 041 0 100 a F aspartate 1 00000 2 736 al 0 100 z V choline truncated 1 00000 3 185 0 100 F J creatine 1 00000 3 009 0 100 gaba 1 00000 2 288 0 100 V glutamate 0 51200 2 352 0 100 i El glutamine 2 00000 2 453 9 100 il lactate 1 00000 1 349 0 100 W myo inositol 1 95313 3 553 0 100 2 F V n acetylaspartate 1 00000 2 010 0 100 scyllo inositol 1 00000 3 340 0 100 F taurine 1 00000 3 424 S 0 100 2 Lineshape Model Voigt X E Update Initial Values Fit the Spectrum Raw Basic SVD Spectral Fitting button Activates a dialog from which you select a Simulation Experiment that contains the prior information that you want to use If the Experiment has more than one sets of pulse sequence parameters a second dialog pops up to allow you to select which portion of the Experiment to use button Activates a file select dialog to browse for an XML file that contains the prior information that you want to use The file should have a prior node inside it It can be a Analysis Prior file that was created from the Vespa Simulation Third Party Output dialow an Analysis preset file or even an Analysis VIFF file in which a different processed dataset has been saved In all cases the prior node wil
62. ut to HTML Update initial Values Fit the Spectrum Linewidth 1 78273 00000 0 00000 Frequency ppm Raw Basic SVD Spectral Fitting PPM 2 235 Hz 2110 215 Value 1 94025704957 Area 647 24 RMS 0 38685 Most mouse events in the plot are as described above in Section 2 3 23 7 3 Voigt Algorithm Parameter Control Panels Voigt fitting algorithm parameter control widgets are located in a notebook whose tabs are arrayed along the top of the left hand panel These include Metabolites Initial Values Baseline Optimize Quality and Results Parameter values in these tabs typically apply to all voxels Only the results panel is updated as you navigate through the Location X widget The controls in each panel are described in more detail below 7 3 1 On the Metabolites Panel On this control panel you select the source of prior information for the metabolite model You can also specify which metabolites are used in the spectral model and manually modify starting values Prior from Database Prior from File Source Peak Include Range i Initial Values Baseline Optimize Quality Results Select Metabolites and Lineshape Model Metabolite prior information source Prior Information From Database Prior Information from File Source PRESS Ideal TE 30 and 144 Peak Indude Range ppm Start 1 000 End 4 100 F Check metabolite box to ind
63. w Basic and Spectral The Raw tab contains information about the data that was imported into the Analysis program In some cases it contains the controls for pre processing raw data Due to the variety of MRS single voxel spectra SVS data formats we have created Appendix B to provide information about the details of each format Here we describe the two typical forms of the Raw sub tab the one for standard data and the other for data that needs pre processing to combine the raw data in multiple files into a single SVS data FID 3 1 1 Standard Raw Data Sub tab In this case standard means that the data is already stored in its file in the final form that is needed to import and use it in Analysis That is the data that is imported will not require any pre processing steps to proceed with further processing and analysis This is typically the case 12 for VASF Siemens Export rda Siemens DICOM and Varian formats In these cases the Raw tab shown below is used to display data file names and header information Standard raw data formats can typically be loaded as one or more files If multiple files are selected then the data is loaded into the screen and you can move navigate through the stack Sogo of SVS data using the Location X Lisi presou widget top right The filenames of all the data loaded are displayed iN sie cWsersisohercodevepostory_sivespaidocs tutoral analyss tutorali 02 muliple A
64. w width in Hz used to smooth the baseline signal estimation These values are obtained by a peak search and some calculations based on peak height and linewidth check Perform peak search routines on abs Real plot rather than the Real data plot check Force Cho and Cr peak PPM values to be at least 0 2 PPM apart drop list Select small peaks any other than NAA Cr Cho area estimation method from NAA Ratio or Peak Search NAA ratio will use literature values to set small peak areas based on a ratio to the NAA peak area Peak search will locate the max data value at the Peak PPM Location listed for the metabolite in the Metabolite tab and convert this peak height into an estimated area drop list Select small peaks any other than NAA Cr Cho PPM estimation method from Peak Search or Reference Peak Ref peak will use literature values to set small peak PPMs based on an offset to the NAA peak area Peak seach will locate the max data value near the Peak PPM Location and use that PPM value drop list spin control This control sets the method for peak linewidth evaluation Methods include Manual Deconvolution and Auto Correlate Deconvolution creates an ideal impulse spectrum using AutoPrior peak ppm values and performs a deconvolution on the data in the region set in the Calculation range widgets The FWHM of the max peak in the deconvolution spectrum is used to set the linewidth value Similarly Auto Correlate performs an
65. width for the lowess algorithm to estimate outliers and apply regional spline filtering spin control float percent You can force the baseline signal estimation on the first pass to be more or less than the algorithm calculates This can be useful if you know that the initial value routines for the metabolites consistently over or under estimates Wavelet Filter Parameters Scale Multiplier Wavelet Dyad Min Scale B spline Parameters Smoothing Factor Spline Spacing pts Order of B splines drop list integer 1 16 Wavelet contributions to the baseline are filtered to be greater than a specified threshold This threshold is based on this widget s multiplier times the calculated metabolite signal line width Higher values result in a smoother baseline spin control float Hz Sets the minimum scale wavelet element that can be used in the baseline estimation in Hz This value overrides the multiplier scale in the event of very narrow metabolite peaks which might result in baseline elements that change too swiftly spin control integer Only used for Variable Knot option Range from1 100 apply less or more smoothing of the spline estimation respectively See notes below spin control float points Only used for Fixed Knot option Describes how closely knots should be spaced across the frequency domain Number of knots depends on the sweep width and hertz per point spin control int power value Used in both Fixed and
66. z 16 9886473597 Ta Tb s Max of 1 000 gt Min LW Hz 0 679545894389 Optimization Weight Calculation Weight Scheme Local Weighting Local scale factor 1000 00 Linewidth multiplier 3 000 V Apply min in Water region Start 4 100 End 5 300 E Apply min in Lipid region Start 0 500 gt End 1 100 Small peaks scale factor 1 000 Update Initial Values Fit the Spectrum Raw Basic SVD Spectral Fitting Optimization Algorithm These settings pertain to the optimization algorithm in general 28 Algorithm drop list Selects the optimization algorithm from None or Constrained Levenburg Marquardt list Parameter Scaling check If checked maintains a workable range between parameters in optimization by scaling prior to the fit and then un scaling after the parameters are optimized This does not affect results Global Iterations spin control Sets the total number of baseline metabolite iterations that are performed before stopping the optimization Stop Tolerance spin control float Tolerance between iteration inside LM algorithm recommend 0 01 to 0 001 Max Matrix Iter spin control For iterations inside the LM algorithm recommend only 20 100 Constraints for Metabolite Model Parameters lt various gt spin control These controls set the range around the initial value that the optimization searches to find a result The Ta and Tb ranges show what the min or max line widt

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