DKE Manual
Contents
1. DKIN and DKIBO In the top field on the right side DICOM Series Description is where the user will specify which DICOMs will be used for estimating the parametric maps In the right bottom field BO Image Series Name a series of extra BO images may be added Series in the left column can be selected by using the Add Series buttons After selecting all relevant image series click Accept Processing is initiated with the current GUI parameter settings A copy of the settings is saved in the data directory in a file call DKEParameters dat DICOM Series Description DKI Image Series Names DICOM Series Description DKI Image Series Names DKI_80_2 5mm DKL_NOISE_2 5mm DKIL_2 5mm DKI_NOISE_2 5mm localizer DKIL_2 5mm MPRAGE_SAG INTERP_OFF localizer T2 FLAIR MPRAGE_SAG_INTERP_OFF Add DKI Series T2 FLAIR Remove DKI Series Remove DKI Series 80 Image Series Name BO Image Series Name DKI_B0_2 5mm Add B0 Series Add BO Series Remove BO Series Remove B0 Series Cancel Accept Cancel 1 4 Basic Settings B 0 Threshold Background threshold Voxels with b 0 intensity values above this threshold after an optional connected component analysis are processed See batch processing on how to turn off the connected component analysis B values Diffusion weightings b values in s mm The first element of the vector must always be 0 Gradient Vectors Select the gradient table from2. a list of available tables or specify a custom table A custom table can be a dat or txt file Each row corresponds to a gradient vector G Gy Gz When specifying a custom table remove gradients that could correspond to the BO image 0 O 0 When using a 4D NIfTi make sure that the 4D order corresponds to the order of the gradient table If a DICOM set is used DKE will order the images according to the information stored in the DICOM tag 0018 0024 SequenceName DWI Spatial Smoothing Check this box to apply spatial smoothing to diffusion weighted images prior to estimation of parametric maps default checked This is accomplished with a linear filter with a Gaussian kernel FWHM Full width at half maximum in mm for the Gaussian smoothing filter An isotropic FWHM of roughly 1 25 times the voxel size is recommended Median Filtering Selective median filtering that is applied to parametric maps default strong filtering An outlier removal median filter with a 3x3x3 voxel window is applied to voxels that violate the minimum directional kurtosis constraints Strong filtering indicates that filtering will be applied to voxels with any constraint violation Weak filtering indicates that median filtering will be applied to voxels with less than 15 unviolated constraints No filtering will disable the median filter When it is suspected that the images are of lower quality it is recommended to set the filtering option to we
3. in diffusional kurtosis imaging Mag Reson Med 2011 Mar 65 3 823 36 http www ncbi nlm nih gov pubmed 21337412 If you use DKE in a publication please cite this paper in addition to standard DKI references For questions or remarks please contact us at dki musc edu Getting Started 1 Installation The software is readily available at our website http academicdepartments musc edu cbi dki DKE dke download htm After registration you will receive an email with a link where the software can be downloaded Note that DKE requires the installation of the MATLAB Compiler Runtime 2012a MCR version 7 17 available www mathworks com products compiler mcr After following the instructions of installation a folder called DKE will be created in your Program files directory Running DKE There are 2 ways of running DKE 1 Through the GUI Graphical User Interface by double clicking on DKEGUI exe DICOM and NIfTI or 2 using the command prompt DICOM NIfTI and Bruker 1 Running DKE using the GUI The video tutorial gives a brief overview of the basic steps for processing DKI data with DKE 1 1 File menu Load all DICOMs in a directory Load a DKI dataset in DICOM format All images must be stored in a single directory no subdirectories DICOM data may consist of multiple series DKI series must consist of one bO i e b 0 image and diffusion weighted images for nonzero b value 1 b value 2 b value 3 etc to b value n in th
4. Diffusional Kurtosis Estimator DKE User s Guide Version 2 6 0 Release date February 2015 Contents Getting ta A a ee eh ia 2 Le Installation a 2 RUNNING DK Ec 0 a a E a E E EEES 3 T Running DKE Using the GU a ad 3 Ll mel a 3 ELM a a a A ee 3 AAA O samt E 4 TA Basic SONES iaa seneus A AREA FREA 4 1 5 Advanced SECUESTRO A At A a dd aa 5 15 1 DKI PrOCOsSiIO gs Tos its lt a ink he tis e as eh tt dea ae eA 5 T S 2 DTI Processing La A E E tose ee ets esse hate ce OAS 6 2 Running DKE in the command window Batch Processing ccssccesscecsssceesseceeseeesseeeesseeecseeceeees 7 ZA COMMANG RN 7 2 2 Batoh A ANN 7 LRP 7 2 2 2 Preproc ssing Parets 7 2 2 3 Imaging diffusion weightings and CirectiONS cccccccccccsssssssscecececessessnseseeeeesessessaeeeeeeeseesees 8 2 2 4 Constraints on directional KUrtOSES ee eeesceesceceeeeeceeeeeesaeceeaeeceeeeecaaeeeeaaeceeaeeeeaeeesaaeeeeaeeesaes 9 2 2 5 Thresholds on Output kurtosis MAPS ocoooocccnncnononononnnnnnnonanonononnnnnnnnnnnononnnnnnnnnnannnnnonnnnnncnnnanonos 9 2 2 6 Tissue background segmentation cccccsssceessecesssecsseeecsseceeseeceseeccssececaseceeseecsseeeeaeeeeaseesees 9 2 2 7 DKI fitting method and ParaMeteLS ccccccccccsssssssssecececescesecesseceeecesseseeaeseeeeseessessaeeeeeesseesees 9 2 2 8 DTI fitting method and PAaraMetels cceccccccccscessessscecececsesesesesaeeeeeceseeseeaeeeeseesseseeeaeeeeeens 10 2 2 9 Diffusion we
5. ak 1 5 Advanced Settings 1 5 1 DKI Processing Check this box to enable DKI processing default checked DKI Fitting Method Select the DKI model fitting method Select directional to apply directional signal fitting or tensor to apply tensor fitting default tensor Directional fitting methods are the linear unweighted and linear weighted schemes default weighted Weighting is based on the diffusion signal magnitude Tensor fitting methods are the constrained linear weighted unconstrained linear unweighted and unconstrained nonlinear schemes default constrained Check the robust fitting box to apply a RESTORE type algorithm Chang et al 2005 outlier detection and removal followed by tensor refitting for tensor fitting Tolerance to outliers is controlled with the user supplied noise tolerance parameter 1 5 2 DTI Processing Check this box to enable DTI processing default unchecked DTI Fitting Method Select the DTI model fitting method Select directional to apply directional signal fitting or tensor to apply tensor fitting default tensor Directional fitting methods are the linear unweighted and linear weighted schemes default weighted Weighting is based on the diffusion signal magnitude Tensor fitting methods are the linear weighted and linear unweighted schemes default weighted Check the robust fitting box to apply a RESTORE type algorithm Chang et al 2005 outlier detection and removal f
6. e dataset All DKI series must use identical sets of b values and gradient directions An optional series DKIBO must exclusively consist of extra bO images For examples of supported DICOM protocols see recommended protocols for various scanners Load a 4D NIfTI image Load a DKI dataset as a single 4D NIfTI image The 4D image must consist of a single b O image followed by subsequent diffusion weighted images BO all B1000 s all B2000 s When different DKI series need to be included in the calculations of the parametric maps you will have to create your own series average before running DKE Save parameters Save the current parameter settings in the GUI to a text file 1 2 Help menu DKI Website Link to DKI website View Help Displays Help file About DKE Displays version and copyright information Exit Exit the program 1 3 Processing Processing is initiated by loading in 4D NIFTI file or a set of DICOMs If DICOM images are loaded the DKI image series must be selected manually This step helps DKE identify the name of relevant DICOM series for processing After the DICOMs are loaded proceed to click the button Next in the bottom left corner of the main window A window with three different fields will pop up The first column contains a list of all DICOM series in the directory Each DICOM series is identified with its series description field The diffusion weighted images will for example be designated as DKI1 DKI2
7. each b value a 1 by nbval 1 cell array of file names should be specified with each cell specifying the gradient file name for the corresponding nonzero b value idx_gradients Indices of gradient directions to be used for DKI map estimation Unacceptable diffusion weighted images e g those affected by motion or patient table vibration induced diffusion signal loss can be excluded here There must be as many cells as there are nonzero b values with each cell corresponding to a nonzero b value idx_1st_img Index of the first diffusion weighted nifti image for each b value typically O or 1 default 1 This is used when preprocess_options format dicom and is rarely changed 2 2 4 Constraints on directional kurtoses Kmin Constraint on minimum directional kurtosis cf Tabesh et al 2011 default 0 This is rarely changed NKmax Parameter defining the constraint on maximum directional kurtosis cf Eq 6 in Tabesh et al 2011 This is rarely changed 2 2 5 Thresholds on output kurtosis maps Kmin_final Kmax_final Lower Kmin_final and upper Kmax_final thresholds applied to output mean axial and radial kurtosis maps The default values are O and 3 respectively 2 2 6 Tissue background segmentation T Background threshold Voxels with b 0 intensity values above this threshold after an optional connected component analysis are processed find_brain_mask_flag Whether 1 or not 0 to apply con
8. ighted image filtering ooooccccnononononaonnonononanononnnnnncncnnnn no nnnnnnnnnannnononnnnncnnnns 11 2 2 10 Rician noise SUDtrACTION seriis aneii a iae ia Aa ET eaa a akad 12 2 2 11 Parametric map filtering a ek oe eases 12 2 2 12 Parametric map interpolation cccococcoconncncnonononannnnnnnonananonononnnnnnnnnonononnnnnnnnnnnnnennnnnnnnnnnns 12 Diffusional Kurtosis Estimator DKE User s Guide Version 2 6 0 Release date February 2015 Diffusional Kurtosis Estimator DKE is a software tool for post processing diffusional kurtosis imaging DKI datasets that includes a suite of command line programs along with a graphical user interface GUI DKE currently supports 32 and 64 bit Windows platforms DKE generates a set of kurtosis axial mean radial parametric maps with a given set of diffusion weighted images acquired from a valid DKI protocol Diffusivity axial mean radial and fractional anisotropy maps using either DKI or diffusion tensor imaging signal models are also calculated in the processing In the latest version of DKE two extra parametric maps KFA and mean kurtosis tensor were added DKE features include DICOM NIfTl and Bruker format support interactive GUI as well as batch mode command line processing and rigid body motion correction DKE implements the methods described in the following paper Tabesh A Jensen JH Ardekani BA and Helpern JA Estimation of tensors and tensor derived measures
9. ion weightings and gradient directions This setting is only used when preprocess_options format dicom or bruker preprocess_options extra_b0 Whether 1 or not 0 there is an additional b O series This setting is only used when preprocess_options format dicom preprocess_options coreg_flag Whether 1 or not 0 to perform 6 parameter rigid body co registration between diffusion weighted images default 1 This setting is only used when preprocess_options format dicom or Bruker preprocess_options series_description List of series descriptions from the DICOM image headers This is used only when preprocess_options format dicom preprocess_options fn_nii 4D nifti image file name This setting is only used if preprocess_options format nifti Co registration is not performed between the diffusion weighted images 2 2 3 Imaging diffusion weightings and directions bval Diffusion weightings b values in s mm units The first element of vector must always be 0 ndir Number of gradient directions If a scalar value is specified the number of gradient directions for all b values is set to the scalar Otherwise a 1 by nbval 1 vector should be specified with each element of the vector corresponding to the number of gradient directions for a nonzero b value fn_gradients Text file containing the gradient vectors Each row corresponds to a gradient vector If a different gradient set was used for
10. nected component analysis to refine the binary brain mask obtained by applying threshold T to b O image default 1 2 2 7 DKI fitting method and parameters dki_method no_tensor Whether 1 or not 0 to estimate parametric maps using directional signal fits instead of the default tensor fit of Tabesh et al 2011 default 0 Directional fits only allow estimation of mean diffusivity and mean kurtosis Directional fit are not recommended unless the number of acquired gradient directions is less than 15 dki_method linear_weighting Unweighted 0 or weighted 1 linear least squares default 1 dki_method linear_constrained Unconstrained 0 or constrained 1 linear least squares cf Tabesh et al 2011 default 1 dki_method nonlinear Unconstrained nonlinear least squares default 0 dki_method linear_violations Whether 1 or not 0 to generate maps of constraint violations default 0 Intensity of each voxel in the violation maps represents the proportion of constraints on directional diffusivities d_viol map and kurtoses kmin_viol and kmax_viol maps violated by the unconstrained linear least squares solution The unconstrained solution used to obtain the violation maps will depend on dki_method linear_weighting and dki_method robust_option parameters dki_method robust_option Robust fitting option default 0 0 do not use robust fitting 1 RESTORE type algorithm outlier detection and removal followed b
11. ollowed by tensor refitting for tensor fitting Tolerance to outliers is controlled with the user supplied noise tolerance parameter Specify the nonzero b value for DTI fitting in the B value box Co register Scans Check this box to enable rigid body co registration of DKI series This only applies to DICOM images Interpolate Check this box to apply linear interpolation to the parametric maps default checked See batch processing for details on how to change the interpolation method default trilinear 2 Running DKE in the command window Batch Processing DKE allows for batch processing of DKI data using a file that uses the MATLAB syntax The batch file format is described below In your program files you can find an example file called dke_parameters dat 2 1 Command Line Launch a command window and start processing by using the command with user specific pathways gt C Users Program Files DKE dke C Users MyDocuments Projects dke_parameters dat 2 2 Batch file 2 2 1 Paths studydir Root folder for data from all study subjects subject_list Cell array of subject sub folders within the root folder studydir 2 2 2 Preprocessing parameters preprocess_options format Input image format dicom nifti or Bruker preprocess_options navg Number of DKI series Each DKI series must contain a b 0 image followed by diffusion weighted images All series must use identical acquisition protocols i e same diffus
12. uced diffusion signal loss can be excluded here There must be as many cells as there are nonzero b values with each cell corresponding to a nonzero b value Indices are relative to the indices specified in idx_gradients dti_method robust_option Robust fitting option default 0 0 do not use robust fitting 1 RESTORE type algorithm outlier detection and removal followed by tensor refitting with a user supplied noise tolerance level dti_method noise_tolerance expressed as a fraction of the diffusion signal level dti_method noise_tolerance Threshold for outlier detection used when dti_method robust_option 1 The diffusion signal for a gradient direction is declared an outlier if abs log diffusion signal log predicted diffusion signal gt dti_method noise_tolerance 2 2 9 Diffusion weighted image filtering fwhm_img Full width at half maximum FWHM in mm of Gaussian kernel for smoothing diffusion weighted images default 1 25 voxel size A zero value indicates no smoothing 2 2 10 Rician noise subtraction fn_noise User supplied map of Rician noise level default i e none Noise subtraction is based on the method of McGibney and Smith 1993 Estimated signal s_hat at each voxel is obtained as s_hat s42 n42 40 5 where s is the measured signal and n is the noise level at that voxel fwhm_noise FWHM in mm of Gaussian kernel for smoothing noise image A zero value indicates no smoothing defa
13. ult 0 2 2 11 Parametric map filtering median_filter_method Selective median filtering applied to voxels that violate the minimum directional kurtosis constraints default 2 0 no filtering 1 weak filtering voxels with less than 15 unviolated constraints will be filtered 2 strong filtering voxels with any constraint violation will be filtered 2 2 12 Parametric map interpolation map_interpolation_method flag Whether 1 or not 0 to interpolate the parametric maps default 1 map_interpolation_method order Interpolation polynomial order 0 nearest neighbor 1 trilinear 2 and up higher order default 1 map_interpolation_method resolution Target resolution isotropic in mm for the interpolated maps default 1 mm
14. y tensor refitting with a user supplied noise tolerance level dki_method noise_tolerance expressed as a fraction of the diffusion signal magnitude dki_method noise_tolerance Threshold for outlier detection used when dki_method robust_option 1 the diffusion signal for a gradient direction is declared an outlier if abs log diffusion signal log predicted diffusion signal gt dki_method noise_tolerance 2 2 8 DTI fitting method and parameters dti_method dti_flag Whether 1 or not 0 to estimate DTI parametric maps based on the DTI in addition to DKI signal model default 0 dti_method dti_only Whether 1 or not 0 to only estimate DTI parametric maps no DKI map estimation default 0 dti_method no_tensor Whether 1 or not 0 to estimate parametric maps using directional signal fits instead of the default diffusion tensor fit default 0 Directional fits only allow estimation of mean diffusivity Directional fits are not recommended unless the number of acquired gradient directions is less than 6 dti_method linear_weighting Unweighted 0 or weighted 1 linear least squares default 1 weighting is based on the diffusion signal magnitude dti_method b_value Nonzero b values used for DTI map estimation dti_method directions Indices of gradient directions to be used for DTI map estimation Unacceptable diffusion weighted images e g those affected by with motion or patient table vibration ind
Download Pdf Manuals
Related Search