Projects:RegistrationLibrary:RegLib C12

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v3.6.3 Slicer Registration Library Case #12: Liver Tumor Cryoablation

Input

fixed image/target		intermediate ref. image		moving image

Modules

• Slicer 3.6.3 recommended modules: BrainsFit

Objective / Background

We seek to align a pre-operative MRI with the intra-operative CT for surgical guidance.

Keywords

MRI, CT, IGT, intra-operative, liver, cryoablation, change detection, non-rigid registration

Input Data

• reference/fixed : pr-op CT, 0.95 x 0.95 x 5 mm voxel size
• moving: intra-op MRI, 0.78 x 0.78 x 2.5 mm axial,

Notes / Overall Strategy

• the intra-op CT is acquired with a clipped FOV (to minimize acquisition time & exposure). This causes difficulty for intensity-based automated registration. We therefore use an intermediate pre-op CT with full FOV to bridge to the MRI
• masking is required to focus the registration algorithm on the structure of interest
• Overall strategy:

1. obtain (manual) a coarse segmentation of the liver in both MRI and CT. Dilate by a few pixels to include the organ boundary
2. perform a manual initial alignment of MR to CT. Use this alignment as starting point for the automated registration
3. run an affine registration with above masks and intial alignment

1. run a non-rigid BSpline registration with above affine alignment as starting point

Discussion: Registration Challenges

• large differences in FOV
• strong differences in image contrast between MRI & CT
• contrast enhancement and pathology and treatment changes cause additional differences in image content
• we have strongly anisotropic voxel sizes with much less through-plane resolution

Procedures

• Phase I: Pilot to determine optimal registration parameters

1. load reference image and one moving image from the series
2. open Registration : BrainsFit module
   1. Registration Phases:
   2. set "reference" fixed and "moving_??" as moving image
      1. select/check Include BSpline registration phase
   3. Output Settings:
      1. select a new transform "Slicer BSpline Transform", rename to "Xf1_moving_??"
      2. select a new volume "Output Image Volume, rename to "moving_??_Xf1"
   4. Registration Parameters: increase Number Of Samples to 200,000
   5. Registration Parameters: set Number Of Grid Subdivisions to 5,5,5
   6. Leave all other settings at default
   7. click: Apply; (runtime < 10 sec. on MacPro)
   8. adjust grid size until registration is acceptable
   9. you can see the commandline text of the registration performed by opening the Window/Error Log window and clicking on BRAINSfit commandline input

• Phase II: Batch Run

1. open a terminal window
   1. via a TextEditor or prototyping/scripting software (e.g. Matlab), copy and modify the prototype line below, by changing only the moving input image:

 /Applications/Slicer36/Slicer3 --launch  /Applications/Slicer36/lib/Slicer3/Plugins/BRAINSFit --useBSpline --splineGridSize 5,5,5 --outputVolumePixelType short /
 --numberOfSamples 200000 --costMetric MMI --fixedVolume Reference/refLung_001.dcm --movingVolume Moving/Moving_001/Moving_001.dcm /
 --bsplineTransform Xforms/Moving_001_XfBSpl5.tfm --outputVolume MovingResampled/Moving_001_r.nrrd >> Logs/Moving_001_RegLog.txt 2>&1

1. 1. replace "/Applications/Slicer36" with your path of 3DSlicer
   2. create result directories MovingResampled, Logs, Xforms
   3. note that because input image is DICOM, and images are 2D only, each image of the time series must be in its own directory, otherwise Slicer will read them as a volume.
   4. paste all commands into a terminal window, or copy into a shell script and execute.

• Phase III: Evaluate Transform files

1. 1. upon completion, read the transform files with an editor and extract the displacements of interest
   2. The ITK transform files describe displacements at the grid nodes, many of which are outside the region of interest. Because BRAINSfit pads the grid with 1 voxel, the grid returned is actually 8x8x8. We use only the plane (*,*,4) for analysis and discard the y-direction displacements, which as expected are all zero.
   3. for details on the ITK transform format see the FAQ here
   4. To obtain displacements at arbitrary coordinates, interpolate the transform into a deformation field, e.g. using this module (details FAQ here):

/Applications/Slicer3.6.3/lib/Slicer3/Plugins/BSplineToDeformationField

Registration Results

	registration masks	manual initial alignment of MRI & CT	affine registered MRI & CT	nonrigid registered MRI & CT
unregistered MRI & CT]]	registration masks]]	manual initial alignment of MRI & CT]]	affine registered MRI & CT]]	nonrigid registered MRI & CT]]

Download

• Data
• download input image data (Input Data, NRRD images, zip file 42 MB)
• download registration parameter presets file (.mrml file 20 kB)
• download guided tutorial (PowerPoint, xx MB)
• download full tutorial set (Input Data, presets, results, tutorial, zip file xx MB)

Link to User Guide: How to Load/Save Registration Parameter Presets

• Results
  • RegLib_C46_RegistrationTransforms.zip : the 200 BSpline registration transforms (ITK transform (text) files, zip file 274 kB)
  • RegLib_C46_MovingResampled.zip : the 200 registered image stack (NRRD image files, zip file 16MB)

Acknowledgments

Thanks to Dr.Stuart Silverman and Dr. Nobuhiko Hata for sharing this case.