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,

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

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

Procedures

• Phase I: Build Masks

1. load RegLib_C12 Dataset (e.g. via "RegLib_C12_SlicerScene.mrml"
2. go to the Editor module
   1. Select "CT_preop_contrast" as master volume
   2. create new labelmap "CT_preop_contrast"
   3. trace the liver contour from axial slices, or use one of the Segmentation modules (e.g. FastMarching) as starting point
   4. Save result labelmap
3. repeat outlining on the MR image
4. In the Editor module, use the Dilate function to expand the outline by 2-3 pixels (click on Apply button 2-3 times)
5. save dilated labelmasks under new name (e.g. CT_mask.nrrd)

• Phase II: MR-CTpre registration

1. Following the concept of manual registration, create an initial transform that roughly aligns the MR to the pre-op CT. Details and links in the Slicer Registration FAQ
   1. In the Data module, create a new transform node (right click on Scene node), rename to "Xf1_ManualInit", then drag the image volume inside the registration transform node
   2. Select the views so that the volume is displayed in the slice views
   3. Go to the Transforms module and adjust the translation and rotation sliders to adjust the current position. To get a finer degree of control, enter smaller numbers for the translation limits and enter rotation angles numerically in increments of a few degrees at a time
2. Affine Registration
   1. go to BRAINSfit module
      1. fixed: "CT_preop", moving: "MRI_preop"
      2. Initialize with transform, select "Xf1_ManualInit"
      3. select/check the following boxes: Include Rigid...", Include Scale", "Include Affine registration phase
   2. Output Settings: select a new transform "Slicer Transform", rename to "Xf2_Affine"
   3. Registration Parameters: increase Number Of Samples to 200,000
   4. Masking: check "ROI" box
      1. Input Fixed Mask: select the "CT_preop_mask" generated above
      2. Input Moving Mask: select the "MR_preop_mask" generated above
      3. click Apply
3. NonRigid Registration
   1. go to BRAINSfit module
   2. fixed: "CT_preop", moving: "MRI_preop"
   3. Initialize with transform, select "Xf2_Affine"
   4. Output Settings: select a new transform "Slicer BSpline Transform", rename to "Xf3_BSpline"
      1. select a new volume "Output Image Volume, rename to "MR_preop_Xf3"
   5. Registration Parameters: increase Number Of Samples to 200,000
   6. Registration Parameters: set Number Of Grid Subdivisions to 7,7,5
   7. Masking: check "ROI" box
      1. Input Fixed Mask: select the "CT_preop_mask" generated above
      2. Input Moving Mask: select the "MR_preop_mask" generated above
   8. Leave all other settings at default
   9. click: Apply

• Phase III: CT_pre-CT_intra registration

1. follow same procedure as for MR-CT registration above

Registration Results

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

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

Acknowledgments

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