InSyTe FLECT/CT Application Note

Transcription

1 Summary This note is a quick guide for FLECT and CT image co-registration and fusion with VivoQuant (VQ3.0Patch1). Scope This application note is for users who process/analyze images acquired with InSyTe FLECT/CT. Revision History Rev Date Author Description 002 May 25, 2018 Austin Moy Wesley Moy Version April 26, 2017 Guixue Bu Version 001

2 Introduction The InSyTe FLECT/CT system acquires separate X-ray CT and FLECT images. Fusion of the FLECT and CT images gives combined molecular and anatomical information in a single image. Due to a mismatch in the geometric center of each subsystem, when fused together, the FLECT and CT images are misaligned. This note outlines the steps to first fuse together and then manually co-register the X-ray CT and FLECT images using VivoQuant. Image Preparation The images used during the fusion procedure are typically acquired in a single imaging session (i.e. the imaging cell is not removed from the system between scans). Detachment and reattachment of the imaging cell between scans may change the physical position of the subject. Three images are required for the co-registration process: 1) X-ray CT image (reconstructed by Exxim) 2) Boundary volume scan 3) FLECT image (reconstructed by the FLECT recon algorithm). Images used for the fusion procedure can be exported to a separate directory and named appropriately at the users discretion. Image Fusion Procedure Loading images into VivoQuant 1. Load the CT image for a specified experiment into VivoQuant. This can be performed either by opening the corresponding CT reconstruction in FluoroView, or in VivoQuant manually by clicking the Open Data button highlighted in red:

3 2. Once loaded, select and load the associated boundary volume and FLECT image (in this order) for a given experiment from the appropriate directories. To do so, click the Append Data box highlighted in red: The boundary volume and FLECT image are resampled so that all three images have the same voxel size. Color Palette Selection and Adjustment The default color palette for each of the three sets of data is Gray. VivoQuant autodetects the minimum and maximum pixel values for each image and sets the corresponding color palette in the range from minimum to maximum.

4 It is necessary to change the color palettes for at least two images so that individual images can be visualized with different color palettes. Hover over the image colorbar on the left side and right click to select the desired color palette. While the palettes can be selected based on user preference, we recommend gray for CT, blue or green for the boundary volume, and nih_fire for FLECT. Occasionally, after appending all data, the boundary volume data will disappear. This can be remedied by moving the colorbar slider from 100 to 0.

5 The color palette range for CT, the boundary volume, and FLECT can be individually adjusted for visualization purposes in one of two ways: 1) Click the button to open the Min/Max menu and adjust accordingly. Click the button to confirm the new color palette range. 2) Move the colorbar slider under each data set to the desired min/max values. The color palette range for each input data set can be individually adjusted for so that each set of data can be visualized in the overlay.

6 Image Fusion and Co-Registration The Reorientation/Registration operator is used to perform manual image fusion. Select Reorientation/Registration from the pull down menu as below:

7 Under the Operator tab, three sets of data that can be operated on appear: 0. Ref CT X-ray CT image 1. Input OT Volume image 2. Input OT FLECT image 0. Ref CT is the reference image and left unselected. Click the tick box next to 1. Input OT and 2. Input OT to select these data sets for co-registration operations (Rotation/Translation/Flip). Once selected, the boundary volume and FLECT image are manually translated to match the X-ray CT image. To use the operator, hold down the Ctrl button on the keyboard and left click the mouse to drag the selected input data (FLECT boundary volume and FLECT recon data) until the boundary volume is visually aligned and co-registered with the CT data. VivoQuant shows a preview of the effect of changes to the rotation/translation parameters in the sagittal, coronal, and transaxial planes. During this process, the user can navigate through different slices in each plane to check if the X-ray CT image and the volume image are aligned in the 3D space. For fine adjustment, select the up and down arrows corresponding to minor translations in the X-, Y-, and Z- planes, moving 0.1 mm per mouse click.

8 Once the X-ray CT image and the volume image are aligned, the user can click the button under the Operator tab to finalize the new rotation/translation parameters. This step may not be undone, however, if the data fusion is not correct, simply unload the data by right clicking on the data set and reload the required data again. Repeat and follow the steps outlined above. After all data sets are successfully fused and the translation confirmed, unload the boundary volume by right clicking on the loaded boundary volume data in the Data Manager window and selecting Unload Data. The final step in the fusion is to return to the Reorientation/Registration menu, select all data, and rotate all data by 270. The fused image can be saved as a DICOM for further processing and analysis.