Documentation/Nightly/Modules/dPetBrainQuantification

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Introduction and Acknowledgements

Author: Martín Bertran and Natalia Martínez (Facultad de Ingeniería, Udelar, Uruguay) Contributor: Guillermo Carbajal, Álvaro Gómez (Facultad de Ingeniería, Udelar, Uruguay) Contact: Guillermo Carbajal, <email>carbajal@fing.edu.uy</email>

Module Description

The purpose of this module is to provide an interface for analysis and quantification of Brain dynamic PET studies. In it simplest form, it takes either a 4D DICOM, or a (Nifiti + Sif) study and performs the Patlak analysis. K-Map estimation is computed using an automated pTAC extraction algorithm. The user can optionally select the region of interest over which the Patlak estimation will take place, and supply its own estimated or extracted pTAC using a .csv input. Ptac curves can be automatically extracted using either IDIF (Image Derived Input Functions) techniques or Hunter PBIF (Population Based Input Functions) techniques. Supplying blood samples is optional for IDIF techniques. For IDIF methods, the required carotid segmentation can be done either automatically or user assisted by providing a ROI.

Use Cases

Use Case 1: Simplest usage

Import a PET dynamic study using either DICOM or Nifti + SIF, a .csv file containing venous blood samples is optional. Select "apply K map estimation" which returns a scalar volume containing the K parameters from patlak estimation

Use Case 2 : Patlack Estimation using Hunter (PBIF) pTAC estimation

Import a dynamic PET study and a .csv file containing at least one venous blood sample. In the pTAC parameters panel choose "PBIF Hunter pTAC estimation with venous samples" Input the patients lean weight and inyected dosage. Optionally you can display the estimated pTAC by clicking the "get pTAC estimation button" Click "apply K map estimation" to get the parametric K map.

Use Case 3 : Patlack Estimation using Chen based IDIF pTAC estimation

Import a dynamic PET study and optionally a .csv file containing at least one venous blood sample. In the pTAC estimation options panel select the type "IDIF pTAC estimation". If no blood sample file is loaded or the "Use venous blood sample" tick box is not checked the estimation will use the hot voxels of the carotid segmentation, more details below. You can display the estimated pTAC by clicking the "get pTAC estimation button" Click "apply K map estimation" to get the parametric K map.

Use Case 4 : Patlack Estimation using pTAC input file

Import a dynamic PET study From the K-Map estimation options menu select "Load pTAC estimation from .csv" this file should contain the pTAC values evaluated at the endtime of each frame. If not, a warning will be issued and interpolation will be attempted Select Apply selected K-Map estimation

Tutorials

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Panels and their use

• PET dynamic Study and Information: Input Parameters
  • Import DICOM Study: Alternative access to the DICOM browser. Used to import DICOM studies into the slicer scene.
  • Nifti + SIF input directory: Allows importing studies in a Nifti + SIF format. This option is recommended to avoid DICOM overflow errorrs.
  • Input Multivolume: Select the input multivolume (Imported from either the DICOM browser or the Nifti + SIF input directory)
  • Import acquired blood samples: Allows the importing of acquired samples through a .csv file. Optional, although some methods require it.

• Visualization Options:
  • Display frame selector: Slider that displays the selected frame into the scene.
  • Display Brain Mask : Shows the obtained Brain Mask. It separates brain from background, used for internal calculations.

• pTAC Estimation Options: The estimation of the K-map requires the plasma activity curve, currently, two options for its estimation are provided.
  • Type: IDIF pTAC estimation : Image derived input function estimation using Chen's approach (ref C). It requires carotid segmentation, which is also provided.
    • Use previous carotid segmentation : Check if you want to use a previously acquired carotid segmentation map. Otherwise, segmentation will be done using the currently selected parameters in the "Carotid Segmentation Options" panel.
    • Use venous blood samples : If a venous sample file has been loaded, it is possible to use it to aid in the estimation. Otherwise, a sample-less estimation will take place.
  • Type: PBIF Hunter pTAC estimation with venous samples: The pTAC is extracted according to population based data curves taken from Hunter (ref H)
    • Dosage inyected in MBq : Patient inyected dosage in MBq
    • Lean Weight in Kg : Patient Lean weight in Kg
  • Chart estimated pTAC : Displays estimated pTAC in a chart
  • get pTAC estimation : Executes the pTAC estimation with currently selected options
  • Write estimated pTAC to .csv file : Allows the saving of the estimated pTAC into a .CSV file.
• Carotid Segmentation Options : Carotid segmentation is required for the IDIF pTAC estimation. Two methods are implemented, one is fully automatic and the other requires a user input ROI over the carotid region. Both estimation methods return a segmentation containing the detected blood vessels and its surrounding tissue
  • Type : Automatic Carotid Segmentation: Default selection, the algorithm searchs for voxels that are both highly similar to a rough estimate of the expected pTAC and that posses sufficient signal intensity in the initial time frames. For more details about the methdo, see CAR
  • Type : ROI Assisted Segmentaion : This option requires a user-input ROI over the carotid region
    • Input ROI : User input ROI
  • Choose a frame for better segmentation: Forces the segmentation to use a particular frame for segmentation. Useful for tracers that reach rapid equilibrium like C-11 Flumazenil, where the automatic method may present issues.
  • Apply Connectivity Filter: Returns the two largest classified clusters. For automatic segmentation, it automatically ignores the upper half of the brain. Usually not needed

Similar Modules

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References

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