jeffrey yap, phd ron kikinis, md wendy plesniak, phd -1- ctsa at rsna 2009 pet/ct analysis using 3d...

Jeffrey Yap, PhD Ron Kikinis, MD Wendy Plesniak, PhD -1-CTSA at RSNA 2009

PET/CT Analysis using 3D Slicer

Jeffrey Yap PhD

Ron Kikinis MD

Wendy Plesniak PhD

Slicer3 Training Compendium


Study Data

CT acquisition:

(jeff, please fill in anything relevant about the dataset)

PET acquisition:

(jeff, please fill in anything relevant about the dataset,Isotope used, etc.)


Clinical Context

Clinical relevance: (jeff)-underlying diagnosis-why were scans done-what was radiologist’s interpretation-treatment?-followup plan.


Clinical Context

Tutorial context:

-background: standard ways to evaluate response to treatment

-how this tutorial addresses clinical needs

-transition to specifics on SUV computation.


Brief Description of Quantitative Measurement:

Standardized Uptake Value

• Under certain circumstances, 18FDG SUV correlates with metabolic rate of glucose and/or the number of viable tumor cells

• Simplified semi-quantitative measure that can be routinely performed in clinical PET studies

• Adjusts for differences in patient size and injected activity

SUV (time) = Radioactive Concentration x Weight Injected Activity


Making assessments from measurements:

Response criteria

• Complete response (CR): Complete resolution of all lesions

• Partial Response (PR): >= 25% decrease in SUVmax

• Stable Disease (SD): < 25% change

• Progressive Disease (PD): >= 25% increase in SUVmax


Learning objective

This tutorial demonstrates how a pre-treatment and followup study are analyzed.

Following this simple tutorial, you’ll be able to use 3D Slicer to:

• Load a MRML scene description file,

• Achieve combined display of PET and CT data,

• Make quantitative measurements of Standardized Uptake Value (SUV) within one or more volumes of interest


Slicer GUI overview

The Graphical User Interface (GUI) of Slicer3 integrates five components:

• the Menu Toolbar

• the Module GUI Panel

• the 3D Viewer

• the Slice Viewer

• the Slice and 3D View Controller

Slice Viewer

3DViewerModule GUI Panel

Slice and 3D View

Controller

Menu Toolbar


Select File->Load Scene:

Load the MRML Scene

This raises the Load Scene Interface

• select the PETCTFusion-Tutorial-Scene.mrml file

• double click the file, or click Open


Navigate to the PETCTFusion Module

Note:

The menu displays a categorized list of modules available in this version of Slicer.

The All Modules menuitem shows all 95 modules in this version.

Using Modules Menubutton: Expose the menu and select the module called “PETCTFusion”.


Explore the PETCTFusion Module

Click on the Help & Acknowledgements Panel to see more information about this module.

Clicking on any Grey Panel Title Bar will toggle it open and closed.

Panels include:

•Help & Acknowledgments

•Data Fusion

•Display

•Quantitative Measures

•Study Parameters


Select the Volumes to Display and Analyze

In each of the volume selectors in the “Data Fusion” panel, select:

the CT volume CT1,

the PET volume PET1,

and the tumor mask PET1-label volume.

When the PET volume is selected, a “wait message” will be displayed while parameters are read from DICOM header.


Adjust the combined display of PET and CT data

In the “Display” panel, choose a colorization option for the PET volume from among

Grey, Heat, or Spectrum.

Adjust the window and level for CT1 and PET1 volumes.

Adjust the Slices Fade Scale to jointly display the datasets.


Explore the dataset

Explore:

in the Slice Viewers, scroll through the slices to locate the green Tumor label and the yellow Liver label (used only to demonstrate multiple-VOI functionality).


View a specific axial slice

Type –740 in the Axial Viewer’s Slice Number Entry widget to view the Tumor label.

This displays the slice positioned at -740 mm within the reference frame of the dataset.


View Tumor Label in all Slice Viewers

To view all Slice Viewers to the Tumor Label:

Select the Scene Snapshots menubutton:

and choose “PreTreatmentPETCT” and the “Restore” option.

Touch the Slices Fade Scale to update all viewers.


SUVmax and SUVmean for each VOI (represented by a different color in the label map) will be displayed in the table.

Compute SUV for all VOIs in the pre-treatment study

In the “Quantitative Measures” panel, click the “Compute/Refresh” button.


Compute SUVbw for follow-up study.

Now select:

the CT volume “CT2”, the PET volume PET2” and the Tumor Mask called “PET2-label” in the Data Fusion Panel.

This dataset contains a green VOI that corresponds to the tumor segmentation the pre-treatment study.


Adjust the display for the follow-up study.

You may want to adjust the Slices Fade Slider and manipulate the 3D View to refresh them.

Adjust display for follow-up study.


Compute SUVbw for follow-up study.

In the “Quantitative Measures” Panel, select Compute/Refresh to compute SUVbw for the green Tumor volume (and yellow liver volume).


Assess response with respect to this VOI

Pre-Treatment Max SUVbw =

Post-Treatment Max SUVbw =

8.019048 g/ml

9.351174 g/ml

+16.61% (SD)


This tutorial has demonstrated:

• use of an interactive interface to load a scene• the combined display of PET and CT volumes in a single

visualization• a workflow to make quantitative measurements of

Standardized Uptake Value (SUV) within a volume of interest

Summary


Acknowledgments

Harvard Clinical and Translational Science Center

National Alliance for Medical Image Computing (NA-MIC)

Neuroimage Analysis Center (NAC)

National Center for Image-Guided Therapy (NCIGT)

Surgical Planning Laboratory, Brigham and Women’s Hospital

jeffrey yap, phd ron kikinis, md wendy plesniak, phd -1- ctsa at rsna 2009 pet/ct analysis using 3d...

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