To facilitate quantitative analysis of FDG PET scans in clinical trials, we have developed open source software (extensions) for 3D Slicer. This website provides an overview of available software, short introductory videos, and links to source code available on github.
PET DICOM Extension
The PET DICOM Extension provides tools to import DICOM PET images into Slicer and performs Standardized Uptake Value (SUV) normalization. Specifically, it calculates Standardized Uptake Value (SUV) conversion factors and creates a corresponding Real World Value Mapping file.
Source code: https://github.com/QIICR/Slicer-PETDICOMExtension
The PET-IndiC Extension allows for fast segmentation of regions of interest and calculation of quantitative indices.
Source code: https://github.com/QIICR/Slicer-QuantitativeIndicesExt
PET Liver Uptake Measurement
This tool allows automated measurement of liver uptake in SUV normalized FDG-18 whole-body PET scans. A detailed description and evaluation of the method can be found in paper "Automated measurement of uptake in cerebellum, liver, and aortic arch in full-body FDG PET/CT scans", which was published in Medical Physics.
Source code: https://github.com/QIICR/PETLiverUptakeMeasurement
PET Tumor Segmentation
This tool provides an Editor-Effect for semi-automated segmentation of tumors and hot lymph nodes in PET scans. A detailed description and evaluation of the method can be found in paper "Semiautomated Segmentation of Head and Neck Cancers in 18F-FDG PET Scans: A Just-Enough-Interaction Approach", which was published in Medical Physics.
Source code: https://github.com/QIICR/PETTumorSegmentation
Quantitative PET Image Analysis using DICOM Standard
The suite of Iowa PET analysis tools can be used in combination with the QIICR Quantitative Reporting extension to analyze tumors in PET scans and export results as DICOM SEG and SR files. A detailed description explaining the involved DICOM SEG and SR's can be found in the paper "DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research." [https://doi.org/10.7717/peerj.2057]
Quantitative Reporting source code: https://github.com/QIICR/QuantitativeReporting
Quantitative Reporting Documentation: https://qiicr.gitbooks.io/quantitativereporting-guide/content
PET Cylinder Phantom Analysis
The PET Phantom Analysis Extension enables automated analysis of Uniform Cylinder Phantoms in PET scans utilized for quality control purposes.
Source code: https://github.com/QIICR/SlicerPETPhantomAnalysis
This work was supported in part by NIH NCI QIN project grant U01 CA140206 as well as the Quantitative Image Informatics for Cancer Research (QIICR) project (U24 CA180918).
The contents of this website does not necessarily represent the official views of the NIH/NCI.