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Table 1 Software characteristics

From: MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging – design, implementation and application on the example of DCE-MRI

 

MITK- ModelFit

UMM Perfusion

Rocketship

DCEMRI.jl

PMI

DATforDCEMRI

3DSlicer PkModeling

Operating system

Linux, Mac OS, Windows

Mac OS

Linux, Mac OS, Windows

Linux, Mac OS, Windows

Windows

Linux, Mac OS, Windows

Linux, Mac OS, Windows

Language

C++

C

Matlab

Julia

IDL

R

C++

License

BSD

BSD

GNUGPL

MIT

GNU GPL

Creative Commons

Slicer (BSD like)

Advanced extensibility

Yes

Yes

No

No

No

No

Yes

Fitting domain

Time, Frequency, anya

Time

Time

Time

Time

Time

Time

Eco-system

Yes (MITK)

Yes (OsiriX)

No

No

Yes (PMI)

No

Yes (3DSlicer)

Image modalities

DCE-MRI, DCE-CT, PET, dynamic MRI, dynamic CT, CESL/CEST,a

DCE-MRI

DCE-MRI

DCE-MRI

DCE-MRI, DSC-MRI, DCE-CT

DCE-MRI

DCE-MRI

Models

Tofts, Extended Tofts, 2CXM, 1TCM, 2TCM, Brix, Three-step linear (3SL), Semi-quantitative metrics (BAT, TTP, AUC, Cmax, Wash-in/Wash-out Slope, final uptake, mean residence time)

Extended Tofts, 1CP, 2CXM, 2C uptake model, two compartment filtration model (2FM)

Tofts, Extended Tofts, Fast Exchange Regime, 2CXM, Tissue uptake, Nested-model selection, Patlak, Semi-quantitative metrics (AUC)

Tofts, Extended Tofts, Plasma Only

Uptake models, Steady-state, Patlak, Model-free deconvolution, Tofts, Extended Tofts, 2CXM, 2C filtration model for kidney, Dual-inlet models for Liver, Semi-quantitative metrics (Slope/Signal enhancement)

Tofts, Semi-quantitative metrics (AUC, MRT - mean residence time)

Tofts, Semi-quantitative metrics (AUC, slope)

Input / Output

DICOM, Analyze, NIFTI, NRRD, VTK, Raw data

DICOM

DICOM, Analyze, NIFTI, Raw data, Matlab data

Matlab data

DICOM, Raw data

R readable data formats

DICOM, Analyze, NIFTI, NRRD, VTK, Raw data

GUI

Yes

Yes

Yes

No

Yes

No

Yes

Fit exploration

Yes

Yes

Yes

No

Yes

No

Yesb

PACS Support

Yes

Yes

No

No

No

No

Yes

Automatization

Yes

Partiallyc

Yes

Yes

Yes

Yes

Yes

Source

http://mitk.org/wiki/MITK

http://ikrsrv1.medma.uni-heidelberg.de/redmine/projects/ummperfusion

https://github.com/petmri/ROCKETSHIP

https://github.com/davidssmith/DCEMRI.jl

https://sites.google.com/site/plaresmedima/

https://github.com/cran/DATforDCEMRI

https://www.slicer.org/wiki/Documentation/4.8/Modules/PkModeling

  1. aPossibility to extend framework to support other fitting domains
  2. bPossibility to generate a 3D+t image that encode the voxel-wise model signal and to explore the image with the MultiVolumeExplorer
  3. cPossibility to loop over all models and selected tissue ROIs for the loaded Data in the UMMPerfusion user interface
  4. The selection of solutions represents well-known or relative similar solutions compared to our work in order to clarify the differences. The selection does not claim to be exhaustive. Commercial solutions are not included. Further R or Matlab are only included in context of concrete tools (DATforDCEMRI and Rocketship) and not as generic fitting environments on their own. The later would be a categorical error. R as well as Matlab can handle generic fitting problems or allow GUIs but by implementing an application from scratch and not by just using it of the shelf or extending an existing one. The following characteristics are assessed in the table: Operating system; Language (Programming language of the software); License (needed to regard if software is used/extended); Advanced extensibility (Indicates if software was designed to easily be extended with new models without the need to change the basis application or its programming logic; implies a advanced level of abstraction and decoupling); Fitting domain (Indicates which domains are supported for the fitting); Eco-system (indicates if software is embedded into image processing eco-system); Image modalities (medical image modalities that are supported be model and fitting techniques); Models (included pharmacokinetic models); Input / Output (most relevant data formats supported by the software); GUI (indicates if software offers a graphical user interface); Fit exploration (indicates if the software allows to interactively investigate the fit and signal curve per voxel/ROI); PACS Support (indicates if the software allows to use DICOM Q/R or receive data via DICOM Send); Automatization (indicates if the software can be used to automatize the analysis with no user interaction); Source (Link to the source codes or developer’s site)
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BMC Bioinformatics

ISSN: 1471-2105

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