OSIPI · Yuvraajb · Mar 23, 2025 · Mar 31, 2025
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+# Analysis Toolboxes for Perfusion MRI
+
+This page provides an overview of software tools and packages designed for the analysis of contrast-agent based perfusion MRI data.
+
+## Overview
+
+Perfusion MRI analysis toolboxes provide implementations of various algorithms for quantifying perfusion parameters from DCE-MRI and DSC-MRI data. These tools facilitate the conversion of signal intensity time courses into quantitative perfusion metrics using pharmacokinetic models and other quantification approaches.
+
+## Available Analysis Toolboxes
+
+### QIN-PROQC (Quantitative Imaging Network - Perfusion Research Oncology Quality Control)
+
+**Developer**: Quantitative Imaging Network (QIN)  
+**Repository**: [GitHub Repository](https://github.com/DrSidG/QIN-PROQC)  
+**Description**: A MATLAB-based platform for quality control and standardization of DCE-MRI analysis in oncology. It includes implementations of several tracer kinetic models including Tofts, Extended Tofts, and Patlak.
+
+### ROCKETSHIP
+
+**Developer**: Stanford University  
+**Repository**: [GitHub Repository](https://github.com/petmri/ROCKETSHIP)  
+**Description**: A MATLAB-based toolkit for kinetic modeling of DCE-MRI data. It provides a comprehensive workflow from T1 mapping to parametric map generation.
+
+### PkModeling
+
+**Developer**: Quantitative Image Informatics for Cancer Research (QIICR)  
+**Repository**: [GitHub Repository](https://github.com/QIICR/PkModeling)  
+**Description**: A C++ library for pharmacokinetic analysis of DCE-MRI, integrated with 3D Slicer via the PkModeling extension.
+
+### DCE-MRI.jl
+
+**Developer**: Julia MRI community  
+**Repository**: [GitHub Repository](https://github.com/notZaki/DCE-MRI.jl)  
+**Description**: A Julia package for DCE-MRI analysis with implementations of various pharmacokinetic models and AIF estimation methods.
+
+### DCE-Tool
+
+**Developer**: Danish Research Centre for Magnetic Resonance  
+**Website**: [DCE-Tool Website](https://www.drcmr.dk/software)  
+**Description**: A MATLAB-based tool for DCE-MRI analysis with a graphical user interface, supporting multiple pharmacokinetic models.
+
+### DSCoMAN (DSC-MRI Analysis)
+
+**Developer**: Medical College of Wisconsin  
+**Website**: [DSCoMAN Website](https://mcw.edu/departments/biophysics/research/software)  
+**Description**: A software package for the analysis of DSC-MRI data, providing relative and absolute cerebral blood flow, blood volume, and mean transit time maps.
+
+### Perfusion BASIL
+
+**Developer**: FMRIB Centre, University of Oxford  
+**Website**: [BASIL Website](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/BASIL)  
+**Description**: Although primarily designed for arterial spin labeling, BASIL includes tools that can be adapted for contrast-based perfusion analysis.
+
+## Comparison of Key Features
+
+| Toolbox | Platform | Models Supported | GUI | AIF | Open Source |
+|---------|----------|------------------|-----|-----|-------------|
+| QIN-PROQC | MATLAB | Tofts, ETM, Patlak | Yes | Manual, Auto | Yes |
+| ROCKETSHIP | MATLAB | Tofts, ETM, 2CXM | Yes | Manual, Auto | Yes |
+| PkModeling | C++/3D Slicer | Tofts, ETM | Yes | Manual | Yes |
+| DCE-MRI.jl | Julia | Tofts, ETM, 2CXM | No | Manual, Auto | Yes |
+| DCE-Tool | MATLAB | Tofts, ETM, 2CXM | Yes | Manual | Yes |
+| DSCoMAN | MATLAB | SVD, cSVD | Yes | Auto | Yes |
+| BASIL | C++/FSL | Kinetic models | Yes | N/A | Yes |
+
+## How to Select an Analysis Toolbox
+
+Consider the following factors when selecting a toolbox for your perfusion MRI analysis:
+
+1. **Compatibility**: Ensure the toolbox works with your data format and operating system
+2. **Models implemented**: Check if the toolbox includes the pharmacokinetic models you need
+3. **Validation**: Look for toolboxes that have been validated in published literature
+4. **Support and documentation**: Consider the availability of documentation and user support
+5. **Customizability**: Determine if you need to modify or extend the existing analysis methods
+
+## Contributing
+
+If you have developed an analysis toolbox for contrast-agent based perfusion MRI that you would like to add to this list, please see our [contribution guidelines](contributionTutorial.md).
+
+## References
+
+1. Sourbron SP, Buckley DL. Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability. Phys Med Biol. 2012;57(2):R1-33.
+2. Heye AK, et al. Assessment of blood-brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review. NeuroImage Clin. 2014;6:262-74.
+3. Jahng GH, et al. Perfusion magnetic resonance imaging: a comprehensive update on principles and techniques. Korean J Radiol. 2014;15(5):554-77.
diff --git a/docs/SampleDatasets.md b/docs/SampleDatasets.md
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+# Sample Datasets for Perfusion MRI
+
+This page provides links to publicly available contrast-agent based perfusion MRI datasets that can be used for research, development, and validation of analysis methods.
+
+## Overview
+
+Sample datasets are essential resources for:
+- Developing and validating new analysis methods
+- Benchmarking different software tools
+- Reproducing published results
+- Training and education
+- Harmonizing acquisition and analysis protocols across sites
+
+## Available Datasets
+
+### QIN Breast DCE-MRI Dataset
+
+**Provider**: Cancer Imaging Archive (TCIA), Quantitative Imaging Network (QIN)  
+**Access**: [TCIA QIN Breast DCE-MRI](https://wiki.cancerimagingarchive.net/display/Public/QIN+Breast+DCE-MRI)  
+**Description**: Multisite, multivendor breast DCE-MRI data with associated clinical data. Includes pre-treatment and early-treatment images for monitoring response to neoadjuvant chemotherapy.
+
+### RIDER Neuro MRI Dataset
+
+**Provider**: Cancer Imaging Archive (TCIA)  
+**Access**: [TCIA RIDER Neuro MRI](https://wiki.cancerimagingarchive.net/display/Public/RIDER+Neuro+MRI)  
+**Description**: DCE-MRI and DSC-MRI scans of brain tumors with test-retest data for reproducibility assessment.
+
+### SPIE-AAPM-NCI PROSTATEx Challenge
+
+**Provider**: Cancer Imaging Archive (TCIA)  
+**Access**: [PROSTATEx](https://wiki.cancerimagingarchive.net/display/Public/SPIE-AAPM-NCI+PROSTATEx+Challenges)  
+**Description**: Multiparametric MRI of the prostate including DCE-MRI sequences. Includes expert annotations for lesion classification.
+
+### Perfusion Training Dataset
+
+**Provider**: OSIPI Task Force 4.1  
+**Access**: [OSIPI Perfusion Training Dataset](https://github.com/OSIPI/OSIPI_StandardizedDatatsets)  
+**Description**: Standardized DCE-MRI and DSC-MRI datasets with known ground truth values, specifically curated for training and educational purposes.
+
+### DCE MRI Phantom Dataset
+
+**Provider**: National Institute of Standards and Technology (NIST)  
+**Access**: [NIST Quantitative MRI](https://www.nist.gov/programs-projects/quantitative-mri)  
+**Description**: Phantom data for testing and validating DCE-MRI quantification methods with controlled conditions and known T1 values.
+
+### KISSDB (Kantonsspital St. Gallen Brain Dataset)
+
+**Provider**: Kantonsspital St. Gallen, Switzerland  
+**Access**: [KISSDB Website](https://www.kispi.uzh.ch/en/research/downloads)  
+**Description**: DSC-MRI brain perfusion dataset with manual segmentation of stroke lesions and tissue types.
+
+## Dataset Specifications
+
+| Dataset | Modality | Anatomy | # of Subjects | Field Strength | Temporal Resolution | AIF Available |
+|---------|----------|---------|---------------|----------------|---------------------|---------------|
+| QIN Breast | DCE-MRI | Breast | 67 | 1.5T, 3T | Variable | Yes (some) |
+| RIDER Neuro | DCE/DSC | Brain | 19 | 1.5T, 3T | 5-6s | Yes |
+| PROSTATEx | DCE-MRI | Prostate | 204 | 3T | 3.5-5s | No |
+| OSIPI Training | DCE/DSC | Various | 20 | 1.5T, 3T | Variable | Yes |
+| NIST Phantom | DCE-MRI | Phantom | N/A | 1.5T, 3T | Variable | N/A |
+| KISSDB | DSC-MRI | Brain | 151 | 1.5T | 1-2s | Yes |
+
+## How to Use These Datasets
+
+1. **Registration**: Most datasets require user registration and agreement to data use terms
+2. **Download**: Follow the provider's instructions for downloading the data
+3. **Format conversion**: You may need to convert data to formats compatible with your analysis tools
+4. **Documentation**: Review the accompanying documentation for acquisition parameters and other metadata
+5. **Citation**: Always cite the dataset in your publications according to the provider's guidelines
+
+## Contributing
+
+If you have a publicly available perfusion MRI dataset that you would like to add to this list, please see our [contribution guidelines](contributionTutorial.md).
+
+## References
+
+1. Kalpathy-Cramer J, et al. Quantitative Imaging Network: Data Sharing and Competitive Algorithm Validation Leveraging The Cancer Imaging Archive. Transl Oncol. 2014;7(1):147-52.
+2. Shukla-Dave A, et al. Quantitative Imaging Biomarkers Alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials. J Magn Reson Imaging. 2019;49(7):e101-e121.
+3. Huang W, et al. Variations of dynamic contrast-enhanced magnetic resonance imaging in evaluation of breast cancer therapy response: a multicenter data analysis challenge. Transl Oncol. 2014;7(1):153-66.