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p-Brain: A Modular Open-Source Framework for Automated Quantitative DCE-MRI of Cerebral Perfusion, Microvasculature,
Edis D Tireli1,2, Stig P Cramer1, Ulrich Lindberg1
1Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Copenhagen University Hospital, Rigshospitalet, Glostrup, Denmark.
Magnetic Resonance in Medicine
|August 14, 2026
Summary
p-Brain is an open-source framework for automated quantitative dynamic contrast-enhanced MRI (DCE-MRI). This modular system enables reproducible analysis and generates accurate brain maps, validated against established methods.
Area of Science:
- Neuroimaging
- Medical Physics
- Biomedical Engineering
Background:
- Quantitative dynamic contrast-enhanced MRI (DCE-MRI) analysis is crucial for understanding brain physiology.
- Existing workflows can be complex, limiting reproducibility and scalability.
- Automated, modular frameworks are needed to streamline DCE-MRI analysis.
Purpose of the Study:
- To introduce p-Brain, a novel modular, open-source framework for reproducible, automated quantitative DCE-MRI.
- To enable flexible pipeline construction by allowing interchangeable analysis stages.
- To validate the accuracy and reliability of p-Brain against established DCE-MRI analysis workflows.
Main Methods:
- Developed p-Brain as a modular framework with interchangeable stages for DCE-MRI analysis.
- Integrated convolutional neural networks (CNNs) for input function derivation.
- Implemented Patlak graphical analysis and Tikhonov-regularised residue deconvolution for kinetic modeling.
- Ensured auditability through structured metadata and quality control artifacts.
Main Results:
- p-Brain reproduces reference algorithms to machine precision.
- Fully automated pipeline analysis shows high agreement (r > 0.96, ICC > 0.96) with reference methods across five quantitative maps (CBF, CBV, MTT, Ki, vb).
- Validated in 12 healthy controls, demonstrating robust performance.
Conclusions:
- p-Brain provides a reproducible, scalable, and accurate solution for quantitative DCE-MRI analysis.
- Its modular design allows for extensibility and adaptation to diverse research needs.
- The framework facilitates reliable generation of critical brain physiological maps.
