ROCKETSHIP

ROCKETSHIP performs quantitative analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data to enable concurrent evaluation of multiple kinetic models and parameters.

Key Features:

• Multiple Kinetic Models: Supports fitting and comparison of multiple DCE-MRI kinetic models to extract pharmacokinetic parameters.
• Data-driven Nested Model Analysis: Implements nested model selection to evaluate model complexity and parameter relevance in a data-driven manner.
• MATLAB implementation: Implemented in the MATLAB programming language for algorithm execution and model fitting.
• Validation with Simulated Data: Performance and robustness assessed using simulated DCE-MRI datasets to evaluate fitting reliability.
• Preclinical and Clinical Applicability: Applied to human brain DCE-MRI and a murine tumor model for cross-scale analysis.

Scientific Applications:

• Pathology Characterization: Extraction of kinetic parameters for tissue pathology characterization from DCE-MRI.
• Treatment Response Assessment: Quantitative evaluation of treatment-induced changes in DCE-MRI kinetics.
• Oncology Research: Analysis of tumor perfusion and permeability in preclinical and clinical tumor studies.
• Neurology Research: Application to human brain DCE-MRI studies for neurological investigation.

Methodology:

Implemented in MATLAB; performs concurrent fitting of multiple kinetic models including data-driven nested model analysis and validated using simulated data, with applications demonstrated on human brain DCE-MRI and a murine tumor model.