Blood flow and delivery of oxygen and nutrients to tissues, collectively referred to as tissue perfusion, are abnormal in many diseases. Therefore, non-invasive perfusion magnetic resonance imaging (MRI) measurements are a critical imaging biomarker for both diagnosis and treatment monitoring. Despite decades of innovation in image acquisition and implementation by all major MRI vendors, the process of converting images to a single number for clinical decision making is currently hindered by a poor reproducibility and accessibility (only for specialist sites) posing a major barrier to multicenter studies and widespread clinical use. This project – a partnership between the Open Science for Perfusion Imaging (OSIPI; perfusion MRI experts) and eScience (software engineers) – will develop a community-led software package, enabling reproducible, standardized, and straightforward analysis of perfusion MRI data. The tool will greatly reduce the barriers to perfusion MRI via easy data integration, click-and-play analysis, and automated batch processing options.
OSIPY
OSIPI's Open-source PYthon library for perfusion imaging
OSIPY - Perfusion Imaging cover. Image generated with AI assistance (tool: ChatGPT 5.2) and curated by the project team.
Participating organisations
Team
Contact person
Petra van Houdt
BD
Ben Dickie
JP
Jan Petr
LT
Luis Torres
MMÁ
María G. Mora Álvarez
Co-applicant
Children's National Hospital
ST
Sirisha Tadimalla
OG
Oliver Gurney-Champion
Co-applicant
Amsterdam UMC
LV
Lena Václavu
Co-applicant
Leiden University Medical Center