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
Jesse Gonzalez
Lead RSE, eScience Research Engineer
The Netherlands eScience Center
0000-0002-2170-3253
Mail JessePetra 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