Ctrl K

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.

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.

Participating organisations

Netherlands eScience Center
Netherlands Cancer Institute (NKI)

Team

Petra van Houdt
Petra van Houdt
Lead applicant
The Netherlands Cancer Institute
Jesse Gonzalez
Lead RSE, eScience Research Engineer
The Netherlands eScience Center
Djura Smits
eScience Research Software Engineer
eScience Center
Peter Kalverla
Program Officer
The Netherlands eScience Center
BD
Ben Dickie
Senior Lecturer
The University of Manchester
JP
Jan Petr
Co-Applicant
Helmholtz-Zentrum Dresden Rossendorf
LT
Luis Torres
MMÁ
María G. Mora Álvarez
Co-applicant
Children's National Hospital
ST
Sirisha Tadimalla
Co-applicant
The University of Sydney
OG
Oliver Gurney-Champion
Co-applicant
Amsterdam UMC
LV
Lena Václavu
Co-applicant
Leiden University Medical Center