04 Sep 23. Featured Paper

Link to paper on Wiley Online Library

Authors

Petra J van Houdt, Sudarshan Ragunathan, Michael Berks, Zaki Ahmed, Lucy E Kershaw, Oliver J Gurney-Champion, Sirisha Tadimalla, Jonathan Arvidsson, Yu Sun, Jesper Kallehauge, Ben Dickie, Simon Lévy, Laura Bell, Steven Sourbron, Michael J Thrippleton, on behalf of the ISMRM Perfusion Study Group

Abstract

Purpose

Software has a substantial impact on quantitative perfusion MRI values. The lack of generally accepted implementations, code sharing and transparent testing reduces reproducibility, hindering the use of perfusion MRI in clinical trials. To address these issues, the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI) aimed to establish a community-led, centralized repository for sharing open-source code for processing contrast-based perfusion imaging, incorporating an open-source testing framework.

Methods

A repository was established on the OSIPI GitHub website. Python was chosen as the target software language. Calls for code contributions were made to OSIPI members, the ISMRM Perfusion Study Group), and publicly via OSIPI websites. An automated unit-testing framework was implemented to evaluate the output of code contributions, including visual representation of the results.

Results

The repository hosts 86 implementations of perfusion processing steps contributed by 12 individuals or teams. These cover all core aspects of DCE- and DSC-MRI processing, including multiple implementations of the same functionality. Tests were developed for 52 implementations, covering five analysis steps. For T₁ mapping, signal-to-concentration conversion and population AIF functions, different implementations resulted in near-identical output values. For the five pharmacokinetic models tested (Tofts, extended Tofts-Kety, Patlak, two-compartment exchange, and two-compartment uptake), differences in output parameters were observed between contributions.

Conclusions

The OSIPI DCE-DSC code repository represents a novel community-led model for code sharing and testing. The repository facilitates the re-use of existing code and the benchmarking of new code, promoting enhanced reproducibility in quantitative perfusion imaging.

Keywords

• Perfusion Imaging
• Python
• Open-source code
• Dynamic contrast-enhanced (DCE) MRI
• Dynamic susceptibility-contrast (DSC) MRI