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11 changes: 6 additions & 5 deletions docs/tf/tf6-2.md
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Expand Up @@ -4,15 +4,16 @@ Task Force 6.2 compares quantification pipelines for DSC/DCE-MRI in clinical app

The aim of this task force is to compare quantification pipelines for DSC/DCE-MRI in clinical applications. Through these challenges, the performance of DSC-/DCE-MRI perfusion analysis tools developed in-house by participating groups, or the available software packages, are tested and evaluated according to technical performance metrics (e.g. bias and precision on DROs, agreement with reference methods in-vivo, reproducibility on in-vivo data, processing time). The aim is to establish a set of benchmarks for perfusion imaging in different applications.

The first challenge by this task force focused on benchmarking DCE software. As the use of artificial intelligence grows, the second challenge focuses on deep learning techniques. The goal is to encourage researchers to put their quantitative methods to the test, to stimulate collaboration, and to chart the heterogeneity of DCE analysis software. In this challenge, participants use deep learning techniques to estimate perfusion parameters in DCE-MRI of the uterus. The task force provides repeated in vivo data to assess the algorithm's precision, and simulated DCE-data to test the accuracy.
The first challenge by this task force focused on benchmarking DCE software in the context of brain tumour. For 2026 - 2027, the challenge will aim to benchmark softwares for the measurement of very low-level contrast agent leakage using DCE-MRI, such that might be expected in normal appearing brain tissue.


!!! abstract "First DCE challenge"
This repository contains all the documentation and datasets provided for the first ISMRM-OSIPI DCE Challenge.

[📘 Go to the first challenge](https://osf.io/u7a6f/)

!!! abstract "Second DCE challenge"
Work-in-progress: topic will be deep learning for DCE analysis. Coming soon.
Work-in-progress: topic will be measuring low-level contrast agent leakage with DCE-MRI. Coming soon.

## Leads

Expand All @@ -25,11 +26,11 @@ The first challenge by this task force focused on benchmarking DCE software. As

## Ongoing projects

The clinical data for this challenge were previously used for studying endometrial hypoxia and kindly shared for this challenge. The dataset includes the MR images of the uterus of 12 healthy female volunteers with regular menstrual cycles. Each volunteer was scanned twice: during days 1–3 of menstruation and the early/mid-secretory phase of their cycle. The two relevant MRI sequences for this challenge are DCE-MRI and IR-TrueFISP.
The use of DCE-MRI to assess very subtle blood-brain barrier leakage in aging and neurological disease is increasingly popular, however the translation from unstandardised measurements used exclusively in specific research settings, to robust biomarkers for use in large multi-centre studies, clinical trials, and clinical practise, is impeded by numerous technical challenges. Low levels of contrast agent leakage result in data with very low signal-to-noise; measurement accuracy is impeded by signal drift over long scans; effect sizes are small, and with high noise levels it can be challenging to adequately power studies. The aim of the second OSIPI DCE-MRI Challenge 2026 - 2027 will be to benchmark data analysis softwares for the estimation of low level BBB leakage from DCE-MRI data. Challengers will be asked to estimate K<sup>trans</sup> in simulated and clinical data test-retest data, to assess the accuracy, precision, and reproducibility of challenge submissions, and to identify sources of uncertainty within these pipelines.

The task force is currently working on the design of the morphological phantom. This numeric phantom will be generated by assuming a series of perfusion parameters, T1 values, and a population-based Arterial Input Function (AIF). A two-compartment exchange model and the spoiled gradient-echo steady-state signal model will be used to create the voxel-wise signal. The assumed T1 values for blood and tissue will be provided to convert the signal to concentration.
The task force is currently working on the design of the simulated dataset, as well as collecting test-retest data in a small group of adults aged 50+ with at least one vascular risk factor, where measurements of subtle BBB dysfunction are of particular interest and are very challenging to measure.

More details are available in the [two-year roadmap](https://docs.google.com/document/d/1FzOFMV420xew2oiSDq4Wi3tRZ45if73Rw-6at2hKNFw/edit#heading=h.m4pavixh6vsi).
More details are available in the [two-year roadmap](https://docs.google.com/document/d/1w2JlVK3hP5dgXMcrK8da5z94ivsK8Or__NU9qUR6WRk/edit?tab=t.0#heading=h.glos1jjtg2kf).

## Publications

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