About the project
In RACOON FADEN, a controlled clinical trial is being conducted to explore validated radiological features after MRI examination for Early detection of Adenomyosis in young patients, to make the outcome data accessible and to establish an infrastructure for extracting uterine imaging biomarkers in the NUM for scalable use.
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Our aim is to compare systematically collected data after MRI examinations during menstruation and ovulation of patients with clinically suspected adenomyosis and asymptomatic volunteers in a case-control study. The imaging biomarkers are automatically extracted by Artificial Intelligence and the image data is compared with the RACOON infrastructure in an iterative process. The correlation of the various quantitative results with disease-determining clinical symptoms can identify new critical features for the Early detection of Adenomyosis. The imaging biomarkers are automatically recognised by Artificial Intelligence and the image data is compared with the RACOON infrastructure in a repeated learning process. This harbours great potential to enable affected patients to receive early, rapid and targeted treatment in the future.
In RACOON FADEN, a controlled clinical study is being conducted to explore validated radiological features after MRI examinations for the Early detection of Adenomyosis in young patients, to make the outcome data accessible and to establish an infrastructure for the extraction of uterine imaging biomarkers in the NUM for scalable use.
Artificial Intelligence is used to extract important information from medical images. The images are compared and enhanced multiple times. This process runs automatically and utilises the RACOON infrastructure.
The correlation of the various quantitative results with disease-determining clinical symptoms can identify new critical features for the Early detection of Adenomyosis.
The clinical data will be organised via NUKLEUS and the image data with their results via RACOON. Follow-up projects should then be able to incorporate image analysis using AI into study concepts and transfer the results data to NUKLEUS ("extraction pipeline").
By integrating the new quantitative imaging biomarkers into the NUM NUKLEUS, we can transfer the scientific and infrastructural results of the FADEN study to other partners in the consortium. The consortium consists of 13 certified clinical centres for endometriosis. Prof. Dr Sylvia Mechsner at the Charité is responsible for gynaecological coordination, while Prof. Dr Matthias May at the UKEr is in charge of radiological coordination. Prospective enrolment of patients will take place via the NUKLEUS infrastructure. The study design was evaluated by the Epidemiological Core Unit (ECU), ethical support is provided by the Ethics Coordination (EC), consent management, pseudonym management and administration of identifying data is carried out by the Trustee Office (THS), clinical data is recorded using the NUKLEUS Clinical Data Management (CDM) systems, and billing is carried out via the NUKLEUS Interaction Core Unit (ICU).
RACOON has successfully set up a hardware and software infrastructure with network nodes at all German university hospitals. The infrastructure architecture consists of a combination of these decentralised components and a secure central environment (RACOON-CENTRAL) to create a powerful overall infrastructure. Research projects can benefit from fast and secure commissioning and seamless scalability across multiple locations. RACOON CENTRAL also includes the functionalities of the decentralised instances, such as structured reporting, image annotation and segmentation, training or inference of Artificial Intelligence (AI) as well as central monitoring of the individual RACOON nodes. These components form a trustworthy, cross-partner research environment whose functionality is constantly being expanded both through generic method packages and through specific workflows and methods that are developed and introduced as part of RACOON research applications. As all applicable requirements (medical device class IIb) are met, routine clinical use for image diagnosis and analysis, including cross-site counselling support, is possible.