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Purpose: The 2019 edition of the data challenge was organized by the French Society of Radiology (SFR) during the Journées Francophones de Radiologie with the aim to: (i) work on relevant problematics of public health (ii) build large multicentric and prospective databases and (iii) boost the French AI community around radiologists. In comparison to the 2018 edition a first objective was to increase the question's complexity by including 3D information and prognostic analysis. The second objective was to improve the database quality and quantity with more balance among classes and data from at least 1000 examinations per question. Material and method: Relevant clinical questions were proposed by organ societies of the SFR. Their feasibility was assessed by experts in the field of AI. A dedicated platform was set up for inclusion centers to safely upload their anonymized examinations in compliance with European regulation. The quality of the database was checked by experts weekly with annotations performed by radiologists. Multidisciplinary teams competed between September 11 th and November 13 th 2019. Results: Three questions were selected using different imaging and evaluation modalities, including: pulmonary nodule detection and classification from 3D CT, prediction of expanded disability status scale in multiple sclerosis using 3D MRIs and segmentation of muscular surface for sarcopenia estimation from 2D CT. A total of 4347 examinations were gathered of which only 6% were excluded. Three independent databases from 24 individual centers were created. A total of 143 participants was split into 20 multidisciplinary teams. Conclusion: Three data challenges with over 1200 GDPR compliant, multicentric, 2D/3D CT and MRI databases were organized for 20 multidisciplinary teams.

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