Knee Osteoarthritis Predictive Imaging Consortium
- Dr Eric Lespessailles
Imagerie Multimodale Multiéchelle et Modélisation du Tissu Osseux et articulaire (I3MTO) / University of Orléans - FR
- Prof. Ilse Jonkers
Department of Movement Sciences KU Leuven - BL
- Dr Richard Ljuhar
Danube University Krems - AT
- Dr John Lynch
University of California San Francisco School of Medicine - US
- Dr Simo Saarakkala
University of Oulu Faculty of Medicine - FI
Osteoarthritis (OA) is the most common disorder of the musculoskeletal system and the major cause of reduced mobility among seniors. It is now considered as a disease of the whole joint organ involving the articular cartilage, subchondral bone and synovial membrane but also the menisci and ligaments. However, the underlying mechanisms through which this debilitating disease occurs and progresses have not been fully elucidated yet. Moreover, there is still no medical treatment for this pathology, and the lack of predictive biomarkers is a major obstacle to their development.
The past years have shown many studies based on the computer-aided diagnosis for knee osteoarthritis, and more recently the prediction of the disease progression. Several research teams around the world have proposed their own methods for imaging markers extraction, but yet no clinical tools have emerged for knee osteoarthritis routine evaluation. Also, the development of high-end imaging modalities (high resolution MRI, quantitative µCT, ...) highlighted deep features (anisotropic bone microarchitecture, uncorrelated multiscale changes, ...) that were not systematically transposed to the highly available modalities.
This STUDIUM consortium aims to gathers experts from several imaging areas focused on the knee osteoarthritis in order to provide a synthesis of the good practices to assess OA related imaging biomarkers. A secondary objective is to include clinicians to help explain the underlying mechanisms observed or revealed by machine learning.
The ultimate goal is to melt the data driven predictive models into an actual diagnostic aid tool for clinicians.
Monday 18th November 2019
- 09:30 Arrival of attendees / coffee
- 10:00 Presentation of the progress of each team
- 12:30 Lunch at the restaurant - Au Don Camillo II - 54 Rue Sainte Catherine (Orléans)
- 14:00 - Presentation by I3MTO team of the FNIH database using TBT texture from Orleans
- Presentation by other team of KOPI about FNIH database
- Presentation by I3MTO team of our results of the MOSART cohort with the use of the Oulu MIPT classifier
Tuesday 19th November 2019
- 10:00 Machine learnIng and Multimodal imaging for knee OSteoArthritis prediction (MIMOSA)
- 12:30 Lunch at the restaurant - Le Brin de zinc - Rue Sainte Catherine (Orléans)
- 14:00 Machine learnIng and Multimodal imaging for knee OSteoArthritis prediction (MIMOSA)
- 20:30 Dinner at the restaurant - Le Tonnelier- 5 Rue d'Alsace Lorraine (Orléans)
Wednesday 20th November
- Free time all day long
Thursday 21th November
- 09:30 Work on the review paper on trabecular bone texture analysis on conventional radiograph in knee osteoarthritis
Detailed plan has been written by Eric Lespessailles, to discuss with attendee
- 12:30 Lunch at the restaurant - La Dariole - 25 Rue Etienne Dolet (Orléans)
- 14:00 Presentation of SEKOIA study by Eric Lespessailles
MOSART cohort “Comparative analysis of different analysis techniques of texture including TBS, 2D/3D confrontation” on anatomical bone samples.
Friday 22th November
- 10:00 Work on the review paper
- 12:30 Lunch at the restaurant - Le Lutétia - 2 Rue Jeanne d'Arc (Orléans)
- 14:00 - Work on the review paper
- Roadmap of the consortium
- Identification and selection of the potentially relevant partners which should be included in the project.
- Consortium planning validation.
- Definition of the third and following visit (dates, partners to invite, milestones and deadlines…)