32nd MAGNIMS Plenary Meeting and Workshop

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Date(s) - 12/04/2018 - 13/04/2018
All Day

Hotel Arena

32nd Plenary Meeting and Workshop

12-13 April 2018, Amsterdam

-Click here to download workshop and plenary meeting agenda as a pdf document-

12th April 2018

MAGNIMS Plenary Meeting


Welcome and introduction Frederik Barkhof

Report from Steering Committee Mara Rocca, Christian Enzinger

Workshop “Big Data and Deep Learning: New Avenues for MRI in MS?” Hugo Vrenken

MAGNIMS website Report from the Website Committee Jaume Sastre-Garriga


  • 2018 ECTRIMS/MAGNIMS fellowships 2018 (Christian Enzinger)
  • Update on ongoing MAGNIMS/ECTRIMS Fellowships
  • Marcello Moccia: “Improving longitudinal spinal cord atrophy measurements for clinical trials in multiple sclerosis by using the Generalised Boundary Shift Integral (GBSI)”; Home: Napoli; Host: London; MAGNIMS collaborators Milan & Bochum; 10 minutes
  • Soheil Damangir: “Optimizing crowd-sourced solutions to generating large reference datasets for WM lesion segmentation”; Home: Stockholm; Host: Amsterdam; MAGNIMS collaborator Barcelona; 10 minutes

MAGNIMS teaching activities 2018

  • MAGNIMS at ECTRIMS 2018 (Berlin) (Mara Rocca, Olga Ciccarelli)

IMI proposal MAGNIMS study group (FB, CG)

MAGNIMS New projects

  • Comparison of the 2017 and 2010 revisions of the McDonald criteria in patients with CIS suggestive of MS: a multicentre study (Massimo Filippi, Alex Rovira)
  • 2018 Revision MAGNIMS guidelines (Mike Wattjes, Alex Rovira)
  • The role of automated lesion segmentation in CIS: Validation on multi-centre, multi-vendor MAGNIMS cohort at 1.5 and 3T (Frederik Barkhof, Olga Ciccarelli)

Updates on planned and on-going projects

  • 3T versus 1.5 T comparison in CIS. Second reading (Marloes Hagens, Amsterdam)
  • Cortical remyelination in multiple sclerosis: a magnetization transfer ratio multicenter study (Benedetta Bodini, Paris)
  • Non-invasive perfusion patterns in MS phenotypes (Castellaro, Calabrese, Verona)
  • Brain age in MS using machine learning (Raffel, Nicholas, Ciccarelli, London)
  • Structural connectivity in MS phenotypes (Llufriu, HC Barcelona)
  • Predicting CIS conversion from baseline MRI by using PRoNTO (D. Pareto, Barcelona)
  • Study of the visual pathway in patients presenting with a CIS (Vidal-Jordana, Barcelona)
  • Periventricular white matter abnormalities and cortical thinning (Lukas Pirpamer; Christian Enzinger)
  • Proposal on grey Matter Segmentation (Alexandra de Sitter; Hugo Vrenken)
  • Whole-cord and voxel-based assessment of cervical cord atrophy in MS patients with different clinical phenotypes: a multi-centre assessment (Paola Valsasina, Massimo Filippi)
  • Spinal cord atrophy in MS – comparison of different approaches to enhance SC multicentre analysis (Carsten Lukas)
  • Large-scale Assessment of Brain Volume Changes in Healthy Individuals (Marco Battaglini, Nicola De Stefano)
  • MAGNIMS multicenter “central vein” trial (Jens Wuerfel, Nikos Evangelou, Alex Rovira)
  • Are the MRI changes in MS with vascular disease additive or interactive: an age matched study of MS with and without vascular risk factors and vascular controls (Ruth Geraldes / Jackie Palace)

Publication status

Review papers

  • WM lesion disorders: differentiating from MS (Oxford workshop Oct 2015) – Published in NRN
  • MS and cerebellum (Basel Workshop 2014) –Published in Neuroscience & Behavioural Reviews
  • MRI as predictor of treatment response and optimization (Rome, September 2015). Claudio Gasperini. Submitted to Neurology
  • The hippocampus in multiple sclerosis (Milan workshop November 2017) (MR/MF). Submitted to the Lancet Neurology
  • Position paper on atrophy measurements (Amsterdam workshop 2013) – Hugo Vrenken.
  • Brain atrophy in clinical practice 2016 (Barcelona) (JSG)
  • BBB workshop 2016 (Copenhagen) (JF)
  • Structural and functional connectivity (London workshop June 2017). Declan Chard

Project papers

  • Automated WM lesion segmentation methods – NeuGRID (Alexandra de Sitter, Hugo Vrenken) – published in NI.
  • Towards a validation of brain atrophy measures for clinical use in MS (Loredana Storelli, Massimo Filippi). Accepted in Radiology
  • Grey Matter Segmentation Reference and Challenge (Alexandra de Sitter, Hugo Vrenken)
  • Individual prediction of clinically definitive MS in patients presenting with clinically isolated syndrome using machine learning (Viktor Wottschel, Olga Ciccarelli)
  • Event-based model analysis in MS (Arman Eshaghi, Olga Ciccarelli)

Next MAGNIMS meetings:

  • 33rd meeting Autumn 2018 Siena (NDS): 8-9 November 2018. Topic for WS: Harmonization on MRI data in multicenter studies.
  • 34th meeting Spring 2019 Graz (CE): dates TBD


Closure 18.00


13th April 2018

MAGNIMS Workshop


MAGNIMS Workshop: “Big Data and Deep Learning: New Avenues for MRI in MS?”

08.30-13.00 Workshop


8:30      Welcome and Introduction

Frederik Barkhof and Hugo Vrenken


Part 1:                  Data sharing


8:35      Data Sharing: experiences from large projects

Prof. Mark Jenkinson, Nuffield Department of Clinical Neuroscience, University of Oxford


8:55      Segmentation / Development Challenges

Dr. Dzung Pham, Center for Neuroscience and Regenerative Medicine, NIH


9:15      Crowd Sourcing / Citizen Science

Dr. Charles Guttmann, Brigham & Women’s Hospital, Harvard Medical School, and University of Bordeaux


9:35      “Lesion annotations in MS: the Vall d’Hebron – Vicorob experience”

Dr. Deborah Pareto, Vall d’Hebron Hospital, Barcelona


9:55      Break – Serving coffee & tea with traditional Dutch cookies


10:15  “Open Science” versus Patient Privacy: The perspective of a privacy officer

Dr. Michel Paardekooper, Privacy Officer, VU University Medical Center, Amsterdam


10:35  “Open Science” versus Patient Privacy: The perspective of an MS researcher

Alexandra de Sitter, MSc, VU University Medical Center, Amsterdam


10:55  (Really) Big Data sources for MS: experiences from the Italian Neuroimaging Network Initiative and other initiatives

Dr. Mara Rocca, Ospedale San Raffaele, Milan


11:15  General Discussion Part 1


Part 2:                  Machine learning


11:30  Deep Learning and other techniques for general image analysis and interpretation

Dr. Cees Snoek, University of Amsterdam


11:50  Deep Learning and other techniques for medical image analysis and interpretation

Prof. Bram van Ginneken, Radboudumc, Nijmegen


12:10  Machine learning applications in MS brain imaging

Dr. Viktor Wottschel, VU University Medical Center, Amsterdam


12:30  Deep Learning and other techniques for analyzing Big Data

Dr. Jorge Cardoso, UCL, London


12:50  General Discussion Part 2


12:59  Final conclusions and closing of workshop