Presentation on Sharing images: The why and how of medical imaging analysis research for the Health-RI infrastructure for the Health-RI FAIR data stewards basics course in Utrecht, on 3 July  202

Bron, Esther

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Sharing images:The why and how of medicalimaging analysis researchDr. Esther BronDept. Radiology & Nuclear MedicineErasmus MC, Rotterdam/NLImaging Data CoordinatorHealth-RI Architecture Teame.bron@erasmusmc.nl  Data stewards course  - Health-RILearning objectives• Insight into research with medical images• Understanding how machine learning is crucial in medical imaging research• Understanding the need for data sharing in image analysis research• Understanding how Health-RI and data stewards can play an important role hereArtificial intelligence(Supervised) machine learningTraining data:Input Output1.            →2.            →::::N.           →Alzheimer’s diseaseVascular cognitive impairmentDementia with Lewy bodiesFrontotemporal dementiaWorld Alzheimer Report 2021; Prince et al., 2011Etiological diagnosisKey challengeClinical criteria fail in early stageWitte stofGrijze stofHers nenMRIMRIGezond (man, 64 jaar) Ziekte van Alzheimer (man, 64 jaar)Imaging biomarkersBrain volumes Voxel-wise information Perfusion MRI (ASL, Qflow)WM microstructure (DTI) fMRI Other (microbleeds, infarcts)200 123 199 133 65 50101 156 144 55 125 70188 171 33 72 40 189102 102 44 56 80 60150 131 30 91 195 155160 171 165 189 173 60• Very successful in Alzheimer’s disease research (Bron et al., 2015; 2021)AI advances dementia diagnosisDementia yes/noClinical dataImaging dataEtiologicaldiagnosisNeed for data• Machine learning methods learn from large datasets• Availability of multi-center clinical data for research is limited• Single hospitals only have few cases of rare dementia subtypes• Machine learning methods should learn from diverse datasets• Different populations• Variation in MRI scanners, variation in MRI sequence• We need: more collaboration and reuse of data!National Health-RI portal12Search & find data | request & obtain | test & returnGoal Imaging: Make image data available to portal• What: Make metadata and data of medical images available • How: Together with representative of Health-RI nodes• Imaging Working group (since October 2022)- Collaborate step-by-step towards this goal- Architecture and design for making imaging data available- Actual implementation in the regions, starting with own organization- Lead: Esther Bron• Imaging Community (since 2018)- Wider perspective, get feedback, seminars on imaging data infrastructure- Lead: Stefan KleinImaging werkgroep• Werkgroep bestaat uit representanten van regionale knooppunten- AUMC: Paul Groot and tactical lead Ronald van Schijndel- UMCU: Wouter Veldhuis, Rudy van der Lek (and lead architect Ruud Bongers)- Radboudumc: Colin Jacobs- LUMC: Michele Huijberts, Marius Staring- UMCG: Eduard Boer, Martijn Veening- Erasmus MC: Esther Bron, Stefan Klein, Hakim Achterberg- MUMC+: t.b.d. (lead architect Igor Schoonbrood / tactical lead Pascal Suppers)- e/MTIC: t.b.d. and tactical lead Toine Kuiper• Deelnemers zijn verantwoordelijk voor- Architectuur en ontwerp voor het beschikbaar maken van beelddata- Daadwerkelijke implementatie daarvan in hun eigen regio, te beginnen met eigen organisatieXNAT● Platform for storage, sharing, and management of medical imaging data● XNAT software is open-source (www.xnat.org), active community ● National & European platform for medical imaging data management and sharing● Most UMCs have their own XNAT as well● Imposes structure: project / subject / experiment / scan● Access control:○ public / restricted / private projects○ owner / member / collaborator user roleshttps://xnat.bmia.nlTake home message• AI / machine learning is main workhorse in medical image analysis nowadays• Data sharing essential to develop medical imaging analysis methods that will benefit clinicians and patients• AI in medical imaging is more than just data science: • Close collaboration with clinicians is crucial to make sure we solve meaningful problems• Each UMC has expertise on working with imaging data (Imaging WG)• Connect to local expertise (e.g. at Radiology Imaging Trialbureau)• Local imaging research databases (XNAT, grand-challenge.org)Sharing imagesEsther BronDept. Radiology & Nuclear MedicineErasmus MC, Rotterdam/NLe.bron@erasmusmc.nlwww.estherbron.com @esther_bron

Sharing images: The why and how of medical imaging analysis research

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Sharing images: The why and how of medical imaging analysis research

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