# Neuroimaging data sharing with FLI-IAM

Camille Maumet, Michel Dojat

► To cite this version:

Camille Maumet, Michel Dojat. Neuroimaging data sharing with FLI-IAM. EBRAINS 2024 - First workshop of EBRAINS-France, Oct 2024, Marseille, France. 2024. [hal-04736937](https://hal.inria.fr/04736937v1).

HAL Id: hal-04736937

https://inria.hal.science/hal-04736937v1

Submitted on 15 Oct 2024

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# Neuroimaging data sharing with FLI-IAM

Camille Maumet¹ and Michel Dojat²

1. Inria, Univ Rennes, Inserm, CNRS, IRISA

2. University of Grenoble Alpes, Inserm U1216, Grenoble Institut Neurosciences
# 10 years of brain data sharing...

<figure><img src="image_3.png" /></figure>

Credits: NIDM timeline inspired by BIDS timeline in Fig. 2 in (Poldrack et al, 2024)
# 10 years of brain data sharing...

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

Why sharing neuroimaging data?
# 10 years of brain data sharing...

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

## Why sharing neuroimaging data?

Power of neuroscience studies

<figure><img src="image_8.png" /></figure>

(Button et. al, 2013)

## Small samples and low statistical power

Sample sizes in neuroimaging

<figure><img src="image_9.png" /></figure>

(Poldrack et. al, 2013)

## High rate of **false positives** in the literature
# 10 years of brain data sharing...

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

## Why sharing neuroimaging data?

Power of neuroscience studies

<figure><img src="image_12.png" /></figure>

(Button et. al, 2013)

## Small samples and low statistical power

Sample sizes in neuroimaging

<figure><img src="image_13.png" /></figure>

(Poldrack et. al, 2013)

High rate of **false positives** in the literature

<figure><img src="image_14.png" /></figure>

**Solution:** Data sharing to get to **larger samples**
# Neuroimaging data sharing

Single study
30 sub.

<figure><img src="image_15.png" /></figure>

OpenNEURO

<figure><img src="image_16.png" /></figure>

NEUROVAULT

<figure><img src="image_17.png" /></figure>

NITRC

<figure><img src="image_18.png" /></figure>

OSF
# Neuroimaging data sharing

Single study
30 sub.

<figure><img src="image_19.png" /></figure>

OpenNEURO

<figure><img src="image_20.png" /></figure>

NEUROVAULT

<figure><img src="image_21.png" /></figure>

NITRC

<figure><img src="image_22.png" /></figure>

OSF

Consortium
1000 sub.

<figure><img src="image_23.png" /></figure>

ABIDE

Autism Brain Imaging
Data Exchange

1000 Functional
Connectomes Project

<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /></figure>

CONSORTIUM FOR
RELIABILITY AND
REPRODUCIBILITY

<figure><img src="image_26.png" /></figure>
# Neuroimaging data sharing

Single study
30 sub.

<figure><img src="image_27.png" /></figure>

<figure><img src="image_28.png" /></figure>

NEUROVAULT

<figure><img src="image_29.png" /></figure>

NITRC

<figure><img src="image_30.png" /></figure>

OSF

Consortium
1000 sub.

<figure><img src="image_31.png" /></figure>

ABIDE

Autism Brain Imaging
Data Exchange

1000 Functional
Connectomes Project

<figure><img src="image_32.png" /></figure>

CRR

CONSORTIUM FOR
RELIABILITY AND
REPRODUCIBILITY

<figure><img src="image_33.png" /></figure>

Cohort
100 000 sub.

<figure><img src="image_34.png" /></figure>

HUMAN
Connectome
PROJECT

biobank™
10 years of brain data sharing...

<figure><img src="image_35.png" /></figure>

Why sharing neuroimaging data?

<figure><img src="image_36.png" /></figure>
2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

## Generalizability and fairness

**X-ray: Lung opacity detection**

Model trained on male images, tested on female images

<figure><img src="image_37.png" /></figure>

(Larrazabal et. al, 2020)

## Biased models

## Why sharing neuroimaging data?

<figure><img src="image_38.png" /></figure>
# 10 years of brain data sharing...

<figure><img src="image_39.png" /></figure>

Why sharing neuroimaging data?

<figure><img src="image_40.png" /></figure>

## Generalizability and fairness

**X-ray: Lung opacity detection**

Model trained on male images, tested on female images

<figure><img src="image_41.png" /></figure>

(Larrazabal et. al, 2020)

Biased models

<figure><img src="image_42.png" /></figure>

**Solution:** Decentralized data sharing to get **more diverse samples**
# 10 years of brain data sharing...

<figure><img src="image_43.png" /></figure>

## Generalizability and fairness

<caption>X-ray: Lung opacity detection</caption>

Model trained on male images, tested on female images

<figure><img src="image_44.png" /></figure>

(Larrazabal et. al, 2020)

Biased models

<figure><img src="image_45.png" /></figure>

**Solution:** Decentralized data sharing to get more diverse samples

## Why sharing neuroimaging data?

<figure><img src="image_46.png" /></figure>

<figure><img src="image_47.png" /></figure>

## Web-based application for **medical imaging** storage and

* Share data with a **Data user agreement**

* Open source software

* Shared governance
# On GDPR compliance...

## Are neuroimages anonymous?

<figure><img src="image_48.png" /></figure>

<figure><img src="image_49.png" /></figure>

<figure><img src="image_50.png" /></figure>

<figure><img src="image_51.png" /></figure>

<figure><img src="image_52.png" /><figcaption>Cyril Pernet Stephan Heunis</figcaption></figure>

Copenhagen Uni HospRSrch Ctr Jülich

(Denmark)

(Germany)

(Open Brain Consent, HBM 2021)
# On GDPR compliance...

## Are neuroimages anonymous?

<figure><img src="image_53.png" /></figure>

<figure><img src="image_54.png" /></figure>

DICOM

Digital Imaging and Communications in Medicine

Name: Depont

First : Nathalie

Birth date : 10/11/1995

...

<figure><img src="image_55.png" /></figure>

<figure><img src="image_56.png" /></figure>

<figure><img src="image_57.png" /></figure>

GliMRLab

Cyril Pernet Stephan Heunis

Copenhagen Uni HospRSrch Ctr Jülich

(Denmark) (Germany)

(Open Brain Consent, HBM 2021)
# On GDPR compliance...

## Are neuroimages anonymous?

<figure><img src="image_58.png" /></figure>

<figure><img src="image_59.png" /></figure>

DICOM

Digital Imaging and Communications in Medicine

Name:
First :
Birth date :

...

1. Removing directly identifiable information

<figure><img src="image_60.png" /></figure>

<figure><img src="image_61.png" /></figure>

<figure><img src="image_62.png" /></figure>

GliMR.com

<caption>Cyril Pernet Stephan Heunis</caption>

Copenhagen Uni HospRSrch Ctr Jülich
(Denmark) (Germany)
# On GDPR compliance...

## Are neuroimages anonymous?

<figure><img src="image_63.png" /></figure>

<figure><img src="image_64.png" /></figure>

DICOM

Digital Imaging and Communications in Medicine

Name:
First :
Birth date :

...

1. Removing directly identifiable information

<figure><img src="image_65.png" /></figure>

<figure><img src="image_66.png" /></figure>

<figure><img src="image_67.png" /></figure>

<figure><img src="image_68.png" /></figure>

<figure><img src="image_69.png" /><figcaption>Cyril Pernet Stephan Heunis</figcaption></figure>

Copenhagen Uni HospRSrch Ctr Jülich

(Denmark) (Germany)
# On GDPR compliance...

## Are neuroimages anonymous?

<figure><img src="image_70.png" /></figure>

<figure><img src="image_71.png" /></figure>

DICOM

Digital Imaging and Communications in Medicine

Name:
First :
Birth date :

...

1. Removing directly identifiable information

<figure><img src="image_72.png" /></figure>

2. Defacing

<figure><img src="image_73.png" /></figure>

<figure><img src="image_74.png" /></figure>

<figure><img src="image_75.png" /></figure>

GliMR Lab

<caption>Cyril Pernet Stephan Heunis</caption>

Copenhagen Uni HospRSrch Ctr Jülich

(Denmark) (Germany)
# On GDPR compliance...

## Are neuroimages anonymous?

<figure><img src="image_76.png" /></figure>

<figure><img src="image_77.png" /></figure>

DICOM

Digital Imaging and Communications in Medicine

Name:
First :
Birth date :

...

1. Removing directly identifiable information

<figure><img src="image_78.png" /></figure>

2. Defacing

<figure><img src="image_79.png" /></figure>

<figure><img src="image_80.png" /></figure>

<figure><img src="image_81.png" /></figure>

<figure><img src="image_82.png" /><figcaption>Cyril Pernet
Copenhagen Uni Hosp
Denmark

Stephan Heunis
Ctr Jülich
(Germany)</figcaption></figure>

<figure><img src="image_83.png" /></figure>

Anonymous (USA)
# On GDPR compliance...

## Are neuroimages anonymous?

<figure><img src="image_84.png" /></figure>

<figure><img src="image_85.png" /></figure>

DICOM

Digital Imaging and Communications in Medicine

Name:
First :
Birth date :

1.

Removing directly identifiable information

<figure><img src="image_86.png" /></figure>

2. Defacing

<figure><img src="image_87.png" /></figure>

<figure><img src="image_88.png" /></figure>

<figure><img src="image_89.png" /><figcaption>Cyril Pernet Stephan Heunis
Copenhagen Uni HospRSrch Ctr Jülich
(Denmark) (Germany)</figcaption></figure>

<figure><img src="image_90.png" /></figure>

<figure><img src="image_91.png" /></figure>

Anonymous (USA)

<figure><img src="image_92.png" /></figure>

Not anonymous (EU)

General Data Protection Regulation
(GDPR) → Individualisation
# On GDPR compliance...

## Are neuroimages anonymous?

<figure><img src="image_93.png" /></figure>

DICOM
Digital Imaging and Communications in Medicine

Name:
First :
Birth date :
...

1. Removing directly identifiable information

<figure><img src="image_94.png" /></figure>

2. Defacing

<figure><img src="image_95.png" /></figure>

Anonymous (USA)

<figure><img src="image_96.png" /></figure>

Not anonymous (EU)

General Data Protection Regulation (GDPR) → Individualisation

<figure><img src="image_97.png" /></figure>

<figure><img src="image_98.png" /></figure>

<figure><img src="image_99.png" /></figure>

<figure><img src="image_100.png" /><figcaption>GliMRup
Cyril Pernet
Copenhagen Uni Hosp
Denmark

Stephan Heunis
Ctr Jülich
(Germany)</figcaption></figure>

## Open Brain Consent GDPR edition

### Consent form

Signed by participants

"[...] data might also be used for other future research projects in the field of medical and cognitive neuroscience."

### Data User Agreement

Signed by researchers

"[...] I will not attempt to [...] retrieve the identity of the study participants."

(Open Brain Consent, HBM 2021)

French

<figure><img src="image_101.png" /><figcaption>Anne Hespel
CHU Rennes</figcaption></figure>

<figure><img src="image_102.png" /><figcaption>Elise Bannier
CHU Rennes</figcaption></figure>

**13 languages:** Bosnian, Czech, German, Greek, Spanish, Finnish, French, Italian, Dutch, Norwegian, Portuguese, Turkish
# Towards federated European neuroimaging data sharing?

<figure><img src="image_103.png" /></figure>
<figure><img src="image_104.png" /></figure>

# France Life Imaging

## National Infrastructure for medical imaging in biology and health

Manager: Régine Trébossen

<figure><img src="image_105.png" /></figure>

regine.trebossen@cea.fr

<figure><img src="image_106.png" /></figure>
# France Life Imaging: a coordinated network for in vivo imaging

Network of 9 regional HUBS
covering the main platforms
(160 imaging equiments)

<figure><img src="image_107.png" /></figure>

4 networks of expertise in
scientific domains + 1
education:

WORKPACKAGES

Nombre de

<figure><img src="image_108.png" /></figure>

1 : Molecular imaging agents

2 : Instrumentation & innovative technologies

3 : Interventionnal imaging

4 : Image processing
Training network

A distributed HUB in data
processing: IAM

(Information Analysis &
Management)

<figure><img src="image_109.png" /><figcaption>Scientific managers</figcaption></figure>

<figure><img src="image_110.png" /></figure>

NEW

<figure><img src="image_111.png" /><figcaption>Technical manager</figcaption></figure>

Sharing

<figure><img src="image_112.png" /></figure>
# FLI-IAM: A dedicated infrastructure for ...

* Storage for produced imaging data

- Raw data

- Processed data

- Analysis results

+ Physiological data, eye-tracking, neuropsy test ...

* Image processing pipelines

- to compose & execute

* Valorisation : to Expose & Share

* Renforced needs

- tracing

- machine learning

- open data

<figure><img src="image_113.png" /></figure>

FLi
France Life Imaging

<figure><img src="image_114.png" /></figure>

32% Clinical studies

<figure><img src="image_115.png" /></figure>

63% Preclinical studies

<figure><img src="image_116.png" /></figure>
# Cloud-based Architecture

<figure><img src="image_117.png" /></figure>
shanoir

- Developped since 2003

- Store & Share pseudo-anonymized data

- Use a specific ontology (Ontoneurolog)

- DUA associated to each study

- Dicom, nifti, bids

- Used in various large multicentre projects

<figure><img src="image_118.png" /></figure>

<figure><img src="image_119.png" /></figure>

For clinical and preclinical imaging data
Virtual Imaging Platform (VIP)

https://vip.creatis.insa-lyon.fr

<figure><img src="image_120.png" /><figcaption>Sorina Pop</figcaption></figure>

<figure><img src="image_121.png" /></figure>
# OBJECTIVES-I

* **Visibility**

- to **Provide** a web portal to **FIND and ACCESS** data & processing tools

* **Diffusion**

- to **Facilitate** compliance to ethical & law rules for data **REUSE & SHARING** ("as open as possible, as restricted as necessary")

- to **Provide** a data management plan (ISO)

- to **Renforce** databases **INTER-OPERABILITY** (FBI, genetics, ...)

* **Valorisation**

- Referencing data and imaging processing tools (DOI)

* **Scientific motivations**

- Challenges organisation (validation, performances, ...)

- Multicenter studies (Statistical robustness, reproducibility, ...)

- 3R policy (Reduce, Raffine, Replace)

<figure><img src="image_122.png" /></figure>
OBJECTIVES-II

* To be a national and european actor for the management of *digital commons*: imaging *in vivo* (FAIR) data

<figure><img src="image_123.png" /></figure>

<figure><img src="image_124.png" /></figure>

OFSEP

<figure><img src="image_125.png" /></figure>

Commowick, O. et al. Nature Scientific Reports, 2018

<figure><img src="image_126.png" /></figure>

**Challenges**
**organisation**

**Integrated to**
**clinical**
**digital**
**environnement**

French national medical

registers

<figure><img src="image_127.png" /></figure>

Genomics

<figure><img src="image_128.png" /></figure>

<figure><img src="image_129.png" /></figure>

INSTITUT FRANÇAIS DE BIONFORMATIQUE

<figure><img src="image_130.png" /></figure>

GOUVERNEMENT

Liberté
Égalité
Fédéralisme

Stratégie
nationale pour
l'intelligence
artificielle

<figure><img src="image_131.png" /></figure>

shanoisrisa.fr

<figure><img src="image_132.png" /></figure>

<figure><img src="image_133.png" /></figure>

Link to
Imagerie in vivo

FRAN (H. Desal CHU Nantes)

<figure><img src="image_134.png" /></figure>

AGENCE
DU NUMÉRIQUE
EN SANTE

SANTÉ NUMÉRIQUE

PROGRAMME DE RECHERCHE

<figure><img src="image_135.png" /></figure>

ECAN

<figure><img src="image_136.png" /></figure>

PRIMUS

**Clinical research**
**partner**
Shared data

shaneir

SHAring IN vivO Imaging Resources

3 public studies

**MSSEG-2** | MS new lesions segmentation challenge of MICCAI 2021

START DATE : 2021-03-01 | END DATE : 2025-02-28
ID : 208 | STATUS : In Progress
EXAMINATIONS : 0 | SUBJECTS : 0

100 subjects MRI brain images NiftI Multiple sclerosis

Request an Access

**MSSEG 2016** | MS lesions segmentation challenge of MICCAI 2016

START DATE : 2021-03-01 | END DATE : 2025-02-28
ID : 209 | STATUS : In Progress
EXAMINATIONS : 0 | SUBJECTS : 0

60 subjects MRI brain images NiftI Multiple sclerosis

Request an Access

**MS-Multi-Spine** | MS lesion segmentation challenge on spinal cord

ID : 259 | STATUS : In Progress
EXAMINATIONS : 0 | SUBJECTS : 0

Spinal cord Multiple sclerosis (MS) Lesion segmentation 200 subjects Request an Access

Data User Agreement

Signed by researchers

"[...] I will not attempt to [...] retrieve the identity of the study participants."

<figure><img src="image_137.png" /></figure>

<figure><img src="image_138.png" /></figure>

3- Access the data

2- Sign the Data User Agreement
A research infrastructure
service for brain research?

<figure><img src="image_139.png" /></figure>

EBRAINS

<figure><img src="image_140.png" /></figure>

FLi

<figure><img src="image_141.png" /></figure>

Destination INFRASERV: Research infrastructures services to support health research, accelerate the green transition and the digital transformation, and advance frontier knowledge

**Objective:**

* To provide access to broad portfolios of installations and scientific services relevant for a large research domain or in support of societal challenge and EU priorities

**Expected impact:**

* Effective access of European researchers to the best research infrastructure services from national and pan-European research infrastructures

* Improved research infrastructure services to address evolving scientific and societal challenges

* Further opening of national research infrastructures and strengthened access programmes of pan-European research infrastructures in the longer term

* Improved transnational access to new users

<table><thead><tr><td>Topic ID</td><td>Topic title</td><td>Type of Action</td><td>Expected number of GAs</td><td>Expected EU contribution per GA M€</td><td>Budget M€</td></tr></thead><tbody><tr><td>HORIZON-INFRA-2025-01-SERV-01</td><td>Research infrastructure services to enable R&I addressing main challenges and EU priorities related to the health domain</td><td>RIA</td><td>4</td><td>5-12</td><td>37.0</td></tr></tbody></table>
# Destination INFRASERV: Proposed topics (1)

**Research infrastructure services to enable R&I addressing main challenges and EU priorities related to the health domain**

1. Support research and development of medical countermeasures for epidemic response;

2. Improve clinical research in the paediatric area;

3. Enable research linking environmental factors to human health;

4. Access to novel radionuclides and facilities

**Research infrastructure services to enable R&I addressing main challenges and EU priorities**

1. For advanced biotechnology and biomanufacturing;

2. To improve the understanding and prediction of future climate changes and their impact.

Note: (both challenge-driven topics) less limited about improving & developing new services, including, when duly justified, if they cannot be offered by the end of the action.
# Destination INFRASERV: Proposed topics (1)

## Research infrastructure services to enable R&I addressing main challenges and EU priorities related to the health domain

1. Support research and development of medical countermeasures for epidemic response;

2. Improve clinical research in the paediatric area;

3. Enable research linking environmental factors to human health;

4. Access to novel radionuclides and facilities

## Research infrastructure services to enable R&I addressing main challenges and EU priorities

1. For advanced biotechnology and biomanufacturing;

2. To improve the understanding and prediction of future climate changes and their impact.

Note: (both challenge-driven topics) less limited about improving & developing new services, including, when duly justified, if they cannot be offered by the end of the action.

To add: Improve clinical research in the neurodegenerative and psychiatric areas
<figure><img src="image_142.png" /></figure>

# Neuroimaging data sharing with FLI-IAM

Camille Maumet and Michel Dojat

Shanoir core development is supported by: **Shanoir Consortium**
**(InriaSoft) and FLI-IAM**

<figure><img src="image_143.png" /></figure>

RÉPUBLIQUE
FRANÇAISE

Liberté
Egalité
Fraternité

Inria

<figure><img src="image_144.png" /></figure>