DELIVERABLE 7 - vph-dare.euIT D7.3 1v0 Final.pdf · DELIVERABLE 7.3 First Prototype of VPH-DARE@IT...

DELIVERABLE 7.3

First Prototype of VPH-DARE@IT Research Platform

Grant agreement no.: 601055 (FP7-ICT-2011-9)

Project acronym: VPH-DARE@IT

Project title: Dementia Research Enabled by IT

Funding Scheme: Collaborative Project

Project co-ordinator: Prof. Alejandro Frangi, University of Sheffield

Tel.: +44 114 22 20153

Fax: +44 114 22 27890

E-mail: [email protected]

Project web site address: www.vph-dare.eu

Due date of deliverable Month 24

Actual submission date Month 25

Start date of project April 1st 2013

Project duration 48 months

Work Package & Task WP 7, Task 7.2, 7.3, 7.4, 7.5

Lead beneficiary USFD

Editor PMO

Author(s) Alberto Biancardi Juan Arenas

Quality reviewer Felix Winter, Timo Urhema

Project co-funded by the European Union within the Seventh Framework Programme

Dissemination level

PU Public X

PP Restricted to other programme participants (including Commission Services)

RE Restricted to a group specific by the consortium (including Commission

Services)

CO Confidential, only for members of the consortium (including Commission

Services)

mailto:[email protected]

http://www.vph-dare.eu/

FP7-601055: VPH-DARE@IT D7.3 – First Prototype of VPH-DARE@IT Research Platform 14/04/2015

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Issue Record

Version no. Date Author(s) Reason for modification Status

0.4 20/03/15 Juan Arenas,

Alberto Biancardi

Initial release Initial Draft

0.8 31/03/15 Alberto Biancardi Addressing feedback of

internal reviewers,

additional updates

Final

1.0 14/04/15 PMO Final Check Finalised

Copyright Notice

Copyright © 2013 VPH-DARE@IT Consortium Partners. All rights reserved. VPH-

DARE@IT is an FP7 Project supported by the European Union under grant agreement no.

601055. For more information on the project, its partners, and contributors please see

http://www.vph-dare.eu. You are permitted to copy and distribute verbatim copies of this

document, containing this copyright notice, but modifying this document is not allowed. All

contents are reserved by default and may not be disclosed to third parties without the prior

written consent of the VPH-DARE@IT consortium, except as mandated by the grant agreement

with the European Commission, for reviewing and dissemination purposes. All trademarks and

other rights on third party products mentioned in this document are acknowledged and owned

by the respective holders. The information contained in this document represents the views of

VPH-DARE@IT members as of the date of its publication and should not be taken as

representing the view of the European Commission. The VPH-DARE@IT consortium does not

guarantee that any information contained herein is error-free, or up to date, nor makes

warranties, express, implied, or statutory, by publishing this document.

Author(s) for Correspondence

Juan Arenas

T: +44 114 222 9736; E: [email protected]; W: www.cistib.org

Alberto Biancardi

T: +44 114 222 9736; E: [email protected]; W: www.cistib.org

http://www.vph-dare.eu/

http://www.cistib.org/

http://www.cistib.org/


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Table of Contents

1. INTRODUCTION ......................................................................................................................... 6

2. FIRST REALISATION OF THE VPH-DARE@IT RESEARCH PLATFORM .................... 7

2.1. GETTING ACCESS TO THE RESEARCH PLATFORM .................................................................... 7 2.2. DISCOVERING THE RESEARCH PLATFORM ............................................................................... 8 2.3. ACCESS TO DATASETS & COHORTS ......................................................................................... 9 2.4. ACCESS TO APPLICATIONS ..................................................................................................... 11 2.5. WORKFLOWS ......................................................................................................................... 13 2.6. INTERACTION BETWEEN THE CLINICAL AND RESEARCH PLATFORM ..................................... 15

3. CLINICAL USE CASES IMPLEMENTATION ...................................................................... 16

3.1. CONCEPTUAL APPROACH ....................................................................................................... 16 3.2. LARGE COHORT STUDIES PATTERN ....................................................................................... 16 3.3. CLINICAL USE CASE IMPLEMENTATION ................................................................................. 18

3.3.1. Exemplar 1: Integration of structural, functional, and cognitive based features of MCI

classification (USFD) .................................................................................................................... 18 3.3.2. Exemplar 2: Classification power of hippocampal subfield volumes to differentiate

early stage Alzheimer’s disease from early stage frontotemporal dementia (UEF) ...................... 19 3.3.3. Exemplar 3: Quantitative metrics of diffusion image quality (UCL-SO) ..................... 20 3.3.4. Exemplar 4: Comparison of biomarker methods across a large cohort (EMC) .......... 21

3.4. RESEARCH PLATFORM CAPABILITIES HIGHLIGHTED THROUGH THE EXEMPLARY CASES ........ 21

4. RESEARCH PLATFORM COMPONENTS ............................................................................ 22

5. CONCLUSIONS .......................................................................................................................... 23

6. LIST OF KEY WORDS/ABBREVIATIONS ............................................................................ 23


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Table of Figures

Figure 1: VDRP Home Page (Before User Authentication) ..................................................... 8 Figure 2: VDRP Home Page (After User Authentication) ....................................................... 8 Figure 3: VDRP Resource Discovery Page .............................................................................. 9 Figure 4: VDRP Dataset Resource Page .................................................................................. 9 Figure 5: VDRP Dataset Query. Output Field Selection ........................................................ 10 Figure 6: VDRP Dataset Query. Inclusion Criteria ................................................................ 10 Figure 7: VDRP Dataset Query. Subset Browsing and Export Format Selection .................. 11 Figure 8: VDRP Datasets. Application List ........................................................................... 12 Figure 9: VDRP Application. Resource Page ......................................................................... 12 Figure 10: VDRP Application. Additional Information ......................................................... 13 Figure 11: VDRP Search. Workflows .................................................................................... 13 Figure 12: VDRP Workflows Resource Page ........................................................................ 14 Figure 13: VDRP Workflows. Execution Configuration ....................................................... 14 Figure 14: VDRP Workflows. Execution Progress ................................................................ 15 Figure 15: VDRP Context. Conceptual Diagram ................................................................... 16 Figure 16: Large Cohorts Studies Pattern ............................................................................... 17 Figure 17: Dataset/Cohort Extraction Pattern ......................................................................... 17 Figure 18: Exemplar 1.Worflow Definition ........................................................................... 18 Figure 19: Exemplar 2.Worflow Definition ........................................................................... 19 Figure 20: Exemplar 3.Worflow Definition ........................................................................... 20 Figure 21: Exemplar 4.Worflow Definition ........................................................................... 21

Table of Tables Table 1: VDRP Components. ................................................................................................. 23


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EXECUTIVE SUMMARY

The “Virtual Physiological Human: DementiA Research Enabled by IT” (VPH-DARE@IT)

project aims to provide a systematic, multifactorial and multiscale modelling approach to

enable improved diagnoses and prognoses of dementias. Its peculiar approach foresees a strict

interplay between two complementary approaches to disease investigation: a

phenomenological approach, where population-wide information is sieved to discover

statistical associations or anomalies, and a mechanistic approach, where virtual physiological

human simulations aim at supplying patient-specific insight into the disease and views of the

possible clinical evolutions for further investigation. The ultimate goal of the research

platform, by the end of the project, is to support both approaches in their implementation by a

user friendly interface that collects a number of components relevant to the dementia domain

(Tools, Model, Biomarker, Datasets) into a single coherent system in order to facilitate the

generation and execution of new studies that will be answering clinical questions.

After presenting at the last year review a first static mock-up of the research platform and

making it known and accessible, work has proceeded towards milestone M72 “Preliminary and

limited software version released and distributed to application partners for evaluation.”

Progress has developed on two fronts: on the one hand the research platform has started being

populated with domain specific datasets (selected retrospective cohorts), computational steps

(e.g., image-processing pipelines), workflows, and tools that are the initial components for the

integrative and extensible software environment; on the other hand collaboration with

VPH-Share (FP7-ICT-269978) has brought significant enhancements to the infrastructure.

The current version provides a workable environment that represents a good starting point for

more concrete applications and, in fact, it was decided at the Project Board level to work

towards a more ambitious goal to demonstrate the platform capabilities to answer clinical

questions in the dementia area; although this is a high risk task for a not yet fully developed

platform, it was reckoned that those additional use cases that need to be supported and taken

into consideration if the platform has to deliver any real value. Although it is not mature enough

product, the platform is well advanced thanks to the collaboration between different work

packages, partners, and projects and it is becoming ready to face the challenges of the coming

years where we expect additional and more complex VPH workflows to be deployed, hopefully

stimulating a new generation of studies to be carried out.


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1. INTRODUCTION

The “Virtual Physiological Human: DementiA Research Enabled by IT” (VPH-DARE@IT)

project aims to provide a systematic, multifactorial and multiscale modelling approach to enable

improved diagnoses and prognoses of dementias. Its peculiar approach foresees a strict

interplay between two complementary approaches to disease investigation: a phenomenological

approach, where population-wide information is sieved to discover statistical associations or

anomalies, and a mechanistic approach, where virtual physiological human (VPH) simulations

aim at supplying patient-specific insight into the disease and views of the possible clinical

evolutions for further investigation. The ultimate goal of the research platform is to support

both approaches in their implementation by a user friendly interface that collects a number of

components relevant to the dementia domain (Tools, Model, Biomarker, Datasets) into a single

coherent system in order to facilitate the generation and execution of new studies that will be

answering clinical questions.

At the last year review a first static mock-up of the research platform was presented; this

mock-up was also made accessible through the VPH-DARE site and presented in different

project meetings and in a webinar conducted to introduce the mock-up to all partners. An

updated version of that mock-up is also part of D7.2 “Use cases identification and workflows

definition for WP7,” together with the actual definition of the use cases for the VPH-DARE@IT

Research platform (VDRP). All these actions have brought valuable feedback into the first

realisation of the VDRP; the development activities have also benefited from the close contact

with the use case definition process, enabling us to anticipate the outcomes of the use cases

deliverable and take them into account for the development of this first release. Although the

initial release is intended to be a “Preliminary and limited software version released and

distributed to application partners for evaluation” as established in milestone M72, we believe

the current version provides a workable environment that represents a good starting point for

more concrete applications. In fact, it was decided collectively (at the Project Board level) to

work towards a more ambitious goal as it is to implement four exemplar clinically relevant use

cases that will be showing the capabilities of the platform to answer clinical questions in the

Dementia area, as detailed in section 3 Clinical use cases implementation. Clearly, this is a high

risk task for a not yet fully developed platform, but at the same time it provides additional use

cases that need to be supported and taken into consideration if the platform has to deliver any

real value.

Along this year we have been progressing in a first implementation of this mock-up in close

collaboration with VPH-Share (FP7-ICT-269978). This collaboration has proved to be fruitful

for both projects, but also for the VPH community. The collaboration has brought a number of

new functionalities that have been made available through the main VPH-Share infrastructure.

These functionalities improve the infrastructure support for VPH projects by enabling them to

set up a customized workspace (in minutes) that specializes the infrastructure in such a way

that each project can leverage project-wide access to their data, tools and workflows in order to

reuse and share them with their projects members and, optionally, external collaborators. These

enhancements have been the result of the collaborative effort between VPH-Dare@IT and

VPH-Share and are now available for the community to capitalize on in a similar way that

VPH-Dare@IT has done to deliver our VDRP infrastructure. Some of the reasons for this

collective benefit lie in the constructive role of VPH-DARE@IT has played, providing

VPH-Share with key requirements and proposals, and in the openness of VPH-Share in

adopting and implementing most of them as global features (i.e. not restricted to the

VPH-DARE@IT customized profile). Among these enhancements it is worth noting the group

(project) customization capability that facilitates and shortens the setting up of bespoke user

interface elements (based on the server IP address) thus enabling projects to take advantage of

the whole VPH-Share infrastructure and yet present to their users a project-specific appearance

and access control (project-wide permissions).


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In addition to these foundation activities, the VDRP has started being populated with domain

specific datasets (selected retrospective cohorts), computational steps (e.g., image-processing

pipelines), workflows, and tools that are the initial components for the integrative and

extensible research platform where all the different multidisciplinary biomedical imaging and

simulation tools will be available from a single access point, which is our plan and expectation

to have fully available by the end of the project.

The current deliverable is organized as described below to provide a proper presentation of this

year activities, but also to introduce the activities currently planned for next year.

Section 2 - First realisation of the VPH-Dare@IT research platform

Section 3 - Clinical use cases implementation

Section 4 - Research Platform Components

2. FIRST REALISATION OF THE VPH-DARE@IT RESEARCH PLATFORM

In this section we will introduce the first version of the VDRP. The contents of this deliverable

are just a snapshot at the time of writing because integration and development activities are

on-going throughout the whole life of the project and, as a result, there will be some differences

due to new features, improvements, component deployment and maintenance activities carried

out on the platform.

In this section we do not intent to describe the whole underlying infrastructure because there is

already extensive documentation on VPH-Share generated along the four years of the project;

instead we will be presenting the specific features that have been developed in collaboration

with VPH-DARE and also the generics parts that are more relevant to the end user in order to

be able to make the most of the platform. As mentioned in the introduction, one of the main

outcomes of this collaboration have been the project oriented features that have been developed

as a consequence of VPH-DARE@IT specific requirement and needs. These features (even in

their initial version) enable any institution or project to start up in minutes his own personalized

web workspace, where they can deploy their data, tools and workflows for internal used or to

be shared with other institutions and/or researchers/clinicians.

The VDRP is currently being populate with a number of cohorts (datasets) and applications in

order to facilitate the next generation of workflows to be build. This deployment of components

is being driven by the implementation of the clinically relevant use cases (defined by project’s

partners) that have been selected as good examples of large cohort phenomenological studies;

next year the prioritization of component deployment will be guided by mechanistic

(VPH-based) workflows. Through this process we are making available various outcomes from

Work Packages (WPs) across the project, as well as third-party tools that are used by the

community.

2.1. GETTING ACCESS TO THE RESEARCH PLATFORM When a new users access the portal, they will be presented with the VPH-DARE@IT Research

Platform home page, which is shown in Figure 1.


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Figure 1: VDRP Home Page (Before User Authentication)

To be able to explore and access the content of the platform the user first needs to log in through

the login option in the header of the portal page; once logged in the user is properly

authenticated therefore he can start to use the platform in a secure way. Figure 2 shows a

capture of the home page after the user is properly authenticated.

Figure 2: VDRP Home Page (After User Authentication)

Potential users need to be granted access to the VDRP by the administrator of VPH-DARE@IT;

currently the process is not yet fully automated, but a VDRP administrator will always be

reachable at [email protected].

2.2. DISCOVERING THE RESEARCH PLATFORM Once the user has been authenticated, the search option can be used to discover the available

resources in the system; in this view the total number of resources available are shown as well

as the different types: Datasets, Workflows, Applications (computational steps and standalone

mailto:[email protected]


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application, as explained in subsection 2.4Access to Applications), files and web services, as

shown in Figure 3.

Figure 3: VDRP Resource Discovery Page

2.3. ACCESS TO DATASETS & COHORTS Users can interact with any available dataset, once they have been granted access, by just

pressing the arrow icon to the right of the resources; this will bring the user to the resource

detail page where the different options are displayed in Figure 4.

Figure 4: VDRP Dataset Resource Page


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The “Query the dataset” option is probably the most useful for a new user. It provides the user

with a friendly interface where the user can select graphically by drag-and-drop the fields that

she or he wants to include in the result (“select” tab) table from the different entities that

constitute the dataset, while in the “where” tab the user can define the criteria for the selection

of output items, as shown in Figure 5 and Figure 6

Figure 5: VDRP Dataset Query. Output Field Selection

Figure 6: VDRP Dataset Query. Inclusion Criteria


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As a result the user will get the subset that matches the criteria; this subset, as seen in Figure

7, can now be exported to csv, excel or pdf for local browsing or further processing, if required.

Figure 7: VDRP Dataset Query. Subset Browsing and Export Format Selection

Note: on a further upgrade of the research platform there will be the possibility to feed the query

results directly into a workflow in order to process the data and also to run federate queries, i.e.

queries that span across multiples datasets.

2.4. ACCESS TO APPLICATIONS There are currently two kinds of modalities where software tools can be deployed on the

platform depending on whether they expose a web-service interface or not:

computational workflow steps – these applications will take advantage of the facilities

of the platform to operate Windows and Linux virtual machines (VM) with preinstalled

tools that have been preconfigured to expose the application interfaces as web-services,

thus enabling the applications to be used as computational steps in any workflow that

relies on them. When VMs are used in this way, the workflow execution engine

(namely Taverna server) takes the responsibility to start the VM when it is required and

switch it off when it is no longer needed;

standalone applications – in this case the (Windows and Linux) VMs have been

preconfigured with preinstalled tools to give the user access to their usual environment

by means of a cloud-based on-demand modality, taking advantage of established

remote display protocols. The platform interface allows its users to start/switch off

effortlessly a cloud machine instance, according to their respective needs thanks to a

user friendly interface; however, knowledge of the file system structure and therefore

some form of training may be required to fully leverage the preinstalled tools.

In WP7 various applications are being deployed, installed and made accessible to VDRP users

once they are properly validated. The current focus is on applications that are being developed

by the rest of the WPs or requested by VDRP users or are needed to implement specific steps

in clinically relevant use cases. While web-services are accessed through the workflow

framework (editing/execution), standalone applications are accessible through the search option

as shown in Figure 8


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Figure 8: VDRP Datasets. Application List

The process to start a standalone application requires the user to go to the application resource

detail page with the arrow button and click on the “Start application” button, as shown in Figure

9. There is also an alternative way to do that through the application tab. In any case a new VM

is started and made available for the user to interact with it; access to the VM is made possible

through a standard ssh-based command line access and through any additional network ports

(TCP or UDP) that have been defined for that machine, as detailed in and Figure 10.

Figure 9: VDRP Application. Resource Page


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Figure 10: VDRP Application. Additional Information

2.5. WORKFLOWS A computational workflow is a collection of computational steps that, connected in a particular

way, can perform tasks of various complexities; in the context of VPH-DARE@IT typically

they help answering questions that are relevant to the clinical or research environments. These

workflows can be fed with data from various datasets to generate new results that will be

evaluated. Workflows can also be easily accessed through the search option (see Figure 11).

Figure 11: VDRP Search. Workflows


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Through the arrow icon the user will get access to the resource specific page where the

different option available are shown (see Figure 12).

Figure 12: VDRP Workflows Resource Page

By clicking in “Configure to execute” button the workflow can be started with the default

input or provided with a different input file to run it (see Figure 13).

Figure 13: VDRP Workflows. Execution Configuration

Through the “Initialize execution” button the workflow can be started. The process behind the

scene will:

Create a workflow execution engine (Taverna Server) application instance on the fly

Send the workflow together with its input file (pre-defined or execution-specific one)

to the execution engine to start the execution

A specific component, the Taverna Plugin deployed on the server, will analyse the

workflow to identify the different applications that are required to execute the

different computational steps starting them in advance.

The workflow would then start to be processed with the input list and data, as shown

in Figure 14.


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Once computational steps are no longer needed the Taverna Plugin will shut them

down, releasing platform resources, while data is stored either in the distributed

FileStore (VPH-Share persistent file system) and/or in a dataset depending on the

kind of results generated.

Additional information on workflows are detailed in section 4 “Workflows composition,

integration and execution” of VPH-Share deliverable D6.5, downloadable at

https://www.biomedtown.org/biomed_town/vphshare/reception/public_repository/deliverable

s/VPH-Share_D65_1v1.pdf?action=download

Figure 14: VDRP Workflows. Execution Progress

2.6. INTERACTION BETWEEN THE CLINICAL AND RESEARCH PLATFORM The research platform is also designed to serve the role of service provider, i.e. to facilitate

access by authenticated external entities to the remote execution of workflows with specific

inputs provided by these entities. In this case the original and derived data are being stored

temporarily in a secure folder of the persistent FileStore until the results are collected by the

external application; once collected all the data is wiped-out from the research platform.

The following use case have been defined in collaboration with the clinical platform to enable

this process to happen and to validate the current implementation, and would be implemented

before the second year review.

https://www.biomedtown.org/biomed_town/vphshare/reception/public_repository/deliverables/VPH-Share_D65_1v1.pdf?action=download

https://www.biomedtown.org/biomed_town/vphshare/reception/public_repository/deliverables/VPH-Share_D65_1v1.pdf?action=download


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3. CLINICAL USE CASES IMPLEMENTATION Early this year four exemplary uses cases where defined. These use cases have been defined by

the project board were elicited to demonstrated how the VDRP platform can be used to

implement large scale studies and how then can be reused or extended. The emphasis next year

will be on the mechanistic VPH-oriented workflows, even though some progress has also been

accomplished this year.

3.1. CONCEPTUAL APPROACH As mentioned in the Introduction, the ultimate goal of the research platform is to enable

researchers to answer clinical question by means of a user friendly infrastructure that collects a

number of components relevant for the dementia domain (Tools, Model, Biomarker, Datasets)

and streamlines its use in order to facilitate the generation of new studies that will be answering

clinical questions (see Figure 15).

Figure 15: VDRP Context. Conceptual Diagram

The focus of this year is on the use of large scale data cohorts where we aim to progress in the

implementation of four selected workflows that are presented in the following sections.

3.2. LARGE COHORT STUDIES PATTERN Before presenting the different use cases, we describe the common pattern that is followed by

the Large Cohorts Studies. Being able to implement this pattern in the research platform is

allowing us to implement the specific realisation that the four selected studies will require. The

pattern is presented in Figure 16


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Figure 16: Large Cohorts Studies Pattern

The Large Cohorts Study Pattern include:

Large Data Cohorts: Large datasets have to be made available to run these studies, the

VPRP provide the means to publish these cohorts into the platform, to select a subset

when needed, to store the results and also to exploit them through an user friendly web

interface.

Computational Steps: The selected cohorts (or a subset) are required to be processed

through a number of computational steps in order to facilitate a classification of the

input data to happen. These steps will generate large amount of potential biomarkers,

usually named features, that will be used by the following stages to reach the results.

Classification Step: One or more classification steps will be required to establish a new

characterization of the original dataset (Diagnosis, Quality validation, …)

Results: Final concrete results (Diagnosis, Quality validation …) need to be accessible

to the platform users.

The goal is to bring/build clinical relevant workflows to the VDRP, where the researcher will

benefit from accessing the larges data cohorts that will be made available along the project as

well a cloud base infrastructure designed to facilitate this task.

Any component deployed on the platform will required some degree of validation in order to

guarantee the deployment is successful and can be therefore share with the user community.

This deployment will required, depending on the case, additional development and integration

effort as some components have not been designed or developed to process hundreds or

thousands of cases in a smooth and efficient way, therefore each components are not just

deployed as they are, but also optimized to streamline their execution, when possible (e.g.

removing user intervention, transform stateful components into stateless ...). Once deployed

the workflow execution will take advantage of the features and flexibility provided by the

VDRP platform to be executed multiple cloud instances on demand, in order to speed up the

process and reduce the execution time.

As commented above Cohorts and Results need to be generated in a way that users can query

and select different subsets depending on their specific needs; to make that happen a second

pattern has been also identified and it is shown in Figure 17.

Figure 17: Dataset/Cohort Extraction Pattern


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3.3. CLINICAL USE CASE IMPLEMENTATION In the following section the four exemplar use cases are described together with the concrete

realisation of the patter in each case.

3.3.1. Exemplar 1: Integration of structural, functional, and cognitive based features of

MCI classification (USFD)

3.3.1.1. Use Case Original Definition

Objective: To determine whether resting state fMRI contributes any differential

diagnostic power to MCI determination

Study Database: Functional MRI cohort (Venice/USFD), ADNI(2nd phase), others

available with rs-fMRI and structural MRI data

Requirements Obtain detailed parameter information on fMRI data from proposed studies

Build pre-processing and analysis pipelines appropriate for fMRI sequences

and desired endpoints for classification

Run parcellation on structural images

Run pre-processing and analysis pipelines on fMRI data

Perform classification algorithm and cross-validation

Challenges: Reducing variability in rs-fMRI endpoints, definition of healthy control

vs MCI to avoid circular logic in classification

3.3.1.2. Implementation

Figure 18: Exemplar 1.Worflow Definition

Implementation plan:

Import Venice data into the VRDP platform (SHT, USFD)

Deploy Conn Toolbox pre-processing computational step removing user interaction to

facilitate study (USFD)

Deploy Conn Toolbox analysis step computational step (USFD)

Validation of computational steps (USFD)

Process Limited Venice Dataset for validation purposes with the workflow deployed

in the research platform. (USFD)

Process whole Venice Dataset with the workflow (USFD)

Results evaluation (USFD)


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Import/Select specific ADNI data (SHT, USFD)

Notes: For the second phase ADNI dataset, availability of image data with the appropriated

level of quality needs to be confirmed.

At the moment of writing this deliverable the initial execution of the workflow with a limited

subset of Venice data is being carried out.

3.3.2. Exemplar 2: Classification power of hippocampal subfield volumes to differentiate

early stage Alzheimer’s disease from early stage frontotemporal dementia (UEF)


Objective: To determine whether hippocampal subfields (or subregions) add power to

classification between AD and FTD

Study Database: ADNI (but no FTD available), Kuopio FTD (UEF)

Requirements Identify FTD cohort to use and differences between imaging parameters if any

Source hippocampal subfield atlas or have rater provide anterior/posterior

boundary on current hippocampal labels

Run parcellation (including hippocampal subfields/subregions) on structural

images)

Alternatively: Perform VBM analysis on cohort using small volume of MTL

GM (hippocampus, amygdala, entorhinal/perirhinal cortex)

Challenges: Obtaining hippocampal subfield atlas, reliable hippocampal subfield

segmentations from 3T structural scans (possibly 1.5T, but resolution might be too low

and noise too high), understanding differences in biomarkers when trying to pool across

cohorts




Import ADNI dataset into the VRDP platform (STH, UCL-SO)

Import retrospective Kuopio FTD dataset into the VRDP platform (STH, UEF)

Import retrospective Sheffield FTD dataset into the VRDP platform (STH, USFD)

Deploy Segmentation computational step and made it available as a web service

(UCL-SO, USFD)


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Deploy ROI statistics computational step and make it available as a web service

(UCL-SO, USFD)

Build computational workflow, testing it with a limited subset from the different

cohorts to validate it before whole execution is started (USFD)

Process all datasets with the workflow (USFD)

Results evaluation (UEF, USFD)

3.3.3. Exemplar 3: Quantitative metrics of diffusion image quality (UCL-SO)


Objective: To determine automatic quantitative metrics that clearly identify poor scans

with minimal user interaction

Study Database: ADNI (2nd phase)

Requirements Run structural pre-processing and diffusion pre-processing

Identify metrics that most correlate with image quality

Provide evidence that images to be excluded contribute significantly to

variability in biomarker measures

Challenges: EPI distortion cannot be corrected if field mapping unavailable, overall

suitability of ADNI data for detecting subtle changes in AD




Import ADNI dataset into the VRDP platform (STH, UCL-SO)

Deploy quality control computational step and made it available as a web service

(UCL-SO, USFD)

Deploy Diagram analysis computational step and made it available as a web service

(UCL-SO, USFD)

Build computational workflow, testing it with a limited subset from the different

cohorts to validate it before whole execution is started (USFD)

Process all datasets with the workflow (USFD)

Results evaluation (UCL-SO)


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3.3.4. Exemplar 4: Comparison of biomarker methods across a large cohort (EMC)


Objective: To determine agreement between similar biomarkers (developed from

different sites) on a large ageing cohort

Study Database: Rotterdam

Requirements:

If allowed, Rotterdam to provide some exemplar data representative of study

images for testing/optimising parameters of structural pipelines

Interested groups submit optimised structural MR pipelines to Rotterdam in

format to be run locally.

Structural pipelines run on site at Rotterdam

Generation of key curves (age, sex, etc.)

Comparison of these curves and individual measures from different groups

Challenges: Optimising pipelines to data, checking results of such a large cohort,

packaging pipelines for on-site execution


In this case as the study database would be Rotterdam the processing components will be

deployed and executed on EMC environment, once the local execution is completed the

different computational steps will be deployed into the VDRP to facilitate the validation of

the results on different datasets. Also the results would be made available as they would be

required to inform models or being accessed by the clinical platform for research purpose.



Pipelines would be deployed and tested on VDRP (UCL-SO,USFD)

Pipelines would be re-deployed and executed on EMC (EMC, UCL-SO, USFD)

Curves would be uploaded into the research platform (EMC, STH)

3.4. RESEARCH PLATFORM CAPABILITIES HIGHLIGHTED THROUGH THE EXEMPLARY

CASES The selected use cases will be able to demonstrate the capabilities of the research platform in:

Handling of Multiple Datasets

o e.g. Venice, ADNI, Kuopio FTD (Exemplar Studies #1, #2, #3)

Integration of new High Throughput Pipelines

o e.g. Anterior/Posterior Hippocampus Segmentation (Exemplar Study #2)


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Integration of third-party tools

o e.g. ConnToolbox & SPM (Exemplar Study #1)

Interoperability across sites

o e.g. with private DB (Exemplar Study #4)

These capabilities are complemented by established value adding features of the VDRP:

Multiple Datasets

o on-line browsing and web-based query tool

o other DBs (MIRIAD, OASIS)

Processing steps can be interactive or non-interactive

o interactive workflows with remote visualization

(no installation required)

Growing library of processing steps

Complex task creation with desktop and web-based composition tools

4. RESEARCH PLATFORM COMPONENTS The following table shows the specific components that are deployed or being deployed at the

time of writing this deliverable on the platform, these components would constitute the building

blocks to be used by the user to generate the workflows that will implement the different studies.

Type Name Status Comments Provider Provider

Contact

Platform

Contact

Due

by

Pipeline XNAT Data

Dowload

Installed UCL-SO Nicolas

Toussaint

Alberto

Biancardi

April

2015

Pipeline Field Bias

Correction


Toussaint

Alberto

Biancardi

April

2015

Pipeline Pairwise

Registration


Toussaint

Alberto

Biancardi

April

2015

Pipeline Groupwise

Registration


Toussaint

Alberto

Biancardi

April

2015

Pipeline Tensor Diffusion

Processing


Toussaint

Alberto

Biancardi

April

2015

Pipeline ASL Processing Installed UCL-SO Nicolas

Toussaint

Alberto

Biancardi

April

2015

Pipeline Full Brain

Parcelation

Installed Preliminary

version

UCL-SO Nicolas

Toussaint

Alberto

Biancardi

April

2015

Pipeline GradWarp

Correction


Toussaint

Alberto

Biancardi

April

2015

Pipeline fMRI Processing Alberto

Biancardi

April

2015

Application Free Surfer Installed 3rd party Alberto

Biancardi

Alberto

Biancardi

April

2015

Application SPM Installed 3rd party Alberto

Biancardi

Alberto

Biancardi

April

2015

Application Conn Toolbox Exposed 3rd party Alberto

Biancardi

Alberto

Biancardi

April

2015

Workflow Exemplary 1 Received USFD Leandro

Beltrachini

Alberto

Biancardi

April

2015

Workflow Exemplary 2 Requested UEF Anne

Remes

Alberto

Biancardi

April

2015

Workflow Exemplary 3 Requested UCL Nicolas

Toussaint

Alberto

Biancardi

April

2015


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Type Name Status Comments Provider Provider

Contact

Platform

Contact

Due

by

Workflow Exemplary 4 Requested EMC Stefan

Klein

Alberto

Biancardi

April

2015

Application SubCortical

Segmentation

Received GIMIAS CLP Philips Fabian

Wenzel

Alberto

Biancardi

April

2015

Dataset Venice Released Lido Annalena

Venneri

Steven

Wood

April

2015

Dataset Miriad Released Miriad Steven

Wood

Steven

Wood

April

2015

Dataset ADNI Deployed ADNI@UCL-SO Steven

Wood

April

2015

Dataset OASIS Deployed OASIS Steven

Wood

Steven

Wood

April

2015

Dataset Kuopio FTD Requested UEF Hilkka

Soininen

Steven

Wood

April

2015

Table 1: VDRP Components.

5. CONCLUSIONS Coming back to the original milestone M72 Preliminary and limited software version released

and distributed to application partners for evaluation. We think that, although is it not still

mature enough, the platform is well advanced thanks to the collaboration between different

work packages, partners, and projects and it is becoming ready to face the challenges of the

coming years where we expect additional and more complex VPH workflows to be deployed.

Those workflows will bring new building blocks that will enable new generation of studies to

be carried out.

6. LIST OF KEY WORDS/ABBREVIATIONS

AD Alzheimer's Disease

ADNI Alzheimer's Disease Neuroimaging Initiative

CLP Command Line Plugin (See deliverable D7.1)

fMRI functional Magnetic Resonance Imaging

FTD Fronto-Temporal Dementia

GIMIAS Graphical Interface for Medical Image Analysis and Simulation

GUI Graphical User Interface

HTTP HyperText Transfer Protocol

MIRIAD Minimal Interval Resonance Imaging in Alzheimer's Disease

MRI Magnetic Resonance Imaging

MCI Mild Cognitive Impairment


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SPM Statistical Parametric Mapping

OASIS Open Access Series of Imaging Studies

rs-fMRI resting state functional Magnetic Resonance Imaging

VDRP VPH-DARE Research Platform

VPH Virtual Physiological Human

XNAT Extensible Neuroimaging Archive Toolkit

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