PROPOSAL SUMMARY PAGE

EUROPEAN COMMISSION

7th Framework Programme

Capacities - Research Infrastructures

Call Identifier: FP7-INFRASTRUCTURES-2010-2

Proposal Full Title:

DIAGNOSTIC ENHANCEMENT OF CONFIDENCE BY AN INTERNATIONAL DISTRIBUTED ENVIRONMENT

Proposal Acronym:

DECIDE

Type of Funding Scheme:

Combination of Collaborative Projects and Coordination and Support Actions: (CP-CSA)

Workprogramme Topics Addressed:

INFRA-2010-1.2.3: Virtual Research Communities

Name of Coordinating Person:

Laura Leone

Coordinating Institution:

GARR

Participant

no.

Participant Organisation name

Country

1

GARR (Coordinator)

italy

2

Alzheimer-Europe

luxembourg

3

Consiglio Nazionale delle Ricerche

Italy

4

Consorzio Cometa

Italy

5

Fatebene Fratelli

Italy

6

San Raffaele Hospital

Italy

7

University of Genova

Italy

8

University of Foggia

Italy

9

Istituto di Ricerca Diagnostica Nucleare

Italy

10

Maat G-knowledge

France

11

Imperial College London

UK

12

Department of Biomedical Physics, University of Warsaw

Poland

13

European Consortium for Alzheimer Disease

France

Proposal summary page

DECIDE

Abstract

The field of medical imaging has developed enormously in the past 20 years. Image databases made of thousands of images are now available that can be used as a reference for individual diagnosis, and sophisticated algorithms can extract information from medical images that cannot be appreciated by the naked eye. The field of neurodegenerative disorders can especially benefit from these acquisitions. Neuroscientists have recently learned that highly prevalent and burdensome chronic brain diseases such as Alzheimers disease (AD) and other neurodegenerative and neurodevelopmental disorders can be diagnosed early with image-based markers of structural and functional brain changes, allowing early pharmacological or rehabilitative interventions.

Discoveries and clinical exploitation of the above neuroimaging markers is prevented by the use of advanced software for data analysis mainly at biggest university centres and from the lack of large normative databases in little hospitals across Europe, especially in the less industrialized countries. However, all EU citizens have the right to Health and Wealth, even if they live in little cities and towns with no human resources and facilities for the extraction of the mentioned markers.

Aim of this project is to design, implement, and validate the model of a GRID-based e-infrastructure supporting e-research and diagnostic/prognostic services, based on the use of large reference databases and advanced algorithms to detect brain disease markers in individual patients suffering from dementia or schizophrenia. These markers will be extracted by the following neuroimaging techniques (non exhaustive list): (i) voxel based statistical analysis of 18F-FDG positron emission tomography (PET) and Tc99-ECD single photon emission tomography (SPET) for the diagnosis of neurodegenerative diseases, (ii) pattern recognition analysis of 18F-DOPA PET for the classification of schizophrenic patients and of structural magnetic resonance imaging (MRI) scans for the diagnosis of neurodegenerative diseases, and (iii) segmentation techniques of MRI images for the extraction of hippocampal volume and quantitative electroenceaphalographic (qEEG) markers for the diagnosis of AD. The neuroimaging markers will be derived by the statistical comparison of the individual data set with large sets of validated reference images of normal persons.

Computer-aided applications will be developed and implemented into a Grid middleware. The GRID infrastructure will allow the following functions: (i) Provide authorized and secure access to largely distributed database for healthy subject data, (ii) Supply efficiently intensive computationally processes as those required by the above applications for research and clinical use, and (iii) Permit clinical images to reside locally and comply with the strict clinical data sharing policies of most hospitals.

The potential impact for research and clinical use of the present e-infrastructure will be on a large scale, by enabling clinicians from local hospitals not owning software and large sets of images to carry out analyses remotely and efficiently by the use a centralized web-Grid service. We will define with National and European regulatory agencies protocols and rules for the qualification of experts enabled to access via Internet portals to the stored software and neuroimaging data within the GRID, for the analysis of the neuroimages for research and clinical use and for the production of the medical reports. These qualified experts could work in SMEs or universities and could establish contracts with the hospitals having no internal human resources and expertise for the extraction of the advanced neuroimaging markers. As an appreciated side effect, the present model of health services is then expected to promote EU spin-off companies and economy.

Index

7Section 1.Scientific and/or technological excellence, relevant to the topics addressed by the call

71.1Concept and objectives

91.1.2. Objectives

101.2Progress beyond the State-of-the-art

101.2.1Enabling e Infrastructures

121.2.2Early diagnosys and new criteria usage in decide

15Research and Education Networks (GARR and the NRENs, GEANT)

16Underlying Grid infrastructure: architecture and services of COMETA e-Infrastructure

201.2.3Grid enabled applications and existing communities

21SPM Applications

25qEEG Applications

271.2.4Training and tutoring

271.3Methodology to achieve the objectives of the project, in particular the provision of integrated services

271.4Networking Activities and associated work plan

271.4.1NA1 Management of the CP-CSA Project [GARR, Laura Leone]

30Tasks

31Deliverables and Milestones

32Resources

32Quality metrics

32Risk analysis and contingency plans

331.4.2NA2 Standardization, Liaison and International Cooperation FBF

33Objectives and expected outcomes

34Activities are organized in five main tasks:

38Deliverables and Milestones

39Resources

40Quality metrics

40Risk analysis and contingency plans

411.4.3NA3 Dissemination, Training and Outreach (Activity Leader: COMETA)

48Trans-national Access and/or Service Activities, and associated work plan

481.4.4SA1 Installation and Maintenance of the enabling network and grid infrastructure MAAT

48Objectives and expected outcomes

48Tasks

50Deliverables and Milestones

50Resources

51Quality metrics

51Risk analysis and contingency plans

521.4.5SA2 Design, exposure of and access to the reference databases IC

52Objectives and expected outcomes

52Tasks

55Resources

55Quality metrics

55Risk analysis and contingency plans

571.5Joint Research Activities and associated work plan

57JRA1 Porting of the diagnostic algorithms UGDIST

58TJRA1.2 Pattern recognition of FDOPA-PET, dealing with the implementation on the Grid infrastructure of the application.

58TJRA1.3 Hippocampal segmentation on structural MRI, dealing with the implementation on the Grid infrastructure of the application.

63Resources

64Quality metrics

64Risk analysis and contingency plans

651.5.2JRA2 Design of the Diagnostic Services CNR

65Objectives and expected outcomes

66Tasks

72Resources

73Quality metrics

73Risk analysis and contingency plans

741.5.3JRA3 User Validation and Testing EADC

74Objectives and expected outcomes

74Tasks

74Resources

75Quality metrics

75Risk analysis and contingency plans

91Section 2.Implementation [GARR]

912.1Management structure and procedures

912.2Individual participants

912.2.1Consortium GARR GARR (Coordinator)

91Profile and Role in the project

92Key Personnel

922.2.2CNR

942.2.3COMETA

96Profile and Role in the Project

972.2.4HSR

97Profile and Role in the Project

99Key Personnel

1002.2.5UGDIST

100Profile and Role in the Project

100Key Personnel

1032.2.6University of Foggia, Italy (UNIFG)

103Profile

103Role in the Project

104Key Personnel

1042.2.7SDN

105Key Personnel

1052.2.8MAAT-G

105Profile and Role in the Project

1062.2.9Imperial College

106Profile and role in the project

107Key personnel

1072.2.10DBP-UW

107DBP UW

107Profile

1082.2.11EADC

108Profile

108Role in the Project

108Key Personnel

1082.3Consortium as a whole

1092.4Resources to be committed

110Section 3.Impact GARR+FBF+HSR

1103.1Expected impacts listed in the work programme

1133.2Dissemination and/or exploitation of project results, and management of intellectual property

1133.3Contribution to socio-economic impacts

114Section 4.Ethical Issues

Section 1. Scientific and/or technological excellence, relevant to the topics addressed by the call

[Recommended length for the whole of Section 1 forty pages, not including the tables]

1.1 Concept and objectives

[Explain the concept of your project. What are the main ideas that led you to propose this work?

Describe in detail the S&T objectives. Show how they relate to the topics addressed by the call. The objectives should be those achievable within the project, not through subsequent development. They should be stated in a measurable and verifiable form, including through the milestones that will be indicated under section 1.3 below.]

1.1.1 The Vision of the DECIDE project

The present project (Diagnostic enhancement of confidence by an international distributed environment, DECIDE) reflects the grand vision of some speeches by Mr. David Byrne, European Commissioner for Health and Consumer Protection.

So today is really your day. The day of the health community. In a second the floor will be yours. You will have the full attention of the Commission and, I hope, the world beyond. But before then I would like to leave you with a few final thoughts The role of the EU in health policy is evolving rapidly. We need to mobilize resources and ideas, facilitate cooperation, coordinate where necessary against common threats, use the advantages of scale, and bring together expertise and ideas from different Member States in pursuit of excellence. While Member States have the responsibility for running their health systems, the EU can help health systems throughout the Union achieve their objectives. By doing so it will also contribute to economic growth and sustainable development for the Union. (Working towards good health for all; Open Health Forum - Brussels, 17 May 2004).

All EU citizens should have access to high-quality early diagnostic and prognostic procedures necessary for selecting the proper therapy, regardless they are in charge to big or little hospitals in capitals or little cities and towns. This may come true by investments of the EU upon GRID-based e-infrastructures that allow sharing information, medical data, and professional expertise across EU hospitals. The DECIDE project is expected to promote clinical research within e-communities and to contribute to reduce inequalities regarding the right to Health and Wealth of European citizens living in little countries with no chance to travel across Europe to meet medical personnel of the most advanced hospitals.

Moreover, Mr. David Byrne said

We need to encourage a counter-current in health economics thinking. A new perspective on health as a productive force in economic prosperity needs to take hold in Europe. Based on agreed methodologies and hard data, this new perspective should confirm a few key messages. (omissis) That health is a productive economic factor in terms of employment, innovation and economic growth. That significant reductions in avoidable and costly ill-health can be achieved with relatively modest investments. (omissis) For our European citizens, access to affordable high-quality healthcare is one of the benchmarks of successful modern governance. ("Health equals Wealth"; European Health Forum Bad Gastein, 3 October 2003).

Indeed, new biomedical technologies and models of health services can be an invaluable powerful engine for the promotion of the economy in the EU and outside.

The DECIDE project also represents an operative proposal as a reply to the appeal by Mrs. Anne-Sophie Parent, AGE Director, at the conference on Healthy and Dignified Ageing in Stockholm on 15-16 September 2009.

The time is right to work together to look for sustainable solutions, through exchange of views and better coordination and cooperation between stakeholders and between countries and regions. AGE hopes that all Member States will support the proposal to have 2012 declared European Year for Active Ageing and Intergenerational Solidarity and that the Swedish Presidency will propose to start to prepare a real European Strategy to be launched in 2012 to ensure that everyone in the EU can enjoy a healthy and dignified ageing.

She pointed out that dementia and its most common form, namely Alzheimers disease (AD), represents one of the toughest scientific, health, and social care challenges of our time. Furthermore, the actual management of these medical issues absorbs a lot of financial resources. According to the latest estimates of EU, the cost of brain diseases in Europe in 2004 was of 386 billion, and the global prevalence of AD is predicted to quadruple to 106 million by 2050.

Keeping in mind this premises, the DECIDE project propose an innovative solution to the problem. The DECIDE project will exploit and link existing European GRID infrastructures, to develop an innovative model of e-community research on diagnosis and prognosis based on advanced neuroimaging markers of neurodegeneration. The DECIDE project will focus on research on early diagnosis/prognosis of dementia and schizophrenia and on the use of these markers in the clinical environment. GRID applications will allow the scientific validation and use of advanced neuroimaging markers to meet the needs of neurologists and psychiatrists of both big and little cities/hospitals for earlier and more accurate diagnosis that use validated quantitative assessment of structural and functional brain images such as (non exhaustive list):

(a) Voxel-based statistical analysis of 18F-FDG PET and Tc99-ECD SPET for the diagnosis of neurodegenerative diseases;

(b) Pattern recognition analysis of 18F-DOPA PET for the classification of schizophrenic patients and of structural MRI scans for the diagnosis of neurodegenerative diseases;

(c) Segmentation techniques of MRI images for the extraction of hippocampal volume and quantitative electroencephalographic (EEG) markers for the diagnosis/prognosis of AD.

These markers will be extracted by the comparison between the neuroimaging data of the local patient and large reference databases shared by the hospitals interconnected by the GRID e-infrastructure. Furthermore, they will be validated by scientific procedures.

From a technological point of view, the computer-aided applications will be developed and implemented into a Grid middleware, taking advantage of the Grid. The GRID-based e-infrastructure will allow the following functions:

(a) Provide authorized and secure access to largely distributed database for healthy subject data;

(b) Supply efficiently intensive computationally processes as those required by the above scientific and applicative purposes ;

(c) Allow clinical images to reside locally and comply with the strict clinical data sharing policies of most hospitals.

The potential impact of the present e-infrastructure will be on a large scale, by enabling researchers of e-communities and clinicians from local hospitals not owning software and large sets of reference neuroimages to carry out analyses remotely and efficiently by the use a centralized web-Grid service.

We will define with National and European regulatory agencies protocols and rules for the qualification of experts enabled to access via Internet portals to the stored software and neuroimaging data within the GRID, for the production of field research and medical reports. These qualified experts of SMEs or universities could establish contracts with the hospitals having no human resources and expertise for the clinical application of the advanced neuroimaging markers. This model of e-research and health services could promote discoveries in the field of neuroimaging markers of neurologic diseases and then biomedical economy in the EU. As a result, we expect to improve field research products and savings in costs as well as to ameliorate the quality of life of patients and caregivers, especially when the next generation of more effective therapies becomes available for all patients. In this framework, new SMEs may offer to virtually all EU hospitals services for the advanced analysis of raw neuroimaging data stored into the GRID. The following figure illustrates the mentioned model as proposed by this project.

1.1.2. Objectives

The main objectives of the DECIDE project are the following:

O1. Link European GRIDs for sharing data analysis software and multimodal patients neuroimages for research of e-communities and for clinical applications;

O2. Develop relational databases of these multimodal neuroimages;

O3. Design and develop an innovative model of research and clinical use of advanced neuroimaging markers of neurodegeneration (with a special focus on early diagnosis/prognosis of AD). In perspective, such a model is potentially able to bust discoveries on these neuroimaging markers and to aloe the clinical use of these markers to all European neurologists engaged with the diagnosis of AD and other neurodegenerative disorders.

O4. Define and perform training protocols and exams for the qualification of experts enabled to analyze neuroimaging data within the mentioned GRID for research purposes and for the production of medical reports. Legal, ethical, and administrative issues will be discussed with key personnel of National and European regulatory agencies;

O5. Validate the GRID-based e-infrastructure for research and clinical use;

O6. Disseminate the results to promote the enlargement of the e-community and associated clinical units, and the development of SMEs providing services for the data analysis and for the production of medical reports.

1.2 Progress beyond the State-of-the-art 1.2.1 Enabling e Infrastructures

The integration of medical diagnostic tools and clinical devices with e-Infrastructures, with the aim of providing specialized services to the medical community, started a few years ago, and has already brought considerable benefits to both the users community (patients) and the specialized physicians, positively impacting on the way the medical praxis is carried out and data are handled.

It contributed to remarkably simplify the global workflow related to the analysis of medical information, to enlarge the global amount of data available for statistical analyses, to distribute the access to the information itself, allowing remote consultation, electronic storage and archiving of relevant images and data, the execution of in-silico experiments and simulations. Many medical disciplines currently benefit from having introduced e-Science in their praxis, research and workflows: cardiology, neurology, drug discovery.

A classical example of the great benefits of e-Science in the domain of medicine is for instance the WISDOM Biomedical data challenge (World-wide In Silico Docking of Malaria), which has been carried out on the EGEE e-Infrastructure in July and August 2005: two reference molecular docking applications have been used to select around 1 Million ligands in the seek for proteins related to the responsible factors for Malaria. The availability of the EGEE infrastructure has massively increased the available computing power, allowing the analysis of 46 Millions ligands, producing 1 Terabyte of final output data, and obtaining in around 1 month results which would have implied more than 80 years of time on single, even powerful, computer.

The Grid domain has with time increasingly responded to the needs of both the medical and bioinformatics communities, providing tools to interface the relevant standards in these domains (DICOM, for instance, as the most relevant example of a whole set of them) to specific middleware components (file catalogues, storage elements, database interfaces, etc) and has learnt to cope with the relevant, strict requirements these communities often have with respect to security, confidentiality of the data, privacy, distribution of the medical data.

The distributed computing community currently use the term HealthGrids to indicate highly demanded, specialized Grid-based infrastructures specifically optimized and customized to properly serve the medial community. HealthGrids implement specialized medical services, aiming at providing a more efficient, personalized medicine, whose focal centre is the single patient, and often integrate different branches of medicine and both medical information management and analysis techniques.

In describing the current status of the art, with special reference to Neurology, the neuGRID project should be mentioned as one of the most outstanding European e-Science Research Infrastructure project in the domain. neuGRID has initially demonstrated the feasibility of porting neurological algorithms to the Grid, and then went well beyond that, building a permanent infrastructure interconnecting relevant Neurological centres in Europe and cooperating with North American ones.

Key research challenges handled by neuGRID are the gridification of algorithm pipelines for brain image analysis, the development of a mid-layer of services between user-facing and grid-facing services to make the infrastructure expandable to a number of algorithm pipelines, testing and validation of the prototype infrastructure. neuGRID aims at providing a centrally-managed, easy-to-use set of tools with which scientists can perform analyses and collaborate.

Although the process of interfacing medicine and e-Infrastructures already started years ago - and already more than one example of HealthGrid can be given- generally speaking, only in few cases (like the one of neuGRID) a high level of specialization has been achieved within a single medical discipline; moreover, in such (few) cases Grids have often been involved more on the medical research side than the daily medical praxis directly impacting on the workflows involving patients and physicians.

DECIDE is a proposed HealthGrid, focused on supporting Neurology in the diagnosis and classification of neuro degenerative diseases (Alzheimer, neuro developmental disorders, schizophrenia) and aims at enhancing the confidence on the diagnosis itself by massively boosting the reliability of the required statistical analysis and integrating different clinical approaches to the diagnosis. It has been conceived to target a specific medical community and try to support physicians in their daily duty of examining patients and carrying out diagnosis of possible neuro degenerative diseases: it aims at pushing higher the level of integration for e-Infrastructures, going well beyond the world of research, to address the daily needs of neurologists while dealing with their patients. DECIDE will make use of both the experience and the infrastructure of the neuGRID project through its main, coordinating partner, the Fatebenefratelli hospital in Brescia, acting as scientific coordinator in DECIDE.

Four different medical imaging analysis techniques will be integrated by the DECIDE approach and will make use of the provided e-Infrastructure: structural Magnetic Resonance (MR), metabolic and receptor Positron Emission Tomography (PET), perfusion Single Photon Emission Computed Tomography (SPECT), Electroencephalography (EEG).

The main strategic idea behind the project is to widen the access to highly specialized diagnostic tools and techniques, and to represent a European reference pilot project, including its own e-Infrastructure, towards the progressive extension of e-Science in the domain of neurology, providing to this new European Virtual Research Community with powerful diagnostic tools, currently only available to a restricted number of patients.

The most relevant innovative features brought by DECIDE in the field of Health Grids are the following :

a. A new, very vertical approach to e-Health, targeting the needs of one community the neurologists provisioning of an e-Infrastructure aimed at supporting them in the daily execution of the diagnosis of neuro degenerative diseases and providing them with the required tools to carry out very demanding statistical analysis on the databases of collected images.

This vertical approach ensures the requirements of the neurological community to be taken into account from the very beginning in the design of the underlying infrastructure, and the interfacing of the relevant reference medial applications, so that the diagnostic services will be tailored to ensure full usability and maximum availability of the available data.

b. The fundamental inclusion of four different medical imaging techniques extends the scope of the diagnosis and allows integrated studies on neuro degenerative diseases, enabling possible synergies in the different clinical praxiss and possibly supporting correlation studies among the different clinical approaches in the field of neurology.

c. A dramatic increase in the overall, total availability of normal cases for the statistical analysis of the medical images, integrating in a comprehensive infrastructure a number of different databases, which are currently often restricted only to internal users within individual hospitals, and therefore represent isolated spots of knowledge and provide very limited amounts of images to the required statistical ensembles.

d. The provisioning of a high-level graphical user interface fully customized for the needs of physicians and neurologists aiming at supporting them in the carrying out of statistical analyses to deal with individual patients. The GUI will be user friendly to easily expose the available algorithms and the corresponding available image data sets, allowing neurologist to concentrate on the diagnostic core business, and providing a clear view on the underlying available data resources, their usage and status.

e. Both computing power and storage capacity will be available to the physicians in need of them to analyse specific cases, and means of controlling the associated grid Jobs, monitor them, analyse their output, storing results and making them easily retrievable will be provided; however the main focus of the project will be on the ease of usage for physicians of the underlying Grid infrastructure

f. A general simplification of the medical and clinical procedures associated to the analysis of individual patients will be possible: doctors will have to upload the relevant images related to one patient and the system will make sure all required statistical comparisons will be immediately triggered upon their request, so that a completely friendly, quickly available diagnostic support tool will be in place to assist them in the exact diagnosis of diseases.

g. Another relevant aspect of DECIDE is the fact that the project consortiums partners spawns very different functional domains: from the direct provisioning and control of the underlying network, to the running of the enabling Grid infrastructure and the provisioning of medical algorithms, their integration, the development of the corresponding exposed GUI, the testing of the provided functionality directly by the specific medical community and representatives from the community of the patients. This will ensure the DECIDE project the very unique strategic condition of having all the crucial elements involved in the provisioning of e-Health under direct control: from the initial provisioning to the final consuming of it, thus being able to fine tune all the elements and orchestrate them in an optimal way to provide the required functionality very efficiently and capitalizing on its experience, providing precious feedback to the project itself, its partners and possible similar future initiatives in the domain of e-Science.

1.2.2 Early diagnosys and new criteria usage in decide

Crucially the DECIDE project aims at providing an infrastructure, at present, for neurodegenerative conditions with already established or suggested criteria for diagnosis, but which should have future widespread applications for implementing diagnostic tools/procedure for psychiatric (i.e. schizophrenia, depression) and other neurological diseases (i.e. mov disorders, epilepsy, neurodevelopmental dis)

I think this should be clear in the present application and I am asking other participant more involved in psychiatry or other neurological diseases (epilepsy fore example) to make notes and implement their parts.

Over the past two decades great progress has been registered in identifying the AD-associated structural and molecular changes in the brain and their biochemical footprints.

New research criteria for the diagnosis of AD have been advanced in revising the dated NINCDS-ADRDA criteria (Dubois et al. 2007). Currently, MRI enables detailed visualisation of structures implicated in the diagnostic feature of AD. FDG-PET has been approved for diagnostic purposes and is sensitive and specific in detecting AD in its early stages and in differentiating AD from FTD. Cerebrospinal fluid biomarkers for detecting the key molecular pathological features of AD in vivo are available and can be assessed reliably.

In vivo imaging are advancing in their development and have increased our ability to accurately identify prodromal and even preclinical AD.

The main focus is Alzheimers disease, but many of the recommendations apply to dementia disorders in general. For example, new diagnostic Criteria for the Behavioral Variant of Frontotemporal Dementia has been proposed (Rascovsky et al 2007) that acknowledge the value of neuroimaging patterns in the clinical diagnosis of the disorder. The proposed new criteria such criteria: (1) significantly reduce the number of diagnostic features, (2) exclude arbitrary distinctions between core and supportive features, (3) allow greater flexibility in how patients can meet diagnostic criteria, (4) provide clearer operational definitions, (5) incorporate genetic and neuroimaging findings, and (6) distinguish between probable/possible or definite bvFTD, depending on the level of diagnostic certainty. All these aspects might take advatage by the DECIDE infrastructure.

The dementia with Lewy bodies (DLB) Consortium has revised criteria for the clinical and pathologic diagnosis of DLB incorporating new information about the core clinical features and suggesting improved methods to assess them: REM sleep behavior disorder, severe neuroleptic sensitivity, and reduced striatal dopamine transporter activity together with reduced metabolism in occipital cortex on functional neuroimaging are given greater diagnostic weighting as features suggestive of a DLB diagnosis (McKeith et al. 2005).

A task force working group considered and classified evidence from original research reports, meta-analysis, and systematic reviews, published before January 2006.. A clear consensus and good practice points were provided. to the EFNS guidance (Waldemar et al. 2007) The recommendations for clinical diagnosis, blood tests, neuroimaging, electroencephalography (EEG), cerebrospinal fluid (CSF) analysis, genetic testing, tissue biopsy, disclosure of diagnosis, treatment of Alzheimers disease, and counselling and support for caregivers were all revised when compared with the previous EFNS guideline. New recommendations were provided. This guideline reports neuroimaging as the most important ancillary investigation in the workup of dementia to aid in differential diagnosis and management decisions. It was also established the importance of the multidisciplinary dementia teams throughout Europe.

.

The growing body of evidence about these new AD/dementias biomarkers allows us to incorporate these into the DECIDE diagnostic e-infrastructure.

DECIDE will be the first integrated platform able to predict progression to Alzheimers Disease in preclinical phase, to establish and support diagnosis in LBD and FTD based on the new criteria defined or suggested by a well-known international groups of researchers (McKeith et al. 2005, Dubois et all, Lancet 2007, Waldemar et al 2007; Rascovsky et al 2007).

DECIDE will provide clinicians with a suite of innovative diagnostic tools using distinctive and reliable biomarkers of AD now available through structural MRI, molecular neuroimaging with PET, EEG and cerebrospinal fluid analyses.

More specifically, to meet the new criteria for AD diagnosis DECIDE must offer to physician reliable quantitative volumetry of region of interest (referenced to well characterised population with age norms that will be collected and made available to the end users) like Hippocampi, Enthorhinal Cortex or Amygdala acquired by MRI. Furthermore, innovative specific pattern recognition algorithm will be included in the DECIDE suite for analyzing functional imaging (PET and SPECT) acquisitions of the brain. These new methods would allow clinicians for extracting potential diagnostic factors from functional imaging data (e.g: validated statistical analysis (SPM) for comparison to normal database) and automatic detection of specific patterns showing for example reduced glucose metabolism in the bilateral temporal parietal regions and in the posterior cingulated region in AD and MCI, frontotemporal hypometabolism in FTLD, cortical hypometabolism and dopamine activity in LBD) that could be potentially informative procedure to be compared to the voxel-based statistics here also proposed (SPM).

Moreover specific pattern recognition of the brain and more discriminative algorithms will be offered to predict treatment outcomes and the efficacy of new disease modifying drugs. According to the new criteria which DECIDE is inspired specific tools will be offered to compare abnormal biomarker proteins (e.g: amyloid beta protein, total TAU, phosphorylated TAU) in the cerebrospinal fluid to a reference aged normal population.

The proposed criteria advocate the use of brain imaging techniques to examine the inner structure and function of the brain and many validation studies have been already conducted and assessed that these new criteria have excellent sensitivity, specificity and accuracy (Jack C. et all, J Magn Reson Imaging 2008). Therefore DECIDE will meet the needs of the community of clinicians and physicians for offering a diagnostic service based on a infrastructure suited for the daily diagnostic routines compliant with new criteria and with consistent clinical/imaging data and high computing power to be used for early diagnosis and care.

Ref:

Early detection of Alzheimer's disease: new diagnostic criteria. Bruno Dubois, Gaetane Picard and Marie Sarazin. Dialogues Clin Neurosci 11(2):135-9 (2009)

Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria.Dubois B, Feldman HH, Jacova C, Dekosky ST, Barberger-Gateau P, Cummings J, Delacourte A, Galasko D, Gauthier S, Jicha G, Meguro K, O'brien J, Pasquier F, Robert P, Rossor M, Salloway S, Stern Y, Visser PJ, Scheltens P. Lancet Neurol. 2007 Aug;6(8):734-46.

The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. Jack CR Jr, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, Borowski B, Britson PJ, L Whitwell J, Ward C, Dale AM, Felmlee JP, Gunter JL, Hill DL, Killiany R, Schuff N, Fox-Bosetti S, Lin C, Studholme C, DeCarli CS, Krueger G, Ward HA, Metzger GJ, Scott KT, Mallozzi R, Blezek D, Levy J, Debbins JP, Fleisher AS, Albert M, Green R, Bartzokis G, Glover G, Mugler J, Weiner MW. J Magn Reson Imaging. 2008 Apr;27(4):685-91.

Research and Education Networks (GARR and the NRENs, GEANT)

DECIDE promotes in Neurology a unified approach to both the diagnostic phase and the clinical one, and beyond that, makes use of the GRID technology, providing access to computing power and storage. A relevant guideline for the project is to rely as much as possible on the GEANT network, the pan-European research network. GEANT provides a powerful interconnection both to European and non-European research communities.

GANT, the high bandwidth pan-European research and education backbone, sits firmly at the heart of global research networking. The GANT backbone network connects 34 National Research and Education Networks (NRENs), which together deliver seamless connectivity to an estimated 40 million research and education users in 3500 institutions across 38 European countries.

In addition to its pan-European reach, the GANT network has extensive links to other world regions through collaboration with further networks, including those in North and Latin America, the Balkans, the Mediterranean, Black Sea, South Africa, Central and Eastern Asia. Links to other EC-funded networks include: TEIN3 (Asia-Pacific) ,ALICE2 (LatinAmerica) EUMEDCONNECT2 (Mediterranean) and ORIENT (China). GANT is also working towards connecting to Central Asia (CAREN) and South Eastern Africa.

GANT and the NRENs have been leading the way towards the provision of world-class eInfrastructures to the Research and Education community, both with respect to technology and capacity. R&E Network users can nowadays rely on a leading-edge tool, enabling them to easily join and convene International collaboration activities, and catering for advanced and widely customizable data transmission solutions, a consolidated international network of trust and mutual cooperation, and a tailored support to diverse user communities and their specific requirements.

It is only natural to extend their proven benefits to other sectors with considerable demands for advanced infrastructures and services, such as health. Not only the medical research sector, but also the wider healthcare one has have developed extensive needs for which the rate of fulfilment would benefit both in economic and capacity terms by collaboration with the research/educational sector: thus, R&E networks are becoming in several countries a natural point of reference for this important and demanding community.

Underlying Grid infrastructure: architecture and services of COMETA e-Infrastructure

1.2.2.1.1 Architecture

The Sicilian e-Infrastructure of the Consorzio COMETA is made of 7 production sites distributed in the three main cities of Catania, Messina and Palermo and located inside the campuses of the local Universities.

Five out of the seven total sites are located inside the campus of the University of Catania and are listed below:

1) Site Name: COMETA-INAF-CATANIA - The site is hosted by the Astrophysical Observatory of the Italian National Institute for Astrophysics (INAF);

2) Site Name: COMETA-INFN-CATANIA The site is physically located inside the Department of Physics and Astronomy of the University of Catania and it is operated by staff of the Sezione di Catania of the Italian National Institute of Nuclear Physics (INFN);

3) Site Name: COMETA-INFNLNS-CATANIA The site is hosted by the Laboratori Nazionali del Sud of the Italian National Institute of Nuclear Physics (INFN);

4) Site Name: COMETA-UNICT-DIIT-CATANIA The site is hosted by the Faculty of Engineering of the University of Catania.

5) Site Name: COMETA-UNICT-DMI-CATANIA The site is hosted by the Department of Mathematics and Informatics of the University of Catania.

The site operational at the University of Messina is:

1) Site Name: COMETA-INGEGNERIA-MESSINA The site is hosted by the Faculty of Engineering of the University of Messina.

The site operational at the University of Palermo is:

2) Site Name: COMETA-UNIPA-PALERMO The site is hosted by the Department of Physical and Astrophysical Sciences of the University of Palermo.

The computing infrastructure is based on IBM Blade Centre H chassis each containing up to 14 IBM LS21 blades interconnected both with a double Gigabit Ethernet network, for normal communications with redundancy and load balancing, and a CISCO Topspin Infiniband-4X network, required to provide the COMETA Grid with HPC functionalities. The infrastructure is built with identical hardware and software at all sites. This choice was made un purpose to allow for the maximum interoperability and realizes a homogeneous environment which is a fundamental condition for an HPC Grid environment able to run distributed parallel jobs of applications adopting the MPI paradigm.

Each blade is equipped with 2 AMD Opteron 2218 rev. F dual-core processors with a clock rate of 2,6 GHz able to natively execute x86 32 and 64 bits binary code. Each processor has 2 GB of DDR2 RAM at 667 MHz (8 GB in total per blade) and it is equipped with a direct communication channel to the other processor on the same motherboard. The memory controller is integrated onboard.

The following table shows the share of the computing power among the seven sites of the Sicilian e-Infrastructure:

Site Name

No. of blades

No. of Cores

Total RAM (GB)

Aggregated SPECint*

Aggregated SPECfp**

COMETA-INAF-CATANIA

74

296

592

3352

3293

COMETA-INFN-CATANIA

71

284

568

3216

3160

COMETA-INFNLNS-CATANIA

28

112

224

1268

1246

COMETA-UNICT-DIIT-CATANIA

44

176

352

1993

1958

COMETA-UNICT-DMI-CATANIA

34

136

272

1540

1513

COMETA-INGEGNERIA-MESSINA

68

272

544

3080

3026

COMETA-UNIPA-PALERMO

154

616

1232

6976

6853

TOTAL

473

1892

3784

21427

21049

(*) SPECint2006_rate_base for 1 LS21 Blade Server = 45.3.

(**) SPECfp2006_rate_base for 1 LS21 Blade Server = 44.5.

The storage infrastructure is based on IBM DS 4200 Storage Systems that provide high features of redundancy, management and reliability. In fact, a DS 4200 Storage System supports several types of RAID and has an intrinsic redundancy of all critical components (fan, power, controller) to assure maximum reliability. It allows expansions up to 56 TB each with SATA disks. Each Storage System is managed by two IBM x3655 servers that export the GPFS pool to all computing nodes. The following table shows the configuration of the Storage Elements at the 7 sites of the COMETA Grid infrastructure.

Site Name

No. of HDs*

Raw disk space (TB)

COMETA-INAF-CATANIA

24

12

COMETA-INFN-CATANIA

126

99

COMETA-INFNLNS-CATANIA

44

15

COMETA-UNICT-DIIT-CATANIA

32

24

COMETA-UNICT-DMI-CATANIA

40

30

COMETA-INGEGNERIA-MESSINA

30

19

COMETA-UNIPA-PALERMO

44

22

TOTAL

340

221

(*) Disks have sizes both of 500 and 750 GB each.

1.2.2.1.2 Grid Services

As explained in the section concerning WP3, one of the goals of SISSI is to maintain and operate at a production quality level both the central and the site-specific Grid services deployed on the COMETA e-Infrastructure. All these services are listed here:

Central Grid services:

Global Information Index (GIIS/BDII);

Workload Management System (WMS);

Logging and Book-keeping (LB);

Logical File Catalogue (LFC);

Metadata Catalogue (AMGA);

File Transfer Service (FTS);

Central Accounting System (HLRMON);

MyProxy Server (MYPROXY);

Site-specific Grid services:

Computing Element (CE);

Storage Element (SE);

User Interface (UI);

Worker Nodes (WNs);

Local Information Index (GRIS);

Local Accounting System (HLR);

and briefly explained below.

Global Information Index (BDII) - The BDII is a Grid service that periodically queries a list of GRISes (see below) and executes the information providers listed in its configuration file, if any. A Virtual Organisation (VO) can configure its BDIIs to query only those sites that are relevant to the VO. In order to improve the scalability and have a better performance, the BDII uses two databases, one read-only and one write-only, which are switched when an update is completed As expected, an increase in the number of sites leads to a proportional increase in the time needed to update the database, and to less up-to-date information, but not to a degradation in the response time of the Information Index. All sites are queried in parallel, but the database has to be updated sequentially.

Workload Management System (WMS) - The Workload Management System is the most important gLite service. It finds the best resource in order to match the requirements of a job (match-making process). Within a Grid infrastructure, this service accomplishes several tasks:

Resource discovery;

Selection of resources that are expected to meet the time or cost constraints imposed by the user;

Job scheduling by mapping pending jobs to specific physical resources;

Job monitoring and migration.

The WMS relies on the BDII for resource discovery.

Logging and Book-keeping (LB) - This Grid service complements the WMS and its function is to log all the information for each job. It is usually queried by the User Interface when a user wants to inspect the status of his/her jobs.

Logical File Catalogue (LFC) - This gLite service maps Logical File Names (LFNs) onto Physical File Names (PFNs), i.e. the high level names given by users to their files distributed on the Grid with the physical locations of those files (including eventual replicas) on the Storage Elements (see below).

Metadata Catalogue (AMGA) - The AMGA metadata catalogue manages metadata associated to Logical Files whose corresponding Physical Files are located on Storage Elements distributed on a Grid infrastructure.

File Transfer Service (FTS) - The File Transfer Service (FTS) is a gLite service that allows for asynchronous transfers of large data-sets (up to PetaBytes) across Grid Storage Elements in a fault tolerant way.

Central Accounting SysteM (HLRMON) - HLRMON is basically a web server that publishes the accounting values collected from local site HLRs and allows for different views.

MyProxy Server (MYPROXY) - The MyProxy service allows users to store special credentials that can be used to delegate proxies to themselves or to other Grid services (e.g., the WMS) when they want to access grid portals or to run very long jobs.

Computing Element (CE) - A Computing Element is a queue of a Local Resource Management System that is seen by the WMS as a computing resource where users jobs can be submitted.

Storage Element (SE) - A Storage Element is portion of storage space that can seen by users as a disk to which data can be stored.

User Interface (UI) - The User Interface is the gateway to a Grid infrastructure and it the gLite service used by users to submit/monitor/retrieve their jobs and to manage their data.

Worker Nodes (WNs) - The Worker Nodes are the computing nodes of a Grid Infrastructure. They are grouped in queues that are published by a site as Computing Elements.

Local Information Index (GRIS) - This service collects periodically the information about the status of a site CE/SE (number of total/busy CPUs, number of running/waiting jobs, total/available disk space, etc.) and publishes it on the BDII.

Local Accounting System (HLR) - This services collects accounting data for jobs and disk occupancy at a site level on a per job/per user basis and publishes them on the central HLRMON.

Virtual Organisation Service (VOMS) - The Virtual Organisation Membership Service (VOMS) is a Grid service that provides information on the user's relationship with his/her Virtual Organisation: groups, roles and capabilities. It is basically a simple account database which serves the information in a special format (VOMS credential). Data are stored in a ORACLE/MySQL database and a failover is implemented using the generic database replication mechanism in a master/slave configuration.

Monitoring Services:

GStat - The Information Index (BDII) provides information about the Grid resources and their status. This information is essential for the operation of the whole Grid. GStat is a monitoring tool based on Python scripts. GStat validates the accessibility of the BDII on a per-site basis and performs internal consistency checks of the published information. This test is performed every few minutes and the results are made available on a web page.

SAM - The Service Availability Monitoring (SAM) aims to provide a site independent, centralized and uniform monitoring tool for all Grid services. It is the main source of monitoring information for high-level Grid operations and is being used in the validation of sites and services with calculation of availability metrics. The main functions of the SAM are to monitor SEs, LFC, FTS, CEs, WMS, l BDII, GRISes, MyProxy, and VOMS services. SAM consists of two packages:

SAM Client runs on a monitoring site UI and submits various job packages to the Grid and monitors their execution. Every change of status is sent to the SAM Server;

SAM Server receives and stores the information sent from the SAM Client and presents it in a dynamic website.

SAM relies on the standard job submission mechanism on a single UI. The tests are in fact different scripts intended for execution on WNs of every monitored site in order to test various Grid functionalities. When the SAM test package is started, all specified scripts are packed in a single job description and are submitted to a list of specified CEs. The administrator is able to choose some predefined testing scripts, and also define new ones, all of which will be packaged together for the SAM execution.

After each test script runs on the WN, the results are published directly to the SAM Server using a web service. It is done in this way in order to be able to have partial results from the tests even when the job fails to finish after a successful submission. The contacted web service on the SAM Server stores the results in a local ORACLE/MySQL database. During the time of the test run or after the test has finished, the SAM administrator can publish intermediate or final results on the SAM website.

1.2.3 Grid enabled applications and existing communities

As the interest in clinical analysis of medical image data is growing, the need for the exploitation of reliable and innovative techniques is increasing too. e-Infrastructures consisting of large repositories paired with high computational power to run computationally intensive algorithms on biomedical images data are widely available. Table 1 shows that a number of efforts at creating large image repositories exist worldwide and tools have been already developed to perform quantitative brain imaging analysis.

Table 1 - initiatives directed at creating large brain image repositories worldwide

The BIRN, CBRAIN, LONI and neuGRID are probably the best known of such efforts. BIRN aims to enable a software fabric for participating centers and to facilitate the collaborative use of tools and processing/analysis frameworks for the study of brain diseases. The Montreal Neurological Institute (MNI) is developing a pan-Canadian platform termed CBRAIN, using a Grid with a Service-Oriented Architecture (SOA) for distributed processing and analysis of 3D/4D brain imaging data. The Laboratory of NeuroImaging (LONI) at UCLA has a powerful clientserver architecture based on a Sun Grid Engine that enables the execution of heterogeneous software modules and processing the US-ADNI dataset. Among all these initiatives it is absolutely mandatory to mention the neuGRID project. NeuGRID is the first e-infrastructure effort at a European level that aims to provide the neuroscience community with services such as the archiving of large coherent amounts of imaging data paired with computationally intensive analyses.

Notably, Table_1 shows that all the above initiatives are mostly aimed to the management of images and analysis only for research purposes, but none of them offers grid-computational facilities specifically addressed for the clinical users community.

In contrast, DECIDE project will offer to clinicians a rich e-infrastructure with innovative algorithms suited to perform single case diagnosis in the field of chronic brain diseases such as Alzheimers and other neurodegenerative and neuro developmental disorders. It needs to be underlined that DECIDE will make extensive use of the neuGRID infrastructure. Its activities will be carried out in close concertation with neuGRID thanks to the presence in the DECIDE consortium of the FBF and MAAT-g partners.

For the first time, a powerful brain analysis suite of tools will be available for carry out analyses by the use of a web-grid-service. One of the grid applications that certainly will be offered to the end users will be the gridified CLASP cortical thickness extraction algorithm (MacDonald D et al, Neuroimage, 2000; Kim JS et al., Neuroimage, 2006) developed by the Montreal Neurological Institute and already gridified and usable in the neuGRID platform. This tool could be considered as one of the best algorithm for the evaluation of the cortical thickness and it is considered to be one of the best markers for the diagnosis of the Alzheimers Disease.

Another important marker of Alzheimer's is the hippocampal volume. Therefore, DECIDE will offer to clinicians the segmentation of the hippocampus using a gridified version of the innovative ACM-Adaboost algorithm developed by the LONI (Morra JH et al, Neuroimage 2008).

The possibility of combining complex and highly specific tools (e.g.: CLASP, ACM-Adaboost, ecc..) will raise the diagnostic confidence of the tools used in many neurological diseases. As a consequence, DECIDE will offer unprecedented power at their clinicians fingertips through the simplicity of the web service interface. Moreover with the DECIDE grid-infrastructures doctors could obtain results immediately, increase productivity and speed up the discovery of the disease modifying drugs. Once DECIDE infrastructure will be up and running a Grid-based platform providing a consistent portfolio of diagnostic services will be exploited. It is clear by now that DECIDE should have a very high social impact too treating brain disorders at high incidence.

In conclusion, Grid-based solutions might be an appropriate answer to provide a secure access to largely distributed database for healthy subject data, supply efficiently intensive computationally processes required by complex diagnostic algorithms and, finally, allow clinical images to be compliant with the strict data sharing policies of the hospitals.

SPM Applications

Although 18FDG-PET has been used to study neurodegenerative disease for over two decades, its diagnostic potential has not been fully exploited. Most studies have been devoted to understand the biology of dementia and are inadequate to assess or demonstrate clinical utility (Gill et al., 2003). The evaluation of a diagnostic test relies upon individual, rather than group differences from a reference population and is assessed with statistical measures such as sensitivity, specificity, predictive value, and likelihood ratio. These measures apply in fact to a single diagnostic comparison. Nowadays, simple visual inspection of the brain scans obtained by PET are no longer acceptable for diagnostic purposes because of the potential lack of crucial information and often misleading results. Unbiased methods for the detection of functional abnormalities in subjects with neurodegenerative disease are nowadays mandatory. The automatic detection of abnormal brain metabolism on individual PET scans requires appropriate reference data sets, spatial normalization of scans, statistical algorithms (to compare the voxels in scan data with normal reference data), and suitable display of the results.

Signorini et al. (1999) demonstrated that this can be achieved by adapting the Statistical Parametric Mapping (SPM) software package that was developed at the Wellcome Institute, London, U.K., originally for analysis of activation studies. Noteworthy, the sum of abnormal t-values in regions that are typically hypometabolic in AD has been used as an indicator with 93% accuracy (Herholz et al. 2002). The same accuracy was achieved even without image reconstruction by a special pattern extraction technique from PET sinograms (Sayeed et al. 2002). Furthermore, several discrimination functions combined with principal component analysis or partial least-squares have been proposed and tested for discrimination between AD and FTD in a sample of 48 patients with autopsy-confirmed diagnosis and achieved accuracies between 80% and 90% (Higdon et al.2004). Furthermore, discriminant functions derived by multiple regression analysis of regional data achieved a 87% correct identification of AD patients versus controls, and a neural network classification method arrived at 90% accuracy, however, showing less accuracy than the above mentioned SPM method.

In addition to SPM, other methods and software packages have been developed and made available providing support for voxel-based approaches. As an example, a commercial software package, 3D-SSP or NEUROSTAT, has been used successfully to identify metabolic alterations in dementia and mild cognitive impairment (MCI) (Ishii 2001, 2003, Drzezga 2003). These methods are based upon the detection of abnormal voxels or upon automatic recognition of the typical anatomical distribution of metabolic abnormalities in AD and not on a comparison with normal subjects. Thus users should take care to check the validity of their results with a comparison with normal reference data.

Noteworthy, a recent study demonstrated that 18FDG-PET significantly increases diagnostic accuracy and confidence (Foster et al., 18FDG-PET Improves Accuracy in Distinguishing Frontotemporal Dementia and Alzheimer's Disease. Brain, in press). This paper shows the utility of 18FDG-PET in distinguishing between AD and FTD using data from patients with neuropathologically confirmed diagnoses. In detail, the authors compared the inter-rater reliability, test characteristics, and diagnostic accuracy of three clinical methods of assessments derived from medical records, and two methods of displaying 18FDG-PET data. After having selected the best method of displaying 18FDG-PET data for interpretation, they evaluated whether 18FDG-PET might provide any diagnostic benefits when it is added to the patients clinical history and examination. The Voxel-based interpretation of 18FDG-PET images was superior to clinical assessment and had also the best inter-rater reliability and diagnostic accuracy of 89.6%. It also had the highest specificity (97.6%) and sensitivity (86%), and positive likelihood ratio for FTD. The authors conclude that 18FDG-PET voxel-based analysis is valuable in differentiating AD and FTD, particularly when findings in a clinical evaluation are not definitive and physicians are not already highly confident with their clinical diagnosis. This work demonstrates the addition of 18FDG-PET to clinical summaries to increase diagnostic accuracy and confidence for both AD and FTD.

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9. Borroni B, Anchisi D, Paghera B, Vicini B, Kerrouche N, Garibotto V, Terzi A, Vignolo LA, Di Luca M, Giubbini R, Padovani A, Perani D. Combined 99mTc-ECD SPECT and neuropsychological studies in MCI for the assessment of conversion to AD. Neurobiol Aging, 2006; 27: 24-31.

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12. Dougall N and Ebmeier KP Perfusion Imaging with Single Photon Emission Computed Tomography. In: The Dementias. K Herholz, D Perani and C Morris eds. Taylor and Francis 2006, pages: 197-228.

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15. Signorini M, Paulesu E, Friston K, Perani D, Lucignani G, Colleluori A, Striano G, et al. Rapid assessment of [18F]FDGPET brain scans in individual patients with Statistical Parametric Mapping. A clinical validation. Neuroimage 1999;9:63-80.

16. Varrone A, Pappat S, Carac C, Soricelli A, Milan G,Quarantelli M, Alfano B, Postiglione A, Salvatore M Voxel-based comparison of rCBF SPET images in frontotemporal dementia and Alzheimers disease highlights the involvement of different cortical networks. European Journal of Nuclear Medicine 29, 11, 1448.1454, 2002.

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19. Salmon E, Garraux G, Delbeuck X, Collette F, Kalbe E, Zuendorf G, Perani D, Fazio F, Herholz K (2003) Predominant ventromedial frontopolar metabolic impairment in frontotemporal dementia. Neuroimage 20:435-40.

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23. Hosaka K, Ishii K, Sakamoto S, et al. Voxel-based comparison of regional cerebral glucose metabolism between PSP and corticobasal degeneration. J Neurol Sci 2002 199:6771.

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The IBFM-CNR unit has already developed and implemented a national centralized web SPM service, GriSPM specifically designed for the remote processing of clinical SPECT and PET neurological images [1-4]. The proposed SPM service was implemented as an open-to-authorized user, Grid-based web service including: (a) remote access to Grid-distributed databases of SPECT and PET images of normal subjects numerically appropriate for statistical analysis, and (b) a noncommercial, free, Grid-distributed computationally efficient SPM version, tailored for the analysis of brain images in neurological diseases (GriSPM). A Grid distributed database was configured providing access to SPECT/PET images of normal subjects at different hospitals/centres selected as Grid Repository Nodes. Two databases of normal images (SPECT and PET) provided by the Nuclear Medicine Department of San Raffaele Scientific Institute (HSR), Milan (Italy), are available on the Grid Repository Node of DIST Genoa University. The normal subjects comprised 19 volunteers (10 men, 9 women; age range 2175 years) and 21 volunteers (11 men, 10 women, age range 2174 years) recruited for SPECT and PET, respectively. Volunteers were cognitively evaluated by experts using neuropsychological batteries and gave their informed consent to participate in the study. SPECT scans were performed using a Millennium VG SPECT system (General Electric) with a scan time of 25 min, 30 min after injection of 99mTc-ECD (0.4 mCi/kg patient weight) as required by a conventional neurological acquisition protocol. SPECT acquisition parameters were: low-energy high-resolution collimator, 20 cm rotation range, 120 projections, 128128 acquisition matrix. SPECT images were reconstructed using a filtered back-projection algorithm: zoom 1.5, filter x,y,z Butterworth (0.510) into an image volume of 128128 (max 70) voxels, 2.942.942 mm pixel size. PET scans were performed using a 3-D PET Discovery LS system (General Electric) with a scan time of 15 min, 45 min after injection of 18F-FDG (1 mCi/10 kg patient weight) as required by a conventional neurological acquisition protocol. PET images were reconstructed using a 3-D reprojection algorithm (Axial filter: ramp 8.5) into an image volume of 12812835 voxels, 2.52.54.25 mm voxel size, over a field of view of 252514.5 cm. GriSPM was validated by physicians and physicists with SPM expertise at HSR (user site). GriSPM software was validated by comparing the results of the original SPM and of GriSPM. Evaluators agreed on the consistency of the two methods in showing comparable statistical t maps in each patient. Chi-squared statistical comparisons between original SPM and GriSPM maps showed excellent agreement for all SPECT and PET patients. Evaluators tested the performance of the GriSPM service in terms of ease of use and quality of results (score 1, low; 2, medium; 3, high). All users gave maximum scores (3) to the GriSPM service for easy of use and quality of results. The GriSPM service is available together with the Gridbased databases of both SPECT and PET images of normal subjects online at www.neuroinf.it (user Doctor, section Statistical analysis of SPECT and PET images). Authorized users upload SPECT/PET neurological studies to the site and perform SPM analysis through the browser on the Grid-based website.

1) S. Scaglione, I. Castiglioni, E. Molinari, F. Cesari, A. Schenone, M. C. Gilardi, F. Beltrame. Neuroinformatics portal as knowledge repository and e-service for neuroapplication and data mining. Proceedings of Mediterranean Conference on Medical and Biological Engineering (MEDICON), Ischia, 2004.

2) Cesari F, Molinari E, La fortuna C, Abutalevi J, Castiglioni I, Perani D, et al. An Italian portal of neuroinformatics: www.neuroinf.it. Q J Nucl Med 2004;48(3):157. Eur J Nucl Med Mol Imaging (2009) 36:11931195

3) S. Bagnasco, F. Beltrame, B. Canesi, I. Castiglioni, P. Cerello, S. C. Cheran, M. C. Gilardi, E. Torres Lopez, E. Molinari, A. Schenone, L. Torterolo. Early diagnosis of Alzheimer's disease using a grid implementation of statistical parametric mapping analysis. in Stud. Health. Technol. Inform., edited by V. Hernandez, I. Blanquer, T. Solomonides, V. Breton and Y. Legre, 2006; 120: 69-81.

4) I. Castiglioni, B. Canesi, A. Schenone, D. Perani, M.C. Gilardi. A Grid-based SPM service (GriSPM) for SPECT and PET neurological studies. Eur. J. Nucl. Med. Mol. Imag., 2009; 36: 1193-1195..

qEEG Applications

It is well known that qualified but partially invasive neuroimaging biomarkers of AD as extracted by structural MRI and PET-FDG may contribute to early diagnosis and prediction of disease progression and therapy response. These biomarkers are relatively expensive and invasive, so cheap and non-invasive EEG biomarkers have been tested with promising results Resting state eyes closed EEG biomarkers reflect mechanisms of brain neural synchronization, and can be provided by low-cost and non-invasive EEG facilities available in all European neurological departments. Specifically, it has been shown that abnormal power density and functional coupling of EEG rhythms characterize subjects with mild cognitive impairment (MCI) and AD, and might contribute to the prediction of conversion from MCI to AD status (Babiloni et al., 2004, 2006a,b,c,d,e, 2007, 2008a,b, 2009; Rossini et al.2006). EEG source power density can be easily obtained by the popular freeware called low resolution brain electromagnetic tomography (LORETA; http://www.uzh.ch/keyinst/loreta.htm). Whereas, functional coupling of EEG rhythms can be computed by spectral coherence and Directed Transfer Function (i.e. directionality of the functional coupling; Blinowska and Kaminski, 2006). Grid porting of the above algorithms would give the access to the efficient and verified algorithms estimating synchronization and transmission in brain to the large community of users and may contribute to the early diagnosis of neurodegenerate impairments.

Babiloni C, Binetti G, Cassetta E, Cerboneschi D, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Lanuzza B, Miniussi C, Moretti DV, Nobili .,Pascual-Marqui RD, Rodriguez G, Romani GL, Salinari S, Tecchio F, Vitali P, Zanetti O, Zappasodi F, Rossini PM. Mapping Distributed Sources of Cortical Rhythms in Mild Alzheimers Disease. A Multi-Centric EEG Study. NeuroImage 2004; 22(1):57-67.

Babiloni C, Binetti G, Cassarino A, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Frisoni G, Galderisi S, Hirata K, Lanuzza B, Miniussi C, Mucci A, Nobili F, Rodriguez G, Romani GL, and Rossini PM. Sources of cortical rhythms in adults during physiological aging: a multi-centric EEG study. Human Brain Mapping. 2006a, 27(2):162-72.

Babiloni C, Binetti G, Cassetta E, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Frisoni G, Hirata K, Lanuzza B, Miniussi C, Moretti DV, Nobili F, Rodriguez G, Romani GL, Salinari S, and Rossini PM Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multi-centric study. Clin Neurophysiol. 2006b, 117(2):252-268

Babiloni C, Benussi L, Binetti G, Bosco P, Busonero G, Cesaretti S, Dal Forno G, Del Percio C, Ferri R, Frisoni G, Ghidoni R, Rodriguez G, Squitti R, and Rossini PM Genotype (cystatin C) and EEG phenotype in Alzheimer disease and mild cognitive impairment: a multicentric study. Neuroimage. 2006c, 29(3):948-64.

Babiloni C, Benussi L, Binetti G, Cassetta E, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Frisoni G, Ghidoni R, Miniussi C, Rodriguez G, Romani GL, Squitti R, Ventriglia MC and Rossini PM Apolipoprotein E and alpha brain rhythms in mild cognitive impairment: A multicentric EEG study . Ann Neurol. 2006d, 59(2):323-34.

Babiloni C, Frisoni G, Steriade M, Bresciani L, Binetti G, Del Percio C, Geroldi C, Miniussi C, Nobili F, Rodriguez G, Zappasodi F, Carfagna T, Rossini PM. Frontal White Matter Volume and Delta EEG Sources Negatively Correlate In Awake Subjects With Mild Cognitive Impairment and Alzheimer's Disease. Clin Neurophysiol. 2006e;117(5):1113-29.

Babiloni C, Cassetta E, Dal Forno G, Del Percio C, Ferreri F, Ferri R, Lanuzza B, Miniussi C, Moretti DV, Flavio Nobili F, Pascual-Marqui RD, Rodriguez G, Romani GL, Salinari S, Zanetti O, Rossini PM. Donepezil effects on sources of cortical rhythms in mild Alzheimers disease: Responders vs. Non-Responders. Neuroimage. 2006f; 31(4):1650-65

Babiloni C, Cassetta E, Binetti G, Tombini M, Del Percio C, Ferreri F, Ferri R, Frisoni G, Lanuzza B, Nobili F, Parisi L, Rodriguez G, Frigerio L, Gurz M, Prestia A, Vernieri F, Eusebi F, Rossini PM. Resting EEG sources correlate with attentional span in mild cognitive impairment and Alzheimer's disease. Eur J Neurosci. 2007 Jun;25(12):3742-57.

Babiloni C, Visser PJ, Frisoni G, De Deyn PP, Bresciani L, Jelic V, Nagels G, Rodriguez G, Rossini PM, Vecchio F, Colombo D, Verhey F, Wahlund LO, Nobili F. Cortical sources of resting EEG rhythms in mild cognitive impairment and subjective memory complaint. Neurobiol Aging. 2008a Nov 20.

Babiloni C, Pievani M, Vecchio F, Geroldi C, Eusebi F, Fracassi C, Fletcher E, De Carli C, Boccardi M, Rossini PM, Frisoni GB. White-matter lesions along the cholinergic tracts are related to cortical sources of EEG rhythms in amnesic mild cognitive impairment. Hum Brain Mapp. 2008b Dec 18.

Babiloni C, Ferri R, Binetti G, Vecchio F, Frisoni GB, Lanuzza B, Miniussi C, Nobili F, Rodriguez G, Rundo F, Cassarino A, Infarinato F, Cassetta E, Salinari S, Eusebi F, Rossini PM Directionality of EEG synchronization in Alzheimer's disease subjects.. Neurobiol Aging. 2009 Jan;30(1):93-102. Epub 2007 Jun 15.

K.J. Blinowska, M. Kaminski. Multivariate Signal Analysis by Parametric Models In: Handbook of Time Series Analysis. Eds. B Schelter, W. Winterhalder, J. Timmer, Wiley-VCH, 2006.

Rossini PM, Del Percio C, Pasqualetti P, Cassetta E, Binetti G, Dal Forno G, Ferreri F, Frisoni G, Chiovenda P, Miniussi C, Parisi L, Tombini M, Vecchio F, Babiloni C., Conversion from mild cognitive impairment to Alzheimer's disease is predicted by sources and coherence of brain electroencephalography rhythms. Neuroscience. 2006 Dec;143(3):793-803. Epub 2006 Oct 13.

1.2.4 Training and tutoring

Collaboration with other initiatives in EGEE and ICEAGE, etc.

1.3 Methodology to achieve the objectives of the project, in particular the provision of integrated services

1.4 Networking Activities and associated work plan

[A detailed work plan should be presented, broken down into activities which should follow the logical phases of the implementation of the project's Networking Activities, and include consortium management and assessment of progress and results. (Please note that your overall approach to management will be described later, in section 2).

Please present your plans as follows:

Describe the overall strategy of the work plan.

Show the timing of the different WPs and their components (Gantt chart or similar).

Provide a detailed work description broken down into activities:

Activity list (please use table 1.3a);

Deliverables list (please use table 1.3b);

Description of each activity, and summary (please use table 1.3c)

Summary effort table (please use table 1.3d)

List of milestones (please use table 1.3e)

Provide a graphical presentation of the components showing their interdependencies (Pert diagram or similar)

Notes:

The number of activities used must be appropriate to the complexity of the work and the overall value of the proposed project. The planning should be sufficiently detailed to justify the proposed effort and allow progress monitoring by the Commission.

Any significant risks should be identified, and contingency plans described.]

1.4.1 NA1 Management of the CP-CSA Project [GARR, Laura Leone]

The Project Management activity intends to ensure consistency and maintain collaboration in the DECIDE Project NAs, SAs and JRAs Activities as requested by a CP-CSA Project. The activity will be focused on the harmonization of the participants activities and to the developing of an overall service management framework to ensure the correct development of the Project in achieving the objectives through an efficient management. The project manager (PM), appointed by the co-ordinating partner, will be responsible to run the project, in agreement with the decision taken by the PMB. The PO, a staff office to deal with administrative and external communication (in collaboration with Dissemination activities NA2) will be created to support the PM in the day-to-day operational management of the project.

1.4.1.1.1 TNA1.1 Administrative Management of the Project GARR

The structure will take into account the specific needs of a CP-CSA project. The management structure and procedures are described in the call work program 2010.

For the project DECIDE, a mapping of the work blocks describing the overall project goals (see Section for a detailed description of these work blocks) into activities (A) is performed. These activities will be activated at different points in time, and the duration of an activity is also limited usually to a duration related to the overall project life time.

DECIDE will be structured into nine activities with sub activities (Tasks):

Area(s) of competence/interest

NA1 - management

Task NA1.1 Administrative management

Task NA1.2 Technical and scientific management

Task NA1.3 Quality Assurance

NA2 - Standardization, liaison and intermational cooperation

Task NA2.1 Harmonization to EGI standards

Task NA2.2 Medical data collection

Task NA2.3 Scientific International Collaboration

Task NA2.4 Geant Collaboration and support to provide networking infrastructure

Task NA2.5 Development assistance to patients communitiesin less advanced regions

NA3 - Dissemination, Training & Outreach

Task NA3.1 Dissemination

Task NA3.2 Training

Task NA3.3 Outreach to the Medical Community

SA1 - Installation and maintenance of the enabling network and grid infrastructure

Task SA1.1 Network provision and operation, including support

Task SA1.2 Grid infrastructure provision and operation, including support

Task SA1.3 GUI deployment and user support

Task SA1.4 Software Release Management

SA2 - Exposure of and access to the reference databases

Task SA2.1 Structural MR reference database

Task SA2.2 PET/SPET reference database

Task SA2.3 EEG reference database

JRA1 - Porting of the diagnostic algorithms

Task JRA1.1 Voxel-based analysis of FDG PET/SPET images

Task JRA1.2 Pattern recognition of FDOPA PET and strucutral MR

Task JRA1.3 Hippocampal segmentation on structural MR

Task JRA1.4 EEG Algorithms

JRA2 - Design of the Diagnostic Service

Task JRA2.1 Algorithm Evaluation and Inclusion

Task JRA2.2 Clinical Requirements and Procedural Tuning

Task JRA2.3 Algorithm and Database Architecture Design

Task JRA2.4 Application Integration and Middleware interfacing

Task JRA2.5 Global Validation

JRA3 User Validation and Testing

Task JRA3. 1 Beta testing

Task JRA3. 2 Interface Usability Assessment

Each activity is coordinated by an Activity Leader who is responsible for the coordination of the activities developed inside each activity. Each activity is divided into Tasks coordinated by Tasks leaders thus ensuring that the activities are compatible with the objectives of the Project. Activities are expected to work in strict coordination providing each other with input and feedback to reach the overall goal of the project. This will be ensured by regular communications realized through :

meetings of each activity (personal meetings and conference calls) at least on a monthly basis

mail exchange

Main goal of each activity is to ensure the progress according to the goals and objectives set for the project, and to early discover potential issues that might have a negative impact on the achievement of the project goals. If necessary, an explicit link to other activities for clarification of issues affecting multiple tasks will be established, including the involvement of the project coordinator. Over the management of the activities, an appropriate project management will link together all the project components maintaining communications with the Commission each time it is needed.

As a first measure, all Activity Leaders will evaluate together with the project coordinator on a regular, at least monthly basis, the progress of each individual activity and of the overall project versus the objectives and goals, including the milestone and deliverable plan.

If any critical issue is discovered that threatens the achievement of a goal, an appropriate counter-measure is worked out and proposed to the overall consortium (if required as preparation for a decision by the Project Management Board). The project progress will be reported as required towards the EU (currently, quarterly reports are planned). On top of that, an overall plenary meeting is foreseen in which all participants of the project should be represented. Planned frequency of these meetings is to have at least one personal plenary meeting per year and plenary phone conferences on demand, but at least on a quarterly basis. It is also one task of these plenary meetings to review the overall work plan at least on a yearly basis (in alignment with the official audit procedure). In addition, such a review can take place at any point in time when a necessity is seen by a partner and the need is confirmed by the project coordinator and the activity leaders. In general, all decision making processes will follow the rules described in detail in the Consortium Agreement. Also there is the escalation procedure in case that no agreement between the partners can be achieved on a working level is described.

The final quality of the documents produced (specifically the deliverables) will be carefully reviewed before the delivery by all the involved partners and (if available) by at least one additional partner and, over that, also by the activity Leaders and the Project Coordinator.

Risk assessment will be made at each starting point of a new activity (e. g. start of a new activity) or start of a new task within the activity). Potential risks will be identified, appropriate counter measures defined, and a process to monitor the identified risks and to trigger appropriate counter measures agreed between all involved partners, the respective activity leader and the project coordinator.

In summary, the project management will take care of:

coordination of the technical activities of the project (in first instance on a per-activity level,

on top of that on an overall project level)

the overall legal, contractual, ethical, financial and administrative management of the consortium

managing the consortium agreement between the participants (ensuring that the rules defined are followed, and updating the agreement if necessary)

coordination at consortium level of knowledge management and other innovation related activities

the implementation of calls by the consortium to find new participants (if the case)

preparing and delivering to the Commission, on a defined periodic basis, a technical budget report

preparing and delivering to the Commission, on a yearly basis, an executive summary on progresses, objectives achieved, status of activities, including potential deviations from work plan costs

The project management of DECIDE is compliant with the requested structure by CP-CSA projects and specifically it is based on:

Project Coordinator

Technical Coordinator

Scientific Coordinator

The project manager (PM), is appointed by the Technical and Scientific coordinator partners, will be responsible to run the project, in agreement with the decision taken by a PM Board. The Project Office, a staff office to deal with administrative and external communication (in collaboration with Dissemination activities NA3) will be created to support the PM in the day-to-day operational management of the project. Further details about the management structure are given in next Sections.

Tasks

1.4.1.1.2 TNA1.1 Administrative Management of the Project GARR

The structure will take into account the specific needs of a CP-CSA project. The management structure and procedures are described in

1.4.1.1.3 TNA1.2 Technical Management of the Project FBF

For managing the Technical Activities a lightweight structure could be the following:

A Technical Board (TB): made up by the managers of all the activities (JRA, NA, SA).

A Technical Manager (TM): proposed by the PD and nominated by the PMB, will chair the TB and deal with the day by day technical discussions curing the coherence of all the technical actions in the view of the projects objectives. It should be one of the members of the EMB.

About the Scientific Management Coordination of the project the main actions to be taken are:

designing, populating, and publishing a website within the first 2 months, aiming to outline the project aims, share technical information among partners, make the project deliverables and results available online, and activate a discussion forum for the scientific community interested into DECIDE. A restricted access section of the website will give the opportunity to access drafts of documents. This discussion area and a devoted interactive working space for partners will be implemented by means of co-operative working tools. Website editing will be carried out within TNA3.1. Website maintenance and update will be provided by GARR for the whole duration of the project. Moreover, a logo and a flyer will be prepared within M4 by FBF.

in-person semi-annua